Blogs
In our previous blog post, "Abnormal Noise Detection: From Human Ears to AI"we discussed the key pain points of manual listening, introduced CRYSOUND's AI-based abnormal-noise testing solution, outlined the training approach at a high level, and showed how the system can be deployed on a TWS production line. In this post, we take the next step: we'll dive deeper into the analysis principles behind CRYSOUND's AI abnormal-noise algorithm, share practical test setups and real-world performance, and wrap up with a complete configuration checklist you can use to plan or validate your own deployment. Challenges Of Detecting Anomalies With Conventional Algorithms In real factories, true defects are both rare and highly diverse, which makes it difficult to collect a comprehensive library of abnormal sound patterns for supervised training. Even well-tuned—sometimes highly customized—rule-based algorithms rarely cover every abnormal signature. New defect modes, subtle variations, and shifting production conditions can fall outside predefined thresholds or feature templates, leading to missed detections (escapes). In the figure below, we compare two wav files that we generated manually. Figure 1: OK Wav Figure 2: NG Wav You can see that conventional checks—frequency response, THD, and a typical rub & buzz (R&B) algorithm—can hardly detect the injected low-level noise defect; the overall curve difference is only ~0.1 dB. In a simple FFT comparison, the two wav files do show some discrepancy, but in real production conditions the defect energy may be even lower, making it very likely to fall below fixed thresholds and slip through. By contrast, in the time–frequency representation , the abnormal signature is clearly visible, because it appears as a structured pattern over time rather than a small change in a single averaged curve. Figure 3: Analysis results Principle Of AI Abnormal Noise Algorithm CRYSOUND proposes an abnormal-noise detection approach built on a deep-learning framework that identifies defects by reconstructing the spectrogram and measuring what cannot be well reconstructed. This breaks through key limitations of traditional rule-based methods and, at the principle level, enables broader and more systematic defect coverage—especially for subtle, diverse, and previously unseen abnormal signatures. The figure below illustrates the core workflow behind our training and inference pipeline. Figure 4: Algorithm Flow Principle During model training, we build the algorithm following the workflow below. Figure 5: Algorithm Judgment Principle How To Use And Deploy The AI Algorithm Preparation First, prepare a Low-Noise Measurement Microphone / Low-noise Ear Simulator and a Microphone Power Supply to ensure you can capture subtle abnormal signatures while providing stable power to the mic. Figure 6: Low-Noise Measurement Microphone Next, you'll need a sound card to record the signal and upload the data to the host PC. Figure 7: Data Acquisition System Third, use a fixture or positioning jig to hold the product so that placement is repeatable and every recording is taken under consistent conditions. Finally, ensure a quiet and stable acoustic environment: in a lab, an anechoic chamber is ideal; on a production line, a sound-insulation box is typically used to control ambient noise and keep measurements consistent. Figure 8: Anechoic Room Figure 9: Anechoic Chamber Model Development First, create a test sequence in SonoLab, select "Deep Learning" and apply the setting. Next, select the appropriate AI abnormal-noise algorithm module and its corresponding API Figure 10: Sequence Interface 1 Then open Settings and specify the model type, as well as the file paths for the training dataset and test dataset. Click Train and wait for the model to finish training (Training time depends on your PC's hardware) Figure 11: Sequence Interface 2 During training, the status indicator turns yellow. Once training is complete, it switches to green and shows a "Training completed" message. Figure 12: Sequence Interface 3 Finally, place your test WAV files in the specified test folder and run the sequence. The model will start automatically and output the analysis results. Test Case Figure 13:Test Environment Figure 14:Test Curve System Block Diagram Figure 15: System Block Diagram 1 Figure 16: System Block Diagram 2 Equipment More technical details are available upon request—please use the "Get in touch" form below. Our team can share recommended settings and an on-site workflow tailored to your production conditions.
As A²B microphones and sensors are increasingly adopted in automotive applications, the demand for reliable testing in both R&D and production is also growing. This article explains why A²B testing matters, highlights the advantages of A²B over traditional analog cabling in terms of interconnect and scalability, outlines key measurement KPIs (such as frequency response, THD+N, phase/polarity, and SNR), and presents a typical test-bench setup along with the corresponding solution configuration. Why A²B Microphone and Sensor Testing Matters In-cabin audio is no longer just "music playback". Modern vehicles depend on high-performance acoustic sensing for hands-free calling, in-cabin communication, voice assistants, ANC/RNC, and more—and these features increasingly rely on multiple microphones and even accelerometers deployed around the cabin. ADI notes that the rapid expansion of audio-, voice-, and acoustics-related applications is a key trend, and that new digital microphone and connectivity approaches are enabling broader adoption. To deliver consistent performance, teams need a test workflow that is repeatable across different node positions, harness lengths, and configurations—without turning every debug session into a custom project. The Interconnect Shift: From Shielded Analog Cables to Digital A²B Historically, scaling microphone counts often meant scaling shielded analog cabling, which adds weight, cost, and integration burden—sometimes limiting these features to premium vehicle segments. A²B (Automotive Audio Bus) addresses that interconnect problem by enabling a scalable, networked digital audio architecture with deterministic behavior—exactly what timing-sensitive acoustic applications need. Figures a and b show how such a design may be realized with the traditional analog and the digital A²B systems, respectively. Figure 1 (a) Analog system design with analog mic elements (shielded wires). (b) Digital system design with digital mic elements (A²B technology and UTP wires). What You'll Measure: Key A²B Microphone KPIs Frequency Response (FR) THD+N Phase / polarity (and channel-to-channel consistency for arrays) SNR AOP (if required by your program/spec) Typical Block Diagram-What the Bench Looks Like At CRYSOUND, we provide more than just the CRY580 A²B interface. We offer a full automotive audio testing solution, including audio acquisition cards, microphones and sensors, acoustic sources, custom fixtures, acoustic test boxes, and vibration shakers, delivering a complete and streamlined testing experience. Figure 2 Here's a description of the testing block diagram, including the use of the latest OpenTest Audio Test & Measurement Software https://opentest.com Solution BOM List The value of end-to-end delivery: reducing system integration time and minimizing coordination costs between multiple suppliers. We cover everything from R&D to production line testing. Figure 3 BOM list of the solution If you'd like to learn more about A²B testing, please fill out the Get in touch form below and we'll reach out shoutly.
In the fields of acoustic research and industrial inspection, sound is no longer just a signal to be "heard",but information that can be "seen". How to visualize, analyze, and quantify sound has been a long-standing pursuit for research institutions and engineers alike. Today, leveraging its deep expertise in acoustics, CRYSOUND has launched the new SonoCam Pi product series—not just an acoustic camera, but an open acoustic platform, redefining the future of acoustic measurement and imaging. Making Acoustic Experiments Simpler And More Efficient In recent years, microphone arrays have been rapidly adopted in acoustic research. However, research institutions commonly face the following challenges: Traditional systems are expensive and offer a limited number of channels. Array design and algorithm development are complex and time-consuming. In-house array development lacks mature supply chains and integrated hardware-software support. To address these challenges, CRYSOUND leveraging nearly 30 years of expertise in acoustic testing and signal processing, has developed the SonoCam Pi platform—an affordable, open, and programmable acoustic solution. It enables researchers, engineers, and university students to enter the world of acoustic imaging and algorithm validation more quickly, flexibly, and cost-effectively. An Acoustic Development Platform For Research And Industry Hardware Highlights: Large Arrays & Multi-Geometry Adaptability 208-channel MEMS microphone array, supporting replacement and customization. Array diameters of 30 cm / 70 cm / 110 cm, enabling easy switching between near-field and far-field measurements. Wideband response from 20 Hz to 20 kHz, suitable for both precision lab testing and on-site measurements. Modular design, allowing rapid deployment and flexible expansion. SonoCam Pi product appearance Software Ecosystem: Open APIs & Algorithm Freedom Provides an API for 208-channel raw audio waveform data. Comes with a MATLAB acoustic imaging algorithm Demo App for rapid algorithm validation. Built-in acoustic imaging algorithms including Far-field Beamforming and Near-field Acoustic Holography. Supports secondary development, enabling users to build customized acoustic analysis tools. In short, SonoCam Pi is not just a hardware device—it is a complete platform for acoustic algorithm development and experimental validation. From Lab To Factory: Applications Of SonoCam Pi Acoustic Drone Detection Powered by array-based localization and identification algorithms, SonoCam Pi can accurately capture the acoustic signature of drones, enabling reliable low-altitude acoustic detection to support security monitoring and drone detection for site security. Drone detection Acoustic Research & Algorithm Development Research institutions can leverage SonoCam Pi's 208-channel raw-data API and MATLAB demo tools to rapidly validate research algorithms such as Far-field Beamforming and Near-field Acoustic Holography. Algorithm development Sound Propagation Path Analysis Supports directional analysis of both structure-borne and airborne sound propagation, helping researchers and engineers more intuitively understand the transmission mechanisms of noise sources. Sound propagation path analysis Automotive NVH Noise Inspection By combining beamforming and acoustic holography techniques, SonoCam Pi can quickly pinpoint interior and exterior noise sources, visualize acoustic radiation, and support NVH optimization as well as overall vehicle sound quality improvement. NVH research Open · Efficient · Intelligent: A New Start For Acoustic Research Whether for algorithm validation in university laboratories or noise diagnostics in industrial environments, SonoCam Pi has become a new-generation acoustic tool for both research and engineering practice, thanks to its outstanding performance, comprehensive ecosystem, and high level of openness. It makes acoustic measurement more portable, more intelligent, and more open—not only enabling users to see sound, but also empowering researchers to reshape the way sound is understood. SonoCam Pi is more than an acoustic camera; it is an acoustic application ecosystem platform. As technology and acoustic algorithms continue to evolve, CRYSOUND will keep advancing SonoCam Pi, enabling acoustic imaging to unlock new potential across more fields and working hand in hand with research and industrial users to explore the limitless possibilities of the acoustic world. If you'd like to learn more about the applications of CRYSOUND's SonoCam Pi, or discuss the most suitable solution for your needs, please contact us via the form below. Our sales or technical support engineers will get in touch with you shortly.
