井下遇难人员定位的浓度场推演模型及其应用
中图分类号:

TD774

基金项目:

国家自然科学基金


Deductive Models of Concentration Field for Locating the Death in Mine and Its Application
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    摘要:

    提出了以有机体腐败产生气体确定压埋遇难人员位置的新思想,建立了以腐败源定位的最小二乘数学模型;通过有机体腐败实验,对比建立的2种神经网络计算方法的定位效果,结果表明,前向反馈神经网络计算方法更适合井下遇难人员定位.这些工作为根据测定的特征气体(硫醇)的浓度分布推断遇难人员位置打下理论分析和技术开发的基础,减少了救护队员在危险垮塌区域的搜救时间,从而提高了救灾的科学性、安全性、有效性.

    Abstract:

    Based on the idea of locating the death in the collapsed area of mine by the gas released from the organism decomposition proposed by the authors, this paper presents the Least Multiply Square (LMS) model for the location and develops two kinds of ANN models for the locating computation. The results of the organism decomposition experiment indicates that the Back Propagation (BP) is better for locating the death in mine. Above works are set up the foundation of the theoretical analysis and the technical development for locating the death by analyzing the concentration distribution of the marker gas, mercaptans, in mine. Based on the technology developed, the period, for the rescue team members staying in that risk area, can be shorten. The rescue work achieve a step forward for more reasonable, feasible and efficient.

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周心权,徐敏,张安琦.井下遇难人员定位的浓度场推演模型及其应用[J].重庆大学学报,2004,27(12):63-67.

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  • 最后修改日期:2004-09-08
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