100 Things #96: Laser Displacement Measurement of a Loudspeaker

Laser displacement measurement is a technique for measuring the peak displacement of a loudspeaker diaphragm at various power levels, frequencies or both. Did you know that SoundCheck can easily be configured to include a laser signal path? This makes it easy to correlate diaphragm displacement with electrical impedance and audio artifacts. In this short video, we demonstrate laser displacement measurements of a loudspeaker.

Laser Displacement Measurement

Get Our Free Laser Displacement Measurement Test Sequence

Ready to try it for yourself? You can read more and download this laser displacement measurement sequence here.

More information on configuring SoundCheck for use with lasers is also available in the  SoundCheck Manual.

 

Video Script: Laser Displacement Measurement of a Loudspeaker

Displacement lasers can be used to measure the peak displacement of a loudspeaker diaphragm at various power levels, frequencies or both. Did you know that SoundCheck can easily be configured to include a laser signal path? This makes it easy to correlate diaphragm displacement with electrical impedance and audio artifacts. Let’s take a look.

First, we create a Laser Signal Path in Calibration and once that’s done, a new calibrated device file for the instrument.  The sensitivity of most lasers is expressed in Volts per Millimeter and in this case, our laser’s sensitivity is 100 volts per millimeter.  After creating custom units, we can enter the sensitivity value, select a hardware channel and we’re ready to measure!

In this sequence, we’re using a stepped sine sweep starting at 1 kHz and ending at 20 Hz, and  we’re also simultaneously measuring the impedance and frequency response of our speaker under test.  The recorded time waveform from the laser can be analyzed just like any other waveform but there’s one additional post processing step required after analysis, converting the displacement level from RMS to peak.

As you can see, configuring SoundCheck for laser measurements couldn’t be easier. The resulting data can be used to study the displacement of the speaker under test and can even be used in conjunction with other SoundCheck measurements to calculate more advanced metrics such as Thiele-Small parameters. You can learn more about advanced speaker measurements on our website, www.listeninc.com.

 

100 Things #95: Time Domain Waveform Filtering

Time Domain Waveform Filtering in SoundCheck lets you apply any filter to a signal in the time domain instead of the frequency domain. This enables you to apply a filter, such as an A-weighting filter, without affecting the peaks or crest factor of the signal. Filters can also be applied to any waveform in the memory list, such as the stimulus, response, or any intermediate waveform. Watch this short video to learn how standard and custom waveform filters are used.

Time Domain Waveform Filtering

Learn More About SoundCheck’s Advanced Features

Read on about more measurement features in SoundCheck.

More information is also available in the  SoundCheck Manual.

 

Video Script: Using Time Domain Waveform Filtering in SoundCheck

Waveform filtering in SoundCheck lets you apply any filter to a signal in the time domain instead of the frequency domain. This is required when you want to apply a filter, such as an A-weighting filter, without affecting the peaks or crest factor of the signal, e.g. peak sound pressure level, A-weighted. It can also be applied to any waveform in the memory list, such as the stimulus, response, or any intermediate waveform.

Both standard and arbitrary filters are available. Standard filters include lowpass, highpass, bandpass and bandstop filters. You can select the cutoff frequencies, and control the slope of the filter using the filter order. SoundCheck’s standard filters are implemented as IIR Butterworth filters, and are ideal for most applications where you need to attenuate certain frequency ranges. For example, you can use a high-pass filter to remove some low frequency background noise or remove dc offset. Alternatively, you might use a lowpass filter to attenuate alias frequencies that could cause your amplifier to clip at very high frequencies that are not of interest.

You can also create your own arbitrary waveform filter by applying any curve from the memory list to the waveform. This can be used to apply weightings such as K-weighting for loudness or a bandpass filter  to a speech stimulus. Or you can even specify your own custom weighting or equalization, for example to see what happens to a customer’s speaker when they boost the bass.

 

100 Things #94: Road Noise and Active Road Noise Cancellation Measurements

Road Noise and Active Road Noise Cancellation Measurements are easy with SoundCheck. Everyone’s familiar with measuring headphone active noise cancellation with SoundCheck, but did you know it’s also great for in-car measurements of road noise and evaluation of road noise cancellation systems? Simply connect the USB-powered AudioConnect 2 to your microphones and laptop, and start making measurements. Watch this short video to see how easy it is with this compact and cost-effective package.

Make Road Noise and Active Road Noise Cancellation Measurements

Learn more

Read more about in-car road noise measurements.

Learn more about automotive testing using SoundCheck.

