基于Bayes理论的五轴加工中心MTBF指标预测方法  

MTBF Estimation for Five-Axis Machining Center Based on the Bayesian Theory

作　　者：李翠玲[1] 杨强[1] 张磊[1] 孙志礼[1] 

机构地区：[1]东北大学机械工程与自动化学院,辽宁沈阳110819

出　　处：《东北大学学报（自然科学版）》2012年第8期1182-1185,共4页Journal of Northeastern University(Natural Science)

基　　金：国家科技重大专项基金资助项目(2009ZX04014-014);辽宁省博士科研启动基金资助项目(201120005)

摘　　要：根据量产的相似机床产品的历史失效数据确定某五轴加工中心MTBF的先验分布,应用Wilcoxon-Mann-Whitney秩和检验法对先验信息与现场数据进行相容性检验,利用Bayes方法融合先验信息和该加工中心小子样现场失效数据对其进行实时可靠寿命预测.研究表明:该加工中心的故障时间满足β=1.909 3,α=919.495 1的两参数Weibull分布;加工中心MTBF的点估计值为815.80(h),区间估计结果为[576.70(h),1 232.42(h)].所述方法适用于小子样情况,对特种机械产品的可靠寿命预测与评估具有普遍意义.The prior distribution of the mean time between failures （MTBF） of a machining center was obtained according to the previous failure data from similar machine tools produced in batches, and the compatibility of the prior information with the in-situ data was examined using the Wilcoxon-Mann-Whitney rank sum test. The reliable life of the machining center was predicted online based on the Bayesian theory combined with the prior distribution data and the small sample failure data of the machining center. The results show that the failure time distribution of the machining center follows the two-parameter Weibull distribution, i.e. , β = 1. 909 3, α = 919. 495 1. The point estimation value of the MTBF is 815.80（h） and its interval estimation value is [576.70（h）, 1 232.42（h）J. The method proposed is suitable for the small sample situation, which is meaningful for the reliabe life prediction of special manufacturing equipment.

关 键 词：加工中心 可靠性 平均故障间隔时间(MTBF) BAYES方法 小子样 

分 类 号：TH122[机械工程—机械设计及理论]