利用运行状态信息的机床刀具可靠性预测方法

被引:13
作者
陈保家
陈雪峰
何正嘉
李兵
机构
[1] 西安交通大学机械制造系统工程国家重点实验室
关键词
运行状态; 刀具; 可靠性预测; 瞬时可靠度;
D O I
暂无
中图分类号
TG71 [刀具];
学科分类号
080201 ;
摘要
针对数控机床类退化失效型设备,提出了一种基于设备运行状态信息的可靠性预测方法,主要包括状态特征指标选取、瞬时可靠度计算以及神经网络预测模型的建立和应用.其中,瞬时可靠度计算是准确预测的关键,结合Bayes方法和KM估计器思想提出的基于状态特征指标比例关联关系的瞬时可靠度算法简单高效.针对刀具加工过程中的磨损量时变数据,以可靠度为评价标准,正确预测出了刀具的失效时间,该过程表明设备状态信息用于可靠性预测的可行性和有效性,是未来可靠性发展的一个重要方向.
引用
收藏
页码:74 / 77+121 +121
页数:5
相关论文
共 10 条
[1]  
BP neural network prediction- based variable-period sampling approach for networked control systems. J.Q. Yia,Q. Wang,D.B. Zhao, et al. Applied. Math. Comput . 2007
[2]  
On-line and indirect tool wear monitoring in turning with artificial neural networks:a review of more than a decade of research. SICK B. Mechanical Sys-tems and Signal Processing . 2002
[3]  
A neural network degrada-tion model for computing and updating residual life dis-tributions. NAGI Z G,MARK A L. IEEE Transactions on Automation Sci-ence and Engineering . 2008
[4]  
Intelligence in reliability en-gineering. CHINNAM R B,,RAI B. . 2007
[5]  
Using degradation measures to estimation a time-to-failure distribution. LU J C,MEEKER W Q. Techn-ometrics . 1997
[6]  
Estimation of Time-to-failure Distribution Derived From a Degradation Model Using Fuzzy Clustering. Wu S.Y,Tsai T.R. Quality and Reliability . 2000
[7]  
Reliability engineering:Old problems and new challenges. Zio E. Reliability Engineering and System Safety . 2009
[8]  
End milling tool breakage detection using lifting scheme and Mahalanobis distance. Cao H,Chen X,Zi Y,et al. International Journal of Machine Tools and Manufacture . 2008
[9]  
Intelligent condition-based prediction of machinery reliability. Heng A,Tan A C C,Mathew J,et al. Journal of Mechanical Systems . 2009
[10]  
Nonparametric estimation from incomplete observations. Kaplan EL,Meier P. Journal of the American Statistical Association . 1958