退化量有缺失的无失效小样本轴承可靠性评估

许凌天; 沈雪瑾; 蒋爽

doi:10.13224/j.cnki.jasp.2020.09.020

退化量有缺失的无失效小样本轴承可靠性评估

doi: 10.13224/j.cnki.jasp.2020.09.020

基金项目: 国家“十二五”规划项目上海大学子项(D.50-0109-15-001)

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- 文章访问数: 159
- HTML浏览量: 10
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- 被引次数: 0
出版历程
- 收稿日期: 2020-03-09
- 刊出日期: 2020-09-28

Reliability assessment of bearings with incomplete performance degradation data under small and non-failure samples

1.
School of Mechanical and Electrical Engineering and Automation,Shanghai University,Shanghai 200444,China
2.
Technology Center,Shanghai Tianan Bearing Corporation Limited,Shanghai 201108,China

摘要

摘要: 针对有试验性能退化量参数记录、且(或)有部分数据缺失情况的小样本无失效轴承试验问题,通过由Taylor和Thompson提出的数据模拟法实现补全样本退化量,结合Bootstrap自助法扩大样本量,再根据基于性能退化轨迹的补充信息方法来进行其可靠性评估。选取7组受试轴承的振动退化量,对比在完整数据和带有缺失数据情况下的分析结果,发现可合理利用原舍弃不合规试验的部分有效信息,使之增加可靠性评估的样本数,从而得到较不用这些数据更为准确的结果,且所得结果较用完整数据结果绝对值相差在01以内。对比由极大似然估计法和加权E-Bayes法分析试验寿命数据的结果,发现该方法所得评估结果更优,与试验实际相比误差在10%以内,对于提高评估精度及降低试验成本有积极的实际意义。
- 可靠性评估 /
- 性能退化 /
- 数据缺失 /
- Bootstrap法 /
- 随机数据模拟
Abstract: A reliability assessment with incomplete performance degradation data under small and non-failure samples was made. A data-based random number simulation method proposed by Taylor and Thompson was used to complete the missing sample degradation data,the Bootstrap method was used to expand the sample size,and the reliability assessment of the bearings was analyzed based on the degradation trajectory-based method. The vibration degradation of 7 groups of tested bearings was selected and analyzed under the conditions of complete and incomplete performance degradation data,respectively. It was found that the method proposed can obtain accurate reliability assessment and the absolute value difference between two results was controlled within 01. The above results were compared with the results obtained by analyzing the lifetime data through the weighted E-Bayes method and the maximum likelihood estimation. It was found that the results obtained by the method were better,and the actual error was within 10% compared with the actual test,showing positive practical significance for improving the evaluation accuracy and reducing the test cost.
- reliability assessment /
- performance degradation /
- incomplete data /
- ,Bootstrap method /
- random number simulation

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参考文献(22)

