Vibration response-based time-variant reliability and sensitivity analysis of rolling bearings using the first-passage method

被引:1
|
作者
Xie, Bin [1 ]
Wang, Yanzhong [1 ]
Zhu, Yunyi [2 ]
Shiyuan, E. [1 ]
Wu, Yu [3 ]
机构
[1] Beihang Univ, Sch Mech Engn & Automat, Beijing 100191, Peoples R China
[2] Beihang Univ, Sch Instrumentat & Optoelect Engn, Beijing 100191, Peoples R China
[3] Chongqing Tiema Transmiss Co Ltd, Chongqing 400050, Peoples R China
关键词
Rolling bearing; Time-variant reliability; Sensitivity analysis; First-passage method; Outcrossing rate; VECTOR MACHINE; SYSTEMS; PHI2;
D O I
10.1016/j.ress.2024.110706
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The vibration response of rolling bearings exhibits random and uncertain characteristics due to factors such as random process loads, material property degradation, and uncertain dimensional parameters. The time-variant reliability of rolling bearings obtained based on such vibration response is more realistic and accurate. In this paper, a novel vibration response-based time-variant reliability and sensitivity analysis model of rolling bearings is proposed. First, the forces on the rolling bearing are analyzed and the stress distribution is derived. Then, the equivalent stiffness and damping in the bearing vibration equation are obtained based on the ball-raceway contact model. To approximate the real degradation process, the vibration equation considering the impact load is proposed, and the statistical characteristics of the impact load with time are obtained from degradation data of the conducted bearing tests. Subsequently, the first-passage method is adopted to efficiently evaluate the time-variant reliability of rolling bearings based on the vibration response. In addition, reliability sensitivity index is derived to analyze the influence of input parameters on the reliability of rolling bearings, which improves design efficiency and provides references for further structural optimization. The accuracy and validity of the proposed model and method are verified by two cases of different bearing types.
引用
收藏
页数:16
相关论文
共 50 条
  • [31] A method for dynamic response analysis of time-variant discrete systems
    Kucharski, T
    COMPUTERS & STRUCTURES, 2000, 76 (04) : 545 - 550
  • [32] Adaptive Approximation of the First-crossing PDF for Time-variant Reliability Analysis
    Yu S.
    Wu X.
    Guo P.
    Wang Z.
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2024, 60 (05): : 264 - 275
  • [33] An efficient single-loop strategy for time-variant reliability sensitivity analysis based on Bayes' theorem
    Zha, Congyi
    Pan, Chenrong
    Sun, Zhili
    Liu, Qin
    STRUCTURES, 2024, 69
  • [34] Time-variant reliability analysis via approximation of the first-crossing PDF
    Shui Yu
    Yanwei Zhang
    Yun Li
    Zhonglai Wang
    Structural and Multidisciplinary Optimization, 2020, 62 : 2653 - 2667
  • [35] Time-Variant Reliability Analysis Method for Uncertain Motion Mechanisms Based on Stochastic Process Discretization
    Yao, Qishui
    Zhang, Quan
    Tang, Jiachang
    Wang, Xiaopeng
    Hu, Meijuan
    IEEE ACCESS, 2022, 10 : 49040 - 49049
  • [36] Time-variant reliability analysis based on high dimensional model representation
    Cheng, Kai
    Lu, Zhenzhou
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2019, 188 : 310 - 319
  • [37] Time-variant reliability modeling based on hybrid non-probability method
    Sun, Bo
    Li, Meng-Meng
    Liao, Bao-Peng
    Yang, Xi
    Cao, Yi-Tong
    Cui, Bo-Feng
    Feng, Qiang
    Ren, Yi
    Yang, De-Zhen
    ARCHIVE OF APPLIED MECHANICS, 2020, 90 (02) : 209 - 219
  • [38] Time-variant system reliability analysis method for a small failure probability problem
    Qian, Hua-Ming
    Li, Yan-Feng
    Huang, Hong-Zhong
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2021, 205
  • [39] An adaptive PC-Kriging method for time-variant structural reliability analysis
    Nan H.
    Li H.
    Song Z.
    Eksploatacja i Niezawodnosc, 2022, 24 (03) : 532 - 543
  • [40] Time-variant reliability analysis using phase-type distribution-based methods
    Li, Junxiang
    Guo, Xiwei
    Cao, Longchao
    Zhang, Xinxin
    ADVANCES IN ENGINEERING SOFTWARE, 2024, 198