Sensor placement optimization of civil engineering structures using GA-SA algorithm

• Autorzy: Li Feng , Shi Binbin

Identyfikatory

DOI

10.24425/ace.2025.155088

• Języki publikacji: EN

Abstrakty

EN

Effectively and accurately obtaining the structure and status information of civil engineering by optimizing the configuration of sensors is the basis for the monitoring of civil engineering structures, and it is also the key content for subsequent monitoring and evaluation. To realize the intelligent development of sensor placement optimization, the simulated annealing algorithm is first used to optimize the genetic algorithm, and the sensor placement optimization method of civil engineering structure using genetic simulated annealing algorithm is obtained. The results showed that in the optimization results under the ℎ1 and ℎ2 functions, the function values of the genetic simulation annealing algorithm were 0.000045 and –1.031624 in the 125th iteration, respectively, and the algorithm quickly obtained the global optimal solution. In the practical application of civil engineering structures, the genetic simulation annealing algorithm convergence was the best when measurement points were less than 27, and the optimal solution was obtained after 16 iterations. After measurement points exceeded 28, the genetic simulated annealing algorithm obtained excellent optimization results. The above results show that the proposed method can provide targeted optimization solutions for different types of civil engineering structures to achieve the goal of monitoring.

• Wydawca: Komitet Inżynierii Lądowej i Wodnej PAN ; Politechnika Warszawska, Wydział Inżynierii Lądowej
• Czasopismo: Archives of Civil Engineering
• Rocznik: 2025
• Tom: Vol. 71, nr 3
• Strony: 97--110
• Opis fizyczny: Bibliogr. 15 poz., il., tab.

Twórcy

autor

Li Feng

• College of Civil Engineering, Henan University of Engineering, Zhengzhou, China,
• Faculty of Engineering, Universiti Malaysia Sarawak, Malaysia

• https://orcid.org/0009-0004-8106-3923

autor

Shi Binbin

• School of Art and Design, Henan University of Engineering, Zhengzhou, China

• https://orcid.org/0009-0002-9857-9243

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