The Algorithm Based On Improved Wavelet Thresholding And Its Application In Gear Fault Diagnosis

Wavelet Transform as a mathematical theory and methods in signal and image processing, intelligent voice identification, nuclear detection neighborhood, machine status and fault diagnosis recognition, ultrasonic detection range of applications such as engineering attracted more and more concern and attention. Gear vibration signals in mechanical fault diagnosis plays a key role, gear vibration signal is used to analyze the state of the running gear in the process, in order to determine the gear failure. However, in the process of collecting the vibration signal, will Affected from a lot of background noise signal and components friction, vibration signal during transmission will also be noise. Therefore, under normal circumstances the collected gear vibration signal is noisy, therefore, gear vibration signal de-noising research, extract the original signal to provide accurate information for the post fault diagnosis is the focus of this study.This thesis studies on vibration signal de-noising gear. Due to their characteristics and noise of gear vibration signal so that the vibration signal with a non-stationary characteristics. However, the Fourier transform is only valid in the frequency domain, can not meet the analysis of non-stationary signals.Fourier transform is only valid in the frequency domain, can not meet the analysis of non-stationary signals. The wavelet transform makes up for the shortcomings of traditional denoising, has the analysis capability of time-frequency localization, so using wavelet transform processing gear vibration signal is more reasonable. consider the wavelet function orthogonality, symmetry, compactly supported other aspects, the thesis selection db5 wavelet function analysis wavelet more efficiently than other gear vibration signals. Because of the hard threshold function method discontinuity wavelet coefficients prone to "pseudo-Gibbs' phenomenon reconstructed signal, the situation there is a deviation between the estimated value and the actual value of the soft threshold function method wavelet coefficients.In order to avoid the shortcomings of the " pseudo-Gibbs' phenomenon and soft threshold of bias. In this paper, we construct a new threshold function, the new threshold function can change flexible between soft threshold function and hard threshold function. Appropriate wavelet function affects denoising effect directly, The threshold plays a key role in the wavelet denoising, the threshold is too Large,part of the useful signal will be removed as noise, useful information will lost too much; the threshold is too small, residual excessive noise component will easily lead signal distortion, affecting denoising effect. In order to achieve better denoising effect on the threshold of this article has been further improved.The wavelet analysis applied to gear fault diagnosis, and achieved good results in the diagnosis of early gear failure, which plays an important role in ensuring the safe and reliable operation of the gear device on. Wavelet analysis has broad application prospects, is a worthy new technologies.