Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Given the presence of multiple degradation failure processes and shock failure processes within the complex system during operation, this paper develops a reliability model that combines the multiple degradation-shock competing failure process and dynamic failure threshold. The Wiener process with random effects is considered asthe degradation process model, which includes random effects to account for the heterogeneity among system units. Additionally, the extreme shock model with a dynamic failure threshold is used to depict the random shock. Then, the copula function is carried out to illustrate the correlation between multiple degradation processes, the reliability model is constructed further. To demonstrate the application of this model, a numerical case study and a micro-electro-mechanical system comprising two micro-mechanical resonators are employed. The parameter sensitivity of the proposed model is analyzed. The outcomes of the study highlight that the reliability model, which combines the Wiener process with random effects and the dynamic failure threshold, more accurately reflects the actual operational state of the complex system.
Czasopismo
Rocznik
Tom
Strony
art. no. 174248
Opis fizyczny
Bibliogr. 36 poz., tab., wykr.
Twórcy
autor
- School of Automation and Information, Xi’an University of Technology, Xi’an, China
autor
- SchoolofIntelligenceScienceandTechnology, UniversityofScienceandTechnology Beijing, Beijing, China
autor
- School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, China
Bibliografia
- 1. A. Shangguan, G. Xie, R. Fei, L. Mu, X. Hei, Train wheel degradation generation and prediction based on the time series generation adversarial network, Reliability engineering and system safety, vol 229,108816, 2023. https://doi.org/10.1016/j.ress.2022.108816
- 2. A. Zhang, Z. Wang, R. Bao, C. Liu, Q. Wu, S. Cao, A novel failure time estimation method for degradation analysis based on general nonlinear Wiener processes, Reliability Engineering & System Safety, vol. 230, no. 108913, 2022. https://doi.org/10.1016/j.ress.2022.108913
- 3. Anqi Shangguan, Guo Xie, Lingxia Mu, et al, Reliability modeling: combining self-healing characteristics and competing failure process, Quality Technology & Quantitative Management,doi: 10.1080/16843703.2023.2202955. 2023.
- 4. A. Patton, Estimation of Multivariate Models for Time Series of Possibly Different Lengths, Journal of Applied Econometrics, vol.21, no. 2, pp:147-173, 2006. https://doi.org/10.1002/jae.865
- 5. B. Liu, M. Xie, Z. Xu, W. Kuo. An imperfect maintenance policy for mission-oriented systems subject to degradation and external shocks. Computers & Industrial Engineering, vol. 102, pp: 21-32, 2016. https://doi.org/10.1016/j.cie.2016.10.008
- 6. B. Zheng, C. Chen, W. Zhang, R. Fu, Y. Hu, et, al, Reliability estimation of complex systems based on a Wiener process with random effects and D-vine copulas, Microelectronics Reliability, vol. 138, no.114640, 2022. https://doi.org/10.1016/j.microrel.2022.114640
- 7. B. Chi, Y. Wang, J. Hu, S. Zhang, X. Chen, Reliability assessment for micro inertial measurement unit based on accelerated degradation data and copula theory, Eksploatacja i Niezawodnosc -Maintenance and Reliability, vol.24, no.3, pp.554-563, 2022. https://doi.org/10.17531/ein.2022.3.16
- 8. C. Zhang, Y. Zhang, H. Dui, S. Wang, MM. Tomovic, Component Maintenance Strategies and Risk Analysis for Random Shock EffectsConsidering Maintenance Costs. Eksploatacja i Niezawodnosc -Maintenance and Reliability 2023: 25(2) http://doi.org/10.17531/ein/162011.
- 9. D. Liu, S. Wang, Reliability estimation from lifetime testing data and degradation testing data with measurement error based on evidential variable and Wiener process, Reliability engineering and system safety, vol.205, no.107231, 2021. https://doi.org/10.1016/j.ress.2020.107231
- 10. D. Liu, S. Wang, Reliability estimation from lifetime testing data and degradation testing data with measurement error based on evidential variable and Wiener process, Reliability Engineering & System Safety, vol. 205, no. 207231, 2021. https://doi.org/10.1016/j.ress.2020.107231
- 11. D. Liu, G. Liao, M. Chen, H. Yin, Two-phase degradation modeling and remaining useful life prediction using nonlinear wiener process, Computers & Industrial Engineering, vol. 160, no. 107533, 2021. https://doi.org/10.1016/j.cie.2021.107533
- 12. D. Liu, S. Wang, C. Zhang, Reliability estimation from two types of accelerated testing data based on an artificial neural network supported Wiener process, Applied Mathematics and Computation, Volume 417, 2022,126757. https://doi.org/10.1016/j.amc.2021.126757
- 13. D. Tanner, M. Dugger, Wear mechanisms in a reliability methodology, Reliability, testing and characterization of mems /moems II, vol.4980, pp: 22-40. doi:10.1117/12.476345, 2003.
- 14. D. Cox, H. Miller, The theory of stochastic processes, London: Chapman and Hall, 1965.
