摘要
根据慢度离差法的基本原理，给出由遗传算法确定 Ａ Ｅ 空间位置、发生时刻及慢度离差 ５个参量的具体方法。结合实验条件，通过数值试验对定位误差等问题进行探讨，并对真实 Ａ Ｅ 定位的误差分布给出统计上的圈定。数值试验结果表明，算法具有较高的精度和较好的收敛性及稳健性；探头数量及布设方式对定位结果的优劣有影响，４ 个以上探头有记录时，即可得到理想的结果；大的定位误差主要来源于台阵外部少数“ Ａ Ｅ”的结果。到时测量的随机误差小于最小测量时间单位的５０％ 时，平均有９７％ 的“ Ａ Ｅ”定位误差分布在３ ｍ ｍ 范围内，小于物理不可分辨精度（探头直径）
Based on the fundamental theorem of Slowness Deviation Method, the specific method to determine the source location, occurring time and slowness deviation of an AE by the Genetic Algorithm have been offered in this paper. Combining with the actual experimental condition, some questions such as AE source location error have been discussed by the numerical tests, and the statistic limitation for error distribution of AE location has been also expressed in the paper. The results show that the algorithm has a high precision, good convergence and stability. The number and distribution of the sensors can strongly influence the accuracy of AE location. The ideal results could be got when four or more sensors are triggered. Large location error comes from a few results of AE location outside the sensor array. Generically, when random arrival time error is smaller than 50% of the minimum time measuring unit, the location error, more than 97% of AE events, is distributed in the range of 3 mm to be smaller than the diameter of a sensor.
出处
《地震》
CSCD
北大核心
1999年第3期245-252,共8页
Earthquake
基金
中国地震局"九五"科研攻关项目
山东省自然基金
关键词
声发射定位
遗传算法
数值试验
地震预报
Acoustic emission, Slowness deviation, Genetic algorithm, Numerical test
