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A novel robust AE/MS source location method using optimized M-estimate consensus sample
International Journal of Mining Science and Technology ( IF 11.8 ) Pub Date : 2022-06-17 , DOI: 10.1016/j.ijmst.2022.06.003
Yichao Rui , Zilong Zhou , Xin Cai , Riyan Lan , Congcong Zhao

Due to the complexity of the real engineering environment, the arrival measurement inevitably contains outliers and leads to serious location errors. In order to eliminate the influence of the outliers effectively, this paper proposes a novel robust AE/MS source localization method using optimized M-estimate consensus sample. First, a sample subset is selected from the entire arrival set to obtain fitting model and its parameters. Second, consensus set is determined by checking the arrivals with the fitting model instantiated by the estimated model parameters. Third, optimization process is performed to further optimize the consensus set. The above steps are iterated, and the final source coordinates are obtained by using all the elements in the optimal consensus set. The novel method is validated by a pencil-lead breaks experiment. The results indicate that the novel method has better location accuracy of less than 5 mm compared to existing methods, regardless of the presence or absence of outliers. With the increase of outlier scale and outlier ratio, the location result of the proposed method is always more stable and accurate than that of the existing methods. Mine blasting experiments further demonstrate that the new method holds good prospects for engineering applications.



中文翻译:

一种使用优化的 M 估计一致性样本的新型稳健 AE/MS 源定位方法

由于实际工程环境的复杂性,到达测量不可避免地包含异常值并导致严重的定位误差。为了有效消除异常值的影响,本文提出了一种新的鲁棒AE/MS源定位方法,该方法使用优化的M-estimate一致性样本。首先,从整个到达集中选择一个样本子集,得到拟合模型及其参数。其次,通过使用估计模型参数实例化的拟合模型检查到达来确定共识集。第三,执行优化过程以进一步优化共识集。对上述步骤进行迭代,利用最优共识集中的所有元素得到最终的源坐标。新方法通过铅笔芯断裂实验得到验证。结果表明,无论是否存在异常值,与现有方法相比,新方法具有更好的定位精度,小于 5 mm。随着离群规模和离群率的增加,所提方法的定位结果总是比现有方法更稳定、更准确。矿山爆破实验进一步证明了新方法具有良好的工程应用前景。

更新日期:2022-06-17
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