吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (3): 829-836.doi: 10.13229/j.cnki.jdxbgxb201503021

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Parameter estimation of reliability model of machining center based on particle swarm optimization and support vector regression

YANG Zhao-jun1, 2, YANG Chuan-gui1, 2, CHEN Fei1, 2, HAO Qing-bo1, 3, ZHENG Zhi-tong1, 2, WANG Song1, 2   

  1. 1.College of Mechanical Science and Engineering, Jilin University, Changchun 130022, China;
    2.Key Laboratory of CNC Equipment Reliability Technique of Machinery Industry, Jilin University, Changchun 130022, China;
    3.Department of Mechanics, Aviation University of Air Force,Changchun 130022,China
  • Received:2014-03-28 Online:2015-05-01 Published:2015-05-01

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Abstract: Based on the Support Vector Regression (SVR) model, a method is proposed to assess the parameters of the reliability model of machining centers by analyzing censored data. An improved Local best Particle Swarm Optimization algorithm (improved lbest PSO) is developed to tune parameters of the SVR model to keep working efficiently. The improved Lbest PSO, developed from the local best PSO (lbest PSO), introduces a mutation operation and an adaptive inertia fact to improve its ability to search the global optimal solution. Additionally, the Least Square Model (LSM), the Maximum Likelihood Model (MLM), the SVR model selected by the Lbest PSO and the Genetic Algorithm (GA) are employed to compare their estimation performance with the proposed method. Results show that the proposed method is superior to all the other models. Finally, this method is used to estimate the parameters of the reliability model of a type of machining center and obtain its mean time between failures.

Key words: computer numerial control machine tool, machining center reliability, Weibull model, support vector regression, particle swarm optimization

CLC Number: 

  • TG659
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