基于改进多目标麻雀搜索算法的FBG传感监测布置方法

FBG Sensing Monitoring Deployment Method Based on an Improved Multi-Objective Sparrow Search Algorithm

摘要: 针对在隧道健康监测下利用少量离散点实现可靠、精准监测的问题，本文提出了一种改进的多目标麻雀优化算法(Improved Multi-Objective Sparrow Search Algorithm with Multi-Point Random Crossover and Specific Variation, IMSSA-MRs)，通过融合特定多点方法与特殊变异更新策略对光纤光栅传感网络布置优化。针对传统麻雀优化算法中的收敛差、局部最优等问题，IMSSA-MRs利用佳点集初始化改善增加种群的多样性，同时提升收敛速度，引入多点交叉、小波变异等更新策略，提高算法全局寻优能力。仿真实验与其他算法的对比结果表明，IMSSA-MRs算法具有更好的收敛性和求解精度，实现光纤光栅传感网络布置中监测精度与数量之间的平衡。

Abstract: To address the challenge of achieving reliable and precise monitoring using a limited number of discrete points in tunnel health monitoring, an Improved Multi-Objective Sparrow Search Algorithm with Multi-Point Random Crossover and Specific Variation (IMSSA-MRs) is proposed in this paper. This approach integrates a specific multi-point method with a specialized variation update strategy to optimize the deployment of fiber optic grating sensor networks. Addressing convergence deficiencies and local optima issues in conventional sparrow search algorithms, the IMSSA-MRs employs optimal point set initialization to enhance population diversity while accelerating convergence. It further incorporates multi-point crossover and wavelet mutation update strategies to improve global search capability. Simulation experiments and comparisons with alternative algorithms demonstrate that IMSSA-MRs exhibits superior convergence and solution accuracy, achieving a balance between monitoring precision and sensor density in FGSN deployment.