Visual reconstruction of flexible structure based on fiber grating sensor array and extreme learning machine algorithm  

作　　者：ZHANG Sisi YAN Jie JIANG Mingshun SUI Qingmei ZHANG Lei LUO Yuxiang 

机构地区：[1]School of Control Science and Engineering,Shandong University,Jinan 250061,China [2]Shandong Institute of Space Electronic Technology,Jinan 250061,China

出　　处：《Optoelectronics Letters》2022年第7期390-397,共8页光电子快报（英文版）

基　　金：supported by the National Natural Science Foundation of China(Nos.62073193,61903224,61873333 and 61903225);the National Key Research and Development Project(Nos.2018YFE02013 and 2020YFE0204900);the Key Research and Development Plan of Shandong Province(Nos.2019TSLH0301 and 2019GHZ004);the Natural Science Foundation of Shandong Province,China(No.ZR2021MF041)。

摘　　要：A visual reconstruction method was proposed based on fiber Bragg grating(FBG)sensors and an intelligent algorithm,aiming to solve the problems of low accuracy and complex reconstruction process in conventional reconstruction methods of flexible structures.Firstly,the wavelength data containing structural strain information was captured by FBG sensors,together with deformation displacement information.Subsequently,a predicted model was built based on an extreme learning machine(ELM)and further optimized by the particle swarm optimization(PSO)algorithm.Different deformation patterns were tested on an aluminum alloy plate,indicating the ability of the predicted model to produce the deformation displacement for reconstruction.The experimental results show that the maximum error can be as low as 0.050 mm,which verifies that the proposed method is feasible and satisfied with the deformation monitoring of the spacecraft structure.

关 键 词：DEFORMATION ALLOY EXTREME 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置] TP181[自动化与计算机技术—控制科学与工程]