JOURNAL ARTICLE

The intelligent fault diagnosis of wind turbine gearbox based on artificial neural network

Abstract

The vibration test system for the gearbox of wind turbine , the wavelet denoising method , the artificial neural networkpsilas essential principles and its features, BP network structures model in the gearbox fault diagnosis are discussed. Tested vibration signals are disposed by the method of wavelet denoising and than as the inputs of BP neural network. By using classical BP neural network, four kinds of typical patterns of gearbox faults have been studied and diagnosed ,and satisfied results have been acquired. The research results indicate that BP neural network have the excellent abilities of parallel distributed processing, self-study, self-adaptation, self-organization, associative memory , and simultaneously its highly non-linear pattern recognition technology is an efficient and feasible tool to solve complicated state identification problems in the gearbox fault diagnosis.

Keywords:
Artificial neural network Computer science Fault (geology) Artificial intelligence Turbine Wavelet Wavelet transform Pattern recognition (psychology) Time delay neural network Vibration Noise reduction Content-addressable memory Control engineering Engineering

Metrics

91
Cited By
5.52
FWCI (Field Weighted Citation Impact)
5
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Industrial Technology and Control Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Advanced Sensor and Control Systems
Physical Sciences →  Engineering →  Control and Systems Engineering
Advanced Algorithms and Applications
Physical Sciences →  Engineering →  Control and Systems Engineering

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