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在开采矿附近对爆炸引起的振动进行统计分析

Paulo Filipe T Lopes¹, José Aurélio M DA Luz², Tiago M Pereira³

¹Beyond Mining Tecnologia e Projetos Ltda, Rua Francisco Feio, 70, Apto 401, Gutierrez, 30441-161 Belo Horizonte, MG, Brazil.

Anais da Academia Brasileira de Ciencias

|August 16, 2023

概括

多变量统计有效地预测爆炸引起的振动,管理矿山附近的结构损坏和人类不适. 这种方法为振动分析和控制提供了自动化.

科学领域:

地质技术工程地质技术工程
环境科学环境科学
应用统计学应用统计学

背景情况:

采矿活动中的爆炸引起的振动对附近的建筑物和人类舒适性构成风险.
预测建模对于减轻这些不良影响和确保安全至关重要.

研究的目的:

应用多变量统计方法来预测采矿爆炸产生的振动水平.
评估这些振动造成的结构损坏和人体不适的可能性.

主要方法:

在一个露天的铁矿矿采矿中进行了广泛的地震监测活动.
通过集群分析和主要组件分析 (PCA) 分析了10个爆炸事件中158次测量的数据.
从法律标准中获得的振动峰值速度等级与从集群分析中获得的等级进行比较.

主要成果:

主要组件分析 (PCA) 有效地解释了爆炸引起的振动数据的变化.
集群分析产生了与法律标准定义的振动类非常相似的振动类.
该研究证实了多变量统计对于振动管理的适用性.

结论:

多变量统计方法,包括PCA和集群分析,是管理爆炸引起的振动的宝贵工具.
这些方法可以在最小的调整下实现,并为自动化提供了潜力.
这些发现支持积极管理与采矿相关的环境影响.

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