标题： 基于网格环搜索和粒子群源定位的声发射传感器网络优化 显示英文标题

标题： Acoustic Emission Sensor Network Optimization Based on Grid Loop Search and Particle Swarm Source Location

摘要： 声发射传感器的布局在无损结构测试中起着关键作用。 本研究提出了一种基于网格的优化方法，专注于多源定位结果，与传统传感器布局优化方法不同，传统方法基于传感器布局和一个源定位构建相关矩阵。 基于地震源走时理论，所提出的方法建立了一个基于最小走时差的定位目标函数，并通过粒子群优化（PSO）算法求解。 此外，基于各种配置下的定位精度，该方法通过网格搜索系统地评估潜在的最优传感器位置。 进行了合成测试和实验室铅笔断裂（PLB）实验，以比较PSO、遗传算法和模拟退火的有效性，得出以下结论：(1) 在合成测试中，所提出的方法平均定位误差为1.78毫米，优于基于传统布局、遗传算法（GA）和模拟退火（SA）的方法。 (2) 对于不同的噪声情况，与传统布局相比，定位精度分别提高了24.89% ({\sigma }=0.5{\mu }s)，12.59% ({\sigma }=2{\mu }s)，和15.06% ({\sigma }=5{\mu }s)。 (3) 对于PLB实验，优化后的布局平均定位误差为9.37毫米，与传统布局相比，定位精度提高了59.15%。 显示英文摘要

摘要： The layout of acoustic emission sensors plays a critical role in non-destructive structural testing. This study proposes a grid-based optimization method focused on multi-source location results, in contrast to traditional sensor layout optimization methods that construct a correlation matrix based on sensor layout and one source location. Based on the seismic source travel-time theory, the proposed method establishes a location objective function based on minimum travel-time differences, which is solved through the particle swarm optimization (PSO) algorithm. Furthermore, based on location accuracy across various configurations, the method systematically evaluates potential optimal sensor locations through grid search. Synthetic tests and laboratory pencil-lead break (PLB) experiments are conducted to compare the effectiveness of PSO, genetic algorithm, and simulated annealing, with the following conclusions: (1) In synthetic tests, the proposed method achieved an average location error of 1.78 mm, outperforming that based on the traditional layout, genetic algorithm (GA), and simulated annealing (SA). (2) For different noise cases, the location accuracy separately improved by 24.89% ({\sigma}=0.5{\mu}s), 12.59% ({\sigma}=2{\mu}s), and 15.06% ({\sigma}=5{\mu}s) compared with the traditional layout. (3) For the PLB experiments, the optimized layout achieved an average location error of 9.37 mm, which improved the location accuracy by 59.15% compared with the Traditional layout.