Valves are the "core control components" of pipeline systems. They perform four key functions—opening/closing, regulating, isolating, and directing—enabling precise control of fluid flow. Once sealing integrity fails, minor cases can lead to process upsets and energy losses, while severe cases may result in fires or explosions, toxic exposure, or environmental pollution. We built a valve leak application around the three things customers care about most on site—fewer missed detections and false alarms, better localization, and more reliable leak-rate estimation—by distilling them into an executable, traceable standardized workflow and closing the loop in the application for end-to-end deployment. Common Causes of Valve Internal Leakage What leads to valve leakage? We summarize it into the following four main causes: Normal wear and tear: Frequent opening and closing gradually wears the sealing surfaces; long-term scouring and erosion from the flowing medium can also degrade the seal fit. Process medium factors: Sulfur compounds and similar components in the medium can cause electrochemical corrosion; residual construction contaminants—such as sand, grit, and particles—can accelerate wear and scratch the sealing surfaces, leading to poor sealing. Improper operation and maintenance: Using an on/off valve for throttling, lack of routine cleaning and preventive maintenance, inadequate servicing, or improper/unsafe operation can all damage sealing surfaces or prevent full closure. Installation and management issues: Outdoor storage exposed to rain, ingress of mud and sand, and sandblasting/field conditions introducing grit or debris into the valve cavity can contaminate and scratch sealing surfaces, ultimately causing internal leakage. Figure 1. Illustration of Valve Internal Leakage When a valve is closed but the sealing surfaces do not fully mate, the pressure differential drives the medium to pass through small gaps from the high-pressure side to the low-pressure side, forming high-velocity micro-jets and turbulent flow. This leakage typically results in several observable signs, including sound/ultrasound, vibration, abnormal pressure behavior, and temperature anomalies or frosting. Figure 2. Symptoms of Valve Leakage Why Contact Ultrasound Works When a valve seal fails, high-pressure fluid passing through tiny gaps at the sealing surfaces generates turbulent flow, producing high-frequency ultrasonic signals in the 20–100 kHz range. The signal intensity is generally positively correlated with the leak rate—the larger the leak, the higher the amplitude. In the field, you can capture ultrasonic signals at measurement points upstream of the valve, on the valve body, and downstream, then apply algorithms to extract and analyze signal features to detect and localize internal leakage. Compared with traditional methods, temperature-based approaches are easily affected by heat conduction and are difficult to quantify; pressure-hold tests are time-consuming and poor at pinpointing the leak location; and listening by ear is inefficient, prone to missed detections and false alarms, and heavily dependent on individual experience. That's exactly why we launched this application—turning an experience-driven task into a standardized, process-driven workflow, supported by acoustics and data analytics. Figure 3. CRY8124 Acoustic Imaging Camera with IA3104 Contact Ultrasound Sensor Workflow and Key Capabilities More standardized workflow: turning on-site operation into guided testing In the CRY8124 valve leak application, the software features a standardized and visualized workflow. Operators follow on-screen prompts to place the contact ultrasound sensor on each measurement point in sequence and simply tap "Test". The results are displayed on the interface, and the algorithm automatically determines whether internal leakage is present after the test. Figure 4. Valve Leakage Detection Feature Page At the same time, the software provides standardized inputs for key parameters such as valve ID, valve type, valve size, medium type, and the upstream/downstream pressure differential. This means test results are easier to align across the same unit, different shifts, and different operators—making retesting and trend management much more consistent. Figure 5. Valve Leakage Detection Feature Page Smarter: automatic diagnosis + leak-rate estimation Our valve leak detection capability focuses on two key improvements: By analyzing the dB level at each measurement point and the features of the ultrasonic signal, the system automatically determines the internal leakage result based on algorithmic data, reducing reliance on manual interpretation. Built-in AI algorithms estimate the leak rate from ultrasonic features at the measurement points, providing a quantitative reference to support valve maintenance decisions. This is the core logic behind our emphasis on a "higher detection rate": when judgments rely less on subjective experience, missed detections and false alarms become far more controllable—especially in complex sites with many valves and multiple parallel branches. Application Scenarios Across different industries, there is a common need for valve leak detection: Figure 6: Application Scenarios Field Case Study Case : A Coal-to-Chemicals Plant in Inner Mongolia (Fuel Gas / Coal Gas System) Below is a real field test case of valve leak at a coal-chemical plant. Any internal leakage in fuel gas or coal gas systems can compromise isolation. If leakage exists, the downstream side may remain gas-charged, and the work area may still be exposed to risks of CO and sulfur-containing acid gases entering the zone—potentially leading to poisoning, fire, or even explosion hazards. Using contact ultrasonics, we performed on-site testing on the suspected valves, quickly identified the leakage points, and estimated the leak rate. This helped the customer turn "isolation confirmed" from an experience-based judgment into data-backed verification, prioritize corrective actions, reduce work risks caused by misjudged isolation, and ensure safer maintenance and stable operation. Figure 7. On-site Test Photos Valve type: Fuel gas compressor room bypass valve (butterfly valve). Test result: 19.8 L/min. Medium / pressure: Fuel gas (H₂, CO, CH₄), 3 MPa. Figure 8. Test Results Valve type: Fuel gas compressor room plug valve Test result: 1.7 L/min. Medium / pressure: Coal gas (mainly CO), 2.5 MPa. Figure 9. Test Results On-Site Test Method: Repeatable 5-Point Measurements Confirm Operating Conditions Ensure there is a pressure differential, and isolate interfering branches as much as possible. Key steps Close the valve to be tested. Open the upstream and downstream valves of the test section. Confirm a pressure differential between upstream and downstream gauges, and verify ΔP > 0.1 MPa. As shown in the figure below When testing Valve A for valve leakage: open Valves B and C, and close Valves A and D. When testing Valve B for valve leakage: open Valves A and C, and close Valves B and D. Figure 10. Valve Status Place Measurement Points (MP1–MP5) Cover upstream → valve core → downstream. MP3: Located at the valve core. MP2: Located 1–2 pipe diameters (D) upstream of the valve (place the point on the pipe wall away from the valve). MP1: Located upstream of the valve, 2–3D away from MP2. If space is limited, MP1–MP2 spacing can be shortened to 0.5D. MP4: Located 1D downstream of the valve (place the point on the pipe wall away from the valve). MP5: Located downstream of the valve, 1–2D away from MP4 (recommended on the pipe wall just after the valve flange). If space is limited, MP5–MP4 spacing can be shortened to 0.5D. D = pipe diameter Figure 11. Test Point Layout NoteFor small, flangeless threaded valves, the spacing between measurement points should be at least three pipe diameters (3D). Fugure12. Test Point Layout FAQ We've listed some common scenario-based questions about valve internal leakage to help you understand the application faster and choose the right solution more efficiently. Q1. How do I choose a Contact Ultrasound Sensor for pipelines at different temperatures? A1. We recommend the following sensor selection based on pipe surface temperature: For low-temperature pipes (below -20°C) or high-temperature pipes (above 50°C), use a needle-type Contact Ultrasound Sensor. For temperatures between -20°C and 50°C, use a ceramic Contact Ultrasound Sensor for signal capture. Q2. Which valves can be tested for valve leakage? A2. This method is suitable for valve leakage detection across a wide range of valve types, including: Gate valves Plug valves Globe valves Ball valves Check valves Butterfly valves Needle valves Pressure relief valves Pinch valves If your valve type is not listed above, please feel free to contact us. Q3. Can we still test if the valve and pipe are insulated? A3. If the insulation fully covers the valve and pipeline, testing may not be possible. You'll need to remove the insulation at the measurement area, or leave an opening of about 7 cm in diameter so the Contact Ultrasound Sensor can directly contact the pipe wall to capture the signal. Q4. What should we pay attention to regarding the pipe surface during data collection? A4. The Contact Ultrasound Sensor must make good contact with a solid surface to reliably capture ultrasonic signals propagating through the pipe. Large particles or debris between the sensor and the pipe surface can lead to inaccurate results. If the pipe wall is rusty, wipe off any large dust or loose particles on the surface before testing. Contact Us If you'd like to learn more about how CRYSOUND acoustics can be applied to valve leak detection, or if you want a more suitable inspection solution based on your on-site process conditions and acceptance criteria, please contact us via the form below. Our engineers will get in touch with you.
