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软岩巷道锚注支护设计是一个涉及水文地质、工程地质、开采条件、岩石力学等诸多因素的复杂非线性难题。针对这一难题,将人工智能领域中专家系统技术与煤矿软岩巷道锚注支护领域专家理论研究成果、实践经验相结合,提出了软岩巷道锚注支护设计专家系统结构模型。基于软岩巷道锚注支护工程知识的特点,建立了软岩巷道围岩地质力学性质知识库、软岩巷道锚注支护设计工程案例知识库以及软岩巷道锚注支护设计专家知识库;同时,运用计算模式推理、BP神经网络推理以及产生式规则推理等3种推理策略,构建了锚注支护专家系统的核心推理机,实现了对软岩巷道锚注支护方案与参数的优化设计。将该专家系统应用于淮北矿区某矿井软岩巷道锚注支护设计中,显著地提高了软岩巷道锚注支护结构和参数选择的科学性与合理性,有效地维护了该软岩巷道围岩的稳定。
The design of bolting and grouting in soft rock roadway is a complex nonlinear problem involving many factors such as hydrogeology, engineering geology, mining conditions and rock mechanics. In view of this problem, combining the expert system technology in the field of artificial intelligence with the theoretical research results and practical experience of experts in the field of bolting and grouting for soft rock roadways in coal mine, the structural model of the expert system of the bolting and grouting support in soft rock roadways is proposed. Based on the characteristics of the engineering knowledge of bolting and grouting support in soft rock roadway, the knowledge base of geotechnical properties of surrounding rock in soft rock roadway, the knowledge base of engineering design of bolting and bolting support in soft rock roadway and the expert knowledge base of bolting and grouting support in soft rock roadway At the same time, using the three inference strategies of computational mode reasoning, BP neural network reasoning and generative rule reasoning, the core reasoning machine of the anchoring support expert system is constructed, and the anchoring and supporting schemes and parameters of soft rock roadway are realized Optimize design. The expert system is applied to the design of bolting and grouting support in the soft rock roadway of a mine in Huaibei Mining Area, which obviously improves the scientificity and rationality of the bolting and grouting support structure and parameter selection for the soft rock roadway and effectively maintains the soft rock tunnel Surrounding rock stability.