Mechanical Fault Detection Based on the Wavelet De-Noising Technique

Abstract

For gears and roller bearings, periodic impulses indicate that there are faults in the components. However, it is difficult to detect the impulses at the early stage of fault because they are rather weak and often immersed in heavy noise. Existing wavelet threshold de-noising methods do not work well because they use orthogonal wavelets, which do not match the impulse very well and do not utilize prior information on the impulse. A new method for wavelet threshold de-noising is proposed in this paper; it not only employs the Morlet wavelet as the basic wavelet for matching the impulse, but also uses the maximum likelihood estimation for thresholding by utilizing prior information on the probability density of the impulse. This method has performed excellently when used to de-noise mechanical vibration signals with a low signal-to-noise ratio.

Morlet Wavelet UDWT Denoising and EMD based Bearing Fault Diagnosis

“…Thus due to the energy preservation, most of the coefficients coming from noise must be small. It is therefore reasonable to do denoising by setting the small coefficients equal to zero [12].…”

Condition Monitoring of Low Speed Bearings: A Comparative Study of the Ultrasound Technique Versus Vibration Measurements

“…In the frequency domain, the enveloping method, also known as demodulation or HFRT (High Frequency Resonance Technique), have been proven to be a very efficient and popular technique for detection of the characteristic frequencies of bearings [11][12][13][14][15][16]. Wavelet analysis has also been successfully applied to bearing defect detection [17][18][19][20][21]. In recent years, artificial neural networks and fuzzy logic have also emerged as popular tools for automated fault diagnosis [18,[22][23][24][25].…”

Oil Debris Signals Enhancement Based On Wavelet Analysis for Wind Turbine Condition Monitoring

“…From the Figure, the signal amplitude mainly depends on the mass of the ferromagnetic metal particles [7]. The output signals are monitored while the oil lubrication system operation.…”