Sound Level Meter
This article presents a multi-channel sound level meter developed on the OpenTest platform and designed to meet the technical requirements of IEC 61672-1. By integrating the SonoDAQ data acquisition system with measurement-grade microphones, the system implements standard A/C/Z frequency weightings, F/S/I time weightings, and enables accurate measurement of standard acoustic quantities such as Lp, Leq, and Ln. The solution is applicable to a wide range of scenarios, including environmental noise monitoring, product noise testing, and automotive NVH applications. From Handheld Sound Level Meters to Multi-Channel Sound Level Measurement Platforms In acoustics and vibration testing, one fundamental question appears in almost every project: “How loud is it?” From office equipment and household appliances to automotive NVH and industrial machinery, regulations, standards, and internal quality criteria all rely on quantitative evaluation of Sound Pressure Level (SPL). Traditionally, this is done using a handheld sound level meter compliant with IEC 61672, placed at a specified position to read an A-weighted sound level for compliance checks and quality verification. IEC 61672 defines detailed requirements for sound level meters in terms of frequency weighting, time weighting, linearity, self-noise, and dynamic range, and classifies instruments into Class 1 and Class 2, with Class 1 having stricter requirements and being suitable for laboratory and type-approval testing. As product structures and test requirements evolve, engineers increasingly expect more than what a single handheld meter can offer: Measure multiple positions simultaneously to compare different locations or operating points Combine sound level data with spectra and octave-band analysis to quickly identify problematic frequency regions Synchronize sound level measurement with speed, vibration, temperature, and other physical quantities for NVH diagnostics Integrate sound level measurement into automated and batch test workflows, rather than relying on manual spot checks This leads to the demand for multi-channel sound level meters: systems that not only meet IEC 61672-1 Class 1 accuracy requirements, but also provide multi-channel capability, scalability, and automation. OpenTest, developed by CRYSOUND, is a new-generation acoustic and vibration test platform. Its dedicated Sound Level Measurement module, combined with CRY5820 SonoDAQ Pro front-end hardware and measurement microphones, enables multi-channel sound level measurements consistent with Class 1 sound level meters. Figure 1. From handheld sound level meters to multi-channel sound level measurement platforms IEC 61672: What Are We Actually Measuring? Meaning of Sound Pressure Level (Lp) Sound Pressure Level (SPL) is a logarithmic measure of the root-mean-square sound pressure prms relative to the reference pressure p0, which is 20 μPa in air, defined as: When prms=1 Pa, the SPL is approximately 94 dB, which is why 94 dB / 1 kHz is commonly used as the reference level for acoustic calibrators. Frequency Weighting: A / C / Z Human hearing sensitivity varies with frequency. IEC 61672 requires all sound level meters to support A-weighting, while Class 1 instruments must also support C-weighting. Z-weighting (Zero weighting, i.e. flat response) is optional. A-weighting (dB(A))Based on the 40-phon equal-loudness contour, with significant attenuation at low and very high frequencies. It is widely used in regulations and standards as an indicator correlated with perceived loudness. C-weighting (dB(C))Much flatter than A-weighting, with less low-frequency attenuation. It is suitable for evaluating peak levels, mechanical noise, and high-level events. Z-weighting (dB(Z))Essentially flat within the specified bandwidth, preserving the original spectral energy distribution, and useful for detailed analysis. While A-weighting dominates regulations, it is not a perfect psychoacoustic model. In cases involving strong low-frequency content, modulation, or tonal components, A-weighted levels may underestimate perceived annoyance.For design and diagnostic work, it is therefore recommended to combine C/Z weighting, octave-band spectra, and sound quality metrics. Time Weighting: Fast / Slow / Impulse IEC 61672 defines the following time weightings: F (Fast): time constant ≈ 125 ms, suitable for rapidly fluctuating sound levels S (Slow): time constant ≈ 1 s, suitable for observing overall trends I (Impulse): designed for impulsive signals, more sensitive to short-duration peaks Common sound level descriptors include: LAF / LAS / LAI: A-weighted sound levels with Fast / Slow / Impulse time weighting LCpeak: C-weighted peak sound level Energy-Based and Statistical Quantities: Leq, SEL, Ln IEC 61672 also defines commonly used acoustic quantities: Leq,T / LAeq,TEquivalent continuous sound level over a time period T, widely used in environmental and product noise evaluation. Sound exposure and sound exposure level: E, LE / LAE (SEL)Represent the total sound energy of an event, commonly used for aircraft, traffic, and single-event noise evaluation. Lmax / Lmin: Maximum and minimum sound levels under a specified time weighting Lpeak (typically LCpeak): Peak sound level based on peak sound pressure Statistical levels Ln (L10, L50, L90, etc.)Levels exceeded for n% of the measurement time, commonly used in environmental noise analysis. Band Levels: Octave and 1/3-Octave Bands Although octave-band filters are specified in IEC 61260, IEC 61672 aligns with them in terms of frequency response and standard center frequencies. Common analyses include: 1-octave band levels (e.g. 31.5 Hz–16 kHz) 1/3-octave band levels, offering finer frequency resolution for identifying narrow-band noise and structural resonances Together, these quantities define the full scope of sound level measurement—from instantaneous readings to time-averaged values, and from broadband levels to frequency-resolved analysis. Sound Level Measurement with OpenTest Setup: Building the Signal Chain from Source to Software Hardware Preparation Data acquisition front-endFor example, CRY5820 SonoDAQ Pro, a modular multi-channel data acquisition system supporting 4–24 channels per unit and scalable to thousands of channels. It features 32-bit ADCs, up to 170 dB dynamic range, 1000 V channel isolation, and ≤100 ns PTP/GPS synchronization accuracy, suitable for both laboratory and field acoustic and vibration testing. SensorsOne or more measurement-grade microphone sets (with preamplifiers), positioned at representative measurement or listening locations. Computer and softwareA PC with OpenTest installed and the Sound Level Measurement module licensed. Connecting Devices and Channels in OpenTest Launch OpenTest and create a new project. In Hardware Settings, click “+”; available devices (including those connected via openDAQ or ASIO) are automatically detected. Select the required acquisition devices (e.g. SonoDAQ) and add them to the project. In Channel Settings, add the microphone channels and configure sampling rate and input range. At this point, the signal chain Sound source → Microphone → DAQ → OpenTest is fully established. Calibration: Setting the Acoustic Reference To ensure absolute accuracy, each channel must be calibrated using a Class 1 acoustic calibrator. Open the Calibration dialog in OpenTest. Select the microphone channels to be calibrated. Mount the calibrator on the microphone and start calibration. Once the reading stabilizes, complete the calibration. OpenTest automatically updates the channel sensitivity so that the 94 dB SPL reference point is aligned. For comparison tests, a handheld sound level meter (e.g. CRY2851) can be calibrated using the same calibrator (e.g. CRY3018) to ensure both systems share the same acoustic reference. Measurement: Acquiring Sound Level Time Histories Switch to the Sound Level Meter module in OpenTest and select: Measurement channels Quantities to compute (Lp, Leq, Ln, etc.) Frequency weighting (A / C / Z, computed simultaneously) Typical operating conditions may include: Idle Typical load Full load For each condition: Stabilize the DUT at the target operating state. Start measurement in OpenTest. Monitor sound level time histories, octave-band plots, and FFT spectra in real time. Stop after sufficient duration and name the dataset accordingly. Each measurement is automatically saved as a dataset for later comparison and analysis. Figure 2. Multi-channel sound level measurement using OpenTest Reporting: From Data to Traceable Documentation After measurements, OpenTest’s reporting function can be used to generate structured reports: Project information, DUT details, operating conditions Selected acoustic quantities (Leq, Lmax, LCpeak, Ln, etc.) Company logo and test personnel information Raw waveforms and analysis results can also be exported for archiving or further processing. Figure 3. OpenTest sound level measurement report Comparison with CRY2851 Handheld Sound Level Meter CRY2851 is a Class 1 sound level meter compliant with IEC 61672-1:2013, supporting A/C/Z weighting, F/S/I time weighting, and a full set of acoustic parameters. Comparison procedure: Environment and operating conditionsLow-background laboratory or semi-anechoic room; multiple operating states. Calibration consistencyBoth systems calibrated with the same Class 1 calibrator (94 dB or 114 dB at 1 kHz). Sensor placement and acquisitionMicrophones positioned as closely as possible at the same measurement point. Result comparisonCompare LAeq, LAF, LCpeak, and other key parameters under identical weighting and time windows. Figure 4. CRY2851 vs. OpenTest multi-channel sound level measurement Typical Applications of the Sound Level Measurement Module Consumer Electronics / IT Equipment Evaluate the impact of cooling strategies on LAeq and LAFmax Combine sound level limits with sound power measurements Integrate FFT, 1/3-octave, and sound quality metrics Automotive NVH / Interior Acoustics Multi-position sound level measurement in the cabin Comparison across driving conditions Coupling with order analysis and sound quality modules Household Appliances and Industrial Machinery Supplement sound power tests with multi-point sound level monitoring Integrate into production lines using sequence mode Identify problematic frequency bands via 1/3-octave analysis Environmental and Long-Term Monitoring Multi-point statistical sound level evaluation (L10, L50, L90) Long-term data logging and remote access If you are already familiar with handheld sound level meters, the OpenTest Sound Level Measurement module effectively upgrades them into a system that is: Multi-channel Traceable (raw data + analysis + reports) Expandable, working seamlessly with sound power, sound quality, FFT, and octave-band analysis modules, and supporting automated test workflows. Welcome to fill in the form below ↓ to contact us and book a demo and trial of the OpenTest Sound Level Meter module. You can also visit the OpenTest website at www.opentest.com to learn more about its features and application cases.
