Title :
Study on feature extraction of high speed precision electric machine vibration signal
Author :
Liu, Qingjie ; Liu, Xiaofang ; Chen, Guiming
Author_Institution :
Second Artillery Eng. Coll., Xi´´an, China
Abstract :
Vibration signals usually contain running condition and fault information of rolling mechanical equipment. In the paper, firstly, a vibration test scheme of high speed precision electric machine is designed; time domain average method is used to filter the periodic noise and random noise of the sampling vibration signals. The result shows that the signal to noise ratio is increased. Then the de-nosing vibration signal is decomposed by means of wavelet packet and the reconstructed signal energy of every frequency segment is calculated. The study identifies that the reconstructed signal of every frequency segment contains corresponding frequency, and the energy can be used as the vibration signals´ eigenvector to estimate the running state of the electric machine.
Keywords :
feature extraction; filtering theory; random noise; signal denoising; vibrations; wavelet transforms; eigenvector; fault information; feature extraction; high speed precision electric machine; periodic noise; random noise; rolling mechanical equipment; time domain average method; vibration signal; wavelet packet; Electric machines; Feature extraction; Filters; Frequency estimation; Sampling methods; Signal design; Signal processing; Signal to noise ratio; Testing; Vibrations; De-nosing; Energy; Vibration signal; Wavelet packet decomposition;
Conference_Titel :
Image Analysis and Signal Processing (IASP), 2010 International Conference on
Conference_Location :
Zhejiang
Print_ISBN :
978-1-4244-5554-6
Electronic_ISBN :
978-1-4244-5556-0
DOI :
10.1109/IASP.2010.5476075
