Damage Detection of Civil Structures Based on Quantum Behavior Particle Swarm Optimization Algorithm
Bing Liu · 2023
In the field of civil engineering, the design and manufacture of structural materials is a very important part of engineering construction. With the continuous development of China's construction industry, the requirements for the quality of civil structural components are getting higher and higher. Therefore, in order to detect the damage of civil structures in time, this paper proposes a quantum behavior particle swarm optimization algorithm to improve the detection capability of civil structures. In this paper, a neural network adaptive learning technology and wavelet transform threshold clustering algorithm based on Monte Carlo simulation, random sequence prediction and support vector machine regression are obtained by combining statistical description method and experimental method. The experimental results show that the minimum error of wavelet detection can reach 2.4%, indicating that the algorithm has certain advantages in civil engineering results detection.