• 中文核心期刊
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  • RCCSE中国核心学术期刊

基于多源信息融合的冲击地压风险预警与弱结构防治技术

贺永亮,王素萍,付玉平,曹雪芬,孙大力

贺永亮,王素萍,付玉平,曹雪芬,孙大力. 基于多源信息融合的冲击地压风险预警与弱结构防治技术[J]. 煤矿安全, 2023, 54(7): 78-84.
引用本文: 贺永亮,王素萍,付玉平,曹雪芬,孙大力. 基于多源信息融合的冲击地压风险预警与弱结构防治技术[J]. 煤矿安全, 2023, 54(7): 78-84.
HE Yongliang. Early-warning and soft structure prevention technology of rock burst risk based on multi-source information fusion[J]. Safety in Coal Mines, 2023, 54(7): 78-84.
Citation: HE Yongliang. Early-warning and soft structure prevention technology of rock burst risk based on multi-source information fusion[J]. Safety in Coal Mines, 2023, 54(7): 78-84.

基于多源信息融合的冲击地压风险预警与弱结构防治技术

Early-warning and soft structure prevention technology of rock burst risk based on multi-source information fusion

  • 摘要: 针对冲击地压的预警结果及预测位置离散性大等问题,研究了多源信息融合的冲击地压预警技术,建立了基于机器学习算法的多源信息融合深度预测模型。通过对冲击地压事件的分析,研究了冲击事故发生的主要原因、特点及影响因素;以煤岩的抗压强度、抗拉强度、弹性能和地应力为冲击地压预测的主要指标,建立了深度神经网络预测模型,确定不同预测指标的权重,通过大数据分析和有限数据验证,确定了模型的可应用型。以陕西某冲击地压矿井为例,对深度神经网络模型进行应用,通过现场实测验证了冲击地压预测模型的有效性和正确性,提出了构建巷道围岩弱结构防治技术吸收冲击地压能量。
    Abstract: Aiming at the problems of large discreteness of early warning results and prediction positions of rock burst, a multi-source information fusion early warning technology is studied, and a multi-source information fusion depth prediction model based on machine learning algorithm is established. Through the analysis of rock burst events, the main causes, characteristics and influencing factors of rock burst accidents are analyzed. Taking the compressive strength, tensile strength, elastic energy and ground stress of coal and rock as the main indicators of rock burst prediction, the depth neural grid prediction model is established to determine the weight of different prediction indicators. Through big data analysis and limited data, the occurrence of rock burst is predicted. Taking the occurrence of rock burst is predicted. Taking a coal mine in Shaanxi Province as an example, the depth neural network model is verified, and the effectiveness and correctness of the prediction model of rock burst are verified through field measurement.
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出版历程
  • 网络出版日期:  2023-08-30
  • 刊出日期:  2023-08-22

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