Identifying Distributed Dynamic Loading in One Spatial Dimension Based on Combing Wavelet Decomposition and Kalman Filter with Unknown Input
Publication: Journal of Aerospace Engineering
Volume 34, Issue 4
Abstract
The identification of distributed dynamic loads is an important but challenging task because a distributed dynamic load is composed of both time and space functions. This paper proposes a novel method for the identification of distributed dynamic loading in one spatial dimension using only partial structural responses. The method is based on combing wavelet decomposition of space functions and the identification of time function by the improved Kalman filter with unknown input (KF-UI) developed by the authors. First, the unknown load space function of a distributed dynamic loading is approximated by wavelet decomposition with unknown scale coefficients. Under the given values of wavelet scale coefficients, the spatial information and the equivalent nodal loads of a beam-type structure can be estimated by finite-element modeling. Structural nodal responses in time-domain and the unknown load time function can be identified based on the improved KF-UI using data fusion of partial measurements of structural acceleration and strain responses. Finally, the objective function is established utilizing the error between the calculated and measured responses, and the optimal wavelet coefficients are estimated by minimizing the objective function. Therefore, the unknown distributed dynamic loading can be estimated by combing the reconstructed load space function from the optimal wavelet coefficients and the identified load time function. Numerical simulations of a simply supported beam under different unknown distributed loading verified the effectiveness of the proposed method.
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Data Availability Statement
All data, models, and code generated or used during the study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by the Natural Science Foundation of China (NSFC) through Grant No. 51678509.
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Journal of Aerospace Engineering
Volume 34 • Issue 4 • July 2021
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© 2021 American Society of Civil Engineers.
History
Received: Jul 1, 2020
Accepted: Dec 1, 2020
Published online: Mar 19, 2021
Published in print: Jul 1, 2021
Discussion open until: Aug 19, 2021
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