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An Algorithm For Tick Detection An investigation was made of a sample of automotive components where some were exhibiting a high frequency “tick” or rattle during each operating cycle. This feature could be heard above the normal operating noise. The problem this posed was to measure and analyze components in an objective fashion and classify components as “good” or “bad”. Armed with a P8004 and DATS software, the Prosig engineers went to work. Prosig Case Study WWW.PROSIG.COM THE EXPERTS IN NOISE & VIBRATION MEASUREMENT

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Page 1: THE EXPERTS IN NOISE & VIBRATION MEASUREMENT An Algorithm For Tick …prosig.com/wp-content/uploads/pdf/caseStudies/prosigTick... · 2013. 5. 29. · components that exhibited the

An Algorithm For Tick Detection

An investigation was made of a sample of automotive components where some were exhibiting a high frequency “tick” or rattle during each operating cycle. This feature could be heard above the normal operating noise. The problem this posed was to measure and analyze components in an objective fashion and classify components as “good” or “bad”.

Armed with a P8004 and DATS software, the Prosig engineers went to work.

Prosig Case Study

WWW.PROSIG.COM

THE EXPERTS IN NOISE & VIBRATION MEASUREMENT

Page 2: THE EXPERTS IN NOISE & VIBRATION MEASUREMENT An Algorithm For Tick …prosig.com/wp-content/uploads/pdf/caseStudies/prosigTick... · 2013. 5. 29. · components that exhibited the

Contact ProsigProsig Ltd (UK)Email: [email protected]: +44 (0)1329 239925

Prosig USA IncEmail: [email protected]: +1 248 443 2470

THE EXPERTS IN NOISE & VIBRATION MEASUREMENT

An Algorithm For Tick DetectionAn investigation was made of a sample of automotive components where some were exhibiting a high frequency “tick” or rattle during each operating cycle. This feature could be heard above the normal operating noise. The problem this posed was to measure and analyze components in an objective fashion and classify components as “good” or “bad”.

A microphone was mounted on the test jig to verify that the sound could be recorded sufficiently well to discriminate the two conditions. That is, could the “tick” on bad components be heard on the recorded signal. After capture, the two signals were replayed through headphones and it was established that the “tick” was still prominent in the recorded signal. The time histories from the microphone were examined. Both looked very similar and it is clear that there are no particular features that would aid in classifying the problem.

F r e q u e n c y spectra were created from the recorded signal. It quickly became clear that there was more energy in the signal with the “tick”. However it was spread over quite a large frequency range.

Having established that most of the difference was in the 5000 - 15000Hz range a filter was applied and the spectra recalculated. When viewed on a linear vertical scale (as opposed to a logarithmic dB scale) it became easy to distinguish those components that exhibited the “tick” noise.

P800424-bit data acquisition system

2 x P8004 System

DATSAnalysis software

1 x DATS Toolbox software

System consists of

WWW.PROSIG.COM

Want to know more?You can read a more detailed write up of this application on the Prosig Noise & Vibration Measurement Blog. Use the QR code to the left or go tohttp://blog.prosig.com/2010/08/23/developing-an-algorithm-for-tick-detection/