Affiliation:
1. College of Materials Science and Engineering, Chongqing University, Chongqing 400044, China
2. School of Mechanical and Transportation Engineering of Guangxi University of Science, Guangxi, China
3. Research Institute of Science and Technology of Chinalco, Beijing, China
Abstract
In recent years, many scholars have conducted in-depth and extensive research on the mechanical properties, preparation methods, and structural optimization of grid structural materials. In this paper, the structural characteristics of composite intelligent grid are studied by combining theoretical analysis with experiments. According to the existing conditions in the laboratory, the equilateral triangular grid structure experimental pieces were prepared. In this paper, principal component analysis combined with nearest neighbor method was used to detect the damage of composite plates. On this basis, the multiobjective robustness optimization of the structure is carried out based on artificial intelligence algorithm, which makes the structure quality and its sensitivity to uncertain parameters lower. Particle swarm optimization (PSO) is used in neural network training. The damage characteristics of different grid structures, different impact positions, and different impact energies were studied. The results show that the structural damage types, areas, and propagation characteristics are very different when the structure is impacted at different positions, which verifies that the grid structure has a good ability to limit the damage diffusion and shows that the grid structure has a good ability to resist damage.
Funder
Fundamental Research Funds for the Central Universities
Subject
General Mathematics,General Medicine,General Neuroscience,General Computer Science
Cited by
4 articles.
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