Please wait a minute...
Chinese Journal of Engineering Design  2024, Vol. 31 Issue (4): 420-427    DOI: 10.3785/j.issn.1006-754X.2024.03.213
Reliability and Quality Design     
Reliability life evaluation method of rolling bearing considering dynamic time-varying loads
Junxing LI1,2,3(),Rui GAO1,Ming QIU1,2(),Yanke LI1,Jingtao LIU1,Zhiwei LIU1
1.School of Mechatronics Engineering, Henan University of Science and Technology, Luoyang 471003, China
2.Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing of Henan, Luoyang 471003, China
3.Collaborative Innovation Center for High-end Bearings of Henan, Luoyang 471003, China
Download: HTML     PDF(1749KB)
Export: BibTeX | EndNote (RIS)      

Abstract  

Load is a factor that cannot be disregarded during the running of rolling bearing, and loads with distinct characteristics will exert varying impacts on the reliability of bearing. In response to the stochastic time-varying nature of equivalent dynamic loads borne by rolling bearings, a reliability life evaluation method of rolling bearing considering dynamic time-varying loads was proposed to solve the problem of low evaluation accuracy caused by ignoring the time-varying bearing load in traditional methods. Based on the grey prediction model, the analysis model of the stochastic time-varying process of the bearing equivalent dynamic load was constructed, and the small sample load data was forecasted and supplemented. On this basis, an reliability life evaluation method of rolling bearing based on dynamic stress-strength interference model was proposed, and the working interval of dynamic load was obtained, so as to obtain the bearing reliability life interval. The reliability life test of cylindrical roller bearing NU206E was carried out to verify the proposed method. The results showed that, compared with the traditional method, the bearing life evaluation value obtained by the proposed method was close to the test values with higher accuracy and shorter evaluation time, and the life interval covering the most test values could be obtained. The method combining gray prediction model and dynamic stress-strength interference model has good engineering application value, and provides a new idea for reliability evaluation of rolling bearing under variable load conditions.



Key wordsrolling bearing      reliability assessment      grey prediction model      time-varying stress      stress-strength interference model     
Received: 06 November 2023      Published: 26 August 2024
CLC:  V 474.2  
Corresponding Authors: Ming QIU     E-mail: lijun-xing2008 @163.com;qiuming69@126.com
Cite this article:

Junxing LI,Rui GAO,Ming QIU,Yanke LI,Jingtao LIU,Zhiwei LIU. Reliability life evaluation method of rolling bearing considering dynamic time-varying loads. Chinese Journal of Engineering Design, 2024, 31(4): 420-427.

URL:

https://www.zjujournals.com/gcsjxb/10.3785/j.issn.1006-754X.2024.03.213     OR     https://www.zjujournals.com/gcsjxb/Y2024/V31/I4/420


考虑动态时变载荷的滚动轴承可靠性寿命评估方法

载荷是滚动轴承运转过程中不可忽视的因素,不同特征的载荷会对轴承的可靠性产生差异影响。针对滚动轴承实际当量动载荷具有随机时变的特点,提出了一种考虑动态时变载荷的滚动轴承可靠性寿命评估方法,以解决传统方法忽略轴承载荷时变性导致的评估精度较低的问题。利用灰色预测模型,构建了轴承当量动载荷随机时变过程的分析模型,对小样本载荷数据进行预测补充;在此基础之上,提出了基于动态应力—强度干涉模型的轴承可靠性寿命评估方法,得到了动载荷的工作区间,从而获得轴承可靠性寿命区间;进行了圆柱滚子轴承NU206E的可靠性寿命测试,对该方法进行验证。结果表明:与传统方法相比,采用所提出的方法得到的轴承寿命评估值与测试值较接近,精度较高,评估时间较短,且能获得覆盖大部分测试值的寿命区间。结合灰色预测模型和动态应力—强度干涉模型的滚动轴承可靠性寿命评估方法具有良好的工程应用价值,为变载工况下的滚动轴承可靠性评估提供了新的思路。


