Health State Estimation and Remaining Useful Life Prediction of Power Devices Subject to Noisy and Aperiodic Condition Monitoring

• Published in: IEEE transactions on instrumentation and measurement Vol. 70; pp. 1 - 16
• Main Authors: Zhao, Shuai, Peng, Yingzhou, Yang, Fei, Ugur, Enes, Akin, Bilal, Wang, Huai
• Format: Journal Article
• Language: English
• Published: New York IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accelerated aging tests; Aging (metallurgy); Algorithms; Condition monitoring; Degradation; Degradation modeling; Diagnostic systems; Electronic devices; Field effect transistors; gamma process; Heterogeneity; Life prediction; Measurement uncertainty; Model accuracy; MOSFETs; Noise levels; Noise measurement; noisy and aperiodic measurements; Numerical analysis; Parameter estimation; particle filter (PF); Pollution measurement; Predictive models; remaining useful life (RUL) prediction; Robustness (mathematics); Semiconductor devices; SiC metal–oxide-semiconductor field-effect transistors (MOSFETs); State estimation; State space models; Uncertainty; Useful life

Condition monitoring of power devices is highly critical for safety and mission-critical power electronics systems. Typically, these systems are subjected to noise in harsh operational environment contaminating the degradation measurements. In dynamic applications, the system duty cycle may not be p...