Capacitor State Monitoring Based on Haar Wavelet Transform and Enhanced Kalman Filter

Aviation electrification is an inevitable trend leading the development of future aviation technology, and its development cannot be separated from high-performance onboard power systems. As a key equipment of the system, the DC converter plays a core role in energy conversion, and its operational reliability directly affects the stability of the entire system. As the core component of the converter, capacitors have become a weak link in system reliability due to their high failure rate. Therefore, accurate monitoring of their health status is of great significance. To achieve fast, high-precision online monitoring of capacitors, this paper proposes an intelligent monitoring strategy that integrates Haar wavelet transform and Kalman filter. This method only requires the collection of inductance current and output voltage signals during regular operation, without the need for additional installation sensors. The capacitance current is reconstructed and used to accurately identify the capacitance value (C) and equivalent series resistance (ESR) throughout the entire life cycle in strong noise environments. The simulation and experimental results show that the strategy has good robustness under different operating conditions, with recognition errors of C and ESR controlled within 3% and 2%, respectively, demonstrating the feasibility of the proposed method.