Experimental Research on a Hybrid Algorithm for Localisation and Reconstruction of the Impact Force Applied to a Rectangular Steel Plate Structure

Abstract

Impact force is the most common form of load which acts on engineering structures and presents a great hidden risk to the healthy operation of machinery. Therefore, the identification or monitoring of impact forces is a significant issue in structural health monitoring. The conventional optimisation scheme based on inversion techniques requires a significant amount of time to identify random impact forces (impact force localisation and time history reconstruction) and is not suitable for engineering applications. Recently, a pattern recognition method combined with the similarity metric, PRMCSM, has been proposed, which exhibits rapidity in practical engineering applications. This study proposes a novel scheme for identifying unknown random impact forces which hybridises two existing methods and combines the advantages of both. The experimental results indicate that the localisation accuracy of the proposed algorithm (100%) is higher than that of PRMCSM (92%), and the calculation time of the hybrid algorithm (179 s) for 25 validation cases is approximately one nineteenth of the traditional optimisation strategy (3446 s).

Identification of Time-Varying External Force Using Group Sparse Regularization and Redundant Dictionary

“…To further improve the identification accuracy, in the follow-up studies, some other regularization methods [ 18 ], such as the function expansion method [ 20 , 21 , 22 ], multiplicative regularization [ 23 , 24 ], sparse regularization [ 25 , 26 , 27 , 28 ], and so on [ 29 , 30 , 31 , 32 ], are introduced into the force identification problem. In particular, for the time-varying external force, it is usually not sparse in the time domain.…”