發(fā)布時間：2018-06-21 07:41

  本文選題：數(shù)控機床 + MTBF��； 參考：《機械工程學報》2017年07期

【摘要】：針對采用參數(shù)Bootstrap方法進行數(shù)控機床可靠性區(qū)間估計時,在重抽樣過程中因缺失定時截尾數(shù)據(jù)而產(chǎn)生較大估計誤差的問題,提出一種能夠充分利用數(shù)控機床定時截尾數(shù)據(jù)的可靠性Bootstrap區(qū)間估計方法。分析數(shù)控機床定時截尾試驗中完整數(shù)據(jù)與定時截尾數(shù)據(jù)的時間關系,在重抽樣時依據(jù)該時間關系重新生成Bootstrap重抽樣樣本,解決了采用參數(shù)Bootstrap方法重抽樣時無法利用定時截尾數(shù)據(jù),進而導致數(shù)控機床可靠性評估誤差較大的問題。采用極大似然估計和Newton-Raphson方法得到了試驗樣本的點估計,采用糾偏加速系數(shù)對極大似然估計帶來偏性誤差進行糾偏,進而得到區(qū)間估計。結合具體實例,對抽樣試驗時間長度T及初步生成完整數(shù)據(jù)的個數(shù)k的設定原則進行了論述。試驗結果表明:與其他區(qū)間估計方法相比,在同一置信水平下,考慮定時截尾數(shù)據(jù)的Bootstrap方法得到的可靠性區(qū)間長度短,可用于數(shù)控機床的可靠性評估。
[Abstract]:When the parameter Bootstrap method is used to estimate the reliability interval of CNC machine tools, the problem of large estimation error caused by missing timed truncated data in the process of heavy sampling is presented. A reliability Bootstrap interval estimation method which can make full use of the time truncated data of CNC machine tools is proposed. The time relation between the complete data and the timed truncated data, regenerating the Bootstrap resampling sample according to the time relation in the heavy sampling, and solving the problem that the time truncated data can not be used when the parameter Bootstrap method is resampling, and the reliability evaluation error of the NC machine tool is large. The maximum likelihood estimation and Newton- are used. The Raphson method obtains the point estimation of the test sample. The deviation error of the maximum likelihood estimation is corrected by the correction acceleration coefficient, and then the interval estimation is obtained. The setting principle of the sampling test time length T and the number k of the initial complete data is discussed with the concrete examples. The test results show that: and the other intervals. Estimation method compared at the same confidence level, considering the reliability interval length Bootstrap method of timing censored data is short, can be used for evaluating the reliability of CNC machine tools.
【作者單位】： 吉林大學機械科學與工程學院;北華大學機械工程學院;
【基金】：國家科技重大專項資助項目(2014ZX04014-011)
【分類號】：TG659

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1 李金洲;基于參數(shù)Bootstrap-核密度估計的數(shù)控機床Bayes可靠性評估方法研究[D];燕山大學;2016年

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本文編號：2047773