Residual life prediction of rolling bearing under multiple stresses

Ming QIU; Kaicen NIU; Junxing LI; Yanke LI; Yanlei XU

doi:10.13224/j.cnki.jasp.20210246

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Residual life prediction of rolling bearing under multiple stresses

Power Transimission | 更新时间：2025-04-07

- Residual life prediction of rolling bearing under multiple stresses
- Journal of Aerospace Power Vol. 37, Issue 5, Pages: 980-988(2022)
- 作者机构：
  
  1.河南科技大学机电工程学院，河南洛阳 471003
  2.机械装备先进制造河南省协同创新中心，河南洛阳 471003
- 作者简介：
- 基金信息：
- DOI：10.13224/j.cnki.jasp.20210246
  CLC：
- 稿件说明：
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Ming QIU, Kaicen NIU, Junxing LI, et al. Residual life prediction of rolling bearing under multiple stresses[J]. Journal of Aerospace Power, 2022, 37(5): 980-988.
DOI：

Ming QIU, Kaicen NIU, Junxing LI, et al. Residual life prediction of rolling bearing under multiple stresses[J]. Journal of Aerospace Power, 2022, 37(5): 980-988. DOI： 10.13224/j.cnki.jasp.20210246.

摘要

为了实现多重应力下滚动轴承的剩余寿命预测，有效利用不用应力下的退化数据，提出了一种基于加速模型和贝叶斯（Bayesian）理论的滚动轴承剩余寿命预测方法。通过拟合优度检验和威布尔（Weibull）概率图检验法对滚动轴承试验中的数据进行有效性分析。利用switching Kalman filters（SKF）判断滚动轴承各时刻的退化状态。当滚动轴承进入加速退化时，用指数模型拟合轴承退化过程，利用广义线性对数模型表示退化模型参数与应力的关系，根据修正后的轴承实时退化数据利用贝叶斯算法更新模型参数，得到滚动轴承剩余寿命的概率密度函数，从而实现滚动轴承剩余寿命预测。采用XJTU⁃SY轴承数据集进行验证，预测结果的均方根误差在20 min以内，证明该方法能够有效预测滚动轴承的剩余寿命。

Abstract

In order to realize the residual life prediction of rolling bearings under multiple stresses，a method for residual life prediction of rolling bearings based on acceleration model and Bayesian theory was proposed by effectively utilizing the degradation data under no stresses.The validity of the rolling bearing test data was analyzed by goodness of fit test and Weibull probability graph test.Switching Kalman filters （SKF） were used to determine the degradation state of the rolling bearing at each moment.When rolling bearing entered into the accelerated degradation，degradation process of bearing was fitted with exponential model，and the generalized linear logarithmic model was used to represent the relationship between degradation model parameters and stress；according to the revised bearing real⁃time degradation data，the model parameters were updated using Bayesian algorithm，the probability density function of the residual life of rolling bearing were acquired for residual life prediction of the rolling bearing.The XJTU⁃SY bearing data set was used for verification，and the root mean square error of the predicted results was less than 20 min，proving that the proposed method can effectively predict the residual life of rolling bearings.

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references

茆诗松 . 加速寿命试验的加速模型 [J]. 质量与可靠性 , 2003 （ 2 ）: 15 ⁃ 17 .

MAO Shisong . Accelerated model of accelerated life test [J]. Quality and Reliability , 2003 （ 2 ）: 15 ⁃ 17 . （in Chinese）

黄婷婷 , 姜同敏 . 加速寿命试验中统计加速模型综述 [J]. 装备环境工程 , 2010 , 7 （ 4 ）: 61 ⁃ 66 .

HUANG Tingting , JIANG Tongmin . Review of statistical acceleration models in accelerated life testing [J]. Equipment Environmental Engineering , 2010 , 7 （ 4 ）: 61 ⁃ 66 . （in Chinese）

李晓阳 , 姜同敏 . 加速寿命试验中多应力加速模型综述 [J]. 系统工程与电子技术 , 2007 , 29 （ 5 ）: 828 ⁃ 831 .

