Affiliation:
1. School of Mechanical and Power Engineering, Henan Polytechnic University, Jiaozuo, P.R. China
Abstract
In order to monitor the wind turbine gearbox running state effectively, a fault diagnosis method of wind turbine gearbox is put forward based on wavelet neural network. Taking a 1.5 MW wind turbine gearbox as the target of study, the frequency spectrum of vibration signal and the fault mechanism of driving part are analyzed, and the eigenvalues of the frequency domain are extracted. A wavelet neural network model for fault diagnosis of wind turbine gearbox is established, and wavelet neural network is trained by using different feature vectors of fault types. The relationship between fault component and vibration signal is identified, and the vibration fault of wind turbine gearbox is predicted and diagnosed by network model. The analysis results show that the method can diagnose fault and fault pattern recognition of wind turbine gearbox very well.
Funder
the postdoctoral fund in China
the Doctor Funds for the Henan Polytechnic University
the Innovative Research Team Project of Henan Polytechnic University
the major scientific and technological research projects of Henan Province, China
the key scientific research project of colleges and universities in Henan Province of China
Subject
Mechanical Engineering,Geophysics,Mechanics of Materials,Acoustics and Ultrasonics,Building and Construction,Civil and Structural Engineering
Cited by
21 articles.
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