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兵工学报 ›› 2021, Vol. 42 ›› Issue (4): 871-877.doi: 10.3969/j.issn.1000-1093.2021.04.021

• 论文 • 上一篇    下一篇

基于无速度参数目标函数的弹着点定位方法

李志明, 范锦彪   

  1. (中北大学 仪器科学与动态测试教育部重点实验室, 山西 太原 030051)
  • 上线日期:2021-06-08
  • 通讯作者: 范锦彪(1974—),男,教授,硕士生导师 E-mail:fjb@nuc.edu.com
  • 作者简介:李志明(1995—),男,硕士研究生。E-mail: 344516116@qq.com

Impact Point Positioning Method Based on the Objective Function without Velocity Parameter

LI Zhiming, FAN Jinbiao   

  1. (Key Laboratory of Instrumentation Science & Dynamic Measurement of Ministry of Education, North University of China, Taiyuan 030051, Shanxi, China)
  • Online:2021-06-08

摘要: 目前基于地震波的弹着点定位方法多数都需要提前测量地震波波速或对其进行反演,导致定位误差大,为此提出一种基于波速方差目标函数的弹着点定位方法。该目标函数的未知参数只有弹着点坐标,无需提前测速或进行波速反演。采用单纯形法对此目标函数寻优,并结合带噪声的密度聚类算法进行弹着点定位,可以有效抑制因波速不均匀带来的定位误差。通过构建的仿真模型验证定位方法的可行性。该定位方法应用于地面静爆试验,利用检波器获得的数据对爆心进行定位,相对定位误差为0.38%,试验验证了定位方法的正确性。

关键词: 弹着点定位, 波速方差, 单纯形法, 带噪声的密度聚类算法

Abstract: In most of the existing impact point positioning methods based on seismic wave, the velocity of seismic wave needs to be inversed or measured in advance, which causes a large positioning error. An impact point positioning method based on objective function is proposed. The unknown parameters of objective function are only the coordinates of the impact point, so there is no need to measure the wave velocity in advance or inverse the wave velocity. The simplex method is used to optimize the objective function, and the density-based spatial clustering of applications with noise (DBSCAN) algorithm is used to locate the impact point.The method can effectively suppress the positioning error caused by uneven wave velocity. A simulation model is esatablished to verify the feasibility of the positioning algorithm. When the positioning method is applied to the ground static explosion experiment and the data obtained by the geophone is used to locate the explosion center, the relative positioning error is 0.38%, which proves the correctness of the positioning method.

Key words: impactpointpositioning, varianceofwavevelocity, simplexmethod, density-basedspatialclusteringofapplicationswithnoisealgorithm

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