Detecting Air Leaks with SoundCheck

Detect loudspeaker air leaks automatically with SoundCheck’s advanced analysis tools! In this video, we’ll show you how to use THD, Rub & Buzz, ePRB, eLP, and Crest Factor measurements to identify air leaks and port noise – no human listening required.

Additional Resources for SoundCheck

Detailed explanations of how to use SoundCheck can be found in the SoundCheck manual.

Video Transcript: Detecting Air Leaks with SoundCheck

Traditionally, loudspeaker enclosure air leaks are detected by human listeners during the final test process. SoundCheck’s algorithms can detect air leaks and characterize port noise automatically. Let’s take a look.

I’ve made recordings of a closed box speaker system with and without an audible air leak using a 60 Hz sinewave.  Let’s listen to them. First without the leak <play wav file> and then with the leak <play wav file>.  Looking at these two recordings in real time on a spectrum analyzer, we can see the spectrum of the speaker with the air leak has significantly higher harmonic content than the one without, particularly the odd order harmonics.

Now, let’s take a look at the SoundCheck algorithms that can detect the air leak. For these demos, I’ll recall previously saved waveforms for analysis. 

First, we’ll establish a baseline using a speaker without a leak.  We’re going to look at  THD, Rub & Buzz, enhanced Perceptual Rub & Buzz or ePRB, Enhanced Loose Particle detection or eLP and Crest Factor.

This display shows us these results, displayed on different graphs. As you would expect for a good speaker, THD, Rub & Buzz and Crest Factor are low, ePRB is below audible levels and there are no eLP events detected.

Now let’s analyze a recording where I’ve introduced an air leak by loosening the screws that secure the front baffle to the rear enclosure. THD and Rub & Buzz are significantly higher, ePRB is well above the audibility threshold of 12 phons and hundreds of eLP events have been detected.

These measurements were made with a microphone pointing at the side of the enclosure, the actual location of the airleak.  If we next analyze the results of the same sweep captured by an on-axis microphone, we’ll see that there is a much smaller delta between the leak and no leak data. 

Configuring pass/fail limits for any of these metrics is much easier using the side mic data so you can see that microphone location is critical for leak detection. If leaks are commonly coming from the front baffle, then a single, on-axis mic should detect them but if the leaks are coming from the back or sides of the enclosure, two or more microphones should be deployed. The good news is if you are doing this on a production line, although you need an extra microphone, the measurement can be made simultaneously with your other QC measurements.

It should be noted that this method may also pick up defects from other causes, but if you’re using it to reject faulty speakers, then that doesn’t really matter. 

These techniques can also be used in R&D for the characterization of port noise, allowing you to compare the results using ports of different shapes and sizes. 

Some of these methods may work better than others on your specific design so I’d recommend that you evaluate all of them with your own products, and focus on those that yield the most reliable results.