Beetle-Swarm Evolution Competitive Algorithm for Bridge Sensor Optimal Placement in SHM

• Published in: IEEE sensors journal Vol. 20; no. 15; pp. 8244 - 8255
• Main Authors: Yang, Jianhui, Peng, Zhenrui
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; beetle-swarm evolution competitive algorithm; Binary codes; Coding; Evolutionary algorithms; Global optimization; high-dimensional dynamic coverage coding; Optimization; phagocytosis and elimination strategy; Placement; Sensor placement optimization; Sensors; Structural health monitoring
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2019.2934996

In structural heath monitoring (SHM), for the sake of optimizing the bridge sensor placement, a beetle-swarm evolution competitive algorithm is proposed with the group evolutionary competition mechanism introducing into beetle antennae search optimization (BAS). This paper uses high-dimensional dynamic coverage coding to initialize the beetle's location as binary codes, which avoids that the original BAS can only solve the continuous optimization problem, and ensures the dispersion of effective information in individuals, so that the coding rules are consistent with the actual coverage density for bridge sensors. In the process of evolutionary, horizontal mutation, crossover, phagocytosis and elimination among individuals are added to improve the diversity of individual evolution, which may avoid the algorithm falling into local optimum, and make the excellent individuals tend to be better. Lastly, the example analysis of Ha-Qi bridge shows that beetle-swarm evolution competitive algorithm has fast convergence speed and global optimization ability, and it is suitable for solving the sensor placement optimization for large bridge.