A two-stage degradation model and reliability analysis related to degradation of binary load-sharing systems

被引:0
|
作者
Zhang, Fan [1 ,2 ]
Cheng, Bohan [3 ]
Wang, Peng [1 ,2 ]
Dong, Lei [1 ,2 ]
机构
[1] Key Laboratory of Civil Aircraft Airworthiness Technology, Civil Aviation University of China, Tianjin
[2] Science and Technology Innovation Research Institute, Civil Aviation University of China, Tianjin
[3] College of Safety Science and Engineering, Civil Aviation University of China, Tianjin
来源
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2024年 / 45卷 / 07期
基金
中国国家自然科学基金;
关键词
degradation correlation; load sharing; Monte Carlo; reliability analysis; remaining life;
D O I
10.7527/S1000-6893.2023.29046
中图分类号
学科分类号
摘要
A two-stage degradation model considering degradation rate interactions is proposed for the degradation of binary load-sharing components in highly complex airborne systems affected by degradation process interactions and load sharing. Firstly,a two-component degradation dependence characterization method based on degradation rate interaction is investigated to establish a two-component degradation correlation model without considering the influence of load sharing. Secondly,considering the influence of load sharing on degradation rate,the system degradation process is divided into two stages with a component failure as a variable point,and a two-component degradation correlation model with the influence of load sharing is constructed. The model parameters are estimated using the great likelihood estimation method,and the reliability model and the remaining life model of the system are constructed. Finally,taking an aviation component as an example,the reliability calculation of the load-sharing system related to binary degradation is carried out,and the proposed method provides support for the reliability analysis of the degradation and failure of binary load-sharing components of complex systems. © 2024 Chinese Society of Astronautics. All rights reserved.
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共 33 条
  • [1] LIU G H, GUAN Q, TANG Y C,, Et al., Interval model⁃ ing for Gamma process degradation model[J], Symmetry-Basel, 14, 5, (2022)
  • [2] ZHOU H X, ZHOU C G, WANG X Y,, Et al., Degrada⁃ tion reliability modeling for two-stage degradation ball screws[J], Precision Engineering-Journal of The Interna⁃ tional Societies for Precision Engineering and Nanotech⁃ nology, 73, pp. 347-362, (2022)
  • [3] SHEN L J, WANG Y D, Et al., Degradation modeling using stochastic processes with random initial degradation[J], IEEE Transactions on Reliability, 68, 4, pp. 1320-1329, (2019)
  • [4] LIN Y H, DING Z Q., An integrated degradation model⁃ ing framework considering model uncertainty and calibra⁃ tion[J], Mechanical Systems and Signal Processing, 166, (2022)
  • [5] CHEN Z, XIA T B, LI Y T,, Et al., Tweedie exponential dispersion processes for degradation modeling,prognos⁃ tic,and accelerated degradation test planning[J], IEEE Transactions on Reliability, 69, 3, pp. 887-902, (2020)
  • [6] TAMSSAOUE F, NGUYEN K T P,, MEDJAHER K, Et al., Online joint estimation and prediction for system-level prognostics under component interactions and mis⁃ sion profile effects[J], ISA Transactions, 113, pp. 52-63, (2021)
  • [7] R eliability analysis of aero-engines based on m ultivariate degrada⁃ tion m odeling under com petitive failure[J], Journal of N ortheastern U niversity (N atural S cience), 42, 6, pp. 807-813, (2021)
  • [8] XU D, XING M L,, WEI Q D,, Et al., Failure behavior modeling and reliability estimation of product based on vine-copula and accelerated degradation data[J], Me⁃ chanical Systems and Signal Processing, 113, pp. 50-64, (2018)
  • [9] ZHOU Y,, LI S,, XIONG N., Improved vine copula-based dependence description for multivariate process monitoring based on ensemble learning[J], Industrial and Engineering Chemistry Research, 58, 9, pp. 3782-3796, (2019)
  • [10] PENG W W, LI Y F, MI J H, Et al., Reliability of com⁃ plex systems under dynamic conditions:A Bayesian mul⁃ tivariate degradation perspective[J], Reliability Engineer⁃ ing and System Safety, 153, pp. 75-87, (2016)