Abstract：In order to extract from the gear fault signal contains the characteristic frequency of fault signal, the demodulation was proposed based on the EEMD adaptive morphology method. The EEMD (Ensemble Empirical Mode Decomposition) is used to reduce the noise in the first place, the original signal with different white noise superposition of the target signal, and then the target signal is decomposed into a finite number of IMF component, selection of main information sum refactoring, reoccupy morphology filter is used to extract the characteristic frequency of fault signal. According to morphologic structure element size selection problem, the genetic algorithm is used to optimize the structure of morphological elements, adaptive to seek the optimal solution. Through digital simulation test and gear fault simulation experiments, and compared with the EMD(Empirical Mode Decomposition) method and SVD(Singular Value Decomposition) method, Results show that the proposed algorithm is superior to other two methods, can extract the fault signal clearly each frequency characteristics.
侯高雁;吕勇;肖涵;秦拓. 基于EEMD自适应形态学在齿轮故障诊断中的应用[J]. , 2014, 33(18): 145-148.
Hou Gao-yan;Lv Yong;XIAO Han;QIN Tuo. Based on the EEMD adaptive morphology in the application of the gear fault diagnosis. , 2014, 33(18): 145-148.
2014, Vol. 33 
