A health management algorithm for composite train carbody based on FEM/FBG hybrid method

Abstract

In this study, a health management program for a composite train carbody was developed using the acquired strain distributions from fiber Bragg grating (FBG) sensor arrays. To determine appropriate locations for the FBG sensors, a finite element analysis (FEA) was executed. In this FEA, a FE model of the Korean tilting train (TTX) was used as a representative composite carbody train. The FEA results of various derailment situations and high speed operation on curved track were used as the database of each deformation case. In the last step, the health management program was produced using LabVIEW software. In this post-processing algorithm, the method of least squares was used to determine the difference between the FEA results and the acquired strains. This program shows the estimated deformations and plots of the acquired strains, as well as displaying an emergency indicator when necessary, all through post-processing of the strains. Finally, this FEM/FBG hybrid method was verified by several simulations using the reproductive sensor data.