AN OPTIMAL APPROACH TO THE PLACEMENT OF SENSORS IN STRUCTURAL HEALTH MONITORING BASED ON HYBRID GENETIC ALGORITHM

摘要：

A hybrid genetic algorithm (HGA) is proposed in this paper to optimize the placement of sensors installed on Nanjing Yangtze River Bridge (NYRB) for structural health monitoring (SHM). The proposed HGA is the combination of genetic algorithm (GA) and simulated annealing (SA) which can enhance the local search ability and avoid the premature convergence in GA. Firstly, the ability of global convergence of the HGA is proved by a classical testing function, Schaffer function. Secondly, the objective function for optimization is defined based on the displacement mode shapes. Given the number of sensors, the HGA is used to find the optimal placement of sensors in NYRB according to the objective function. The results show that the proposed HGA is robust and can converge to global optimum. Finally, the optimal sensor placement on NYRB for is determined.

作者: Guang Ma Fang-Lin Huang Xue-Min Wang

作者单位: School of Civil Engineering and Architecture, Central South University, Changsha 410075, P.R. China

会议类型: 国际会议

会议名称: 第二届国际结构状态评估、监测与改进会议(The Second International Conference on Structural Condition Asessment,Monitoring and Improvement)

会议地点: 长沙

会议语种:英文

页码: 929-934

在线出版日期: 2007-11-19（万方平台首次上网日期，不代表论文的发表时间）