Listen’s enhanced Loose Particles algorithm measures transient distortion independently of harmonic distortion, with correlation to human hearing and offering high accuracy, easy perception, and fast analysis. eLP is ideal for identifying transient distortion in any environment, like identifying rattling buttons in audio devices, and automotive Buzz, Squeak and Rattle (BSR) measurements. SoundCheck sequences can quantify measurements into an eLP event count, making limit setting reliable in production environments.
Measure transient distortion independently from Rub & Buzz distortion
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You can try this algorithm for yourself! Visit our enhanced Loose Particles page for all things eLP including methodology, algorithm research, and more
Learn more about enhanced Loose Particles
Listen founder and president Steve Temme, and support manager Steve Tatarunis, co-wrote a technical article on practical impedance measurement. The paper dives into both single channel and dual channel measurement methods, considerations, techniques, measuring thiele-small parameters, and more.
Did you know that SoundCheck’s new enhanced Loose Particle algorithm measures transient distortion independently of harmonic or Rub & Buzz distortion? This has many applications ranging from production line driver testing to detecting rattling buttons, wires, fasteners and other loose parts being vibrated by the loudspeaker driver, for example, in a car door or smart speaker.
This is really useful to help you find the root cause of many production line problems. It’s also really easy to correlate with what you hear. Let’s take a look.
This is a very simple set-up I have here, pretty much what you might use on a production line – a measurement microphone, SoundCheck, and an AmpConnect 621 audio interface with a built-in amplifier. I have 2 loudspeakers, a good one, and one that exhibits significant transient distortion.
Here’s the good one…
And here’s the bad one…
Let’s look at how our new enhanced loose particle algorithm analyzes them.
This one’s the good speaker. You can see a nice smooth response waveform.
And here’s the speaker with transient distortion – this actually has a loose solder bead trapped inside the voice coil gap. You can see these little glitches on the waveform, that’s the rattling solder bead.
In the first step of our algorithm, we remove the fundamental, leaving just the distortion artifacts. And we can play this through SoundCheck to listen to the recorded artifacts and correlate what you hear to the measured results. Here’s the good speaker… and here’s the bad one…. This really helps us understand how the measurement relates to what we hear, and helps us set limits.
Next we apply an envelope analysis to get a time domain measurement… you can see the energy in the recorded waveform, plotted against time. You can see the transient defects as random bursts of energy. And you can also see that we have a lot more defects in the bad-sounding speaker than the good one.
Now we calculate the Prominence of each of these energy bursts. In this context, prominence describes the magnitude of the peak relative to the adjacent minimums. It’s actually an established mathematical concept used in other branches of science, but we’re the first to apply this concept to audio measurements. This was actually the result of extensive research at Listen, in which we determined that the prominence of a peak reflects the impulsiveness of the distortion artifacts more accurately than the absolute magnitude of the peaks.
So, calculating the prominence results in a numerical magnitude for each event in the time envelope, and we then set a threshold – that’s the level above which the event will be counted as a transient artifact. I’m using 10dB – this is generally a good starting point, although it varies depending on the acceptable distortion for the product. And remember, to help with setting limits you can play back the filtered artifact waveform to correlate the prominence level with audibility.
Finally, we count the number of events that exceed the threshold over the measurement duration – you can see that the Loose Particle count for the bad speaker is 110, compared to 0 for the good speaker.
We use the loose particle count to set a pass/fail limit. This gives us reliable results under a variety of conditions because, in a typical fast production measurement, background noise events typically only occur once or twice compared to many loose particle transients. So as long as you set the limit according to your environment, you can always get reliable results.
So there we have it! This new transient distortion measurement, accurately and reliably detects transient distortion, analyzing it separately from harmonic and rub & buzz distortion. It’s accurate even with background noise, and easy to correlate to audibility. Limit-setting is easier than with other methods, and it also works well in applications beyond driver testing such as Buzz Squeak and Rattle measurements in cars, and rattling components in audio devices.