DOI: 10.3390/electronics15153390 ISSN: 2079-9292

Reliability Assessment of EMU Onboard Power Supply Boards Based on Output Ripple Degradation and a Nonlinear Wiener Process

Haijing Hou, Jiaqi Zhang, Qiyu An, Hua Zhang, Qi Dong, Bo Liu

Reliability assessment of EMU onboard power supply boards is constrained by scarce field failure data and the intrusive nature of component-level degradation monitoring. Moreover, conventional linear degradation models may inadequately characterize the non-monotonic fluctuations and time-varying degradation rates of board-level health indicators. To address these limitations, this study proposes a mechanism-informed reliability assessment method using output ripple voltage as a non-invasive degradation indicator. A thermally accelerated degradation test was conducted on power supply boards used in video-monitoring servers, and a stable-baseline output-ripple relative-increment indicator was constructed to mitigate the effects of the initial burn-in process and sample-to-sample baseline differences. A nonlinear Wiener process with a power-law time scale was then developed to characterize the non-monotonic evolution, stochastic fluctuations, and time-varying degradation rate of the output ripple. Arrhenius-based lifetime extrapolation and time-censored MTBF analysis were subsequently performed. Compared with the linear and quadratic-drift Wiener processes, the proposed model achieved the largest maximized log-likelihood and the lowest AIC and BIC values; both information criteria were 22.56 lower than the corresponding values of the quadratic-drift model. Using an activation energy of 0.7 eV, the thermal acceleration factor was 41.19. Under the baseline scenario threshold of 150 mV, the predicted MTTF, R90 lifetime, and R50 lifetime were 16.20, 7.77, and 13.92 equivalent operating years, respectively, while the point estimate of the functional-failure-based time-censored MTBF was 43.45 years. The proposed method provides a non-invasive reliability assessment framework for condition monitoring, early warning, and preventive maintenance of EMU onboard power supply boards when failure data are scarce.

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