Diagnosis of bearing incipient faults using fuzzy logic based methodology

With the increasing demand of stable running condition of mechanical products and low maintenance costs of machinery devices, fault detection and diagnosis attracted considerable interests, early fault diagnosis is desirable for accuracy and appropriate assessment, due to the fact that it could prov...

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Bibliographic Details
Main Authors: Jihong Yan, Lei Lu, Debin Zhao, Gang Wang
Format: Conference Proceeding
Language:English
Subjects:
Bearing failure component
Covariance matrix
early stage fault diagnosis
Fault diagnosis
Feature extraction
Fuzzy logic
Principal component analysis
Wavelet packets
wavelet packets analysis
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Summary:With the increasing demand of stable running condition of mechanical products and low maintenance costs of machinery devices, fault detection and diagnosis attracted considerable interests, early fault diagnosis is desirable for accuracy and appropriate assessment, due to the fact that it could provide fault information as soon as possible and prevent fast deteriorating of the failure. In this paper, a methodology is presented for incipient defect diagnosis of deep grove ball bearings through energy spectrum extracted by wavelet packet transform, differential defect features selected based on principal component analysis and feature fusion by fuzzy logic algorithm for defect diagnosis. The application results demonstrate the accuracy and effectiveness of the proposed method.
DOI:10.1109/FSKD.2010.5569134