采空区塌陷预测的多元识别模型

来源期刊：有色金属科学与工程2012年第6期

论文作者：付玉华 肖国喜

文章页码：63 - 66

关键词：采矿工程; 采空区；多元识别；塌陷预测

Key words：mining engineering; goaf; multiple indexes identification; collapse prediction

摘    要：将可拓理论应用于采空区塌陷预测，建立了采空区塌陷预测的多元识别模型.以直接顶板岩性、采空区体积率、直接顶板厚度、采空区的垂直深度、工程地质及水文地质条件、矿体层倾角、采空区空间叠置层数等7个主要影响因素作为预测模型的评价指标，从某矿区采空区实测数据中选择17组数据作为训练样本，建立采空区塌陷的多元识别模型，利用该模型对训练样本回判，其误判率为零，对另外7组预测样本逐一进行了判别分析.研究结果表明：该模型判别性能良好，判别准确度高，是采空区塌陷预测中的一种非常有效的新方法.

Abstract: Based on the extension theory method，a multiple indexes identification model for predicting goaf collapse is established with influential factors such as lithology of direct roof, volume rate of the goaf region, direct roof thickness, the vertical goaf depth from the surface, hydrogeologic and engineering geologic conditions, the inclination angle of coal bed and space superposition layer of the goaf region as the evaluation indexes of the forecasting model. Seventeen groups of data selected from the measured data of the goaf region as training samples are tested by the established model, and the correct rate is 100 %. Furthermore，another seven groups of forecast samples are predicted by the multiple indexes identification model. The results show that with the good discriminant performance and accuracy, the model is a new and highly efficient method for the prediction of goaf collapse.