| 基于引力搜索法的隧道围岩微震定位研究 |
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| 引用本文： | 王剑锋,李天斌,马春驰,张航,韩瑀萱,周雄华,姜宇鹏.基于引力搜索法的隧道围岩微震定位研究[J].岩土力学,2019,40(11):4421-4428. |
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| 作者姓名： | 王剑锋 李天斌 马春驰 张航 韩瑀萱 周雄华 姜宇鹏 |
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| 作者单位： | 1. 成都理工大学 环境与土木工程学院，四川 成都 610059；2. 成都理工大学 地质灾害防治与地质环境保护国家重点实验室，四川 成都 610059；3. 四川巴陕高速公路有限责任公司，四川 成都 610059；4. 悉尼大学 土木工程学院，悉尼 澳大利亚 NSW200 |
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| 基金项目： | 青年科学基金（No. 41807255）；国家自然科学基金面上项目（No. 41772329）；中铁二院工程集团有限公司科研项目（科2017-10）。 |
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| 摘 要： | 针对目前深埋隧道围岩微震源定位难且精度不高等问题，采用启发式算法——引力搜索法（GSA）对隧道围岩微震源位置进行搜索，并将该算法与粒子群算法和单纯形法的搜索结果进行对比。发现在双速度模型和三速度模型下，引力搜索法相较于粒子群算法和单纯形法，都具有快速收敛、精度较高的优点，且与震源位置的距离能够控制在10 m以内。对双速度模型，引力搜索法的精度相对于单纯形法提高了83.71%，相对于粒子群算法提高了7.77%。对三速度模型，引力搜索法的精度相对于单纯形法提高了70.67%，相对于粒子群算法提高了39.36%。可见，该方法为深埋隧道微围岩震源定位提供了一种新思路。
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| 关 键 词： | 微震监测 隧道工程 启发式算法 引力搜索法 震源定位 |
| 收稿时间： | 2018-09-19 |
Gravitational search algorithm based microseismic positioning in tunnel surrounding rock |
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| WANG Jian-feng,LI Tian-bin,MA Chun-chi,ZHANG Hang,HAN Yu-xuan,ZHOU Xiong-hua,JIANG Yu-peng.Gravitational search algorithm based microseismic positioning in tunnel surrounding rock[J].Rock and Soil Mechanics,2019,40(11):4421-4428. |
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| Authors: | WANG Jian-feng LI Tian-bin MA Chun-chi ZHANG Hang HAN Yu-xuan ZHOU Xiong-hua JIANG Yu-peng |
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| Institution: | 1. College of Environment and Civil Engineering, Chengdu University of Technology, Chengdu, Sichuan 610059, China;
2. State Key Laboratory of Geohazard Prevention and Geo-environment Protection, Chengdu University of Technology, Chengdu 610059, China;
3. Sichuan Ba-Shan Expressway Co., Ltd., Chengdu, Sichuan 610059, China;
4. School of Civil Engineering, University of Sydney, Sydney, Australia NSW2006 |
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| Abstract: | To overcome the difficulty of deep buried tunnel microseismic source positioning and low positioning accuracy problems, a heuristic algorithm, gravitational search algorithm (GSA), is used to in this paper to search the location. The algorithm is compared with results of the particle swarm optimization and the simplex algorithm. Research shows that, under the two and three velocity models, the gravitational search algorithm has the advantages of fast convergence and high precision over the particle swarm optimization and the simplex algorithm. The distance from the source location can be controlled within 10 m, which meets the need of tunnel construction better. For the two velocity model, the accuracy of gravitational search algorithm is 83.71 percent higher than the simplex, and 7.77 percent higher than the particle swarm optimization. For the three velocity model, the accuracy of gravitational search algorithm is 70.67 percent higher than the simplex, and 39.36 percent higher than the particle swarm optimization. Through the analysis, gravitational search algorithm (GSA) can provide a new idea for the position of micro-seismic source in deep buried tunnels. |
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| Keywords: | microseismic monitoring tunnel engineering heuristic algorithm gravitational search algorithm seismic source location |
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