An Optimal Algorithm for Planning Shearer Trailing Drum Cutting Path

Hong Zhang,Yunbing Hou,Shanjun Mao,Mei Li,Zhenming Sun,Zhen Li,Jinzheng Wang,Gong-Da Wang

doi:10.1155/2021/1354705

Abstract

The intelligent adaptive cutting of the shearer is one of the key technologies to realize the intelligent working face. However, since the “memory cut” technology is the mainstream technology, which cannot actively adapt to the coal seam variations, the trailing drum usually cuts at a fixed height without a planned cutting path. This paper analyzes the shearer’s location characteristics before and after the advancement to propose a complete calculation method for the advancing path of the shearer, which simulates all of its possible advancing paths for subsequent n cuttings. The multitree and depth-first search algorithms are utilized to filter out the optimal advance path under different mining requirements. Simultaneously, this paper indicates that the vertical curvature of the armored face conveyor (AFC) should be considered in the calculation process of the optimal advancing path at different positions of the working face to obtain the shearer’s planned cutting path for subsequent n cuttings. The proposed algorithm in this paper has apparent advantages over the “memory cut” technology and provides a good solution for the intelligent planning of cutting and pitch steering of the shearers.

Highlights

Coal is still an important energy source in the world
Taking a working face of Guotun Coal Mine as an example, the optimal advancing path is compared with the “memory cut” advancing path. e working face of Guotun Coal Mine is a longwall working face, in which the face width is 188 m, the coal seam thickness is 4.2–6.0 m, and the coal seam dip angle is 0–15°, equipped with MG900/2245-GWD coal shearer and SGZ1000/2000 armored face conveyor (AFC). e shearer has a cutting depth of 0.8 m and a maximum floor-based quantity of 39 cm
A section of the coal seam bottom boundary is chosen arbitrarily from the local model ahead of the working face for testing. e initial pitch angle of the shearer is −5.35°, and all possible advancing paths for the successive five cuttings are shown in Figure 11. e overlimit paths are screened out using constraint conditions, such as the maximum pitch angle of the shearer and the maximum height of the floor step

Summary

Introduction

Coal is still an important energy source in the world. compared with other energy industries, the technological level of the coal industry is relatively backward. e integration is low, the information level is insufficient, the mining environment is dangerous [1, 2], and safety accidents occur from time to time. erefore, the coal industry’s development trend requires upgrading and optimizing traditional mining technologies and constructing intelligent and unmanned mines based on some technologies, such as the Internet of ings, virtual simulation [3, 4], and big data. The optimized “memory cut” technology can accurately predict the cutting path of the cut, all optimization methods are optimized for the leading drum cutting curve, while the trailing drum still cuts at a fixed height These methods cannot adapt well to the spatial shape variations of the coal seam ahead of the working face. In order to achieve the maximum recovery, the proposed method employs the local high-precision 3D dynamic geological model to obtain the accurate coal seam bottom boundary data ahead of the working face and comprehensively considers the shearer drum adjustment, the vertical curvature of the armored face conveyor (AFC), the pitch angle of shearer, and the mining technology requirements to plan the cutting path of the shearer trailing drum for subsequent n cuttings

Cutting Path Planning Method

Calculation of the Shearer Advancing Path

Cutting Path Planning Optimization Algorithm

Results and Discussion

Conclusions