Recursive Method in Modal Parameter Identification of Aerospace Structures under Non-Gaussian Noise

Abstract

Operational modal parameter identification is a tough problem in aerospace engineering due to the complex mechanics environment, various noises, and limited computational resources. In this paper, a novel, recursive, robust, and high-efficiency modal parameter identification approach is proposed for this issue. The kernelized time-dependent autoregressive moving average (TARMA) model is adopted to model the nonstationary responses, a recursive estimator is established based on the maximum correntropy criterion, and sliding-window technique is applied to fix the computational complexity, which ensures the approach its estimation accuracy, robustness, and high efficiency. Finally, steps of the identification procedure and model selection are presented. An experimental scheme is proposed for validation, and the proposed approach is comparatively assessed against the classical recursive pseudo-linear regression TARMA method via Monte Carole tests of a time-varying experimental system. The results of the comparative study demonstrate that the proposed method achieves similar estimation accuracy and higher computation efficiency under the Gaussian environment. Moreover, a superior estimation accuracy and enhanced robustness are rendered under additive non-Gaussian impulsive noise.