| In order to judge the running state of the equipment, it analyzing the vibration signals which were collected, last diagnosing fault, this is spectrum analysis. But now spectrum analysis technique is based on single spectrum analysis on fault diagnosis, the diagnosis of such technology is not high. Rely on empirical mode decomposition for the fault diagnosis of rotating machinery bearing, but need to calculate the extreme point of function first of all. Ensure to collect the extreme value point of all signal, this limits the application of empirical mode decomposition.In this paper, we study multiple spectrum analysis algorithm and GEMD analysis algorithm of fault diagnosis, specific work is as follows:(1) In view of the current spectrum analysis technique for a single frequency spectrum analysis and diagnosis accuracy is not high phenomenon, this paper main research multiple spectrum analysis algorithm. The principle of the algorithm is to diagnose fault rely on the method of exclusion.(2) Need to solve the problem of extreme value point when using empirical mode decomposition. Genetic algorithm can find out the function extreme value point when the function not guide or derivative does not exist. First calculates the extreme point of function and ensures acquiring all the extreme value point of function. Secondly carries on the empirical mode decomposition, finally structures spectrum envelope and analysis of the fault.(3) Applies multiple spectrum analysis algorithm in fault diagnosis of rotating machinery shaft, through Experiments verify the feasibility of the algorithm, it have a high accuracy than a single spectrum analysis technology. Most of rotating machinery bearing fault signal are high frequency signal. Envelope spectrum analysis of GEMD can extract the high frequency signal very well, Applies the algorithm in fault diagnosis of rolling bearing and Applies the algorithm in fault diagnosis of rolling bearing, Verifies the feasibility of this method. |
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