Analysis of edge delamination damage of CFRP based on Lamb wave and improved Bayesian fusion algorithm

doi:10.19936/j.cnki.2096-8000.20240528.016

Abstract

Abstract: Bayesian fusion method has good positioning results on damage of CFRP, but there will be obvious positioning errors in the sensor network edge area. In order to solve the problem that the original algorithm is inaccurate in the layered damage localization of the sensor network edge, firstly, the localization effect of Bayesian fusion algorithm composed of two different damage factors on damage of CFRP is analyzed in this paper, and the feasibility of Bayesian fusion algorithm formed by ToF damage factor on the damage localization and accurate for the edge layereddamage localization are verified. Then, on the basis of the probabilistic imaging algorithm formed by the damage factor DI, the linear weight is replaced by the exponential weight with faster attenuation, and the improved probabilistic imaging algorithm is re-substituted into the algorithm framed by Bayesian to form a new Bayesian fusion algorithm. The results show that compared with the existing fusion reconstruction algorithm, the improved fusion reconstruction algorithm reduces the error by at least 58%, and the positioning error is not more than 5 mm.

Key words: Bayesian fusion, CFRP, damage factor, exponential weight, edge layered damage, positioning accuracy

CLC Number:

TB332

LÜ Wei, WEN Xue, FU Weigang, TANG Jingkun. Analysis of edge delamination damage of CFRP based on Lamb wave and improved Bayesian fusion algorithm[J]. COMPOSITES SCIENCE AND ENGINEERING, 2024, 0(5): 114-120.

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