جانمایی بهینه حسگرها جهت پایش سلامت سازهی پلها با استفاده از الگوریتم ژنتیک

Abstract

One of the challenges in the health monitoring of bridge structures is the extraction from the structure. This is done by sensors in the structure. Optimization of the locating and use of the least possible number of sensors, so as to provide the most needed data on the structural status, has always been of interest. This approach could significantly reduce the cost of the health monitoring of bridge structures and hoped for widespread use of this system in other construction. However, some defects are present in the existing methods, such as the focus on a single optimal index, the selection of modal order and sensor number based on experience, and the long computation time. A new strategy named MSE-MGA (Modal Strain Energy-Modified Genetic Algorithm) is proposed in this study to address these problems. This approach is based on three steps. At first, it selects modal order using modal participation factor. Then, the modal strain energy method is adopted to conduct the initial sensor placement. Finally, the modified genetic algorithm is utilized to determine the optimal number and locations of the sensors. A bridge sample is modelled to verify the effectiveness of this method and after the above steps, the optimal number and arrangement of the sensors in this model is determined.