Model-Based Mechanical State Parameter Estimation for High-Voltage Circuit Breakers

This paper presents a model-based parameter estimation approach for high-voltage circuit breaker operating mechanisms using the dynamic model and stroke curves. First, an equivalent dynamic model of the mechanism is established, and its fidelity is validated through comparison with a virtual prototype model built in ADAMS, confirming the validity of the modeling assumptions. Then, the parameter estimation task is formulated as an optimization problem that minimizes the discrepancy between model predictions and actual stroke curves, and the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm is adopted to search for the optimal parameter set. Subsequently, to ensure estimation reliability, a thorough identifiability analysis is conducted, including sensitivity and correlation analyses, which collectively indicate that the key parameters are well identifiable. Afterward, experimental tests are performed on a 252 kV circuit breaker under various operating conditions, and the results demonstrate that the parameter identification errors are consistently below 6.3%. Finally, we compare the proposed method with three representative data-driven classifiers on the same dataset for a classification task. The comparison shows that our method achieves higher accuracy than others. Furthermore, the proposed method yields physically interpretable parameters directly linked to mechanical components, providing valuable information for condition assessment and maintenance planning in engineering applications.