@article{GUO2026, 
author = {Lei GUO and Jianbiao SHEN and Shenlong LI and Xunming LI and Tonghui LI and Nan ZHANG and Muyang ZHANG and Xingjian WANG},
title = {Reliability analysis of an electromechanical integrated transmission system based on Copula correlation modeling},
year = {2026},
journal = {Journal of Beijing University of Aeronautics and Astronautics},
volume = {52},
number = {8},
pages = {2748-2755},
keywords = {Copula function, electromechanical integrated transmission device, system reliability, dependence structure modeling, joint failure analysis},
url = {https://www.sciopen.com/article/10.13700/j.bh.1001-5965.2026.0098},
doi = {10.13700/j.bh.1001-5965.2026.0098},
abstract = {Considering the correlated failure characteristics of multiple subsystems in an electromechanical integrated transmission system arising from load transfer, control loops, and functional coupling, this study introduces a Copula-based approach to model the internal dependency structure while preserving the marginal reliability models of individual subsystems. By mapping subsystem lifetime data into a unified probability space via cumulative distribution functions, the proposed method achieves decoupled modeling of marginal distributions and dependency structures. The process for creating failure time samples is described, and a Gaussian Copula is chosen to build the system-level joint failure model based on an examination of the dependency characteristics of several Copula families combined with engineering failure mechanisms. The dependency structure of the generated samples is validated using the Kendall τ rank correlation coefficient, and the results show good consistency with the predefined correlation matrix. Additional investigation finds high-risk areas of joint failure and reveals a significant coupling link between the drive motor controller and the motor drive subsystem. The results demonstrate that the Copula-based framework can effectively characterize system-level correlated failures, providing quantitative support for coordinated monitoring and maintenance decision-making.}
}