Affiliation:
1. State Key Laboratory of Control and Simulation of Power System and Generation Equipments, Department of Thermal Engineering, Tsinghua University, People’s Republic of China
Abstract
A fault diagnosis method of wind turbine bearing based on intrinsic time-scale decomposition (ITD) is put forward. In the proposed method, the vibration signal of the main bearing is decomposed into several proper rotation components by the ITD method. The frequency centers of the proper rotation components that contain predominant energy are computed and considered as fault feature vectors. The nearest neighbor algorithm is applied to identify the fault types of the wind turbine bearing. The experimental data of the wind turbine spherical roller bearing in four conditions (normal, outer race fault, inner race fault and roller fault) are applied to evaluate the performance of the proposed method. The results demonstrate the feasibility and accuracy of this approach for the diagnosis of the wind turbine bearing faults under uncertain conditions.
Subject
Mechanical Engineering,Mechanics of Materials,Aerospace Engineering,Automotive Engineering,General Materials Science
Cited by
54 articles.
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