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首页> 外文期刊>IEEE sensors journal >Beetle-Swarm Evolution Competitive Algorithm for Bridge Sensor Optimal Placement in SHM
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Beetle-Swarm Evolution Competitive Algorithm for Bridge Sensor Optimal Placement in SHM

机译：甲虫传感器桥梁传感器的竞争竞争算法在SHM中的最佳放置

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摘要

In structural heath monitoring (SHM), for the sake of optimizing the bridge sensor placement, a beetle-swarm evolution competitive algorithm is proposed with the group evolutionary competition mechanism introducing into beetle antennae search optimization (BAS). This paper uses high-dimensional dynamic coverage coding to initialize the beetle's location as binary codes, which avoids that the original BAS can only solve the continuous optimization problem, and ensures the dispersion of effective information in individuals, so that the coding rules are consistent with the actual coverage density for bridge sensors. In the process of evolutionary, horizontal mutation, crossover, phagocytosis and elimination among individuals are added to improve the diversity of individual evolution, which may avoid the algorithm falling into local optimum, and make the excellent individuals tend to be better. Lastly, the example analysis of Ha-Qi bridge shows that beetle-swarm evolution competitive algorithm has fast convergence speed and global optimization ability, and it is suitable for solving the sensor placement optimization for large bridge.
机译：在结构性Heath监测（SHM）中，为了优化桥梁传感器放置，提出了一种甲虫 - 群演化竞争算法，其与甲虫天线搜索优化（BAS）引入甲虫天线搜索优化（BAS）。本文使用高维动态覆盖编码，以将甲壳列的位置初始化为二进制代码，这避免了原始的BAS只能解决连续优化问题，并确保在个人中的有效信息的分散，因此编码规则是一致的桥接传感器的实际覆盖密度。在进化的过程中，添加了水平突变，交叉，吞噬作用和个人之间的消除以改善个体演进的多样性，这可能避免算法落入局部最佳，使优秀的个人趋于更好。最后，海琪桥的示例分析表明，甲虫 - 群演化竞争算法具有快速的收敛速度和全局优化能力，适用于求解大桥的传感器放置优化。

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