Blind Source Separation of Mechanical Fault Based on Quantum Genetic Algorithm

doi:10.3969/j.issn.1000-1093.2014.10.024

Abstract

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

CLC Number:

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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