scholarly journals Accelerometer Optimization Placement Using Improved Particle Swarm Optimization Algorithm Based on Structural Damage Identification

Author(s):  
Zhuoda Jiang ◽  
Yang Gao
2012 ◽  
Vol 446-449 ◽  
pp. 3171-3175
Author(s):  
Hui Yong Guo ◽  
Jun Sheng Yuan ◽  
Zheng Liang Li

In order to solve structural damage identification problem, a damage identification method based on improved Particle Swarm Optimization (IPSO) is presented. First, structural frequency and modal strain energy are utilized to obtain damage information. Then, evidence fusion theory is utilized to integrate the information and preliminarily identify structural damage locations. After the damaged locations are determined, Particle Swarm Optimization (PSO) is used to identify structural damage extent. Some improved strategies are presented to enhance the search efficiency. The simulation results demonstrate that the proposed method can estimate the damage locations and extent with good accuracy.


2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Jia Guo ◽  
Deqing Guan ◽  
Jianwei Zhao

A method based on the wavelet transform and improved particle swarm optimization (WIPSO) algorithm is proposed to identify the microdamage of structures. First, the singularity of wavelet coefficients is used to identify the structural damage location, and then, the improved particle swarm optimization (IPSO) algorithm is used to calculate the optimal solution of the objective function of the structural damage location to determine the structural damage severity. To study the performance of WIPSO, the structural microdamage severity is set within 10%, and a numerical simulation and experimental structure under different damage scenarios are considered. In addition, the ability of wavelet coefficients to identify the location of the structural damage under different noise levels is studied. To evaluate the performance of IPSO, the standard particle swarm optimization algorithm with an inertia weight factor of 0.8 (0.8PSO), the genetic algorithm (GA), and the bat algorithm (BA) are also considered. The results show that WIPSO can effectively and accurately identify the structural damage location and severity. Wavelet transform is very robust to the structural damage location. Compared with the standard 0.8PSO and other mainstream algorithms, IPSO has good convergence and performs more stable and more accurate in the identification of structural damage severity.


2014 ◽  
Vol 599-601 ◽  
pp. 1453-1456
Author(s):  
Ju Wang ◽  
Yin Liu ◽  
Wei Juan Zhang ◽  
Kun Li

The reconstruction algorithm has a hot research in compressed sensing. Matching pursuit algorithm has a huge computational task, when particle swarm optimization has been put forth to find the best atom, but it due to the easy convergence to local minima, so the paper proposed a algorithm ,which based on improved particle swarm optimization. The algorithm referred above combines K-mean and particle swarm optimization algorithm. The algorithm not only effectively prevents the premature convergence, but also improves the K-mean’s local. These findings indicated that the algorithm overcomes premature convergence of particle swarm optimization, and improves the quality of image reconstruction.


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