 

Video Script: Road Noise and Active Road Noise Cancellation Measurements

Everyone’s familiar with measuring headphone active noise cancellation with SoundCheck, but did you know it’s also great for measuring active road noise cancellation and road noise reduction in cars?

In this application, you want to measure the road noise at the location of the driver or passenger ears. A simple and cost-effective way to do this is to position two microphones near the outside of your ears or use a Head and Torso simulator. Here, we attached two SCM microphones to a Listen hat using some clips – we call this a low-budget HATS. This has the added advantage that if you are out on real roads, you can measure in the driver’s position.

Our configuration is simple. The microphones are connected to an AudioConnect 2 audio interface for microphone power and signal conditioning. This is a great application for this interface, as it’s USB powered, so you don’t need a power outlet in your car – you can just run it off your laptop. The AudioConnect 2 is connected via a single USB cable to the computer that is running SoundCheck for analysis.

As you can see, it’s a compact setup that easily fits on your dashboard or passenger seat.

To measure road noise, we simply need to drive at a fixed speed, remain silent – that means no talking, coughing, or children in the back seat –  and record for a fixed period of time. You can then look at both the sound pressure level and the frequency spectra of the road noise.

To evaluate a road noise reduction system, simply repeat the measurement with the noise cancellation turned on and subtract one result from the other to provide a value for the noise-reduction system of the car.

This is just one of many automotive audio measurements you can make with SoundCheck. Others include end of line QC, evaluation of components, tuning, Max SPL, impulsive distortion, Buzz, Squeak and rattle, POLQA analysis of communications systems and more. Check out the automotive section of our website for more information.

 

 

100 Things #93: Group and Batch Processing of Data Curves

Group and Batch Processing is a really neat feature in SoundCheck that saves huge amounts of time when processing data. Curves, values and waveforms can be grouped and processed together, and the analysis, post processing or statistics runs almost as quickly as on a single piece of data. This can be done during a sequence, or offline with previously collected data. It even extends to imported data – for example, if you want to run a POLQA analysis on a batch of recordings made in a different system, you can simply import the wav files and calculate scores for hundreds or even thousands of waveforms all at once.

Save Time Processing Data with Group and Batch Processing

Learn more

Read our Knowledgebase Article on using batch processing.

Learn more about the POLQA module in SoundCheck (video contains a demo of batch processing).

 

Video Script:

Audio test and measurement involves collecting and analyzing a lot of data. You might have multiple inputs and outputs, or you need to collect data not just once but over and over again. Perhaps you’re averaging measurements on a single unit over multiple runs, or testing multiple units in a production facility. Handling and processing all this data efficiently, in realtime, can be complex.

SoundCheck processes large groups of data quickly and easily with its group and batch processing capabilities. Curves, values and waveforms are grouped and processed together, and the analysis, post processing or statistics runs almost as quickly as on a single piece of data.

This is useful, for example, if you’re repeating a series of sequence steps on a single device, to calculate the deviation in its response at various positions, or if you’re averaging sensitivity values of a batch of 15 microphones for a spec sheet.

Groups of data can be analyzed and processed either within a test sequence or offline.

In a sequence, groups of data can be automatically created, saved in the Memory List and automatically analyzed together the same way every time the sequence is run. Here’s a simple example sequence where I capture recordings using a 6 mic array, group the recorded waveforms and use a single analysis step to get responses from each of the microphones. The same process can also be used in post processing or limit steps. SoundCheck also makes it easy to keep track of your data by allowing you to append your data names with Signal Path and Input data names.

Data processing outside of a sequence is known as “offline mode” – let’s take a look at an example. Here, I’ll group the frequency responses of 5 microphones I measured previously and calculate their sensitivity values at 1kHz in a single post processing step, rather than using 5 such steps. Note how fast it is in both cases!

SoundCheck’s batch processing capabilities even extend to imported data. For example, if you want to run a POLQA analysis on a batch of recordings made in a different system, you can simply import the wav files and calculate scores for hundreds or even thousands of waveforms all at once.

SoundCheck’s batch processing capabilities handle large amounts of data extremely fast, helping both R&D labs and production facilities to reduce test times. To learn more about SoundCheck’s extensive audio measurement toolkit, check out www.listeninc.com.

 

Steve Temme Featured on THD Podcast (Part 2) – Transient Distortion and more

In the second of a 2-part series on the THD Podcast, Steve Temme continues his discussion about why its important for engineers to be able to correlate audio measurements to audibility. He demonstrates Listen’s latest transient distortion algorithm, which offers the unique ability to listen to the recorded waveform with the stimulus removed so that just the distortion artifacts can be heard. This aids understanding of the measurement and makes it very easy to set limits.

