Adaptive Residual Useful Life Prediction for the Insulated-Gate Bipolar Transistors with Pulse-Width Modulation Based on Multiple Modes and Transfer Learning - Mines Paris Accéder directement au contenu
Article Dans Une Revue Fractal and Fractional Année : 2023

Adaptive Residual Useful Life Prediction for the Insulated-Gate Bipolar Transistors with Pulse-Width Modulation Based on Multiple Modes and Transfer Learning

Wujin Deng
  • Fonction : Auteur
Yan Gao
Wanqing Song
Gaojian Li
  • Fonction : Auteur
Jin Liu
  • Fonction : Auteur
Aleksey Kudreyko

Résumé

Currently, residual useful life (RUL) prediction models for insulated-gate bipolar transistors (IGBT) do not focus on the multi-modal characteristics caused by the pulse-width modulation (PWM). To fill this gap, the Markovian stochastic process is proposed to model the mode transition process, due to the memoryless properties of the grid operation. For the estimation of the mode transition probabilities, transfer learning is utilized between different control signals. With the continuous mode switching, fractional Weibull motion (fWm) of multiple modes is established to model the stochasticity of the multi-modal IGBT degradation. The drift and diffusion coefficients are adaptively updated in the proposed RUL prediction model. In the case study, two sets of the real thermal-accelerated IGBT aging data are used. Different degradation modes are extracted from the meta degradation data, and then fused to be a complex health indicator (CHI) via a multi-sensor fusion algorithm. The RUL prediction model based on the fWm of multiple modes can reach a maximum relative prediction error of 2.96% and a mean relative prediction error of 1.78%. The proposed RUL prediction model with better accuracy can reduce the losses of the power grid caused by the unexpected IGBT failures.

Dates et versions

hal-04409360 , version 1 (22-01-2024)

Identifiants

Citer

Wujin Deng, Yan Gao, Wanqing Song, Enrico Zio, Gaojian Li, et al.. Adaptive Residual Useful Life Prediction for the Insulated-Gate Bipolar Transistors with Pulse-Width Modulation Based on Multiple Modes and Transfer Learning. Fractal and Fractional, 2023, 7 (8), pp.614. ⟨10.3390/fractalfract7080614⟩. ⟨hal-04409360⟩
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