Research on Fault Diagnosis Method for Rotating Machinery Vibration Based on Wavelet Transformation and Probabilistic Neural Network

Based on wavelet transformation and Neural Network Data Fusion,a Fault Diagnosis Technology is proposed.Fault feature extraction is carried out using wavelet decomposition,probabilistic neural network fault diagnosis technologies by optimizing the selection,and by the MATLAB Simulation.The simulation and results verify that using wavelet decomposition extract fault characteristics of the energy vector,which has strong generalization ability and anti-noise ability to adapt to Wide dynamic range and small sample,and building the adaptive probabilistic neural network is a good anti-noise capability,classification advantage of the high rate of diagnostic accuracy.Integration of the wavele and neural network application will provide a better classification of diagnosis results,and better reliability and accuracy.