Study On The Fault Diagnosis Of Asynchronous Induction Motor Base On The Wavelet Analysis

In the Heating Ventilating and airconditioning area, the asynchronous motor has been widely used as fan motor. The fraction defective is about 15%,, and it is just second to compressor (about 15% of total). Currently, many companies apply the FFT spectrum analysis based on Fourier analysis to motor analysis. Although it is effective for steadily random signal, its statistics inchudes sine wave component only.In fact, the detective signals usually include both weak and unsteadily defective signals, and those can't be analyzed by FFT spectrum analysis. The wavelet analysis with the character of local time-frequency domain has rised these years, because its principle is to use wide scale to analyze low frequency wave and use narrow one on the contrary. Thus, wavelet analysis as an ideal signal processing tool can be applied to the filtering, singularity detecting and the prediction of signal etc.This paper is to study the feasibility of applying wavelet analysis to detection of induction motor in the commercial Air-conditioning area. The way with wavelet analysis is to use the wavelet transformation to analyze the input signal of induction motor and transform the signal to different spectrum, and it can detect the fault through comparing both deficient and normal motors. Through the analysis of different motors, we can find the correspondence between defective signals and the faults in motors. Thus we can verify efficiency of the wavelet transformation.When detecting the real fault motor signal, with the use of Multi-frequency range decomposition based on Wavelet Packet theory, we can extract eigenvalue of the motor fault signal and establish motor fault feature list, thereby ensure the validity of Wavelet analysis for the fault motor estimation.The aim of the research is to apply the Wavelet analysis theory to quality analysis of air-conditioner's components.