TY - JOUR
T1 - Optimal placement of triaxial accelerometers using hypotrochoid spiral optimization algorithm for automated monitoring of high-rise buildings
AU - Mahjoubi, Soroush
AU - Barhemat, Rojyar
AU - Bao, Yi
N1 - Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/10
Y1 - 2020/10
N2 - Optimal sensor placement aims to use a limited number of sensors to obtain as much information about a structure as possible. This study investigates the optimal placement of triaxial accelerometers for automated monitoring of high-rise buildings using a newly developed hypotrochoid spiral optimization algorithm. The 632-meter-tall Shanghai Tower is used as an example structure to demonstrate and compare the hypotrochoid spiral optimization algorithm with seven existing optimization algorithms, including the artificial bee colony algorithm, flower pollination algorithm, spiral optimization algorithm, Jaya algorithm, lion pride optimization algorithm, particle swarm optimization algorithm, and teaching-learning based optimization algorithm. Three objective functions based on the modal assurance criterion are applied to measure the utility of sensor configurations for modal identification. Two different structural models with different types of elements are investigated to identify the effect of structural models on the optimal sensor placement. The results reveal that the hypotrochoid spiral optimization algorithm provides the best solution using a detailed structural model and multi-objective function.
AB - Optimal sensor placement aims to use a limited number of sensors to obtain as much information about a structure as possible. This study investigates the optimal placement of triaxial accelerometers for automated monitoring of high-rise buildings using a newly developed hypotrochoid spiral optimization algorithm. The 632-meter-tall Shanghai Tower is used as an example structure to demonstrate and compare the hypotrochoid spiral optimization algorithm with seven existing optimization algorithms, including the artificial bee colony algorithm, flower pollination algorithm, spiral optimization algorithm, Jaya algorithm, lion pride optimization algorithm, particle swarm optimization algorithm, and teaching-learning based optimization algorithm. Three objective functions based on the modal assurance criterion are applied to measure the utility of sensor configurations for modal identification. Two different structural models with different types of elements are investigated to identify the effect of structural models on the optimal sensor placement. The results reveal that the hypotrochoid spiral optimization algorithm provides the best solution using a detailed structural model and multi-objective function.
KW - Automated monitoring
KW - Hypotrochoid spiral optimization algorithm
KW - Metaheuristics
KW - Modal assurance criterion
KW - Optimal sensor placement
KW - Optimization
KW - Structural health monitoring
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U2 - 10.1016/j.autcon.2020.103273
DO - 10.1016/j.autcon.2020.103273
M3 - Article
AN - SCOPUS:85085237286
SN - 0926-5805
VL - 118
JO - Automation in Construction
JF - Automation in Construction
M1 - 103273
ER -