基于改进灰狼算法的岩石声发射定位研究

针对岩石力学试验中传统的声发射定位算法存在局限性，将灰狼算法(GWO)引入声发射定位研究中，该算法模仿了狼群的领导阶层与狩猎机制，用α、β、δ和ω 4种灰狼来模拟头狼领导，通过搜寻猎物、包围猎物和攻击猎物3个步骤实现目标的发现到捕获的全过程。在原始灰狼算法的基础上，针对其局部搜索能力欠佳的缺陷，修改收敛因子递减方式和淘汰最劣个体，提出基于种群记忆淘汰制的改进灰狼算法(BGWO)。基于预制裂隙岩石试件单轴压缩声发射试验结果，对比分析BGWO、GWO、引力搜索法(GSA)、Geiger算法、最小二乘法(LS)算法等5种定位算法的性能，发现改进后的BGWO算法在声发射定位搜索效率、搜索精度、稳定性和试验结果模拟方面效果优于其他算法。

ACOUSTIC EMISSION LOCALIZATION RESEARCH OF ROCK BASED ON IMPROVED GREY WOLF ALGORITHM

Because of the limitations in traditional acoustic emission positioning algorithms of rock mechanics experiments, we introduce the gray wolf algorithm(GWO)into the acoustic emission positioning research. This algorithm imitates the leadership and hunting mechanism of wolves through simulating head wolf leadership. On the basis of the original gray wolf algorithm, aiming at the defect of its poor local search ability, we propose an improved gray wolf algorithm(BGWO)based on the population memory elimination system. The BGWO algorithm modifies the method of decreasing the convergence factor and eliminates the worst individual. We compare and analyze the performance of five positioning algorithms. They are BGWO,GWO,Gravity search algorithm(GSA),Geiger algorithm and LS algorithm in the experimental of uniaxial compression acoustic emission of prefabricated fractured rock specimen. We find out that the BGWO algorithm is better than other algorithms in terms of acoustic emission positioning search efficiency, search accuracy, stability and simulation of experimental results.