Degradation Estimation of Electromechanical Actuator Using Dynamic Feature-Enhanced Proportional Copula Fusion Method

As the widespread adoption of electromechanical actuators (EMAs) in commercial and military aviation continues to grow, the requirement for accurate degradation estimation becomes increasingly important. While various methods exist for estimating their degradation, few studies have explored the interrelationships between failure modes, thereby impacting the accuracy of the results. To address this challenge, this article proposes a novel degradation estimation method for EMAs. This method estimates health indicators (HIs) for EMA degradation with multiple failure modes by integrating the continuous hidden Markov model (CHMM) and an improved Copula function, termed the Proportional Copula function. Initially, HIs are obtained by establishing an HI extraction model using the CHMM. Subsequently, a joint probability model of HIs is formulated based on the Copula function. Afterward, considering both individual nonlinearity and inter-HI coupling, the Proportional Copula function model is constructed to fuse the HIs. Ultimately, the established degradation model yields a degradation parameter, the Fusion HI, which can estimate the degradation of EMAs. The proposed method has been validated using both simulation and practical data. The results demonstrate its effectiveness in degradation estimation for EMAs under multiple failure modes.