Abstract
Inspired by sensor coverage density and matching & preserving strategy, this paper proposes an Improved Artificial Bee Colony (IABC) algorithm which is designed to optimize bridge sensor placement. We use dynamic random coverage coding method to initialize colony to ensure the diversity and effectiveness. In addition, we randomly select the factors with lower trust value to search and evolve after food source being matched in order that the relatively high trust point factor is retained in the exploitation of food sources, which reduces the blindness of searching and improves the efficiency of convergence and the accuracy of the algorithm. According to the analysis of the modal data of the Ha-Qi long span railway bridge, the results show that IABC algorithm has faster convergence rate and better global search ability when solving the optimal placement problem of bridge sensor. The final analysis results also indicate that the IABC’s solution accuracy is 76.45% higher than that of the ABC algorithm, and the solution stability is improved by 86.23%. The final sensor placement mostly covers the sensitive monitoring points of the bridge structure and, in this way, the IABC algorithm is suitable for solving the optimal placement problem of large bridge and other structures.
Highlights
Civil engineering structures, such as large span bridges and super high-rise buildings, are developing towards a direction of oversize and complexity [1,2]
Considering that different sensor placement numbers correspond to different coverage densities, differential evolutionary thinking and multiple food source matching factor trust values have different characteristics [44], based on the Artificial Bee Colony (ABC) algorithm, this paper presents an improved artificial bee colony algorithm named Improved Artificial Bee Colony (IABC) for optimal placement of bridge sensors
Aiming at the practical problems existing in the optimal placement of bridge sensors, this paper proposes an IABC algorithm with the DRCC and MPS evolution mechanism based on the ABC
Summary
Civil engineering structures, such as large span bridges and super high-rise buildings, are developing towards a direction of oversize and complexity [1,2]. Sensors are to be installed at key parts of the structure to obtain internal physics and force characteristics data for bridges as well as other civil structures data, perform scientific numerical calculations to assess the degree of structural damage and safety indicators. The greater the number of sensors deployed, the more accurate the resulting response data that can be obtained While this is still feasible for small bridges and other structures, for large and complex bridges, the corresponding hardware facilities, transmission, storage and other costs will be greatly increased, which is not conducive to the actual implementation of the project [8,9]. There are 1251 nodes and 1373 cells
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