TY - GEN
T1 - A Novel Harmony Search Cat Swarm Optimization Algorithm for Optimal Bridge Sensor Placement
AU - Luo, Bin
AU - Yi, Lingzhi
AU - Wu, Hengshan
AU - Qiu, Yun
AU - Li, Xiangguang
AU - Tang, Feilong
AU - Zhang, Yuan
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In the past three decades, many large span bridges have been built to meet the economic and social development, but due to environmental and overload factors that cause continuous damage and accelerate the aging of bridges, long-term monitoring of bridges is extremely important to ensure that bridges reach their designed service life as much as possible.The optimal placement of sensors is the most basic and essential part of the structural health monitoring (SHM) system because the good or bad sensor placement will directly affect the monitoring quality. To optimize the placement of sensors, in this paper, a novel algorithm for harmony search cat swarm optimization (HSCSO) is proposed by combining the harmony search (HS) algorithm. We confirm the usefulness of the algorithm by two types of simulations: first, three benchmark functions, and second, optimal placement of sensors based on engineering examples.The results show that whether for the three benchmark functions or the placement of sensor optimization based on engineering instances, our algorithm displays a more powerful global search capability, and to some extent solves the problem that the cat swarm optimization (CSO) algorithm is prone to fall into local optimal solutions, and has a faster convergence speed and less computation time.
AB - In the past three decades, many large span bridges have been built to meet the economic and social development, but due to environmental and overload factors that cause continuous damage and accelerate the aging of bridges, long-term monitoring of bridges is extremely important to ensure that bridges reach their designed service life as much as possible.The optimal placement of sensors is the most basic and essential part of the structural health monitoring (SHM) system because the good or bad sensor placement will directly affect the monitoring quality. To optimize the placement of sensors, in this paper, a novel algorithm for harmony search cat swarm optimization (HSCSO) is proposed by combining the harmony search (HS) algorithm. We confirm the usefulness of the algorithm by two types of simulations: first, three benchmark functions, and second, optimal placement of sensors based on engineering examples.The results show that whether for the three benchmark functions or the placement of sensor optimization based on engineering instances, our algorithm displays a more powerful global search capability, and to some extent solves the problem that the cat swarm optimization (CSO) algorithm is prone to fall into local optimal solutions, and has a faster convergence speed and less computation time.
KW - CSO
KW - HS
KW - SHM
KW - optimal sensor placement
UR - https://www.scopus.com/pages/publications/85142104804
U2 - 10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics55523.2022.00046
DO - 10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics55523.2022.00046
M3 - 会议稿件
AN - SCOPUS:85142104804
T3 - Proceedings - IEEE Congress on Cybermatics: 2022 IEEE International Conferences on Internet of Things, iThings 2022, IEEE Green Computing and Communications, GreenCom 2022, IEEE Cyber, Physical and Social Computing, CPSCom 2022 and IEEE Smart Data, SmartData 2022
SP - 41
EP - 47
BT - Proceedings - IEEE Congress on Cybermatics
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Congress on Cybermatics: 15th IEEE International Conferences on Internet of Things, iThings 2022, 18th IEEE International Conferences on Green Computing and Communications, GreenCom 2022, 2022 IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2022 and 8th IEEE International Conference on Smart Data, SmartData 2022
Y2 - 22 August 2022 through 25 August 2022
ER -
