基于量子遗传的机械故障盲源分离方法研究

doi:10.3969/j.issn.1000-1093.2014.10.024

兵工学报 ›› 2014, Vol. 35 ›› Issue (10): 1681-1688.doi: 10.3969/j.issn.1000-1093.2014.10.024

基于量子遗传的机械故障盲源分离方法研究

李志农^1，2，皮海玉¹, 肖尧先¹

（1.南昌航空大学无损检测技术教育部重点实验室，江西南昌 330063；

收稿日期:2014-01-18 修回日期:2014-01-18 上线日期:2014-11-28
通讯作者: 李志农 E-mail:lizhinong@tsinghua.org.cn
作者简介:李志农（1966—）男，教授
基金资助:
国家自然科学基金项目(51265039、51075372、50775208)；江西省教育厅科技计划项目(GJJ12405)；湖南科技大学机械设备健康维护湖南省重点实验室开放基金项目(201204)；广东省数字信号与图像处理技术重点实验室开放基金项目（2014GDDSIPL-01）

Blind Source Separation of Mechanical Fault Based on Quantum Genetic Algorithm

LI Zhi-nong^1，2, PI Hai-yu¹, XIAO Yao-xian¹

(1.Key Laboratory of Nondestructive Testing, Ministry of Education, Nanchang Hangkong University, Nanchang 330063, Jiangxi,China；2.Guangdong Key Laboratory of Digital Signal and Image Processing, Shantou University, Shantou 515063, Guangdong, China)

Received:2014-01-18 Revised:2014-01-18 Online:2014-11-28
Contact: LI Zhi-nong E-mail:lizhinong@tsinghua.org.cn

摘要/Abstract

摘要： 针对基于遗传算法的机械故障源分离(GA-BSS)方法存在的不足和量子遗传的独特优势，提出了基于量子遗传的机械故障盲源分离(QGA-BSS)方法，并与传统的GA-BSS方法进行了比较。仿真结果表明，提出的方法优于GA-BSS方法，尤其是在快速收敛性方面，避免了GA-BSS方法早熟收敛，同时也大幅度地减少了计算量。将提出的方法应用到轴承故障分离中，能很好地提纯出轴承故障特征。实验结果证明，提出的QGA-BSS方法是有效的。

关键词: 信息处理技术, 量子遗传, 盲源分离, 故障诊断

Abstract: For the deficiency in the blind separation method of mechanical fault sources based on the genetic algorithm, which is named as GA-BSS method, and the unique advantages of quantum genetic algorithm, a blind separation method of mechanical fault sources based on the quantum genetic algorithm, which is named as QGA-BSS method, is proposed. The proposed method is compared with the traditional GA-BSS method. The simulation results show that the QGA-BSS method is superior to the traditional GA-BSS method, especially in the convergence speed. The proposed method avoids the premature convergence in the GA-BSS method and greatly reduces the amount of calculation. Finally, The proposed method is applied to the separation of bearing fault, and can extract the bearing fault features from the mixture signals successfully .The experimental results prove that the proposed QGA-BSS method is effective.

Key words: information processing technology, quantum genetic algorithm, blind source separation, fault diagnosis

中图分类号:

李志农，皮海玉, 肖尧先. 基于量子遗传的机械故障盲源分离方法研究[J]. 兵工学报, 2014, 35(10): 1681-1688.

LI Zhi-nong, PI Hai-yu, XIAO Yao-xian. Blind Source Separation of Mechanical Fault Based on Quantum Genetic Algorithm[J]. Acta Armamentarii, 2014, 35(10): 1681-1688.

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基于量子遗传的机械故障盲源分离方法研究

Blind Source Separation of Mechanical Fault Based on Quantum Genetic Algorithm

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