DELAMINATION IDENTIFICATION OF COMPOSITE LAMINATED BEAMS BASED ON SUPPORT VECTOR MACHINE

Abstract

Abstract: Support vector machine (SVM) has not yet been introduced to detect delaminations for fibre reinforced composite materials, and this paper is proposed to assess the delaminations in carbon fiber reinforced polymer (CFRP) beams based on SVM regression, through the changes in modal frequencies due to the damage occurs. Firstly, the finite element model of CFRP beam was established to generate the database of "delamination variables vs. modal frequencies" as well as the test cases for numerical validation. Three different parameter optimization methods, namely, cross validation (CV), genetic algorithm (GA) and particle swarm optimization (PSO), were applied to obtain the suitable parameters for SVM to improve the prediction accuracy. Furthermore, the Polytec laser scanning vibrameter was adopted to conduct the model testing for CFRP beam specimens. The measured frequencies of the specimens were used for validating the SVM regression experimentally, which confirmed that the SVM can be used to detect delamination in CFRP beams.

Key words: support vector machine, CFRP, damage detection, frequency

CLC Number:

TB332

HE Meng-yue,LIANG Zhi-hong,ZHANG Zhi-fang*. DELAMINATION IDENTIFICATION OF COMPOSITE LAMINATED BEAMS BASED ON SUPPORT VECTOR MACHINE[J]. Fiber Reinforced Plastics/Composites, 2018, 0(7): 12-18.

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