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Indexed by:会议论文

Date of Publication:2021-04-12

Page Number:474-478

Key Words:structural health monitoring; sensor placement; partheno-genetic algorithms; simulated annealing; adaptive; best coverage model; finite element method

Abstract:An optimized sensor network design. will be beneficial to both safety ensuring and cost reduction considerations of structural health monitoring (SHM) systems. A new best coverage model for sensor placement optimization (SPO) problems in SHM is presented. The formulation of the optimization problem is to maximize the response information which can reflect the presence of damage in a structure as well as to minimize the number of sensors by searching the optimized patterns of sensor placement topology on the feasible region of the structure being monitored. A novel evolutionary method called adaptive simulated annealing partheno-genetic algorithms (ASAPGA) which use particular partheno-genetic operators and adaptive mechanism is adopted to solve the SPO problem. The methodology is applied to sensor placement of a concrete faced rockfill dam monitoring, and results show that the new strategy achieves fast and stable sensor deployment and maximize the response information coverage.