Research on the Cutting Path Control of Coal Mining Machine Based on Dynamic Geological Models

Planned cutting is a core technique for intelligent coal mining, relying on high-precision geological models of fully mechanized mining faces to plan the cutting trajectory of mining equipment, with model accuracy as a prerequisite for intelligent mining. To address the limitations of traditional interpolation methods in dynamic model updating and the technical gap between geological information and equipment control parameters, this study proposes a coal mining machine cutting path control method based on dynamic geological models. An improved smooth discrete interpolation method is developed to realize dynamic updating of the geological model, effectively improving the accuracy of local geological models and ensuring safe mining operations. Meanwhile, a method for converting geological information into coal mining equipment control parameters is proposed, breaking the technical barrier between geological data and production control information and laying a foundation for unmanned and intelligent mining. Field tests conducted in a shaft coal mine in Shaanxi demonstrate that the method achieves precise control of the coal mining machine’s trajectory: during a 7-day trial, the working face advanced 56 m and mined 51,000 tons of coal with minimal human intervention. Comparative analysis shows that the error between the planned cutting based on the dynamic geological model and manual cutting is within 10 cm, and the drum height curve is smoother, reducing frequent adjustments and facilitating equipment protection. Dynamic model updating ensures high accuracy, with an average absolute error of 0.029 m at 5 m from the update point and 0.101 m at 10 m, meeting the requirements for automated cutting. The successful application of this method verifies its feasibility in actual mining processes, providing a new technical approach for achieving unmanned and intelligent coal mining.