Reliability Assessment for Multivariate Degradation System Based on Uncertainty and Chatterjee Correlation Coefficient
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| Veröffentlicht in: | Systems vol. 13, no. 11 (2025), p. 953-977 |
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| 024 | 7 | |a 10.3390/systems13110953 |2 doi | |
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| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231636 |2 nlm | ||
| 100 | 1 | |a Tang Jiayin |u Department of Statistics, School of Mathematics, Southwest Jiaotong University, Chengdu 611756, China; shi_jiajiaya@126.com | |
| 245 | 1 | |a Reliability Assessment for Multivariate Degradation System Based on Uncertainty and Chatterjee Correlation Coefficient | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Considering the effects of complex correlations between variables and uncertainty of degradation processes in multivariate degradation systems, a system reliability assessment method that integrated Chatterjee correlation coefficient and stochastic process theory is proposed. First, due to temporal uncertainty and measurement error in the univariate degradation process, a general Wiener-process-based state space model is constructed to determine the marginal distributions. Secondly, the nonlinear and asymmetric correlation between variables is analyzed by the nonparametric Chatterjee correlation coefficient. The multivariate joint degradation model is constructed by combining the Vine copula technique. The copula structure selection is optimized based on the goodness-of-fit criterion for modeling the degradation dependency network. In order to verify the validity of the method, comparative experiments based on the C-MAPSS aero-engine degradation dataset are conducted. Compared with the independent model ignoring the correlation of the variables, Vine copula with Chatterjee coefficient shows the rationality of the system reliability assessment. The system reliability curve lies between the cases of complete independence and complete dependence of variables. Compared to the traditional Vine copula model with Kendall coefficient, the method in this paper shows a significant improvement in asymmetric correlation characterization, with a Vuong test value of 6.37. The assessment method given in this paper provided an improved paradigm for reliability assessments of complex systems. | |
| 653 | |a Reliability analysis | ||
| 653 | |a Machine learning | ||
| 653 | |a Stochastic processes | ||
| 653 | |a Physics | ||
| 653 | |a Datasets | ||
| 653 | |a System reliability | ||
| 653 | |a Random variables | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Brownian motion | ||
| 653 | |a Complex variables | ||
| 653 | |a Goodness of fit | ||
| 653 | |a Sensors | ||
| 653 | |a State space models | ||
| 653 | |a Multivariate analysis | ||
| 653 | |a Complex systems | ||
| 653 | |a Methods | ||
| 653 | |a Degradation | ||
| 653 | |a Uncertainty | ||
| 653 | |a Correlation coefficients | ||
| 700 | 1 | |a Jiang Mengjia |u Department of Statistics, School of Mathematics, Southwest Jiaotong University, Chengdu 611756, China; shi_jiajiaya@126.com | |
| 700 | 1 | |a Mao Yamin |u CETC Rong Wei Electronic Technology Co., Ltd., Chengdu 610036, China; snwiapple@163.com | |
| 773 | 0 | |t Systems |g vol. 13, no. 11 (2025), p. 953-977 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3275564766/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3275564766/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3275564766/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |