Abstract
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.
Highlights
During the service life of a structure, microdamages occur, which are difficult for direct visual identification; these microdamages will accumulate and eventually lead to structure failure or even collapse. erefore, research on structural microdamage has become increasingly urgent
A simple, yet powerful, technique based on wavelet transform combined with the improved particle swarm optimization (WIPSO) algorithm for microdamage location and quantification in the structure is proposed, and the microdamage of the structure is defined within 10%
IPSO improves the calculation method of the inertial weight of the standard PSO to balance the global and local searches of damage identification, so the IPSO will not fall into the local optimization and prematurity in research problems similar to those in this paper. rough numerical simulations of a fixed beam structure and a onestory one-span frame structure, the accuracy and running speed of structural damage identification by wavelet transform and improved particle swarm optimization (WIPSO) are obtained. en, IPSO is compared with genetic algorithm (GA) [44, 49], 0.8PSO, and bat algorithm (BA) [50] to obtain the performance. e numerical simulation and experimental research under different damage scenarios show that WIPSO can quickly and accurately identify the structural damage and has great potential in damage identification of structures
Summary
During the service life of a structure, microdamages occur, which are difficult for direct visual identification; these microdamages will accumulate and eventually lead to structure failure or even collapse. erefore, research on structural microdamage has become increasingly urgent. Based on the natural frequency, the modal strain energy damage identification method of the displacement mode can be used, and the effectiveness of the method for identifying the damage location of complex structures was verified by numerical simulation [7]. Scholars and research groups are trying to study how to combine wavelet analysis and intelligent algorithms to identify the location and severity of the structural damage. A simple, yet powerful, technique based on wavelet transform combined with the improved particle swarm optimization (WIPSO) algorithm for microdamage location and quantification in the structure is proposed, and the microdamage of the structure is defined within 10%. IPSO improves the calculation method of the inertial weight of the standard PSO to balance the global and local searches of damage identification, so the IPSO will not fall into the local optimization and prematurity in research problems similar to those in this paper. IPSO improves the calculation method of the inertial weight of the standard PSO to balance the global and local searches of damage identification, so the IPSO will not fall into the local optimization and prematurity in research problems similar to those in this paper. rough numerical simulations of a fixed beam structure and a onestory one-span frame structure, the accuracy and running speed of structural damage identification by WIPSO are obtained. en, IPSO is compared with GA [44, 49], 0.8PSO, and BA [50] to obtain the performance. e numerical simulation and experimental research under different damage scenarios show that WIPSO can quickly and accurately identify the structural damage and has great potential in damage identification of structures
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