RESEARCH PAPER
Predicting Remaining Useful Life of AC Contactors Based on a Novel Doubly Truncated Degradation Model Considering Arcing Mode Transitions
1
Hebei University of Technology, China
Submission date: 2026-02-11
Final revision date: 2026-03-21
Acceptance date: 2026-03-31
Online publication date: 2026-04-25
KEYWORDS
remaining useful life predictionAC contactormultiple arcing modesnonlinear degradation correlationzero and bounded degradation increments
TOPICS
ABSTRACT
Accurate remaining useful life (RUL) prediction of AC contactors is essential for efficient operation and maintenance of the manufacturing system. Existing methods cannot adequately capture the degradation of AC contactors due to their inability to depict the special characteristic of zero and bounded arcing Joule integrals (i.e., degradation increments). To tackle this problem, the physical model of arcing Joule integrals is first derived through arcing mechanism analysis. Bounds of arcing Joule integrals are obtained by introducing critical breaking phase angles to the physical model, and four arcing modes are identified. A method for measuring the similarity between arcing modes is proposed, and then an arcing mode similarity based discrete-time Markov chain is constructed to depict arcing mode transitions. Motivated by zero and bounded arcing Joule integrals, an increment process with zero and bounded increments is proposed to characterize the degradation of a single-phase contact pair. Finally, the superiority of the proposed method is illustrated by real and numerical cases.
REFERENCES (35)
1.
Xing C, Liu S, Peng S, Gao S, Liu Y, Li J, Cao Y. Remaining electrical life prediction of AC contactor based on CAE-BiGRU-Attention. Measurement Science and Technology 2024; 35(1): 015041, 10.1088/1361-6501/ad05a1.
2.
Sun S, Liu J, Wang J, Shao X, Zhao Y. Research on evaluation and prediction method of electrical life of contactor individual. IEEJ Transactions on Electrical and Electronic Engineering 2024; 19(10): 1596–1609. https://doi.org/10.1002/tee.24....
3.
Liu S, Li Y, Peng S, Cao Y. Classification and prediction of AC contactor degradation states based on K-Means clustering and Bayes-BiLSTM. Journal of Electrical Engineering & Technology 2025; 20(3): 1899–1910. 10.1007/s42835-024-02065-6.
4.
Xing C, Liu S, Li Y, Xu J, Li J. Degradation stage division and identification of AC contactor’s contact system. IEEE Sensors Journal 2025; 25(4): 7068–7078. 10.1109/JSEN.2025.3527471.
5.
Tang S, Wang F, Sun X, Xu X, Yu C, Si X. Unbiased parameters estimation and mis-specification analysis of Wiener process-based degradation model with random effects. Applied Mathematical Modelling 2022; 109: 134–160. https://doi.org/10.1016/j.apm.....
6.
Cao X, Shi X, Zhao J, Duan Y, Yang X. Dynamic grouping maintenance optimization by considering the probabilistic remaining useful life prediction of multiple equipment. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2024; 26(3): 187793. https://doi.org/10.17531/ein/1....
7.
Li K, Zhao C, Niu F, Zheng S, Duan Y, Huang S, Wu Y. Electrical performance degradation model and residual electrical life prediction for AC contactor. IEEE Transactions on Components, Packaging and Manufacturing Technology 2020; 10(3): 400–417. 10.1109/TCPMT.2020.2966516.
8.
Sun S, Wang Q, Du T, Wang J, Li S, Zong J. Quantitative evaluation of electrical life of AC contactor based on initial characteristic parameters. IEEE Transactions on Instrumentation and Measurement 2021; 70: 1–10. 10.1109/TIM.2020.3031160
9.
Zheng S, Niu F, Li K, Huang S, Liu Z, Wu Y. Analysis of electrical life distribution characteristics of AC contactor based on performance degradation. IEEE Transactions on Components, Packaging and Manufacturing Technology 2018; 8(9): 1604–1613. 10.1109/TCPMT.2018.2841425
10.
Ge F, Qiu T, Zhang M, Ji J. Experimental research on the thermal characteristic of low-voltage alternating current (AC) arc faults. Fire Safety Journal 2023; 136: 103732. https://doi.org/10.1016/j.fire....
11.
Wu Z, Wu G, Huang H, You Y. A novel residual electrical endurance prediction method for low-voltage electromagnetic alternating current contactors. IEEE Transactions on Components, Packaging and Manufacturing Technology 2015; 5(4): 465–473. 10.1109/TCPMT.2015.2415852
12.
Fan W, Gao X, Han L, Xu Z, Chen C, Chen L. Adaptive Multistage Sparse Gaussian Process Regression for Bearing Remaining Useful Life Prediction. IEEE Transactions on Instrumentation and Measurement 2025; 74: 1–10. 10.1109/TIM.2025.3627353.
13.
Liu Z, Li Q, Chen X, Ren Y, Cheng Y. Adaptive Remaining Useful Life Prediction Model for Lithium-Ion Batteries Based on Polynomial Fitting. IEEE Transactions on Instrumentation and Measurement 2025; 74: 1–11. 10.1109/TIM.2025.3541667.
14.
