A fault diagnosis method of discrete wavelet transform and neural networks is proposed

by using signal feature extraction mechanism

aviation spiral bevel gear fault diagnosis and state recognition is studied.A test rig of spiral bevel gear system vibration testing is built

the testing of normal and defective gear transmission is carried out.The influence of noise on gearbox vibration data signal system is removed through the wavelet threshold.By using discrete wavelet transform

the signal energy features is extracted

gear system fault state classification recognition is carried out by using neural networks with feedback algorithm.The results show that the gear fault recognition result effective rate is to 100%.An effective way for gear system fault analysis is provided.