Study on aero-engine faults diagnosis based on wavelet neural network

Abstract

Abstract:

In order to effectively identify the common fault types of aviation engine, a new method of engine fault diagnosis based on wavelet packet and neural network is proposed. Taking a certain type of aero-engine as research object,the vibration signal is decomposed and reconstructed through wavelet packet to obtain feature vector of its working condition. Then these data are input into the wavelet Elman neural network as training sample data and test sample data. Experimental results show that this method is feasible and the fault types of aero-engine is well recognized.

Key words: wavelet transform, neural network, aero-engine, fault diagnosis

CLC Number:

V263.6

YANG Yonggang, GU Jie. Study on aero-engine faults diagnosis based on wavelet neural network[J]. .

References 13

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