Research on FBG-Based CFRP Structural Damage Identification Using BP Neural Network

Photonic Sensors

Yuxi Jia¹  Mingshun Jiang²  Qingmei Sui²  Hang Xiao²  Xiangyi Geng²  Lei Jia²  Shanshan Lv²  Shizeng Lu³ 

[1]Key Laboratory for Liquid-Solid Structural Evolution & Processing of Materials (Ministry of Education), Shandong University

[2]School of Control Science and Engineering, Shandong University

[3]School of Electrical Engineering, University of Jinan

关键词: Carbon fiber reinforced polymer;    damage identification;    FBG sensors;    neural network;    finite element analysis;   

DOI  :  10.1007/s13320-018-0466-0

来源: DOAJ

【 摘 要 】

Abstract A damage identification system of carbon fiber reinforced plastics (CFRP) structures is investigated using fiber Bragg grating (FBG) sensors and back propagation (BP) neural network. FBG sensors are applied to construct the sensing network to detect the structural dynamic response signals generated by active actuation. The damage identification model is built based on the BP neural network. The dynamic signal characteristics extracted by the Fourier transform are the inputs, and the damage states are the outputs of the model. Besides, damages are simulated by placing lumped masses with different weights instead of inducing real damages, which is confirmed to be feasible by finite element analysis (FEA). At last, the damage identification system is verified on a CFRP plate with 300 mm × 300 mm experimental area, with the accurate identification of varied damage states. The system provides a practical way for CFRP structural damage identification.

【 授权许可】

Unknown