基于随机截尾数据的加工中心可靠性评估  

Reliability Evaluation of Machining Centers Based on Random Censored Data

作　　者：罗静 马仕川 杨立波 LUO Jing;MA Shichuan;YANG Libo(College of Mechanical Engineering,Chongqing University of Technology,Chongqing 400054,China;Dalian Kede CNC Co.,Ltd.,Dalian 116600,China)

机构地区：[1]重庆理工大学机械工程学院,重庆400054 [2]大连科德数控有限公司,辽宁大连116600

出　　处：《重庆理工大学学报（自然科学）》2020年第2期69-74,共6页Journal of Chongqing University of Technology：Natural Science

基　　金：国家科技重大专项资助项目(2017ZX04011013);重庆重点产业共性关键技术创新专项项目(cstc2017zdcy-zdzx X0005)

摘　　要：传统故障频次法在统计故障时间时,通常会忽视故障数据的随机截尾性,造成工作总时间统计不准确,可靠性评估值偏低。运用故障总时间法,将随机截尾时间转化为加工中心的故障总时间,采用图示法和赤池信息准则(AIC)初步确定故障数据分布模型,然后利用线性相关性检验和K-S检验确定其最终分布模型,再根据可靠性函数进行可靠性指标的计算。本方法评估出加工中心的MTBF指标为1 887 h,相比于传统故障频次法的917 h,更能客观反应加工中心可靠性的真实水平。The traditional fault frequency method usually neglects the random truncation of fault data when calculating fault time,which results in inaccurate statistics of total working time and low reliability evaluation value. The stochastic truncation time is transformed into the total fault time of the machining center by using the total fault time method. The fault data distribution model is initially determined by graphic method and Chichi Information Criterion( AIC). Then the final distribution model is determined by linear correlation test and K-S test,and the reliability index is calculated according to the reliability function. Compared with the traditional fault frequency method,the evaluation results of this method can more objectively reflect the true level of reliability of machining centers.

关 键 词：随机截尾 加工中心 分布模型 可靠性评估 

分 类 号：TP114[自动化与计算机技术—控制理论与控制工程]