Study on Fault Detection of Rolling Element Bearing Based on Translation-Invariant Denoising and Hilbert-Huang Transform

2012 ◽  
Vol 7 (5) ◽  
Author(s):  
Lijia Xu
Keyword(s):  
Fault Detection ◽  
Rolling Element Bearing ◽  
Translation Invariant ◽  
Hilbert Huang Transform ◽  
Rolling Element ◽  
Element Bearing

scholarly journals Incipient Fault Detection of Rolling Element Bearing Running at Slow Speed

2015 ◽  
Vol 10 (5) ◽  
pp. 360-365
Author(s):  
Chiranjan Manda ◽  
Ravi Ranjan Prasad ◽  
Partha Pratim Sengupta
Keyword(s):  
Fault Detection ◽  
Rolling Element Bearing ◽  
Slow Speed ◽  
Rolling Element ◽  
Element Bearing ◽  
Incipient Fault ◽  
Incipient Fault Detection

Rolling Element Bearing Fault Detection Using Redundant Second Generation Wavelet Packet Transform

2011 ◽  
Vol 199-200 ◽  
pp. 931-935 ◽  
Author(s):  
Ning Li ◽  
Rui Zhou
Keyword(s):  
Wavelet Transform ◽  
Fault Detection ◽  
Second Generation ◽  
Wavelet Packet ◽  
Vibration Signal ◽  
Rolling Element Bearing ◽  
Bearing Fault ◽  
Rolling Element ◽  
Element Bearing ◽  
Second Generation Wavelet

Wavelet transform has been widely used for the vibration signal based rolling element bearing fault detection. However, the problem of aliasing inhering in discrete wavelet transform restricts its further application in this field. To overcome this deficiency, a novel fault detection method for roll element bearing using redundant second generation wavelet packet transform (RSGWPT) is proposed. Because of the absence of the downsampling and upsampling operations in the redundant wavelet transform, the aliasing in each subband signal is alleviated. Consequently, the signal in each subband can be characterized by the extracted features more effectively. The proposed method is applied to analyze the vibration signal measured from a faulty bearing. Testing results confirm that the proposed method is effective in extracting weak fault feature from a complex background.

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