Sound Quality
Learn how to measure Loudness (ISO 532-1), Sharpness, and Tonality (ECMA-74) with OpenTest — free, open-source software. Step-by-step guide for automotive NVH, consumer electronics & home appliances engineers. This article is for engineers working in acoustics and vibration testing. It introduces how to perform sound quality measurements in OpenTest based on the ISO 532 loudness standard and the ECMA-74 tonality evaluation methods. By measuring and comparing three key psychoacoustic metrics — Loudness, Sharpness, and Prominence (Tonality) — teams in consumer electronics, automotive NVH, home appliances and IT equipment can turn “how good or bad it sounds” into quantitative engineering data, and complete a standardized sound quality workflow on a single platform from data acquisition, through analysis, to reporting. Why Sound Quality Measurements Matter In traditional noise testing, we usually rely on dB values to describe how “loud” a device is. But more and more studies and real-world projects are reminding engineers that “loudness” is only part of the story. In automotive NVH, home appliances, IT equipment and consumer electronics, user acceptance of product sound depends much more on whether it sounds pleasant, sharp, tiring or annoying, not just the overall sound pressure level. Industry surveys also show that most manufacturers now treat “how good it sounds” as being just as important as “how quiet it is”, and they start paying attention to sound quality already in early design phases. At the same sound level, poor sound quality can significantly drag down overall product satisfaction. This is exactly why Sound Quality as a discipline exists: through a set of psychoacoustic metrics such as Loudness, Sharpness and Tonality/Prominence, it turns subjective impressions like “sharp”, “boomy”, “harsh” or “smooth” into data that is measurable, comparable and traceable, so engineering teams can go beyond noise control and truly design and optimize product sound around listening experience. Key Metrics in Sound Quality Measurement In engineering practice, sound quality is not a single number, but a set of psychoacoustic quantities. Commonly used metrics include Loudness, Sharpness, Roughness, Fluctuation Strength, Prominence/Tonality, etc. Figure 1 – Key metrics in sound quality measurement Loudness (ISO 532-1) Loudness and Loudness Level describe how loud a sound is perceived by the human ear, rather than just its sound pressure level in dB. Internationally, the ISO 532-1:2017 standard based on the Zwicker method is widely used for loudness calculation. It can handle both stationary and time-varying sounds and correlates well with subjective perception in many technical noise applications. From an engineering point of view, loudness has clear advantages over A-weighted SPL: It accounts for the ear’s different sensitivity to frequency (human hearing is more sensitive in the mid-high range) At the same dB level, loudness often tracks “does it feel loud or not?” more accurately Sharpness (DIN 45692) Sharpness reflects whether a sound is perceived as sharp or piercing. When the high-frequency content has a higher proportion, people tend to feel the sound is more “sharp” or “edgy”. Sharpness was standardized in DIN 45692:2009, and is typically calculated based on the specific loudness distribution from a loudness model, applying additional weighting in the higher Bark bands. The result is expressed in acum. In applications such as fans, compressors and e-drive whine, reducing sharpness often improves subjective comfort more effectively than just lowering the overall dB level. Roughness (asper) Roughness corresponds roughly to fast amplitude modulation in the 15–300 Hz range, which gives a “raspy, vibrating” impression — for example in certain inverter whines or gear whine where the sound feels like it is “shaking”. Unit: asper Classical definition: 1 asper corresponds to a 1 kHz, 60 dB pure tone amplitude-modulated at about 70 Hz with 100% modulation depth The deeper the modulation and the closer the modulation frequency is to the sensitive region (around 70 Hz), the higher the perceived roughness In engineering, roughness is often used to describe how much a sound feels like it is “buzzing” or “scratching”, and it is particularly relevant for subjective evaluation of technical noise in e-drive systems, gearboxes and compressors. Fluctuation Strength (vacil) Fluctuation Strength captures slower amplitude fluctuations — amplitudes that go up and down in the range of roughly 0.5–20 Hz, perceived as “pulsing” or “breathing”, with a typical peak sensitivity around 4 Hz. Unit: vacil A classical definition of 1 vacil: a 1 kHz, 60 dB pure tone with 4 Hz, 100% amplitude modulation In cabin idle “breathing noise”, or fans whose level periodically rises and falls, fluctuation strength is a key descriptor You can think of Fluctuation Strength and Roughness as two sides of the same “modulation” coin: Fluctuation Strength: slow modulation (a few Hz), perceived as “breathing” or “pulsing” Roughness: faster modulation (tens of Hz), perceived as “vibrating, raspy, grainy” Prominence / Tonality (ECMA-74) Many devices are not particularly loud overall, yet become extremely annoying because of one or two narrowband tonal components. These “sticking out tones” are usually quantified by Tonality / Prominence. In IT and information technology equipment noise, ECMA-74 specifies methods based on Tone-to-Noise Ratio (TNR) and Prominence Ratio (PR) to evaluate tonal prominence and to determine whether a spectral line is a “prominent tone”. Historically, these metrics come from psychoacoustic research and are now widely used in automotive, aerospace, home appliances and IT equipment to predict and optimize annoyance. For example, studies have shown that, with loudness controlled, Sharpness, Tonality and Fluctuation Strength are important predictors for the annoyance of helicopter noise. Why Sound Quality Is More Useful Than Just “Watching dB” In many projects, you may have already seen questions like these: Two fan designs have similar sound power levels, but one “sounds smooth” while the other has a clear whine After noise reduction, overall SPL is a few dB lower, but user feedback hardly improves On the production line, A-weighted SPL is used as the only criterion, and some “bad-sounding” units still slip through Fundamentally, that is because: Sound pressure level / sound power = “how much energy is there” Sound quality metrics = “how the ear feels about it” With metrics like Loudness, Sharpness, Roughness, Fluctuation Strength and Prominence, you can decompose vague complaints like “it just sounds uncomfortable” into: Which frequency region has too much energy (leading to high sharpness) Whether there is strong amplitude modulation (causing high roughness or fluctuation strength) Whether any tonal component is sticking out clearly above its surroundings (high tonality / prominence) In engineering iteration, these metrics can be mapped directly to: Structural optimization (stiffness, modes, blade shape, etc.) Control strategies (e.g. PWM frequency, fan speed curves and transitions) Material and noise treatment / isolation choices This gives you much clearer and more actionable directions than “just reduce dB”. Sound Quality Analysis in OpenTest As a platform for acoustics and vibration testing, OpenTest supports a complete sound quality workflow from acquisition → analysis → reporting. Fill in the form at the bottom ↓ of this page to contact us and get an OpenTest demo. Example Device: Office PC Fan Noise To make the process concrete, we use a very accessible device as our example: a typical office PC. Test objective: evaluate sound quality metrics of its fan noise under different operating conditions, in order to: Compare subjective noise performance of different cooling and fan control strategies Provide quantitative input to NVH reviews (e.g. does loudness exceed the target, is sharpness too high?) Build a foundation for further sound quality optimization (e.g. suppressing whine frequencies, smoothing speed transitions) Test environments might be: A semi-anechoic room / low-noise lab (recommended); or A quiet office environment for early-stage, comparative evaluation Measurement System: SonoDAQ + OpenTest Sound Quality Module On the hardware side, we use a CRYSOUND SonoDAQ multi-channel data acquisition system (for more detailed model information, please contact us), together with one or more measurement microphones placed near the PC fan or at the listening position, according to the test requirements. Figure 2 – SonoDAQ Pro multi-channel data acquisition system Of course, OpenTest also supports connection via openDAQ, ASIO, WASAPI and other mainstream audio interfaces, so you can reuse existing DAQ devices or audio interfaces for measurement where appropriate. On the software side, the Sound Quality module in OpenTest is one of the measurement modules. Combined with FFT analysis, octave analysis and sound level analysis, it can cover most standard audio and