THD Podcast #92: Steve Temme discusses Transient Distortion Measurement (Loose Particles)

Additional Resources for Transient Distortion Measurement

All about the Transient Distortion measurement algorithm discussed in this Podcast.

More about SoundCheck’s audio measurement algorithms.

 

More about Steve Temme and the History of Listen, Inc.

SoundCheck Innovation Timeline – highlights of Listen’s product and algorithm introductions.

Reflections on Listen’s 25th Anniversary (2020) – Reprint of an article from Loudspeaker Industry Sourcebook.

 

About the THD Podcast

The Total Harmonic Discussion / the THD Podcast, hosted by Dave Lindberg and Simon Weston, is a weekly discussion on audio and headphone technologies and the people who bring the technology to market. All episodes can be found on its Youtube Channel, and it’s also available on Spotify, Amazon Music, iHeartRadio, Rumble, BitChute, Limited, Apple, and Google.

 

100 Things #92: Continuous Log Sweep with Time Selective Response Analysis

Did you know that SoundCheck was the first audio test system to implement the continuous log sweep stimulus, way back in 2001. Also known as a frequency log sweep, or Farina sweep, this stimulus is used with time selective response (TSR) analysis. TSR analysis allows reflections to be windowed out, making it great for loudspeaker simulated free field measurements and room acoustics measurements. It’s also valuable as a smart trigger for robust open loop measurement testing. Watch this video for a quick overview.

Continuous Log Sweep with Time Selective Response Analysis

Learn more

Read on about stimulus and analysis capabilities in SoundCheck.

 

Learn more about Simulated Free Field Measurements

Short Video Demonstration of free field measurements without an anechoic chamber

Full-length Demonstration of free field measurements without an anechoic chamber

Article explaining simulated free field measurements (reprinted from Voice Coil Magazine)

The Original 1992 paper introducing the Simulated Free Field Measurement Technique

 

Learn more about room acoustics measurements using the Log Sweep Stimulus

Full-length Demonstration of Room Acoustics measurements

 

Video Script:

Did you know that SoundCheck was the first audio test system to implement a continuous log sweep stimulus? We introduced it back in 2001,  shortly after Angelo Farina’s landmark AES paper on the subject. Let’s take a look at how it works and how it’s used.

A continuous log sweep, sometimes known as a frequency Log sweep or Farina sweep,  is a continuous sine sweep with equal time and energy in every octave. Since it sweeps slower at low frequencies but speeds up as the frequency increases,  it’s a great choice for fast measurements. It differs from a conventional stepped sine stimulus, in that the continuous log sweep plays across all frequencies in the range with a defined sweep rate per decade, whereas the stepped sine sweep “steps” through different frequencies across the range.

Both stimuli can measure frequency response and harmonic distortion, but the analysis methods differ. A continuous log sweep uses a time selective response, or TSR analysis. This involves calculating an impulse response and applying a user-defined time window that can isolate or  remove any reflections caused by the test environment. A stepped sine requires a HarmonicTrak analysis. Only the continuous log sweep with TSR analysis can window out reflections, allowing a simulated free field measurement even when you are not in a fully anechoic environment.

Let’s take a look. In the TSR analysis step, we’ll enable this checkbox here to output an impulse response to the memory list so we can view it. It can be displayed either on a linear or logarithmic scale.  The window size at the top is where we define the start and stop points of the window that’s applied to the impulse response. We can look at this in SoundCheck to help us decide which points to use. Here, we can clearly see a large impulse that has been autodelayed to 0 seconds to show the direct sound from our sound source. And because we’re in a non anechoic environment, just a normal room, you can see reflections from the walls, floor, ceiling, table etcetera.  in the impulse response. We can adjust the window to remove them, and you can see the frequency response updates. 

This technique is very powerful, but like all techniques there are tradeoffs. So Log TSR analysis might not be the best option for all applications. The measurement resolution is affected by the window size – as the window size narrows,  the frequency resolution reduces, and you can see the effects on the frequency response. This is particularly noticeable at the lower frequencies where  the lack of resolution can make the data inaccurate if the window is too small. We need to be careful to configure the window size to capture the direct sound but be wide enough to get the greatest frequency resolution, without any reflections due to the test environment.

