Özet:

Squeak and Rattle problems seriously affect the quality of the vehicles. In the adjustment stage of the automobile development process, engineers mainly rely on subjective evaluation to diagnose squeak and rattle noises, which is prone to misjudgment, missed judgment and time-consuming problems. There are gaps in relevant objective evaluation methods. This article proposed that speaker identification is used to identify squeak and rattle noises from the audio recorded in the test, to achieve objective and accurate results. In this paper, four kinds of squeak and rattle noise audios are used as samples, Mel Frequency Cepstrum Coefficient is extracted as feature vector to construct target Gaussian mixture models (GMM). The expectation, variance and correlation coefficient of the Gaussian mixture model can be calculated to describe the difference of multiple squeak and rattle noises. Using samples to judge accuracy rate, the results indicated that the acceptance accuracy rate reaches 100 %, and the rejection accuracy rate reaches more than 95 %.

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