vibration test needs. Configuring Measurement Parameters After creating a new project in OpenTest, proceed as follows: 1. Channel configuration and calibration In Channel Setup, select the microphone channels to be used and set sensitivity, sampling rate and frequency weighting as required Use a sound calibrator (e.g. 1 kHz, 94 dB SPL) to calibrate the measurement microphones, ensuring that loudness and related metrics have a reliable absolute reference 2. Switch to the “Measure > Sound Quality” module Select the metrics to be calculated: Loudness, Sharpness, Prominence Set analysis bandwidth, frequency resolution and time averaging modes Optionally configure test duration and labels for different operating conditions Essentially, this step turns the “calculation definitions” in ISO 532, DIN 45692 and ECMA-74 into a reusable OpenTest sound quality scenario template. Acquiring Sound Data for Different Operating Conditions Once the test environment is set up and the parameters are configured, click Start to measure sound quality data under different operating conditions. Each test record is saved automatically for later analysis. Because sound quality focuses on how it sounds during real use, it is recommended to record several typical conditions, for example: Idle / standby (fan off or low speed) Typical office load (documents, multi-tab browsing, etc.) High load / stress test (CPU/GPU at full load) With this breakdown, engineers can clearly manage which sound quality result corresponds to which operating condition. Figure 3 – Overlaying multiple sound quality test records in OpenTest From Multiple Measurements to One Sound Quality Report After measuring multiple operating conditions (e.g. idle, typical office and full-load stress test), you can do the following in OpenTest. In the data set list, select the records you want to compare and overlay: Compare loudness curves under different conditions See whether sharpness spikes during acceleration or speed transitions Identify conditions where prominent narrowband tones appear (high prominence) In the Data Selector, save the associated waveforms and analysis results: Export .wav files for later listening tests or subjective evaluations Export .csv / Excel for further statistics or modelling Click the Report button in the toolbar: Enter project, DUT and operating condition information Select sound quality metrics and plots to include (e.g. loudness vs. time, bar charts of sharpness, spectra with marked tonal prominence) Generate a sound quality report with one click for internal review or customer submission Figure 4 – Example of a sound quality report in OpenTest The generated report includes measurement conditions and operating modes, key sound quality metrics such as Loudness, Sharpness and Prominence, as well as a comparison with traditional acoustic metrics (sound pressure level, 1/3-octave spectra, sound power, etc.), making it easier for project teams to discuss using a set of metrics that are both objective and closely related to perceived sound. Typical Application Scenarios You can build different sound quality test scenarios in OpenTest for different businesses, for example: Consumer electronics / IT equipment (laptops, routers, fans, etc.) Use loudness + sharpness + (where applicable) roughness to evaluate the “subjective comfort” of different thermal / fan strategies Compare sound quality across different speed curves or PWM schemes Automotive NVH / e-drive systems Use multi-channel acquisition to record interior noise and speed signals synchronously Combine order analysis with sound quality metrics to see how “sharp” an e-drive whine is and whether there is pronounced modulation causing roughness Home appliances and industrial equipment When sound power already meets standards, use sound quality metrics to further screen for “annoying noise”, instead of relying only on dB If you are building or upgrading your sound quality testing capabilities, you can use ISO 532 and ECMA-74 as the backbone and let OpenTest connect environment, acquisition, analysis and reporting into a repeatable chain. That way, each sound quality test is clearly traceable and much more likely to evolve from a single experiment into a long-term engineering asset. Welcome to fill in the form below ↓ to contact us and book a demo and trial of the OpenTest Sound Quality module. You can also visit the OpenTest website at www.opentest.com to learn more about its features and application cases.
CRY580 A²B Interface is a bidirectional bridge designed to connect the A²B (Automotive Audio Bus) ecosystem with standard test & measurement setups (e.g., SonoDAQ, CRY6151B, Audio Precision). This article explains what makes A²B testing challenging—most analyzers don’t have a native A²B interface—and how CRY580 solves it by encoding/decoding A²B streams and converting them into measurable Analog or S/PDIF outputs, while supporting multi-channel I²S/TDM audio paths for fast, repeatable validation. Faster Automotive Audio Testing with CRY580 One bidirectional A²B bridge for testing: apply an analog/digital test stimulus for A²B amplifier testing, and bring A²B microphone or accelerometer sensor streams out as analog or S/PDIF for measurement. The A²B Audio Bus Is Reshaping In-Vehicle Audio A²B technology enables cost-effective audio data transport over long distances, combining multichannel audio (I²S/TDM), control (I²C), and power delivery over affordable cabling. Bidirectional data transfer at 50 Mbps bandwidth Low and deterministic latency(50 µs) System-level diagnostics Slave nodes can be locally-powered or bus-powered Programmable using ADI's SigmaStudio® GUI Uses cost-effective cables(unshielded twisted pair) The Testing Pain: A²B Adds Performance—And Complexity Traditional audio analyzers do not include A²B interfaces, making it impossible to directly test A²B devices. To perform accurate testing, a dedicated A²B codec is required to decode and convert A²B audio signals into standard analog or digital formats for measurement and analysis. How Bridging to Measurements Works in Practice How A²B Technology and Digital Microphones Enable Superior Performance in Emerging Automotive Applications A²B Microphone A²B Accelerometer A²B Amplifier "Bridging" in practice means converting A²B audio signals into standard analog or digital formats for testing: for A²B amplifier testing, injecting analog/digital stimulus into the A²B bus; and for A²B sensor testing, extracting A²B audio data to analog or S/PDIF for measurement. The CRY580 serves as the ideal bidirectional test bridge, facilitating seamless conversion and measurement in both directions. Introducing CRY580: An A²B Interface Built for Automotive Testing The CRY580 is a versatile A²B interface designed to seamlessly bridge A²B networks with testing equipment. It provides both decoding and encoding capabilities, allowing for the efficient transfer of audio data between A²B devices and standard measurement systems. Whether you're testing A²B microphones, amplifiers, or sensors, the CRY580 enables smooth and reliable testing workflows, ensuring accurate results across a range of automotive audio applications. Who Buys CRY580 and What They Test OEM / Tier1 Audio Teams: Integration, debugging, and acceptance testing across A²B networks. A²B Microphone & Mic-Array Suppliers: Sensitivity, frequency response (FR), and phase consistency checks. A²B Amplifier / Audio Processor Suppliers: Amplifier testing with injected stimuli, as well as mapping and performance verification. Test Labs: Standardized A²B measurement processes and delivery. Manufacturing / EOL QC: Repeatable pass/fail testing with faster fault isolation. Typical Test Setups: More Than Just an Interface At CRYSOUND, we provide more than just the CRY580 A²B interface. We offer a full automotive audio testing solution, including audio acquisition cards, microphones and sensors, acoustic sources, custom fixtures, acoustic test boxes, and vibration shakers, delivering a complete and streamlined testing experience. Here’s a description of the testing block diagram, including the use of the latest OpenTest Audio Test & Measurement Software https://opentest.com The CRY580 A²B Interface can be used in conjunction with the Audio Precision. Digital Interface Analog Interface "Performing A²B microphone performance tests (Frequency Response, THD+N, Phase, SNR, AOP) in an anechoic chamber, using the CRY5820 SonoDAQ Pro, CRY580 A²B Interface, and other equipment.” Why CRYSOUND: A Complete Automotive Audio Test Ecosystem The value of end-to-end delivery: reducing system integration time and minimizing coordination costs between multiple suppliers. We cover everything from R&D to production line testing. BOM list of the solution CRY580 bridges A²B to mainstream test & measurement setups in both directions, turning complex in-vehicle audio validation into a faster, repeatable workflow from R&D to end-of-line production. To discuss your use case, system configuration, or a demo, please fill out the Get in touch form below and we’ll reach out shortly.
