Application of vibration analysis and data mining techniques for bearing fault diagnosis in two stroke IC engine gearbox

2020 ◽  
Author(s):  
K. N. Ravikumar ◽  
Hemantha Kumar ◽  
K. V. Gangadharan
Keyword(s):  
Data Mining ◽  
Fault Diagnosis ◽  
Vibration Analysis ◽  
Ic Engine ◽  
Data Mining Techniques ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis

Distributed bearing fault diagnosis based on vibration analysis

2016 ◽  
Vol 66-67 ◽  
pp. 521-532 ◽  
Author(s):  
Boštjan Dolenc ◽  
Pavle Boškoski ◽  
Đani Juričić
Keyword(s):  
Fault Diagnosis ◽  
Vibration Analysis ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis

scholarly journals Mutual Information-Assisted Wavelet Function Selection for Enhanced Rolling Bearing Fault Diagnosis

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Ruqiang Yan ◽  
Mengxiao Shan ◽  
Jianwei Cui ◽  
Yahui Wu
Keyword(s):  
Fault Diagnosis ◽  
Mutual Information ◽  
Vibration Analysis ◽  
Quantitative Measure ◽  
Rolling Bearing ◽  
Test System ◽  
Wavelet Function ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Function Selection

This paper presents an enhanced rolling bearing fault diagnosis approach, based on optimized wavelet packet transform (WPT) assisted with quantitative wavelet function selection. Mutual information is utilized as a quantitative measure to select the most suitable wavelet function for the WPT-based vibration analysis. Energy features from coefficients of an optimal set of orthogonal wavelet subspaces which resulted from the WPT-based vibration analysis are input to different classifiers. The fault states of the rolling bearings can then be identified. Experiment studies conducted on a rolling bearing test system have verified the effectiveness of the proposed approach for rolling bearing fault diagnosis.

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