- 15. Y. Zhang, Q. Chen, D.Yan, H. Zhang, Equivalent circuit modelling of large hydropower plants with complex tailrace system for ultra-low frequency oscillation analysis, Applied Mathematical Modelling, vol.103, pp:176-194, 2022. https://doi.org/10.1016/j.apm.2021.10.017
- 16. F. Sun , H. Li , Y. Cheng , H. Liao, Reliability analysis for a system experiencing dependent degradation processes and random shocks based on a nonlinear Wiener process model, Reliability engineering and system safety,vol 215,107906, 2021. https://doi.org/10.1016/j.ress.2021.107906
- 17. H. Lyu, S. Wang, X. Zhang, Z. Yang, M. Pecht, Reliability modeling for dependent competing failure processes with phase-type distribution considering changing degradation rate, Eksploatacja i Niezawodnosc -Maintenance and Reliability, vol.23, no.4, pp.627-635.2021. https://doi.org/10.17531/ein.2021.4.5
- 18. J. Wang, Z. Li, G. B., Ming J. Zuo, An improved model for dependent competing risks considering continuous degradation and random shocks, Reliability Engineering & System Safety, vol. 193, no. 106641, 2020. https://doi.org/10.1016/j.ress.2019.106641
- 19. J. Ma, L. Cai, G. Liao, H. Yin, X. Si, P. Zhang, A multi-phase Wiener process-based degradation model with imperfect maintenance activities, Reliability Engineering & System Safety, vol. 232, no. 109075, 2023. https://doi.org/10.1016/j.ress.2022.109075
- 20. J. Shi, Y. Qiao, S. Wang, X. Cui, D. Liu, A reliability estimation method based on two-phase Wiener process with evidential variable using two types of testing data, Quality & Reliability Engineering International, doi: 10.1002/qre.3234, 2022. https://doi.org/10.1002/qre.3234
- 21. J. Li, Z. Wang, Y. Zhang, C. Liu, H. Fu, A nonlinear Wiener process degradation model with autoregressive errors, ReliabilityEngineering & System Safety, vol. 173, pp. 48-57, 2018. https://doi.org/10.1016/j.ress.2017.11.003
- 22. J. Tang, C. Chen, L. Huang, Reliability assessment models for dependent competing failure processes considering correlations between random shocks and degradations. Quality & Reliability Engineering International, vol.35, pp:179-191, 2019. https://doi.org/10.1002/qre.2390
- 23. K. Lijesh, M. khnosari, Characterization of abrasive wear using degradation coefficient, Wear, vol 450, no.203220, 2020. https://doi.org/10.1016/j.wear.2020.203220
- 24. P. Jiang, B. Wang, F. Wu, Inference for constant-stress accelerated degradation test based on Gamma process, Applied Mathematical Modelling, vol. 67, pp: 123-134, 2019. https://doi.org/10.1016/j.apm.2018.10.017
- 25. P. Jiang, B. Wang, X. Wang, Z. Zhou, Inverse Gaussian process based reliability analysis for constant-stress accelerated degradation data, Applied Mathematical Modelling, vol.105, pp. 137-148, 2022. https://doi.org/10.1016/j.apm.2021.12.003
- 26. R. Nelsen, An Introduction to Copulas, 2nd ed. New York: Springer, 2006.
- 27. S. Tang, F. Wang, X. Sun, X. Xu, C. Yu, X. Si, Unbiased parameters estimation and mis-specification analysis of Wiener process-based degradation model with random effects, Applied Mathematical Modelling, vol. 109, pp. 134-160, 2022. https://doi.org/10.1016/j.apm.2022.03.039
- 28. W. Li, H. Pham, Reliability modeling of multi-state degraded systems with multi-competing failures and random shocks. IEEE Transactions on Reliability. vol. 54, pp:297-303, 2005. https://doi.org/10.1109/TR.2005.847278
- 29. W. Gao, Y. Wang, X. Zhang, Z. Wang, Quasi-periodic Inspection and Preventive Maintenance Policy Optimisation for a system with Wiener Process degradation. Eksploatacja i Niezawodnosc -Maintenance and Reliability 2023: 25(2) http://doi.org/10.17531/ein/162433
- 30. W. Hsu, Recent progress in silicon MEMS oscillators. In: Proceedings of the 40th Annual Precise Time and Time Interval (PTTI)meeting, pp. 135-146, 2008.
- 31. W. Dong, S. Liu, S. Bae, Y. Cao, Reliability modelling for multi-component systems subject to stochastic, Reliability Engineering & System Safety, vol.205, 107260, 2021. https://doi.org/10.1016/j.ress.2020.107260
- 32. X. Wang, L. Li, M. Chang, K. Han, Reliability modeling for competing failure processes with shifting failure thresholds undersevere product working conditions, Applied Mathematical Modeling, vol.89, pp.1747-1763,2021. https://doi.org/10.1016/j.apm.2020.08.032
- 33. X. Dai, S. Qu, H. Sui, P. Wu, Reliability modelling of wheel wear deterioration using conditional bivariate gamma processes and Bayesian hierarchical models, Reliability Engineering & System Safety, vol. 226, no. 108710, 2022. https://doi.org/10.1016/j.ress.2022.108710
- 34. Y. Wang, H. Pham, Modeling the Dependent Competing Risks with Multiple Degradation Processes and Random Shock Using Time-Varying Copulas. IEEE Transactions on Reliability, vol. 61, pp:13-22, 2012. https://doi.org/10.1109/TR.2011.2170253
- 35. Z. Wang, H. Huang, Y. Li, N. Xiao. An approach to reliability assessment under degradation and shock process. IEEE Transactions on Reliability, vol.60, no.4, pp:852-863. 2011. https://doi.org/10.1109/TR.2011.2170254
- 36. Z. Ye, M. Xie, Stochastic modelling and analysis of degradation for highly reliable products. Applied Stochastic Models in Business and Industry, vol. 31, no.1, pp: 16-32, 2015, https://doi.org/10.1002/asmb.2063
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f583f2c6-44c9-45b8-b0bd-5a6cfff31a79