Different Threshold Wavelet Denoising Methods Applied In Centrifugal Fan Characteristic Signal Analysis

Wavelet denoising and the separability index of state feature class are proposed to evaluate the denoising effect. While introducing the Fisher standard discriminant rate F to measure class separability, the Fisher standard discrimination rate of each characteristic parameter after noise detection b...

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Bibliographic Details
Published in2020 15th Symposium on Piezoelectrcity, Acoustic Waves and Device Applications (SPAWDA) pp. 593 - 597
Main Authors Luo, Chen-xu, Qiao, Jun-bei, zhou, Jia-wei, Gong, San-peng, Niu, Ying
Format Conference Proceeding
LanguageEnglish
Published IEEE 16.04.2021
Subjects
Acoustic distortion
Fans
Fisher standard
G-P algorithm
Noise measurement
Noise reduction
Separability index
Threshold method
Ventilators
Vibrations
Wavelet analysis
Wavelet denoising
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Summary:Wavelet denoising and the separability index of state feature class are proposed to evaluate the denoising effect. While introducing the Fisher standard discriminant rate F to measure class separability, the Fisher standard discrimination rate of each characteristic parameter after noise detection by using the rigrsure-sln soft threshold for airflow pulsation and fan noise signal are improved obviously. In this paper, the G-P algorithm is used to calculate the relationship among airflow pulsation, fan noise and vibration signal. It is found that rigrsure-sln soft-threshold method is better than other threshold method for denoising the airflow pulsation and the fan noise signal. The phase diagram of the airflow pulsation and the noise collection signal of the ventilator are disordered due to the influence of noise, and the signal after wavelet denoising shows a clear and regular chaotic attractor.
DOI:10.1109/SPAWDA51471.2021.9445433