LI Xiaoyang , JIANG Tongmin . Review of multiple⁃stress models in accelerated life testing [J]. Systems Engineering and Electronics , 2007 , 29 （ 5 ）: 828 ⁃ 831 . （in Chinese）

王浩伟 , 徐廷学 , 赵建忠 . 融合加速退化和现场实测退化数据的剩余寿命预测方法 [J]. 航空学报 , 2014 , 35 （ 12 ）: 3350 ⁃ 3357 .

WANG Haowei , XU Tingxue , ZHAO Jianzhong . Residual life prediction method fusing accelerated degradation and field degradation data [J]. Acta Aeronautica et Astronautica Sinica , 2014 , 35 （ 12 ）: 3350 ⁃ 3357 . （in Chinese）

王浩伟 , 徐廷学 , 刘勇 . 基于随机参数Gamma过程的剩余寿命预测方法 [J]. 浙江大学学报（工学版） , 2015 , 49 （ 4 ）: 699 ‑ 704 .

WANG Haowei , XU Tingxue , LIU Yong . Remaining useful life prediction method based on Gamma processes with random parameters [J]. Journal of Zhejiang University （Engineering Science） , 2015 , 49 （ 4 ）: 699 ⁃ 704 . （in Chinese）

王浩伟 , 滕克难 , 盖炳良 . 基于加速因子不变原则的加速退化数据分析方法 [J]. 电子学报 , 2018 , 46 （ 3 ）: 739 ⁃ 747 .

WANG Haowei , TENG Kenan , GAI Bingliang . The method of analyzing accelerated degradation data based on acceleration factor constant principle [J]. Acta Electronica Sinica , 2018 , 46 （ 3 ）: 739 ⁃ 747 . （in Chinese）

王华伟 , 吴海桥 . 基于信息融合的航空发动机剩余寿命预测 [J]. 航空动力学报 , 2012 , 27 （ 12 ）: 2749 ⁃ 2755 .

WANG Huawei , WU Haiqiao . Residual useful life prediction for aircraft engine based on information fusion [J]. Journal of Aerospace Power , 2012 , 27 （ 12 ）: 2749 ⁃ 2755 . （in Chinese）

刘小平 , 张立杰 , 沈凯凯 , 等 . 考虑测量误差的步进加速退化试验建模与剩余寿命估计 [J]. 兵工学报 , 2017 , 38 （ 8 ）: 1586 ⁃ 1592 .

LIU Xiaoping , ZHANG Lijie , SHEN Kaikai , et al . Step stress accelerated degradation test modeling and remaining useful life estimation in consideration of measuring error [J]. Acta Armamentarii , 2017 , 38 （ 8 ）: 1586 ⁃ 1592 . （in Chinese）

EBRAHEM A H , HIGGINS J J . Non⁃parametric analysis of a proportional wearout model for accelerated degradation data [J]. Applied Mathematics and Computation , 2006 , 174 （ 1 ）: 365 ⁃ 373 .

司小胜 , 胡昌华 , 李娟 , 等 . Bayesian更新与EM算法协作下退化数据驱动的剩余寿命估计方法 [J]. 模式识别与人工智能 , 2013 , 26 （ 4 ）: 357 ⁃ 365 .

SI Xiaosheng , HU Changhua , LI Juan , et al . Degradation data⁃driven remaining useful life estimation approach under collaboration between Bayesian updating and EM [J]. Pattern Recognition and Artificial Intelligence , 2013 , 26 （ 4 ）: 357 ⁃ 365 . （in Chinese）

GEBRAEEL N . Sensory⁃updated residual life distributions for components with exponential degradation patterms [J]. IEEE Transactions on Automation Science and Engineering , 2006 , 3 （ 4 ）: 382 ⁃ 393 .

ELWANY A , GEBRAEEL N . Real⁃time estimation of mean remaining life using sensor⁃based degradation models [J]. Journal of Manufacturing Science and Engineering , 2009 , 131 （ 5 ）: 51 ⁃ 59 .

张鹏 , 胡昌华 , 白灿 , 等 . 考虑随机效应的两阶段退化系统剩余寿命预测方法 [J]. 中国测试 , 2019 , 45 （ 1 ）: 5 ⁃ 11 .