TSR Analysis  offers significant benefits for several applications. We use it for the high frequency measurements in a loudspeaker simulated free field measurement, which we can then splice together with the low frequency Stepped Sine Sweep stimulus measurement. It’s also valuable for room acoustics, for example, for calculating RT60 and clarity measurements. And if you’re running open loop tests, our cross-correlation smart trigger uses a continuous log sweep to provide a way of triggering an open loop measurement that is extremely robust and far less susceptible to false triggers than other methods. 

To learn more about the applications of a continuous log sweep stimulus, check out the technical papers and demo videos on our website.

Steve Temme Featured on THD Podcast – Perceptual Distortion and More

Steve Temme recently featured on the THD Podcast. In this engaging episode, he discusses his 30+ year career in audio measurement and some of the changes he’s seen in that time. He also talks about the importance of understanding measurements and being able to correlate measurements to audibility. He also demonstrates the latest in perceptual distortion measurement algorithms, and explains how they improve production line yield while still maintaining product quality.

THD Podcast #91: Steve Temme discusses correlation of audio measurements with audibility

Additional Resources for Perceptual Distortion Measurement

All about the enhanced Perceptual Rub & Buzz measurement algorithm discussed in this Podcast.

More about SoundCheck’s audio measurement algorithms.

 

More about Steve Temme and the History of Listen, Inc.

SoundCheck Innovation Timeline – highlights of Listen’s product and algorithm introductions.

Reflections on Listen’s 25th Anniversary (2020) – Reprint of an article from Loudspeaker Industry Sourcebook.

 

About the THD Podcast

The Total Harmonic Discussion / the THD Podcast, hosted by Dave Lindberg and Simon Weston, is a weekly discussion on audio and headphone technologies and the people who bring the technology to market. All episodes can be found on its Youtube Channel, and it’s also available on Spotify, Amazon Music, iHeartRadio, Rumble, BitChute, Limited, Apple, and Google.

100 Things #91: Measurement of Intermodulation Distortion

Intermodulation Distortion measurements are a great alternative to harmonic distortion for measuring narrowband devices such as hearing aids and communication devices. In such devices, harmonic distortion measurements tend to underestimate the distortion as the higher-order harmonics fall outside the pass band of the device. In this short video, Steve Temme demonstrates and explains the two IM distortion measurement options in SoundCheck – intermodulation distortion and frequency distortion and discusses how they can be used for low frequency speaker measurements, narrowband devices and microphones.

Measurement of Intermodulation Distortion

Learn more

Read on about more analysis capabilities in SoundCheck.

Video Script:

Although harmonic distortion is perhaps the most commonly measured distortion metric, it’s often not ideal for measuring narrowband devices such as hearing aids and communication devices. These products often have a high frequency cut-off around 3-5 KHz, so the higher-order harmonics fall outside the pass band of the device, so harmonic distortion measurements often underestimate the distortion.

A useful alternative we offer in SoundCheck is intermodulation distortion. Intermodulation distortion relies on the interactions between two simultaneous pure tones to produce measurable intermodulation products. These measurements actually present a more realistic representation of real-world signals such as speech and music that are rich with intermodulation products than the single tone used in harmonic distortion

SoundCheck offers two intermodulation distortion measurement options – Intermodulation Distortion and Difference Frequency Distortion. For Intermodulation Distortion, we superimpose a sweeping frequency tone against a fixed frequency tone. For Difference Frequency measurements, we use a stimulus consisting of two sweeping tones separated by a specified frequency interval, which can be a fixed difference or a fixed ratio. These are fully customizable.

In both cases, the two signals interact to produce intermodulation products. With Intermodulation Distortion, these are equal to the sum and difference of the upper frequency and integer multiples of the lower frequency. Difference Frequency distortion, only considers the components that are the difference and multiples of the difference, between the excitation frequencies.

Each type has its own specific applications. For example, Intermodulation distortion is mostly used for loudspeaker measurements, particularly at low frequencies, and Difference Frequency distortion is ideal for testing narrowband devices as the frequencies can be chosen so that the intermodulation products mostly fall within the pass band. This is easy to do in SoundCheck – simply configure your two test stimuli, and select your analysis – either Intermodulation Distortion, or Difference Frequency Distortion – in the analysis editor.

Intermodulation distortion is also a valuable technique for measuring microphones. Usually, the harmonic distortion from the source speaker playing the test tone is greater than the harmonic distortion that you are trying to measure from the microphone. However, if separate test tones are fed individually to two separate loudspeakers, the loudspeaker’s harmonic distortion has no influence on the measured intermodulation frequency components, enabling accurate measurement of the microphone’s intermodulation distortion.

To learn more about intermodulation and other types of distortion, check out our website, and stay tuned for a new in-depth seminar on distortion.

