Optimal Sensor Placement in Structures Using Improved Adaptive Genetic Algorithm with Modified Modal Assurance Criteria for SHM Systems
With the growth of advanced constructive engineering technology, more and more large-scale structures, such as buildings, towers, wharfs, and so many other structures have been built all over the world. Due to uncontrolled environment, these civil infrastructures may be damaged severely by the natural disasters and the man made changes around the environment. To avoid this, monitoring of structure is necessary and it is done with the help of structural health monitoring (SHM) systems. In this system, optimal sensor placement (OSP) is an important part of monitoring to increase the ability of ensuring data accuracy. However, some defects are present in the existing method, such as the initial sensor locations and the long computation time. A new OSP method named MSE-IAGA is presented in this paper to settle the issue. First, a modal strain energy (MSE) method is proposed to locate the initial number of sensors in the structural building. Then, an improved adaptive genetic algorithm (IAGA), which uses the root mean square of off-diagonal elements in the modified modal assurance criterion (MMAC) matrix as the fitness function, is proposed to place optimal number of sensors for enhanced computational efficiency. A study of sensor placement on a numerically simulated three storey building structure is provided to verify the effectiveness of the MSE-IAGA strategy.
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Kalima Benazir P, Suresh P. Optimal Sensor Placement in Structures Using Improved Adaptive Genetic Algorithm with Modified Modal Assurance Criteria for SHM Systems. Journal of Multimedia Technology & Recent Advancements. 2016; 3(1): 30–37p.
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