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 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.