100 Things #90: Curve Smoothing

Curve smoothing in SoundCheck allows for non-destructive processing of data, resulting in smooth and easy to visually understand curves. Curve smoothing can lessen the effects of reflections in the test space, reduce noise, or make curves less jagged for publishing data. The smoothing post processing step in SoundCheck features an array of different, to facilitate different levels of the smoothing process, including various smoothing widths and windowing options.

Curve Smoothing

Learn more about SoundCheck post processing options

SoundCheck has a full suite of post processing capabilities including curve smoothing, resampling, resolution, curve arithmetic, and more.  Read more details in our SoundCheck features and applications section.

Each sequence uses a stimulus configured to the device under test, and recommended hardware.

Video Script:

Curve smoothing, as its name suggests, is a useful post-processing option that turns your jagged lines into smooth curves. It  may be applied to a curve for a number of reasons – to reduce the appearance of noise in the signal, to minimize reflections and other artifacts from the measurement environment, or simply to make a curve look better for presentation in sales and marketing literature. When smoothing is applied, the points of the curve are modified so that individual points that are higher than the immediately adjacent points are reduced, and points that are lower than the adjacent points are increased.

SoundCheck uses sliding-average smoothing also known as “boxcar” averaging where each point in the curve is replaced by the average of n adjacent points where n is a positive integer known as the smoothing width.  SoundCheck supports standard 1/n octave smoothing widths from one octave to 1/24th octave as well as user defined log and linear values.  In addition to a default rectangular window, a Hanning window may also be applied during the smoothing function. Smoothing is symmetrical at the midpoints of the curve but tapers to zero at the curve’s end-points.  If the curve has uneven or non-standard spacing in the frequency domain, interpolation is used.

In addition to the standard Smoothing post-processing step, the smoothing function is also available in the Resolution post-processing step. This is useful when the final curve resolution is higher than or “not a mathematical factor” of the original resolution.

This feature’s been available in Soundcheck since it was launched in 1995. If you haven’t tried it yet, check it out!

100 Things #89: Apply Equalization To A Test Stimulus

Did you know you can equalize a stimulus in SoundCheck to remove the influence of hardware and components from your measurements? All of SoundCheck’s stimulus options can have EQ applied, include Stweep, waveforms, noise, and more. An EQ can also adjust a stimulus to focus on different frequencies, like boosting low or high frequencies for power testing. THD+N measurements benefit from this ability, as even applying a flat EQ curve to a Stweep smooths out frequency transitions.

Apply Equalization To A Test Stimulus

Learn more about SoundCheck stimulus flexibility

The stimulus is just one part of the completely flexible SoundCheck system. Learn more about SoundCheck’s features and applications.

If you want to try for yourself, our SoundCheck sequence library includes applications from measuring loudspeakers to microphones, VR headsets to cars, and more. Each sequence uses a stimulus configured to the device under test, and recommended hardware.

Video Script:

Did you know you can equalize any stimulus inside SoundCheck during its playback? In any test application, it is important to ensure that the inherent characteristics of the measurement hardware do not influence the measurement. For example, if you’re using a source speaker to measure a DUT microphone, you don’t want the loudspeaker’s frequency response to influence the measurement. You may also want to apply your own custom EQ curve to weight certain frequencies different, for example, boost low frequencies more than higher frequencies for power testing. You can import whatever EQ you prefer.

We can also equalize the source speaker using a reference microphone. First, we measure the speaker’s response, then invert it to give us the EQ curve. This curve can then be applied to any stimulus playing through the source speaker to correct for both magnitude and phase non-linearities.

When you check the ‘Apply EQ’ checkbox in SoundCheck’s stimulus step, the EQ curve is applied to the stimulus and saved to the memory list, ready for playback during the acquisition step.

This feature is available for all stimulus step types. For step-based stimuli such as Stweep and Multitone, where the stimulus doesn’t have all frequency components, EQ is applied only at those frequency points that are present. For Broadband stimuli like speech, music and Noise, ‘Apply EQ’ behaves like a time waveform filter.

There’s also another reason why you might want to use EQ in a step based stimulus such as a Stweep. When EQ is applied, even if there is no EQ curve, the transition from frequency step to frequency step is smoothed. This is particularly helpful for measurements such as THD+N, which are sensitive to ringing.

Naturally, ‘Apply EQ’ can be turned off if you want to characterize the speaker itself.

SoundCheck’s stimulus step provides many advanced options for a wide range of use cases. To learn more, check out our website or speak to your local sales engineer.