摘要
运用人工神经网络技术 ,综合岩石介质条件、赋存环境条件以及工程因素 3大方面的 5个指标 ,即岩石单轴抗压强度、岩石质量指标、煤体强度、地下水状况、工作面月推进速度 ,建立了采场顶板稳定性动态预测模型。并以工作面月推进速度 4 0m、6 0m、80m、10 0m分别预测了新集井田顶板稳定性分区。根据 5个指标因素分析结果 ,对顶板稳定性影响程度由大到小排序为岩石质量指标、地下水状况、岩石单轴抗压强度、煤体强度、工作面月推进速度。在上述研究成果上提出了不同顶板类型的控制对策。
Five indices of the medium conditions, occurence background, and engineering factors of rocks, such as uniaxial compressive strength, rock quality distribution, coal mass strength, groundwater status, and monthly advance of working face are used in establishing, the dynamical evaluation model of the roof stability with artificial neural network(ANN). The subzone of roof stability is forecasted from data of working face advance of 40m, 60m, 80m and 100m per month, respectively. The result of ANN analysis of 5 indeces shows the factors effecting on the roof stability in a sequence from high to low degree are rock quality distribution, groundwater status, rock uniaxial compressive strength, coal mass strength and face advance. The measures for controlling different types of roof stability are suggested pertinently according to above results.
出处
《工程地质学报》
CSCD
2003年第1期44-48,共5页
Journal of Engineering Geology
基金
国家自然科学基金资助 (批准号 :40 172 0 5 9)
国家杰出青年基金 (批准号 :5 0 0 2 5 413 )
