华南理工大学学报(自然科学版) ›› 2019, Vol. 47 ›› Issue (5): 96-102.doi: 10.12141/j.issn.1000-565X.180091

• 机械工程 • 上一篇    下一篇

基于Ⅱ型广义 logistic 分布和粒子群优化的 退化可靠性建模

张金豹 赵永强 刘明 孔令贤   

  1. 哈尔滨工业大学 机电工程学院,黑龙江 哈尔滨 150001
  • 收稿日期:2018-03-04 修回日期:2018-12-26 出版日期:2019-05-25 发布日期:2019-04-01
  • 通信作者: 张金豹( 1986-) ,男,博士生,主要从事疲劳寿命预测及可靠性建模研究. E-mail:zjb1357@163.com
  • 作者简介:张金豹( 1986-) ,男,博士生,主要从事疲劳寿命预测及可靠性建模研究.
  • 基金资助:
    国家自然科学基金资助项目( 51505100) 

Reliability Modelling for Degradation Based on Type-Ⅱ Generalized Logistic Distribution and Particle Swarm Optimization
 

 ZHANG Jinbao ZHAO Yongqiang LIU Ming KONG Lingxian   

  1.  School of Mechatronics Engineering,Harbin Institute of Technology,Harbin 150001,Heilongjiang,China
  • Received:2018-03-04 Revised:2018-12-26 Online:2019-05-25 Published:2019-04-01
  • Contact: 张金豹( 1986-) ,男,博士生,主要从事疲劳寿命预测及可靠性建模研究. E-mail:zjb1357@163.com
  • About author:张金豹( 1986-) ,男,博士生,主要从事疲劳寿命预测及可靠性建模研究.
  • Supported by:
     Supported by the National Natural Science Foundation of China( 51505100) 

摘要: 广义概率分布能够更加准确地描述性能退化数据的特性,降低奇异点和概率分 布选择错误时带来的影响,为此,文中引入Ⅱ型广义 logistic 分布( Ⅱ-GLD) 进行退化可靠 性评估. 通过加入位置参数和尺度参数对时变退化量建模,根据各时刻分布的分位数和对 应试验数据之间的均方误差建立目标函数,结合粒子群优化( PSO) 算法实现对目标函数 中多个参数的同时估计. 运用所提方法对实例进行退化可靠性评估、验证和对比,结果表 明:该模型计算得到的退化数据均值和标准差与实际值的相对误差在 8%以内,不同失效 阈值下的可靠性评估结果与试验数据吻合良好;对比分析表明,与正态分布和威布尔分布 相比,Ⅱ-GLD 能够有效挖掘退化数据的尾部特性,真实反映产品的初期退化. 

关键词: 可靠性, 退化数据, Ⅱ型广义 logistic 分布, 分位数, 粒子群优化

Abstract: As the generalized probabilistic distribution can describe the characteristics of performance degradation data with high precision and reduce the impacts caused by the outliers and the fault selection of probabilistic distribution,the type-Ⅱ generalized logistic distribution ( Ⅱ-GLD) is applied to the degradation reliability evaluation in this paper. In the investigation,the parameters of location and scale are introduced in the modeling of time-dependent degradation data,the objective function is established according to the meansquare error ( MSE) between the quantiles of Ⅱ-GLD and the experiment data,and particle swarm optimization ( PSO) algorithm is utilized to estimate parameters simultaneously. Then,the proposed approach is applied to a practical example for the evaluation of degradation reliability,followed with a verification and comparison. The results show that the relative errors between the mean and the standard deviation are below 8%,and that the reliability evaluation results match well with the pseudolifetime data in different failure thresholds. Moreover,it is indicated that,as compared with the normal distribution and the Weibull distribution,Ⅱ-GLD can explore the tail characteristics of degradation data more effectively and represent the initial degradation of the product faithfully. 

Key words: reliability, degradation data, type-Ⅱ generalized logistic distribution, quantile, particle swarm optimization

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