Deng M, Xu M, Bian W, Liu D, Deng A. Deep Bayesian Stochastic Process Model for Remaining Useful Life Prediction of Rolling Bearings. IEEE Transactions on Instrumentation and Measurement 2025; 74: 1–15. 10.1109/TIM.2025.3635312
15.
Fan L, Xu X, Ni Y. Multi-failure mode reliability of monorail vehicle gear transmission system based on multi-index staged degradation. Applied Mathematical Modelling 2024; 136: 115602, https://doi.org/10.1016/j.apm.....
16.
Fang G, Pan R. A class of hierarchical multivariate Wiener processes for modeling dependent degradation data. Technometrics 2024; 66(2): 141–156, https://doi.org/10.1080/004017....
17.
Yan B, Wang H, Ma X. Correlation-driven multivariate degradation modeling and RUL prediction based on Wiener process model. Quality and Reliability Engineering International 2023; 39(8): 3203–3229. https://doi.org/10.1002/qre.31....
18.
Frahm G, Junker M, Szimayer A. Elliptical copulas: applicability and limitations. Statistics & Probability Letters 2003; 63(3): 275–286. https://doi.org/10.1016/S0167-....
19.
Zheng Y, Zhang Y. Reliability analysis for system with dependent components based on survival signature and copula theory. Reliability Engineering & System Safety 2023; 238: 109402. https://doi.org/10.1016/j.ress....
20.
Tang X, Li D, Zhou C, Phoon K, Zhang L. Impact of copulas for modeling bivariate distributions on system reliability. Structural Safety 2013; 44: 80–90. https://doi.org/10.1016/j.stru....
21.
Sun F, Fu F, Liao H, Xu D. Analysis of multivariate dependent accelerated degradation data using a random-effect general Wiener process and D-vine Copula. Reliability Engineering & System Safety 2020; 204: 107168. https://doi.org/10.1016/j.ress....
22.
Zhang J, Yan R, Wang J. Reliability optimization of parallel-series and series-parallel systems with statistically dependent components. Applied Mathematical Modelling 2022; 102: 618–639. https://doi.org/10.1016/j.apm.....
23.
Luo X, Shevchenko PV. The t copula with multiple parameters of degrees of freedom: bivariate characteristics and application to risk management. Quantitative Finance 2010; 10(9): 1039–1054, 10.1080/14697680903085544.
24.
Demarta S, McNeil A J. The t copula and related copulas. International statistical review 2005; 73(1): 111–129. https://doi.org/10.1111/j.1751....
25.
Ge Q, Menendez M. Exploring the variance contributions of correlated model parameters: A sampling-based approach and its application in traffic simulation models. Applied Mathematical Modelling 2021; 97: 438–462. https://doi.org/10.1016/j.apm.....
26.
Shea J J. Modeling contact erosion in three phase vacuum contactors. IEEE Transactions on Components, Packaging and Manufacturing Technology 1998; 21(4): 556–564, 10.1109/95.740048.
27.
Luo J, Shao H, Lin J, Liu B. Meta-learning with elastic prototypical network for fault transfer diagnosis of bearings under unstable speeds. Reliability Engineering & System Safety 2024; 245: 110001. https://doi.org/10.1016/j.ress....
28.
Chen Z, Xia T, Li Y, Pan E. Random-effect models for degradation analysis based on nonlinear Tweedie exponential-dispersion processes. IEEE Transactions on Reliability 2022; 71(1): 47–62. 10.1109/TR.2021.3107050.
29.
Chen Z, Xia T, Li Y, Pan E. Tweedie exponential dispersion processes for degradation modeling, prognostic, and accelerated degradation test planning. IEEE Transactions on Reliability 2020; 69(3): 887–902. 10.1109/TR.2019.2955596.
30.
Yan W, Xu X, Bigaud D, Cao W. Optimal design of step-stress accelerated degradation tests based on the Tweedie exponential dispersion process. Reliability Engineering & System Safety 2023; 230: 108917. https://doi.org/10.1016/j.ress....
31.
Levitin G, Xing L, Xiang Y. Optimal multiple replacement and maintenance scheduling in two-unit systems. Reliability Engineering & System Safety 2021; 213: 107803. https://doi.org/10.1016/j.ress....
32.
Shi R, Lü Y, Zhang Y, Meng J, Chen R, Hu R. Remaining Useful Life Estimation with Coupling Dual Random Effects Based on Nonlinear Wiener Process. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2025; 27(4): 202908. https://doi.org/10.17531/ein/2....
33.
Peng C, Li J, Ren L, Li D, Chen J. Remaining useful life prediction of binary stochastic degradation equipment based on mixed Copula functions. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2026; 28(1): 209903. https://doi.org/10.17531/ein/2....
34.
Li X, Chen D, Wu J, Kang R. 3-Dimensional general ADT modeling and analysis: Considering epistemic uncertainties in unit, time and stress dimension. Reliability Engineering & System Safety 2022; 225: 108577. https://doi.org/10.1016/j.ress....
35.
Kendall MG. A new measure of rank correlation. Biometrika 1938; 30(1/2): 81–93. https://doi.org/10.2307/233222....
Share
RELATED ARTICLE
| eISSN: | 2956-3860 |
| ISSN: | 1507-2711 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
