地下震源波束交叉定位算法研究
发布时间：2019-06-07 13:50
【摘要】：传统的浅层地下爆炸定位是利用多个地震检波器阵列获取地下震动信号,经过信号特征提取方法得到地下震动信号初至波时刻,然后利用时差定位算法完成震源位置的测量。由于地下介质结构比较复杂,各种横波、纵波相互交叠,群速不稳,震源近场频散现象明显,导致时差定位精度不高。针对这些问题,本文提出了一种基于到达角度的分布式交叉定位算法,即通过各传感器节点获取直达纵波的角度信息,建立纵波波束模型,进行波束交叉定位,实现地下震源的精确定位。 根据小区域浅层地下震源定位需求,本文在设计地下浅层交叉定位系统基础上,经过外场模拟试验获取震源与传感器间俯仰角、方位角信息,进行坐标转换并利用最小二乘定位算法、加权融合定位算法、三维空间优化交叉定位算法、最小二乘-泰勒级数定位算法分别对获取的信息进行计算,预测出震源位置信息,采用BP神经网络训练的方法筛选有效实验数据,利用最小二乘、加权数据融合算法分别拟合出震源位置信息,分析不同定位算法得到的定位结果和定位精度,并设计软件平台直观地显示预测震源位置和定位结果。 实验结果表明：在20m*20m地下震动监测范围内,地下交叉定位均方根误差为0.40m,基本满足分布式浅层地下震动定位的需求。
[Abstract]:In the traditional shallow underground explosion location, several geophone arrays are used to obtain the underground vibration signal, and the first arrival wave time of the underground vibration signal is obtained by the signal feature extraction method, and then the source position is measured by using the time difference location algorithm. Because of the complexity of the underground medium structure, all kinds of shear waves, P-waves overlap with each other, the group velocity is unstable, and the dispersion of the source near the field is obvious, which leads to the low accuracy of time difference positioning. In order to solve these problems, a distributed cross-location algorithm based on angle of arrival is proposed in this paper, that is, the angle information of direct P-wave is obtained by each sensor node, the P-wave beam model is established, and the beam cross-location is carried out. The accurate location of underground source is realized. According to the requirements of shallow underground source location in small area, based on the design of underground shallow cross positioning system, the pitch angle and azimuth information between source and sensor are obtained by external field simulation test. The coordinate transformation is carried out and the source position information is predicted by using the least square positioning algorithm, the weighted fusion positioning algorithm, the three-dimensional spatial optimization cross-location algorithm and the least square Taylor series positioning algorithm, respectively, and the source position information is predicted by using the least square positioning algorithm, the weighted fusion positioning algorithm, the three-dimensional spatial optimization cross-location algorithm and the least square series positioning algorithm. The effective experimental data are screened by BP neural network training method. The focal position information is fitted by least square and weighted data fusion algorithm, and the positioning results and positioning accuracy obtained by different positioning algorithms are analyzed. The software platform is designed to display the predicted source position and location results intuitively. The experimental results show that the root mean square error of underground cross positioning is 0.40m in the range of 20m*20m underground vibration monitoring, which basically meets the needs of distributed shallow underground vibration location.
【学位授予单位】：中北大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P631.4
[Abstract]:In the traditional shallow underground explosion location, several geophone arrays are used to obtain the underground vibration signal, and the first arrival wave time of the underground vibration signal is obtained by the signal feature extraction method, and then the source position is measured by using the time difference location algorithm. Because of the complexity of the underground medium structure, all kinds of shear waves, P-waves overlap with each other, the group velocity is unstable, and the dispersion of the source near the field is obvious, which leads to the low accuracy of time difference positioning. In order to solve these problems, a distributed cross-location algorithm based on angle of arrival is proposed in this paper, that is, the angle information of direct P-wave is obtained by each sensor node, the P-wave beam model is established, and the beam cross-location is carried out. The accurate location of underground source is realized. According to the requirements of shallow underground source location in small area, based on the design of underground shallow cross positioning system, the pitch angle and azimuth information between source and sensor are obtained by external field simulation test. The coordinate transformation is carried out and the source position information is predicted by using the least square positioning algorithm, the weighted fusion positioning algorithm, the three-dimensional spatial optimization cross-location algorithm and the least square Taylor series positioning algorithm, respectively, and the source position information is predicted by using the least square positioning algorithm, the weighted fusion positioning algorithm, the three-dimensional spatial optimization cross-location algorithm and the least square series positioning algorithm. The effective experimental data are screened by BP neural network training method. The focal position information is fitted by least square and weighted data fusion algorithm, and the positioning results and positioning accuracy obtained by different positioning algorithms are analyzed. The software platform is designed to display the predicted source position and location results intuitively. The experimental results show that the root mean square error of underground cross positioning is 0.40m in the range of 20m*20m underground vibration monitoring, which basically meets the needs of distributed shallow underground vibration location.
【学位授予单位】：中北大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P631.4
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