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	3-Parameter Weibull distribution for random truncated NC machine tool fault data
	Zhang Ying-zhi ; Shen Gui-xiang ; Wu Su ; Xue Yu-xia ; He Yu
	2010-10-12 ; 2010-10-12
关键词	Practical Theoretical or Mathematical/ machine tools numerical control parameter estimation reliability Weibull distribution/ 3-parameter Weibull distribution random truncated NC machine tool fault data reliability test data numerically controlled machine tool data truncation data analysis parameter estimation reliability analysis/ E1520A Machining E1560 Production equipment E1020 Maintenance and reliability E0210J Statistics
中文摘要	In the engineering practice, the reliability test data of the numerically controlled (NC) machine tool were analyzed and evaluated mostly without consideration of the data truncation time. The data were normally fitted by the 2-parameter Weibull distribution, resulting in large error in the data analysis and the parameter estimation. Aiming at this problem, a total fault time method was used to pretreat the fault data, and the relevant parameters were got assuming that the data follow the 2-parameter Weibull distribution, then a 3-parameter Weibull distribution model was established using the improved interpolation technique to evaluate the position parameter. Taking the random truncated fault data of a certain series of 6 NC machine tools in a year as an example to demonstrate the detailed calculation process. The obtained results can improve the accuracy of the reliability analysis and evaluation on NC machine tools.
语种	中文
出版者	Editorial Board of Journal of Jilin University ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/80636]
专题	清华大学
推荐引用方式 GB/T 7714	Zhang Ying-zhi,Shen Gui-xiang,Wu Su,et al. 3-Parameter Weibull distribution for random truncated NC machine tool fault data[J],2010, 2010.
APA	Zhang Ying-zhi,Shen Gui-xiang,Wu Su,Xue Yu-xia,&He Yu.(2010).3-Parameter Weibull distribution for random truncated NC machine tool fault data..
MLA	Zhang Ying-zhi,et al."3-Parameter Weibull distribution for random truncated NC machine tool fault data".(2010).

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