Research Of Motor's Rotor Fault Diagnosis System Based On Dsp

This paper studies the Motor Fault Diagnosis System based on DSP. The system includes current signal data acquisition and rotor broken bars fault diagnosis. This study uses the squirrel cage induction motor as a data collection source. Using digital signal processor DX32 to do high_speed data acquisition for the motor signals. Using ADC ADS8O3 analog signal on the current ADC, furthermore, to analyse and to process the signal, then to make fault diagnosis based on those analysis.In the hardware design, this system adopted STM32F103VC to process data and to control the core, and use ADS803 as the core components of the system's A/D conversion, and using ADC for the collected data. Using CPLD for for data catching and transmission controling, and using CY7C68013A as USB interfaces for data transmission. Hardware design is simple and has high stability and high reliability for the collected data to achieve real-time, high-speed transmission.In the algorithm design, the system uses the wavelet packet analysis Coif5 signal to do 5 level wavelet packet decomposition,then the fault feature vector will be extracted from the results of the decomposition. Moreover, the feature vectors for online fault analysis and diagnosiswill be extracted from the neural network BP algorithmIn the system development and software design, in the MDK environment for development of the DSP program, MATLAB will be used for the current signal's simulation., meanwhile, MATLAB function library will be used for wavelet decomposition, and the toolbox's neural network will be adopted for fault diagnosis. VC is implemented in MATLAB in the simulation results'demonstration.