Construetion And Condition Monitoring Technology Research Of Smart Composites Based On Fiber Bragg Grating Sensors

Carbon fiber reinforced resin matrix composites have great advantages in reducing the structure weight and improving overall properties because of the excellent specific strength and specific modulus,high fatigue resistance,good designability and large scale integral molding.It has shown great application prospect in many fields of military and civil.However,due to the influence of curing residual stresses,extreme environmental conditions,stress concentration and impact,the material is prone to invisible internal damages such as matrix cracking and delamination,which are serious threats to the security of composite structures and restrict their application.Therefore,monitoring the curing process of composites and the status in subsequent service,deeply understanding the curing characteristics,and timely perceiving,locating and evaluating the structural damage,impact and other hidden dangers are of great significance to improve the reliability of composites.In recent years,the proposing of smart materials provides a new idea for composites condition monitoring.By integrating sensing elements with composites,smart composites are constructed,which are different from traditional materials and can realize the perception of the working status and the external environment changes.The fiber Bragg grating(FBG)is considered to be an ideal sensing element for smart composites owing to its small size,high precision,strong resistance to electromagnetic interference and good compatibility with host materials.Based on the sensing mechanisms of fiber Bragg grating,the smart composite curing deformation and status monitoring systems are established by researching the integration of smart composites,signal processing and feature extraction,structural damage identification and low speed impact position identification technology,aiming at realizing the curing process monitoring of composites,and the timely perception and accurate evaluation of structural anomalies,damage and other hidden dangers.The main research work are as follows:(1)based on the theoretical analysis of sensing mechanisms of fiber Bragg grating and properties of composites,the cross-sensitivity,leading out methods and protection of embedded FBG sensors in the construction of smart composites are experimentally studied,and a detailed construction scheme is presented.Combining with the finite element analysis,the FBG sensors are embedded into the typical positions of the composite,and the evolution of the internal temperature field and strain field during the curing process of the cross-ply composite are monitored in real time.The cured laminate is heated twice before opening the mold.Through comparing and analyzing the differences of internal strain in two cooling processes,the curing and post-curing characteristics of the carbon fiber composites are deeply understood,providing the foundation for the optimum design of composite curing process.(2)Based on the macroscopic mechanical behavior analysis of composite laminate,the temperature and strain sensing characteristics of FBG sensors integrated both into the internal and on the surface of the smart composite are studied experimentally and systematically.The influence of the integrated positions of FBG sensors on their response characteristics are discusses and the response relationships under different dynamic and static loads with different energy and different angles are established.(3)A smart composite damage identification method based on artificial neural network is proposed.The dynamic response signals of composites with different degree of damages are monitored by FBG sensor array.The damage features and the corresponding damage status are taken as the input and output of the neural network respectively,and the damage identification model is constructed.Then the weights and thresholds of the network are fine-tuned by the error back-propagation algorithm,establishing the internal relationship between signal features and structural damage and accurately identifying the damages of different degrees.(4)Aiming at the influence of wave velocity variation on impact location accuracy in anisotropic composites,a method of low-velocity impact region identification without wave velocity based on deep neural network is proposed.The low velocity impact signals of different regions are monitored by FBG sensor array.After feature extraction and dimensionality reduction,they are used as input of the neural network,and the corresponding impact regions are used as outputs to build position identification model.Through the training process,the internal relationship between the signal characteristics and the impact regions is established to realize the low velocity impact position identification based on deep neural network without wave velocity.Based on the fiber Bragg grating sensing technology,this paper presents a detailed construction scheme of smart composites embedded with FBG sensors and monitors the curing process of cross-ply composite in real time,providing the foundation for the optimum design of composite curing process.Methods of smart composite damage identification and low velocity impact location identification based on neural network are proposed to realize the timely perception,evaluation and location of the hidden dangers of smart composite structures such as damage and low speed impact.It provides a theoretical and practical basis for the popularization and application of smart composites.