Dynamic force reconstruction techniques from incomplete measurements. (November 2018)

• Record Type: Journal Article
• Authors: Jayalakshmi, V.; Lakshmi, K.; Mohan Rao, A. Rama
• Is Part Of: Journal of vibration and control. Volume 24:Number 22(2018)
• Page Start: 5321
• Page End: 5344
• Publication Date: 2018-11
• Subjects: Structural health monitoring -- input force identification -- direct and inverse algorithm -- improved Tikhonov regularization -- minimum mean square error algorithm -- particle swarm optimization -- modelling errors; Vibration -- Periodicals; Damping (Mechanics) -- Periodicals; 620.3
• DOI: 10.1177/1077546317752709
• Languages: English
• ISSNs: 1077-5463

Abstract

We present two time-domain algorithms derived from the popular Newmark's time integration algorithm, to reconstruct the input force excitation from the vibration measurements. While the first method uses a direct formulation of the time integration algorithm, the second one uses a regularization tool to solve the associated inverse problem. A modified regularization technique is employed to improve the accuracy of the identification problem. Numerical studies with limited measurements, with measurement noise, multiple load identification etc., are presented to investigate the practical applicability of the two methods. Studies have clearly favored the inverse algorithm with modified regularization technique. Finally modeling errors associated with force reconstruction are investigated and a technique is proposed to identify the system parameters simultaneously while reconstructing the input dynamic force, using a recently developed quantum particle swarm optimization algorithm developed by the authors. The numerical simulation studies presented clearly indicate that the force, as well as the system parameters, can be identified accurately using the proposed algorithm.