Impact Force Identification on Carbon Fibre–Epoxy Honeycomb Composite Panel Based on Local Convex Curve Criterion

Qiu, Bingsen; Zhang, M.; Xie, Yaoguo; Qu, Xinggen; Li, X.

doi:10.1007/s11340-019-00526-y

Cited by 9 publications

(1 citation statement)

References 34 publications

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“…Chang et al [ 19 ] proposed an implicit Landweber method for single-source and multi-source force reconstructions, and the response sensitivity was utilised to reconstruct the time history of dynamic force. Qiu et al [ 20 ] proposed a novel criterion, called the local convex curve, to realise accurate reconstruction of the impact force time history by suppressing the tail disturbance of the reconstructed time history.…”

Section: Introductionmentioning

confidence: 99%

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

Qiu

et al. 2022

Sensors

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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).

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Section: Introductionmentioning

confidence: 99%