[1]	傅惠民,张勇波.Weibull分布定时无失效数据可靠性分析方法［J］.航空动力学报,2010,25(12):2807-2810. FU Huimin,ZHANG Yongbo.Method of reliability analysis for time truncated zero-failure data based on Weibull distribution［J］.Journal of Aerospace Power,2010,25(12):2807-2810.(in Chinese)
[2]	KWON Y.Design of Bayesian zero-failure reliability demonstration test for products with Weibull lifetime distribution［J］.Journal of Applied Reliability,2014,14(4):220-224.
[3]	KWON Y.The effect of scale parameter in designing reliability demonstration test for lognormal lifetime distribution［J］.Journal of Applied Reliability,2014,14(1):53-57.
[4]	夏新涛,叶亮,李云飞,等.基于多层自助最大熵法的可靠性评估［J］.兵工学报,2016,37(7):1317-1329. XIA Xintao,YE Liang,LI Yunfei,et al.Reliability evaluation based on hierarchical bootstrap maximum entropy method［J］.Acta Armamentarii,2016,37(7):1317-1329.(in Chinese)
[5]	夏新涛,朱文换,孙立明,等.基于自助最大熵法的滚动轴承无失效数据可靠性评估［J］.轴承,2016(7):32-36,53. XIA Xintao,ZHU Wenhuan,SUN Liming,et al.Reliability evaluation for zero-failure data of rolling bearings based on bootstrap maximum entropy method［J］.Bearing,2016(7):32-36,53.(in Chinese)
[6]	高攀东,沈雪瑾,陈晓阳,等.无失效数据下航空轴承的可靠性分析［J］.航空动力学报,2015,30(8):1980-1987. GAO Pandong,SHEN Xuejin,CHEN Xiaoyang,et al.Reliability analysis for aircraft bearing with zero-failure data［J］.Journal of Aerospace Power,2015,30(8):1980-1987.(in Chinese)
[7]	LIN L S,LI D C.A new approach to assess product lifetime performance for small data sets［J］.European Journal of Operational Research,2013,230(2):290-298.
[8]	GALETTO F,ERTO P.Comments on new practical Bayes estimators for the 2-parameter Weibull distribution (and reply)［J］.IEEE Transactions on Reliability,1988,37(5):562-565.
[9]	高攀东,沈雪瑾,陈晓阳,等.基于自助法的小样本Weibull分布可靠性分析［J］.机械设计与研究,2015,31(2):164-167. GAO Pandong,SHEN Xuejin,CHEN Xiaoyang,et al.Reliability analysis under Weibull distribution in small samples based on bootstrap［J］.Machine Design and Research,2015,31(2):164-167.(in Chinese)
[10]	秦荦晟,陈晓阳,沈雪瑾.小样本下基于竞争失效的轴承可靠性评估［J］.振动与冲击,2017,36(23):248-254. QIN Luosheng,CHEN Xiaoyang,SHEN Xuejin.Reliability assessment of bearings based on competing failure under small sample data［J］.Journal of Vibration and Shock,2017,36(23):248-254.(in Chinese)
[11]	EFRON B.Bootstrap methods:another look at the jackknife［J］.The Annals of Statistics,1979,7(1):1-26.
[12]	张中益,沈雪瑾.基于神经网络的小样本轴承球可靠度评估［J］.工业控制计算机,2019,32(5):66-67,70. ZHANG Zhongyi,SHEN Xuejin.Reliability assessment of small sample bearing balls based on artificial neural network［J］.Industrial Control Computer,2019,32(5):66-67,70.(in Chinese)
[13]	张晓东,赵建斌,安海.基于退化数据的小样本时变可靠性评估方法［J］.强度与环境,2017,44(6):57-64. ZHANG Xiaodong,ZHAO Jianbin,AN Hai.Time-variant reliability evaluation approach of small samples based on degradation data［J］.Structure and Environment Engineering,2017,44(6):57-64.(in Chinese)
[14]	茆诗松,罗朝斌.无失效轴承的可靠性分析［J］.数理统计与应用概率,1989,4(4):489-506. MAO Shisong,LUO Chaobin.Reliability analysis of failure-free bearings［J］.Mathematical Theory and Applied Probability,1989,4(4):489-506.(in Chinese)
[15]	LU C J,MEEKER W Q.Using degradation measures toestimation time-to-failure distribution［J］.Technometrics,1993,35(2):161-174.
[16]	TAYLOR M S,THOMPSON J R.A data based algorithm for the generation of random vectors［J］.Computational Statistics and Data Analysis,1986,4(2):93-101.
[17]	KINGSBURY E,WALKER R.Motions of an unstable retainer in an instrument ball bearing［J］.Journal of Tribology,1994,116(2):202-208.
[18]	GENTLE J E.Computation statistics［M］.Berlin:Springer,2009.
[19]	杨赵岩,陈晓阳,冯戴一楠,等.柔性轴承随动加载疲劳寿命试验设计［J］.机械设计与研究,2018,34(6):99-102,108. YANG Zhaoyan,CHEN Xiaoyang,FENG Daiyinan,et al.Fatigue life test design of flexible bearing under tracking-loading［J］.Machine Design and Research,2018,34(6):99-102,108.(in Chinese)
[20]	QIN Luosheng,SHEN Xuejin,CHEN Xiaoyang,et al.Reliability assessment of bearings based on performance degradation values under small samples［J］.Journal of Mechanical Engineering,2017,63(4):248-254.
[21]	GEBRAEEL N,LAWLEY M,LIU R,et al.Residual life predictions from vibration-based degradation signals:a neural network approach［J］.IEEE Transactions on Industrial Electronics,2004,51(3):694-700.
[22]	蔡忠义,陈云翔,项华春,等.基于无失效数据的加权 E-Bayes 可靠性评估方法［J］.系统工程与电子技术,2015(1):219-223.