ZHANG Peng , HU Changhua , BAI Can , et al . Remaining useful life estimation method for two⁃phase degradation system with random effects [J]. China Measurement and Testing Technology , 2019 , 45 （ 1 ）: 5 ⁃ 11 . （in Chinese）

BAE S J , YUAN T , NING S , et al . A Bayesian approach to modeling two⁃phase degradation using change⁃point regression [J]. Reliability Engineering and System Safety , 2015 , 134 （ 2 ）: 66 ⁃ 74 .

CHEN N , TSUI K L . Condition monitoring and remaining useful life prediction using degradation signals:revisited [J]. IIE Transactions , 2013 , 45 （ 9 ）: 939 ⁃ 952 .

王坚永 , 庄中华 , 吴秀鸾 , 等 . 滚动轴承可靠性加速寿命试验研究 [J]. 轴承 , 1996 （ 9 ）: 23 ⁃ 28,45 .

WANG Jianyong , ZHUANG Zhonghua , WU Xiuluan , et al . Study on reliability accelerated life test of rolling bearing [J]. Bearing , 1996 （ 9 ）: 23 ⁃ 28,45 . （in Chinese）

徐东 , 徐永成 , 陈循 , 等 . 滚动轴承加速寿命试验技术研究 [J]. 国防科技大学学报 , 2010 , 32 （ 6 ）: 122 ⁃ 129 .

XU Dong , XU Yongcheng , CHEN Xun , et al . Research on accelerated life test for rolling element bearings [J]. Journal of National University of Defense Technology , 2010 , 32 （ 6 ）: 122 ⁃ 129 . （in Chinese）

中国电子技术标准化研究所 . 可靠性试验用表 [M]. 北京 : 国防工业出版社 , 1987 : 234 ⁃ 239 .

PARK J I , BAE S J . Direct prediction methods on lifetime distribution of organic light⁃emitting diodes from accelerated degradation tests [J]. IEEE Transactions on Reliability , 2010 , 59 （ 1 ）: 74 ⁃ 90 .

PARK C , PADGETT W J . Stochastic degradation models with several accelerating variables [J]. IEEE Transactions on Reliability , 2006 , 55 （ 2 ）: 379 ⁃ 390 .

ELWANY A H , GEBRAEEL N Z , MAILLART L M . Structured replacement policies for components with complex degradation processes and dedicated sensors [J]. Operations Research , 2017 , 59 （ 3 ）: 684 ⁃ 695 .

周源泉 , 叶喜涛 . 论加速系数与失效机理不变的条件:Ⅰ 寿命型随机变量的情况 [J]. 系统工程与电子技术 , 1996 , 18 （ 1 ）: 55 ⁃ 67 .

ZHOU Yuanquan , YE Xitao . Study on accelerated factor and condition for constant failure mechanism:Ⅰ the case for lifetime is a random variable [J]. Systems Engineering and Electronics , 1996 , 18 （ 1 ）: 55 ⁃ 67 . （in Chinese）

盖炳良 , 滕克难 , 王浩伟 , 等 . 基于加速因子的Wiener退化产品可靠性评估方法 [J]. 战术导弹技术 , 2017 （ 6 ）: 31 ⁃ 36 .

GAI Bingliang , TENG Kenan , WANG Haowei , et al . Reliability assessment approach for wiener‑type degradation based on acceleration factor [J]. Tactical Missile Technology , 2017 （ 6 ）: 31 ⁃ 36 . （in Chinese）

WANG B , LEI Y G , LI N P , et al . A hybrid prognostics approach for estimating remaining useful life of rolling element bearings [J]. IEEE Transactions on Reliability , 2020 , 69 （ 1 ）: 1 ‑ 12 .

雷亚国 , 韩天宇 , 王彪 , 等 . XJTU⁃SY滚动轴承加速寿命试验数据集解读 [J]. 机械工程学报 , 2019 , 55 （ 16 ）: 1 ⁃ 6 .

LEI Yaguo , HAN Tianyu , WANG Biao , et al . XJTU⁃SY rolling element bearing accelerated life test datasets:a tutorial [J]. Journal of Mechanical Engineering , 2019 , 55 （ 16 ）: 1 ⁃ 6 . （in Chinese）

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