Optimization of Fault Monitoring Method Based on Acceleration Sensor

With the continuous progress of the space station project, the rotary mechanism is widely used in the space station. Serious failure of rotating mechanism can cause motor burnout and then safety problems. Therefore, it is necessary to monitor and diagnose rotating mechanism. The vibration signal of the rotating mechanism is nonlinear and non-stationary. Therefore, the acceleration sensor vibration signal is decomposed by CEEMD method to get the intrinsic mode function. Next, Fourier transform is used to obtain time-frequency information according to the obvious components of fault characteristics, and the information entropy of time-frequency information is calculated. The degree of dimensionality reduction about fault feature is determined by selecting the number of principal components through adaptive cumulative contribution. Finally, the fault feature is trained by support vector machine and tested with data. Experimental results show that the optimized method is less computational and can accurately extract fault feature information.