基于改进GA算法的远场震源定位方法
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摘要
针对震源置于远场时定位精度急剧下降的问题,提出了基于改进GA算法的远场震源定位方法。改进GA算法综合利用拟牛顿法收敛速度快和GA算法可全局搜索的特点实现震源定位,仿真结果表明,改进GA算法运行速度约为GA算法的3倍。针对传感器单轴排列导致y轴定位精度无法保证的问题,提出将传感器的位置布置改为双轴,在双轴上各自设置独立的子目标函数,保证双轴误差最小,分析结果表明,新目标函数的收敛速度更快、更稳定,可有效提高y轴定位精度。
In view of problem that positioning accuracy drops sharply when seismic source is placed in far-field,a far-field seismic source positioning method based on improved GA algorithm was proposed.The improved GA algorithm makes use of fast convergence speed of quasi-Newton method and global search of GA algorithm to realize seismic source positioning.Simulation results show that the improved GA algorithm runs about three times faster than the GA algorithm.In view of problem that positioning accuracy of y-axis cannot be guaranteed due to uniaxial arrangement of sensors,it was proposed to change the position of the sensors to two axes and set independent sub-objective functions on both axes to minimize the biaxial error.Analysis results show that the new objective function converges faster and runs more stably,and can effectively improve y-axis positioning accuracy.
In view of problem that positioning accuracy drops sharply when seismic source is placed in far-field,a far-field seismic source positioning method based on improved GA algorithm was proposed.The improved GA algorithm makes use of fast convergence speed of quasi-Newton method and global search of GA algorithm to realize seismic source positioning.Simulation results show that the improved GA algorithm runs about three times faster than the GA algorithm.In view of problem that positioning accuracy of y-axis cannot be guaranteed due to uniaxial arrangement of sensors,it was proposed to change the position of the sensors to two axes and set independent sub-objective functions on both axes to minimize the biaxial error.Analysis results show that the new objective function converges faster and runs more stably,and can effectively improve y-axis positioning accuracy.
引文
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[2]程久龙,宋广东,刘统玉,等.煤矿井下微震震源高精度定位研究[J].地球物理学报,2016,59(12):4513-4520.CHENG Jiulong,SONG Guangdong,LIU Tongyu,et al.High precision location of micro-seismic sources in underground coal mine[J].Chinese Journal of Geophysics,2016,59(12):4513-4520.
[3]王子珺.地震动破坏性与地震预警理论方法研究[D].北京:北京交通大学,2017.
[4]李楠.微震震源定位的关键因素作用机制及可靠性研究[D].徐州:中国矿业大学,2014.
[5]郭跃东,宋旭东.梯度下降法的分析和改进[J].科技展望,2016,26(15):115.
[6]于杰.改进的多步拟牛顿法及其收敛性[D].南京:南京航空航天大学,2011.
[7]李健,高永涛,谢玉玲,等.基于无需测速的单纯形法微地震定位改进研究[J].岩石力学与工程学报,2014,33(7):1336-1346.LI Jian,GAO Yongtao,XIE Yuling,et al.Improvement of microseism locating based on simplex method without velocity measuring[J].Chinese Journal of Rock Mechanics and Engineering,2014,33(7):1336-1346.
[8]LI J,WU S C,GAO Y T,et al.An improved multidirectional velocity model for micro-seismic monitoring in rock engineering[J].Journal of Central South University,2015,22(6):2348-2358.
[9]马永杰,云文霞.遗传算法研究进展[J].计算机应用研究,2012,29(4):1201-1206.MA Yongjie,YUN Wenxia.Research progress of genetic algorithm[J].Application Research of Computers,2012,29(4):1201-1206.
[10]赛琳伟.基于遗传算法的团簇结构全局搜索[D].大连:大连理工大学,2012.
[11]朱钰,韩昌佩.一种种群自适应收敛的快速遗传算法[J].计算机科学,2012,39(10):214-217.ZHU Yu,HAN Changpei.Improved genetic algorithm with adaptive convergence populations[J].Computer Science,2012,39(10):214-217.
[12]汪民乐.遗传算法的收敛性研究[J].计算技术与自动化,2015,34(1):58-62.WANG Minle.Research on convergence of genetic algorithm[J].Computing Technology and Automation,2015,34(1):58-62.
[13]余涛,刘泽燊.基于Spark的并行遗传算法研究[J].计算机时代,2017(1):43-46.YU Tao,LIU Zeshen.Research of massive parallel genetic algorithm based on spark[J].Computer Era,2017(1):43-46.
[14]丁恩杰,刘亚峰,吕雅洁.感知矿山物联网发展现状及展望[J].信息通信技术,2015,9(5):15-20.DING Enjie,LIU Yafeng,LYU Yajie.Situation and prospect of IoT in mine[J].Information and Communications Technologies,2015,9(5):15-20.
[15]徐逸鹤,徐涛,王敏玲,等.井中震源的远场波场特征研究[J].地球物理学报,2015,58(8):2912-2926.XU Yihe,XU Tao,WANG Minling,et al.Far-field wavefield characteristics of downhole seismic sources[J].Chinese Journal of Geophysics,2015,58(8):2912-2926.