Input force identification using Kalman filter techniques: application to soil-pile interaction

Chin-Hsiung Loh; Ai-Lun Wu; Jann N. Yang; Chia-Han Chen; Tzou-Shin Ueng

doi:10.1117/12.773816

8 April 2008 Input force identification using Kalman filter techniques: application to soil-pile interaction

Chin-Hsiung Loh, Ai-Lun Wu, Jann N. Yang, Chia-Han Chen, Tzou-Shin Ueng

Proceedings Volume 6932, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2008; 693223 (2008) https://doi.org/10.1117/12.773816
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2008, San Diego, California, United States

Abstract

An identification method for estimating the time varying excitation force acting on a structural system based on its response measurement is presented in this study. The method employs the simple Kalman filter to establish a regression model between the residual innovation and the input excitation forces. Based on the regression model, a recursive least-squares estimator is proposed to identify the input excitation forces incorporating with the measurement noise and the modeling error. In applying the method, the ambient vibration measurement of a structural system was used first. The stochastic subspace identification is applied to estimate the system matrix "A" and the measurement matrix "C". Then the Kalman filter with a recursive estimator is applied to determine the input excitation forces. The dynamic excitation forces are estimated from the measured structural responses by an inverse algorithm while least-square method with a recursive estimator is employed to update the estimation in the sense of real-time computation. Verification of the method with numerical simulation through MIMO system is conducted first. Identification of soil forces during the shaking table test of soil-pile interaction is also demonstrated.

Citation Download Citation

Chin-Hsiung Loh, Ai-Lun Wu, Jann N. Yang, Chia-Han Chen, and Tzou-Shin Ueng "Input force identification using Kalman filter techniques: application to soil-pile interaction", Proc. SPIE 6932, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2008, 693223 (8 April 2008); https://doi.org/10.1117/12.773816

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