摘要
针对加工中心功能铣头可靠性评估中小样本和高成本的特点,提出融合性能退化试验数据与现场故障数据的贝叶斯可靠性评估方法。该方法通过基于故障机理的性能退化试验设计和数据分析,导出功能铣头的寿命模型、积累先验信息并外推伪寿命数据;应用贝叶斯方法构建融合试验信息和现场故障数据的评估模型,并最终实现对功能铣头可靠性的评估。以某加工中心的功能铣头为示例进行方法描述,并与基于性能退化试验数据分析和基于现场数据统计的评估方法进行对比,结果表明,该方法具有更高的评估精度,具有一定的工程应用价值。
Reliability assessment of milling head is deemed as one of the critical issues within the field of reliability engineering for machining centers,which is suffered from the difficulty induced by small sample size and expensive reliability tests.A novel reliability assessment method is introduced by incorporating the cost-effective accelerated degradation test（ADT） with the Bayesian information fusion method.The accelerated degradation test is utilized to derive the reliability model of the milling head,to accumulate prior information,and to generate pseudo-lifetime data.The Bayesian method is implemented to construct the reliability assessment model by incorporating the information obtained in the ADT with available field data.Finally,reliability assessment is carried out based on this Bayesian model.To illustrate the approach,an application to a milling head of a gantry machining center is investigated.A comparison of the estimated results between the proposed method and the ADT data based or field data based Bayesian methods is presented.The proposed method is demonstrated more precise and flexible for practical use than others.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2014年第6期185-191,共7页
Journal of Mechanical Engineering
基金
国家自然科学基金资助项目(11272082)
关键词
功能铣头
加速退化试验
可靠性评估
贝叶斯方法
milling head
accelerated degradation test
reliability estimation
Bayesian method
