Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation

Electromagnetic coils are one of the key components of many systems. Their insulation failure can have severe effects on the systems in which coils are used. This paper focuses on insulation degradation monitoring and remaining useful life (RUL) prediction of electromagnetic coils. First, insulation degradation characteristics are extracted from coil high-frequency electrical parameters. Second, health indicator is defined based on insulation degradation characteristics to indicate the health degree of coil insulation. Finally, an insulation degradation model is constructed, and coil insulation RUL prediction is performed by particle filtering. Thermal accelerated degradation experiments are performed to validate the RUL prediction performance. The proposed method presents opportunities for predictive maintenance of systems that incorporate coils.

Automated summary

This paper focuses on insulation degradation monitoring and remaining useful life (RUL) prediction of electromagnetic coils, proposing a health indicator and prediction method based on insulation degradation characteristics. Experimental validation of the predictive performance was carried out, offering new insights for predictive maintenance of systems with coils.