关键词: 滚动轴承,  可靠性评估,  灰色预测模型,  时变应力,  应力—强度干涉模型 
Fig.1 Flow chart for reliability life evaluation of rolling bearing
Fig.2 Cylindrical roller bearing NU206E
参数数值
内径/mm30
外径/ mm62
滚子直径/mm8.5
滚子数量/个13
额定动载荷/kN36
Table 1 Basic parameters of cylindrical rolling bearing NU206E
Fig.3 Rolling bearing life test bench
工况参数数值
径向载荷/kN10.54
轴向载荷/kN0
转速/(r/min)5 000
Table 2 Rolling bearing life test work condition
样品编号寿命/h

(2021)SM102-22

(2021)SM102-24

28

161.5

(2021)SM102-26391.5
(2021)SM102-30113.5
(2021)SM102-3295.5
(2021)SM102-3445
(2021)SM102-3896
(2021)SM102-40142
Table 3 Rolling bearing life test results
Fig.4 Radial load of rolling bearing
Fig.5 Normal Q-Q plot of rolling bearing external load data
方法寿命/h相对误差/%评估时间/h
实验测试48391.5
传统方法200316.67
本文方法61.4728.0620
Table 4 Evaluation results of rolling bearing life under different methods
[1]   张小丽, 陈雪峰, 李兵, 等. 机械重大装备寿命预测综述[J]. 机械工程学报, 2011, 47(11): 100-116. doi:10.3901/jme.2011.11.100
ZHANG X L, CHEN X F, LI B, et al. Review of life prediction for mechanical major equipments[J]. Journal of Mechanical Engineering, 2011, 47(11): 100-116.
doi: 10.3901/jme.2011.11.100
[2]   ZAIDI S S H, AVIYENTE S, SALMAN M, et al. Prognosis of gear failures in DC starter motors using hidden Markov models[J]. IEEE Transactions on Industrial Electronics, 2011, 58(5): 1695-1706.
[3]   戚其松, 李成刚, 董青, 等. 起重机生命周期载荷谱预测及基于疲劳寿命的结构优化设计[J]. 工程设计学报, 2023, 30(3): 380-389.
QI Q S, LI C G, DONG Q, et al. Prediction of load spectrum for crane life cycle and structural optimal design based on fatigue life[J]. Chinese Journal of Engineering Design, 2023, 30(3): 380-389.
[4]   武滢, 谢里阳. 随机载荷作用下疲劳寿命分布预测模型[J]. 工程设计学报, 2010, 17(6): 435-438.
WU Y, XIE L Y. Prediction on probability distribution of fatigue life under spectrum loading[J]. Chinese Journal of Engineering Design, 2010, 17(6): 435-438.
[5]   LI H F, WEI J L, LI S H, et al. Fatigue life prediction of high-speed train bearings based on the generalized linear cumulative damage theory[J]. Fatigue & Fracture of Engineering Materials and Structures, 2023, 46(6): 2112-2120.
[6]   杨晨, 池茂儒, 吴兴文, 等. 基于车辆动力学的动车组轴箱轴承动态载荷计算方法[J]. 机械工程学报, 2023, 59(14): 179-189. doi:10.3901/jme.2023.14.179
YANG C, CHI M R, WU X W, et al. Dynamic load calculation method of EMU axle box bearing based on vehicle dynamics[J]. Journal of Mechanical Engineering, 2023, 59(14): 179-189.
doi: 10.3901/jme.2023.14.179
[7]   WANG Z W, ZHANG W H, YIN Z H, et al. Effect of vehicle vibration environment of high-speed train on dynamic performance of axle box bearing[J]. Vehicle System Dynamics, 2019, 57(4): 543-563.
[8]   GUO R X, WANG Y G. Remaining useful life prognostics for the rolling bearing based on a hybrid data-driven method[J]. Proceedings of the Institution of Mechanical Engineers Part I: Journal of Systems and Control Engineering, 2021, 235(4): 517-531.
[9]   MENG Z, LI J, YIN N, et al. Remaining useful life prediction of rolling bearing using fractal theory[J]. Measurement, 2020, 156: 107572.
[10]   MEDDOUR I, MESSEKHER S E, YOUNES R, et al. Selection of bearing health indicator by GRA for ANFIS-based forecasting of remaining useful life[J]. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2021, 43(3): 1-14.
