基于QGA和SK的滚动轴承故障诊断新方法

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摘要基于量子遗传算法收敛速度快、全局寻优能力强的特点，将谱峭度法和量子遗传算法相融合，提出一种滚动轴承故障诊断的新方法。该方法以经初始带通滤波后的原信号的谱峭度作为量子遗传算法的适应度函数，重新优化设计最优滤波器，以设计的最优带通滤波器对原始信号滤波并进行包络分析，从而实现轴承故障的诊断。实测数据分析表明，本文方法所得峭度谱值明显增大，包络谱线更加干净，故障特征频率更加明显。同时研究发现，本文方法诊断精度几乎不受传感器位置的影响。

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	徐可君1
	任帅2
	秦海勤1
	李志农2

关键词 ：滚动轴承, 量子遗传算法, 谱峭度, 包络分析, 故障诊断,

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

收稿日期: 2014-03-10 出版日期: 2015-06-15

引用本文:

徐可君1，任帅2,秦海勤1，李志农2. 基于QGA和SK的滚动轴承故障诊断新方法[J]. 振动与冲击, 2015, 34(11): 105-109.
XU Ke-jun1, REN Shuai2, QIN Hai-qin1, LI Zhi-nong2. Rolling Bearing Fault Diagnosis by fusing Quantum Genetic Algorithm and Spectral Kurtosis. JOURNAL OF VIBRATION AND SHOCK, 2015, 34(11): 105-109.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2015/V34/I11/105

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