Spatial audio performance can vary significantly across devices—even when similar audio algorithms are used. This article explains the role of the IMU in spatial audio, outlines key IMU testing challenges, and introduces CRYSOUND's production-ready IMU testing solution based on a three-axis, three-degree-of-freedom (3-DoF) rotary table. You'll learn the working principles, test flow, and application scenarios to help ensure stable and consistent spatial audio performance in mass production. The Role of IMU in Spatial Audio: From Hearing Sound to Perceiving Space In recent years, spatial audio has become a key feature in TWS earbuds, over-ear headphones, and AR/VR devices. Users now expect more than conventional stereo sound—they want to perceive sound direction and distance in a natural, three-dimensional space. When the head turns, the sound source should remain fixed in space; when the head tilts or nods, the sound field should respond accordingly. To achieve this effect, a device must not only render spatial audio content, but also accurately understand how the user's head is moving in real time. This capability is enabled by the IMU (Inertial Measurement Unit). An IMU integrates gyroscopes and accelerometers to measure angular velocity, acceleration, and orientation. In spatial audio systems, it serves as the core sensor that tracks head motion and feeds motion data into spatial audio algorithms. If the IMU lacks accuracy or stability, or if it does not align well with the audio algorithm, users may experience common issues such as: Response latency: the sound field lags behind head movement, causing discomfort or even mild dizziness; Tracking drift: sound positioning gradually shifts over time and no longer remains spatially fixed; Instability and jitter: noisy IMU output causes audible fluctuations in sound position. As immersive audio, AR experiences, and spatial communication continue to evolve, audio devices are transforming from simple playback tools into intelligent perception systems. As a result, IMU stability and test quality have become foundational requirements for next-generation spatial audio products. Three Major Challenges in IMU Testing for Spatial Audio Despite the importance of IMU performance, testing and validating IMUs is often underestimated during development and mass production. In practice, the industry commonly faces three core challenges: Lack of objective test methods tailored to spatial audio Traditional audio testing focuses on metrics such as frequency response, distortion, and sensitivity. These methods are not suitable for evaluating dynamic spatial perception, and subjective listening tests or manual motion checks lack objective and repeatable standards. Inability to reproduce real head movements with high precision Spatial audio relies heavily on head movements such as turning, nodding, and tilting. Manual rotation cannot maintain consistent angles or speeds, nor can it reliably repeat motion patterns across devices. Without precise and repeatable motion simulation, IMU issues may go undetected before products reach users. Low testing efficiency, making full inspection impractical Manual testing is time-consuming and inconsistent. In mass production, it often forces manufacturers to rely on sampling inspection instead of full inspection, increasing the risk of quality variation. At their core, these challenges stem from the absence of a controllable, repeatable, and quantifiable IMU orientation testing method. Overview of CRYSOUND's Spatial Audio IMU Testing Solution To address these challenges, CRYSOUND has developed an IMU testing solution specifically designed for spatial audio and smart wearable applications. The goal is to provide an objective, automated, and production-ready testing approach. The system consists of: PC-based test software for test control, data acquisition, and analysis; A three-degree-of-freedom rotary table for simulating head motion; Communication interfaces (such as a Bluetooth adapter) for data exchange; Shielded enclosure and customized fixtures to ensure stable connections and safe device mounting. During a typical test, the host software establishes a connection with the device under test via Bluetooth or a wired interface, then sends commands to enable IMU data output. The rotary table sequentially moves to predefined orientations, while IMU data is collected and compared against reference angles. The entire process is automated, requiring the operator only to place the device and start the test, minimizing training effort and human error. Key Hardware: Why a Three-DoF Rotary Table Is Ideal for IMU Testing In spatial audio IMU testing, a three-degree-of-freedom rotary table provides a highly controllable and production-friendly solution. It accurately reproduces head movements across all three orientation axes and ensures consistent motion paths through programmatic control. Compared with manual operation or simplified mechanical setups, a 3-DoF rotary table offers higher repeatability, better control over angle and speed, and more stable test cycles—making it well suited for mass production environments where consistency and throughput are critical. The three axes correspond to common head motions: Yaw axis: simulates left-right head rotation; Pitch axis: simulates nodding movements; Roll axis: simulates head tilting. The rotary table achieves an absolute positioning accuracy of ±0.05° and a repeatability of approximately ±0.06°, providing a reliable reference for evaluating IMU orientation accuracy. System Features: How the Solution Addresses Real Production Needs Building on this hardware and automated workflow, CRYSOUND's IMU testing solution delivers value in several key areas: High-precision motion simulationServo-driven control and three-axis motion allow precise and repeatable reproduction of head movements, eliminating the uncertainty inherent in manual testing. Controlled test speed and production throughputWith a maximum rotational speed of up to 200°/s and efficient Bluetooth communication, a six-orientation IMU test can be completed in approximately 60 seconds per unit, making full inspection feasible in production. Objective and quantifiable evaluationIMU output data is directly compared against known reference angles, reducing reliance on subjective judgment. Test results can be exported as reports or raw data and support MES integration for production tracking and quality analysis. Typical Application Scenarios This IMU testing solution is designed for manufacturers working with spatial audio and smart wearable products, including: Bluetooth earbuds and headphones, especially TWS and over-ear models with spatial audio features; VR controllers or devices requiring multi-orientation consistency checks; Smartphones and other consumer electronics requiring gyroscope validation; Smartwatches and fitness bands for IMU calibration and production testing. If you'd like to learn more about IMU testing—or discuss your blade process and inspection targets—please use the "Get in touch" form below. Our team can share recommended settings and an on-site workflow tailored to your production conditions.
In industrial testing, research, and quality validation, data acquisition devices (DAQs / audio interfaces / measurement microphone front-ends) are the “front door” of the entire system. As technology and applications become more specialized, a wide variety of DAQ devices has emerged: High-precision front-ends designed specifically for acoustics and vibration General-purpose dynamic signal acquisition modules Common USB sound cards and measurement microphones Hardware is not the bottleneck anymore. The real challenge is: How do you connect, configure, and manage devices from different brands and protocols in one software platform? OpenTest is built around this pain point. With an open, multi-protocol hardware access architecture, it turns acquisition from “isolated devices” into a unified platform, enabling cross-brand, multi-device data acquisition and analysis. Multi-Protocol Hardware Access: Reducing Vendor Lock-In OpenTest supports several mainstream connection methods. You can choose the appropriate protocol based on your hardware type and driver environment (actual compatibility depends on software version and device drivers): openDAQ – For open DAQ integration. Used to connect open hardware such as CRYSOUND SonoDAQ and manage channels and acquisition parameters in a unified way ASIO / WASAPI / MME / Core Audio – Mainstream audio interfaces on Windows and macOS, supporting professional audio interfaces and USB measurement microphones such as RME, Echo, miniDSP, etc. Other proprietary protocols – Can be added according to project requirements This means you no longer need to be locked into a single hardware brand or a single piece of software. Existing devices can be brought smoothly under one platform for centralized management. Multi-Device Collaboration: One Project, Many Acquisition Tasks Complex tests often require multiple signal sources to be acquired together, for example: Dynamic signals such as microphones and accelerometers Operating parameters such as speed, temperature, pressure, torque Auxiliary audio paths for monitoring and playback With OpenTest’s multi-protocol architecture, you can manage multiple devices within the same project. For NVH and structural testing, this kind of cross-device collaboration significantly reduces repetitive work like: Recording in multiple software tools → exporting → manual time alignment → re-analysis Getting Started: Connecting Devices Quickly Connect your data acquisition device to the PC running OpenTest USB connection, or Network connection (ensure the device and PC are on the same subnet) In the Hardware Setup panel, click the “+” icon in the upper-right corner. OpenTest will automatically scan for connected devices Check the devices you want to use and click Confirm to add them to the active device list Switch to the Channel Setup list, click the “+” icon in the upper-right corner, select the channels required for the current project (channels from different devices can be combined), and click Confirm to add them to the project Select the channels; OpenTest will automatically start real-time monitoring and analysis. You can then switch to different measurement modules according to your test needs Presets + Fine Tuning: Easy to Start, Easy to Standardize To help teams enter the testing state quickly, OpenTest supports a “presets + adjustments” configuration approach: Turn commonly used hardware parameters and acquisition settings into reusable templates Apply templates directly when creating a new project to avoid starting from scratch Still keep full flexibility to fine-tune settings for different operating conditions and devices For production line or regression testing, templating adds an important benefit: uniform test conditions, comparable results, and traceable processes across time and across operators. Logging and Monitoring: Designed for Long-Term Stability For long-duration, multi-device acquisition, the worst case is discovering that something dropped out halfway. OpenTest provides observability features to address this: Device and channel status monitoring – Quickly detect disconnections, overloads, and abnormal inputs Operation and error logs – Record key actions and error events to support troubleshooting and process optimization This is especially critical for continuous production testing and durability tests, significantly reducing the chance of “realizing halfway through that nothing was actually recorded.” Typical Application Scenarios Acoustics and vibration R&D – Use the same platform to connect front-end DAQs and audio interfaces, quickly complete acquisition, analysis, and report generation Automotive NVH / structural testing – Acquire noise, vibration, and operating parameters together, minimizing cross-software alignment work Production line automated testing – Template-based configuration + monitoring/logging + automated reporting to improve consistency and traceability OpenTest’s goal is not to make you replace all your hardware, but to bring your existing hardware together on one platform so that data acquisition becomes more efficient, more controllable, and much easier to standardize. Visit www.opentest.com to learn more about OpenTest features and hardware options, or contact the CRYSOUND team for demos and application support.
