Rolling Bearing Fault Diagnosis by fusing Quantum Genetic Algorithm and Spectral Kurtosis

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Journal of Vibration and Shock ›› 2015, Vol. 34 ›› Issue (11) : 105-109.

XU Ke-jun1, REN Shuai2, QIN Hai-qin1, LI Zhi-nong2

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Abstract

Based on rapid convergence and good global search capacity, a new method for rolling bearing fault diagnosis was discussed by combining quantum genetic algorithm(QGA) and spectral kurtosis(SK). The method takes the value of SK，which was gained by primary band-pass filter, as the fitness function of QGA to design optimal band-pass filter. Then the original signal was filtered by the optimal band-pass filter. The characteristic frequency of rolling bearing fault can be nicely obtained by envelope analysis. The method was used to analysis real testing signal. The result shows that the value of SK was much larger, the envelope spectral of filtered signal and the characteristic frequencies were much clearer than the traditional SK results. The result also shows that the location of signal transducer has few impacts on the new method.

Key words

rolling bearing / quantum genetic algorithm / spectral kurtosis / envelope analysis / fault diagnosis

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XU Ke-jun1, REN Shuai2, QIN Hai-qin1, LI Zhi-nong2. Rolling Bearing Fault Diagnosis by fusing Quantum Genetic Algorithm and Spectral Kurtosis[J]. Journal of Vibration and Shock, 2015, 34(11): 105-109

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