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Intelligent Decision System for Vertical Shaft Blasting Scheme Based on Knowledge Base and Its Application

Due to the complex and changeable surrounding rock geology of the shaft, the design of the shaft blasting is affected by many factors. It is difficult to determine the blasting parameters scientifically and reasonably using traditional methods. Aiming at the above key technical problems, a design method of vertical shaft blasting scheme based on the integration of knowledge base and artificial intelligence (AI) is proposed in this paper. Firstly, the characteristic weight of factors affecting the design of the blasting was obtained based on the analytic hierarchy process (AHP) of particle swarm optimization, and according to the experience of experts, the type of surrounding rock, rock sturdiness coefficient(f), section shape, and gross diameter were selected as the key indicator for the decision-making of the blasting scheme. Secondly, the expert knowledge base and inference machine are established. This paper puts forward the research method of integrating knowledge base with a relational database, describes and expresses information content with knowledge attributes, and establishes an explosion expert knowledge base based on expert experience, industry norms, and typical cases. The cyclic search algorithm and production rule reasoning strategy were developed, and a hybrid reasoning machine for vertical shaft blasting design was established. Then, a visual intelligent design system for vertical shaft blasting is established by using computer development technology. Finally, the system has been applied in Jinzhuang Coal Mine. Compared with the traditional blasting scheme, the total number of holes in the optimized scheme of the system model is reduced by 8.39%, the single-cycle progress is increased by 11.1%, the hole utilization rate is increased by 10%, and the unit explosive consumption is reduced by 15.57%, The comprehensive effect is good, it provides a new way for vertical shaft blasting design.