sound power
Under regulations such as the EU Machinery Noise Directive, more and more products—from toys and power tools to IT equipment—are required to declare their sound power level on labels and in documentation, rather than simply claiming they are “quiet enough.” For typical office devices like notebook computers, idle noise is often around 30 dB(A), while full-load operation can approach 40 dB(A). These figures are usually obtained from sound power measurements performed in accordance with ISO 3744 and related standards. Sound Pressure vs. Sound Power A noise source emits sound power, while what we measure with a microphone is sound pressure. Sound pressure varies with room size, reverberation, and microphone distance, whereas sound power is the source’s own “noise energy” and does not change with installation or environment. That makes sound power a better metric for external product noise specification. In simple terms: Sound power is the cause – the energy emitted by the source (unit: W / dB); Sound pressure is the effect – the sound pressure level we hear and measure (unit: Pa / dB). ISO 3744 defines how to do this in an “essentially free field over a reflecting plane”: arrange microphones around the source on an enveloping measurement surface, measure the sound pressure levels on that surface, then apply specified corrections and calculations to obtain stable, comparable sound power levels. Device Under Test: An Everyday Notebook Computer Assume our DUT is a 17-inch office notebook. The goal is to determine its A-weighted sound power level under different operating conditions (idle, office load, full load), in order to: Compare different cooling designs and fan control strategies; Provide standardized data for product documentation or compliance; Supply baseline data for sound quality engineering (for example, whether the fan noise is annoying). The test environment is a semi-anechoic room with a reflecting floor. The notebook is placed on the reflective plane, and multiple microphone positions are arranged around it (using a hemispherical frame or a regular grid). Overall, the setup satisfies ISO 3744 requirements for the measurement surface and environment. Measurement System: SonoDAQ Pro + OpenTest Sound Power Module On the hardware side, we use SonoDAQ Pro together with measurement microphones, arranged around the notebook according to the standard. OpenTest connects to SonoDAQ via the openDAQ protocol. In the channel setup interface, you select the channels to be used and configure parameters such as sensitivity and sampling rate. From Standard to Platform: Why Use OpenTest for Sound Power? OpenTest is CRYSOUND’s next-generation platform for acoustic and vibration testing. It supports three modes—Measure, Analysis, and Sequence—covering both R&D laboratories and repetitive production testing. For sound power applications, OpenTest implements a sound-pressure-based solution fully compliant with ISO 3744 (engineering method), and also covering ISO 3745 (precision method) and ISO 3746 (survey method). You can flexibly select the test grade according to the test environment and accuracy requirements. The platform includes dedicated sound power report templates that generate standards-compliant reports directly, avoiding repeated manual work in Excel. On the hardware side, OpenTest connects to multi-brand DAQ devices via openDAQ, ASIO, WASAPI, and NI-DAQmx, enabling unified management of CRYSOUND SonoDAQ, RME, NI and other systems. From a few channels for verification to large microphone arrays, everything can be handled within a single software platform. Three Steps: Running a Standardized ISO 3744 Sound Power Workflow Step 1: Parameter Setup and Environment Preparation After creating a new project in OpenTest: In the channel setup view, select the microphone channels to be used and configure sensitivity, sampling rate, frequency weighting, and other parameters. Switch to Measure > Sound Power and set the measurement parameters: Test method and measurement-surface-related parameters; Microphone position layout; Measurement time; Other parameters corresponding to ISO 3744. This step effectively turns the standard’s clauses into a reusable OpenTest scenario template. Step 2: Measure Background Noise First, Then Operating Noise According to ISO 3744, you must measure sound pressure levels on the same measurement surface with the device switched off and device running, in order to perform background noise corrections. In OpenTest, this is implemented as two clear operations: Acquire background noiseClick the background-noise acquisition icon in the toolbar. OpenTest records ambient noise for the preset duration.In the survey method, OpenTest updates LAeq for each channel once per second;In the engineering and precision methods, it updates the LAeq of each 1/3-octave band once per second. Acquire operating noiseAfter background acquisition, click the Test icon. OpenTest will:a. Record notebook operating noise for the preset duration;b. Update real-time sound pressure levels once per second;c. Automatically store the run as a data set for later replay and comparison. Step 3: From Multiple Measurements to One Standardized Report After completing multiple operating conditions (for example: idle, typical office work, full-load stress): In the data set view, select the records you want to compare and overlay them to observe sound power differences under different conditions; In the Data Selector, click the save icon to export the corresponding waveform files and CSV data tables for further processing or archiving; Click Report in the toolbar, fill in project and device information, select the data sets to include, adjust charts and tables, and export an Excel report with one click. The report includes measurement conditions, measurement surface, band or A-weighted sound power levels, background corrections, and other key information. It can be used directly for internal review or regulatory/customer submissions, following the same idea as other standardized sound power reporting solutions. From a Single Notebook Test to a Reusable Sound Power Platform Running an ISO 3744 sound power test on a notebook is just one example. More importantly: The standardized OpenTest scenario can be cloned for printers, home appliances, power tools, and many other products; Multi-channel microphone arrays and SonoDAQ hardware can be reused across projects within the same platform; The test workflow and report format are “locked in” by the software, making it easier to hand over, review, and audit across teams. If you are building or upgrading sound power testing capability, consider using ISO 3744 as the backbone and OpenTest as the platform that links environment, acquisition, analysis, and reporting into a repeatable chain—so each test is clearly traceable and more easily transformed from a one-off experiment into a lasting engineering asset. Visit www.opentest.com to learn more about OpenTest features and hardware solutions, or contact the CRYSOUND team by filling out the “Get in touch” form below.