[11]   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.
[12]   BEN ALI J, CHEBEL-MORELLO B, SAIDI L, et al. Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network[J]. Mechanical Systems and Signal Processing, 2015, 56: 150-172.
[13]   孙志礼, 王超. 载荷为随机变量时滚动轴承的可靠性设计[J]. 东北工学院学报(自然科学版), 1991, 12(5): 516-523.
SUN Z L, WANG C. Reliability design of rolling bearings under a load as random variable[J]. Journal of Northeastern University (Natural Science), 1991, 12(5): 516-523.
[14]   房亚东, 陈桦. 现代设计方法与应用[M]. 北京: 机械工业出版社, 2013.
FANG Y D, CHEN H. Modern design method and application [M]. Beijing: China Machine Press, 2013.
[15]   伊枭剑, 董海平, 翟志强, 等. 基于应力—强度干涉模型的火工品可靠性设计方法[J]. 北京理工大学学报, 2014, 34(10): 1007-1011.
YI X J, DONG H P, ZHAI Z Q, et al. Reliability design for initiating devices based on stress-strength interference model[J]. Transactions of Beijing Institute of Technology, 2014, 34(10): 1007-1011.
[16]   陈文华, 朱海峰, 樊晓燕. 齿轮系统传动误差的蒙特卡洛模拟分析[J]. 仪器仪表学报, 2004, 25(4): 435-437, 444.
CHEN W H, ZHU H F, FAN X Y. Monte-Carlo simulation analysis of transmission error for gear drive systems[J]. Chinese Journal of Scientific Instrument, 2004, 25(4): 435-437, 444.
[17]   刘晓静. 基于蒙特卡洛方法的可靠性灵敏度分析[J]. 机械管理开发, 2021, 36(11): 53-55.
LIU X J. Reliability sensitivity analysis based on Monte Carlo method[J]. Mechanical Management and Development, 2021, 36(11): 53-55.
[18]   杨晓蔚. 滚动轴承的可靠性设计[J]. 轴承, 2013(12): 1-5. doi:10.3969/j.issn.1000-3762.2013.12.001
YANG X W. Reliability design of rolling bearings[J]. Bearing, 2013(12): 1-5.
doi: 10.3969/j.issn.1000-3762.2013.12.001
[19]   李仁兴, 周金宇, 孙奎洲, 等. 随机载荷下滚动轴承系统疲劳可靠性分析[J]. 机床与液压, 2012, 40(1): 157-160.
LI R X, ZHOU J Y, SUN K Z, et al. Reliability analysis for rolling bearing systems under random load[J]. Machine Tool & Hydraulics, 2012, 40(1): 157-160.
[20]   张义民, 贺向东, 刘巧伶, 等. 任意分布参数的机械零件的可靠性稳健设计(二): 轴[J]. 工程设计学报, 2004, 11(5): 238-242.
ZHANG Y M, HE X D, LIU Q L, et al. Reliability-based robust design of mechanical components witharbitrary distribution parameters, Part 2: Axles[J]. Chinese Journal of Engineering Design, 2004, 11(5): 238-242.
[1] Junxing LI,Shijie NING,Ming QIU. Reliability design of radial clearance of rolling bearing[J]. Chinese Journal of Engineering Design, 2023, 30(6): 738-745.
[2] Wen-bing TU,Xiao-wen YUAN,Jin-wen YANG,Ben-meng YANG. Research on dynamic characteristics of rolling bearing under different component fault conditions[J]. Chinese Journal of Engineering Design, 2023, 30(1): 82-92.
[3] LU Feng-yi, ZHAO Ke-yuan, XU Ge-ning, QI Qi-song. Reliability assessment of small sample based on multiple source information fusion and fuzzy fault tree[J]. Chinese Journal of Engineering Design, 2017, 24(6): 609-617.
[4] GUO Ming, CHEN Zong-Nong, WANG Qing-Jiu. Control of Preload of Bearing on Precision Machine Tool[J]. Chinese Journal of Engineering Design, 2001, 8(2): 85-87.
[5] CUI Dong-Yin, WANG Guang-Fu. Discussion on Rolling Bearing Fit Selection from Burning Loss of Rolling Bearings[J]. Chinese Journal of Engineering Design, 2000, 7(4): 5-7.