Research On Optimal Configuration Of Health Monitoring Sensors For Three-dimensional Braided Composite Material

Due to advantages such as light weight,high specific strength,high specific modulus,low thermal expansion coefficient,no delamination,and fatigue resistance,3D braided composite materials have become one of the preferred advanced load-bearing structural materials in aerospace and other fields.Monitoring the structural health of the material is important for the long-term operation of aerospace composite materials.In this paper,the structural health was monitored based on the carbon nanotubes(CNT)yarn sensor embedded in the material,and the strain and damage of the samples were monitored in real time.To solve the problems of CNT yarn sensors,such as many targets for optimization and configuration,and discontinuous function of targets,the non-dominated neighborhood immune multi-target optimization algorithm and an improved algorithm were used.The correctness of the algorithm was verified through experiments and finite element simulations,laying a technical basis for monitoring structural health.Based on the four-step 3D six-direction knitting process,the analytical research on the preparation method of the CNT yarn sensor proved that the CNT yarn sensor with a diameter of 100 μm was more suitable for embedding the 3D braided composite materials,and analyzed the maximum number of yarns that could be embedded and the embedding position of the CNT yarn sensor.Through the stress experiment and data analysis of the damaged samples,the mathematical model of the concentrated distribution of strain of the damage source and the positioning model of the damage source were established.In addition,building a non-dominated neighborhood immune multitarget optimization algorithm was also conducive to the optimization and configuration of the CNT yarn sensor,and obtained the optimal number and position of different samples embedded in the sensor,providing a theoretical basis for the optimization and configuration of the CNT yarn sensor.In this paper,the four-step 3D six-direction braiding process was used to embed the CNT yarn sensor into the fabricated part of the 3D braided composite material according to the optimization and configuration results.To solve the problem of curing the CNT yarn sensor,the VARTM process was used to cure the fabricated part,and the usage of “vacuum diversion compression molding protected by accurate positioning with the protection of the end lines through encapsulation with high-temperature wax”was proposed to cure the fabricated part and CNT yarn sensor,which obtained good results and laid a technical basis for curing the CNT yarn sensor.The correctness of the embedded CNT yarn sensor after optimization and configuration in this paper was verified by the axial tensile and compressive stress experiment of the non-destructive samples.The damage source positioning algorithm was used to analyze the small damaged samples(whose length and width were less than 10 cm),and it proved that after optimization and configuration,the embedded CNT yarn sensor could locate the damage source,and the maximum positioning error was less than 0.6mm.The damage source positioning experiment was performed on the large damaged samples(whose length and width were greater than 10 cm and less than 100 cm),and the maximum positioning error was less than 1 mm,proving that the optimization and configuration principle of the CNT yarn sensor could be applied to the damage monitoring of 3D braided composite material,and the damage positioning accuracy was relatively high.Furthermore,in this paper,a full-scale 3D model was built according to the law of motion of yarn made of 3D braided composite materials.Based on the 3D model,the bonding parameters and the modulus between the materials were analyzed,and a fullscale finite element model of the mesostructure was built.Using the finite element model,the strain of the CNT yarn sensor under axial tension and compression was analyzed.The experimental results showed that the CNT yarn sensor embedded in the samples could effectively reflect the overall strain of the samples,and verify the rationality of the optimization and configuration algorithm of the CNT yarn sensor and the effectiveness of the results.In short,this study provides a theoretical basis for the monitoring of the health of 3D braided composite materials used in the aerospace field in China.