Research on Fault Distribution Parameters Estimation and Reliability Assessment of CNC Grinding Machine Tools

被引：0

作者：

Fan, Jinwei ^{[1
]}

Ji, Shi ^{[1
]}

Yuan, Shuai ^{[1
]}

机构：

[1] Beijing Univ Technol, Sch Mech Engn, Beijing 100124, Peoples R China

来源：

PROCEEDINGS OF THE 2015 2ND INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS ENGINEERING, CHEMICAL ENGINEERING AND BIOTECHNOLOGY (MMECEB) | 2016年 / 49卷

关键词：

Reliability; Probability Density Function; Least Square Method; Parameter Estimation; MTBF; CNC;

D O I：

暂无

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

Fault distribution type identification and probability density function parameters estimation are the prerequisite of CNC grinding machine tools' reliability assessment. The procedure of fault data grouping, the technique of probability density function parameters estimation based on least square method and the method of reliability index(mean time between failures, MTBF) calculation are proposed. The probability density function parameters estimation and curve fitting, the comparison of goodness of fit, the MTBF solution of some type crankshaft are carried out by the method proposed in the paper. The results of statistical calculation and direct calculation by definition are close. The procedure of reliability assessment proposed here can be programmed easily and it provides one measure for reliability assessment of CNC grinding machine tools.

引用

页码：918 / 921

页数：4

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