Electric motors are widely used in modern automobiles and home appliances (such as in-vehicle electric seats and appliance fans), and their smooth operation directly affects product quality and user experience. Motor noise issues are often summarized as BSR (Buzz, Squeak, and Rattle), which refers to abnormal sounds generated by automotive motors and related components. BSR has been a long-standing issue in manufacturing. It not only lowers the perceived quality of the product but also may signal problems such as bearing wear, loose parts, and other faults. Allowing defective products to reach the market can seriously damage brand reputation and user experience. Traditional "Manual Listening": Painful and Unreliable In the past, BSR detection usually relied on "manual listening," but human hearing has significant limitations: Subjective Misjudgment: When BSR noise is masked by background noise, the human ear cannot easily identify it. Judgments are based on experience, and results lack objective support. Unable to Quantify Analysis: The severity of BSR is difficult to quantify, making it difficult to establish clear quality standards. Low Efficiency and Fatigue: After prolonged testing, the human ear becomes fatigued, and detection accuracy declines, increasing the risk of defective products slipping through. Breaking the Bottleneck: Intelligent Solutions to Overcome Manual Limitations CRYSOUND, deeply rooted in the field of acoustic testing, has launched a BSR-based end-of-line (EoL) acoustic test solution for electric motors. By combining hardware, software, and AI, CRYSOUND has created a closed-loop testing process that gives motor abnormal sound detection an intelligent upgrade. Core Components: BSR Detection Hardware System + Testing Software Platform Soundproof Chamber: Creates a controlled, low-noise testing environment, blocking external noise that could disrupt BSR detection. Data Acquisition Module: Accurately captures sound and vibration data from the motor during operation, ensuring that even subtle anomalies are not overlooked. Algorithm Analysis: Processes, analyzes, and intelligently evaluates the captured signals, making BSR defects difficult to hide. Test Workflow: From Signal Capture to Intelligent Decision 1. First, sensors precisely capture sound and vibration signals, converting the sound of the motor into digital data. 2. Then, the system processes the data and automatically generates visual analysis results, clearly showing where abnormalities occur and how severe they are. 3. Finally, professional algorithms such as transient analysis, FFT spectrum analysis, and sound-quality evaluation are applied. With deep learning models, the system can automatically identify BSR caused by bearing wear, looseness, foreign-object interference, and other factors, greatly reducing human misjudgment and accurately separating good products from defective ones. Multi-Scenario Coverage: From Motors to High-End Manufacturing, Boosting Quality Control Across Industries This solution has been widely applied in the following areas: Motor Assemblies: BSR detection for various micro motors, drive motors, actuators, and other motor-related components. Automotive Parts: In the body domain—air-conditioning vents, seat systems/rails/motors, electric door handles, and other components; in the cockpit domain—HUD motors, display rotation mechanisms, electric sunroofs, and related parts; in the chassis domain—braking systems, steering systems, and associated components; in the autonomous driving domain—LiDAR modules and other systems requiring BSR evaluation. Home Appliances: BSR detection for motors and motorized components used in high-end household appliances and smart home devices. Others: Industrial scenarios requiring stringent sound quality assessment and high-precision BSR detection. Five Major Advantages: Making Quality Inspection Smarter AI Acoustic Detection: By replacing manual inspection with machines, detection becomes more objective and efficient and supports continuous, high-throughput operation in production environments. Accurate BSR Capture and Visual Presentation: The characteristics of BSR are visually displayed through data charts, making problems easy to identify at a glance. Supports Full EoL Testing, Traceable Results: All process data is retained, making quality traceability clear and compliant with regulations. Highly Integrated One-Stop Solution, Improved Production Efficiency: This highly integrated, one-stop solution streamlines the testing process and seamlessly connects to the production line, enhancing overall production efficiency. Helps Improve Yield and Reduce Customer Complaints: Ensures strict quality control, making it difficult for defective products to leave the factory and significantly reducing customer complaints. If you are interested in CRYSOUND's intelligent BSR noise detection solution or would like to discuss your specific testing needs, please fill out the "Get in touch" form below and our team will be happy to assist you.
In audio and vibration testing, engineering teams often find themselves jumping between multiple software tools and data acquisition systems from different vendors. Interfaces vary, workflows are fragmented, and new engineers can spend a significant amount of time just learning the tools before they can focus on the engineering problem itself. OpenTest, developed by CRYSOUND, is a next-generation acoustic and NVH testing platform designed for engineers, researchers, and manufacturers. Built around the principles of an open ecosystem, AI-driven intelligence, and high compatibility, it allows users to complete the entire workflow—from acquisition to reporting—within a single software environment. OpenTest supports three operating modes: Measure, Analysis, and Sequence, covering both laboratory validation and repetitive production testing. Core capabilities include real-time monitoring and analysis, FFT and octave analysis, sweep analysis, sound power testing, sound level meter functions, and sound quality analysis. The platform also provides standard test reports and dedicated sound power reports that comply with international standards. On the hardware side, OpenTest connects to a wide range of multi-brand DAQ devices via mainstream audio protocols such as openDAQ, ASIO, and WASAPI, as well as optional proprietary drivers such as NI-DAQmx, enabling unified management of CRYSOUND SonoDAQ, RME, NI, and other devices within a single platform. On the software side, its modular plugin architecture exposes interfaces for Python, MATLAB, LabVIEW, C++ and more, making it easy for teams to package in-house algorithms and domain applications as plugins and deploy them within the same environment. From Acquisition to Report: A Three-Step Quick-Start Workflow 1. Installation and Basic Connectivity – Let the Signals In Download the latest installer from the official website www.opentest.com and complete the installation. Connect your DAQ device to the PC; for your first trial, you can simply use the built-in PC sound card to run a quick test. In the OpenTest setup section, scan for available devices and select the devices and channels you want to use. Once added to the project, your basic connectivity is complete. 2. Run Basic Tests with Real-Time Analysis – See It First, Then Optimize In the channel management view, select the input/output channels you want to use and configure key parameters such as sensitivity, sampling rate, and gain. The system automatically activates the Monitor panel, where you can view real-time waveforms, FFT spectra, and key metrics such as RMS level and THD at a glance. When needed, you can enable the built-in signal generator to output excitation signals and use the recording function for long-duration acquisition, preserving data for later comparison and analysis. 3. Perform In-Depth Analysis and Reporting in the Measure Module – Turning Data into Decisions Switch to the Measure module to access advanced applications such as FFT analysis, octave analysis, sweep analysis, sound power testing, sound level meter, and sound quality—providing everything you need for deeper investigation. Use the data set functionality to review and overlay historical records, so you can compare different samples, operating conditions, or tuning strategies side by side. Waveforms and analysis results can be exported at any time. With the reporting function, you can generate test reports with a single click, closing the loop from test execution to final deliverables. Who Is OpenTest For? New acoustic and vibration test engineers who want to establish a complete workflow quickly using a single toolchain. Laboratories and corporate teams that need to manage multi-brand hardware and consolidate everything into one unified software platform. Project teams in automotive NVH, consumer electronics, and industrial diagnostics that require high channel counts, automation, and AI-enhanced analysis capabilities. Wherever you are on your testing infrastructure journey, OpenTest lets you start with a free entry-level edition and adopt an open, intelligent, and scalable ecosystem with a low barrier to entry. Visit www.opentest.com to explore detailed features, supported hardware, and licensing and plan options, and book a demo to see how OpenTest and CRYSOUND can help you build an efficient, open, and future-ready acoustic and vibration testing platform.
Monitoring and controlling noise are closely linked, with monitoring providing the means and control serving as the goal. Relying solely on monitoring has limited impact on improving acoustic environments. As an example, one of our customers discovered that conventional monitoring equipment alone was inadequate for pinpointing the noise source. The tendency for nearby noise sources to evade detection hampered effective control measures. The customer needed a solution for tracing noise sources, requiring detailed information on noise exceedance events to identify and manage the source and type of noise effectively. To address this, we created a targeted solution by incorporating noise localization devices and pan-tilt cameras. This enhanced monitoring platform combines directional data with video footage, providing a comprehensive view of noise exceedance incidents. The noise localization devices accurately locate the noise in both horizontal and vertical dimensions. Through further processing, they associate the intensity and spatial distribution of the noise over time. This enables the relevant personnel to trace the noise at key historical time periods and its corresponding directional information, significantly improving work efficiency. In addition, the cameras and tracing devices are interconnected. When noise exceeds the limits, the cameras can perform corresponding actions to track the noise source based on the directional information provided by the localization devices, while preserving relevant video recordings. Ready to monitor and control noise? We are here to help! Our team of experts can provide solutions for your noise monitoring and control application. Contact us to learn more below.
Partial discharge is a phenomenon that cannot be completely eliminated from high-voltage motors and generators. However, it is crucial to closely monitor and address partial discharge, as it can impact the performance of insulating materials. In the power industry, inspectors rely on observing the working status and performance of motors by studying the trend of partial discharge intensity in the generator. If the intensity of partial discharge in the generator shows an upward trend, it indicates a potential issue within the generator. At this point, it becomes necessary to analyze the underlying cause of this phenomenon and conduct a thorough examination of the motor's functionality. By taking proactive measures to address partial discharge, our clients can ensure the reliability and longevity of their generator systems. CRYSOUND's Acoustic Imager has proven to be an effective tool in detecting suspension discharge and surface discharge, assisting our clients in identifying and resolving potential problems early on. The CRYSOUND Acoustic Imager enables inspectors to analyze the intensity of partial discharge in the generator and closely monitor the functionality of the motors, thereby ensuring the safety of the environment. If you are facing similar challenges or have any questions related to partial discharge in generators, feel free to reach out to our team at CRYSOUND. We are here to provide expert guidance and support every step of the way. Contact us.
