Research On Structural Health Monitoring Of Composite Materials Based On Fiber Bragg Grating Sensing

Composite materials have excellent strength, stiffness ratio, fatigue resistance and durability, hasbeen used in the aerospace, building materials, automotive, high-speed rail and other fields. However,since the thickness direction without reinforcement, so the composite material is very sensitive todamage. Efficient technique for nondestructive testing of composite material structural damageinspection and continuous monitoring is important. Currently, the report based on fiber Bragg gratingstrain sensor array and BP neural network for composite material structural damage identification isless. n this article will FBG strain sensor measurement and artificial neural network combined withdamage detection applied to composite panels on the glass matrix composites were static stress anddynamic stress testing laboratory, constructed of composite materials for structural health monitoringsystem based on fiber grating.Firstly, analyzed the importance of damage identification from the basic definition of compositematerials and widely used in aerospace composites, the status quo at home and abroad in thecomposite fiber grating health monitoring applications are outlined. Secondly, elaborated FBGsensing principle, and using FBG sensors were static and dynamic testing laboratory glass fibercomposites, Analysis of the impact of laying fiber grating static stress and shock signal material, hasbeen the sensor specific technical indicators and corresponding dynamic response curve. Then usingANSYS finite element analysis software to establish a specimen edges simply supported plate modelsimulations indicate damage pore size distribution can significantly affect the strain composite platespecimen. Finally, the establishment of a fiber grating strain sensor array is a two-dimensional loadingposition response signal and load the sample space for studying and identifying the sample space, theestablishment of a simply supported on four sides of the board of damage identification based on fiberBragg grating strain sensor array BP neural network system, the realization of composite structuraldamage identification and location.