Abstract
The boom-type roadheader is the foremost mining equipment in coal mines. At present, the automatic cutting technology is still immature for adjusting cutting speed automatically in accordance with rock strength, resulting in energy dissipation. In this study, we put forward a method with respect to detecting the geological strength index of coal seam profile through visual inspection, as well as characterize the geological strength index and control the cutting head for adjusting speed automatically based on inspecting fracture features on coal rock’s surface, aiming at achieving energy conservation control of boom-type roadheader. The image processing algorithm is adopted for detecting joint characteristics of palisades fracture, and a quantitative model of the geological strength index is established. The fractal dimension is used to obtain the distribution of geological strength indicators of a coal seam, and the heading machine’s cutting head is controlled for adjusting speed automatically. A vision control platform of boom-type roadheader is built in the laboratory to perform ground simulation experiments. According to experimental results, the difference between the geological strength index of the coal seam detected through visual inspection and the set value in the geological strength index chart is up to 3.5%, and the results are basically consistent, so the quantification of geological strength index can be performed rapidly and effectively. The average energy consumption of boom-type roadheader decreases by 5.4% after adopting self-adaptation control, realizing energy conservation and consumption reduction as well as intelligent control of coal mine machinery.
Funder
National Natural Science Founds of China
Shaanxi Coal Joint Fund
Subject
Geology,Geotechnical Engineering and Engineering Geology
Reference32 articles.
1. Research and engineering progress of intelligent coal mine technical system in early stages;Wang;Coal Sci. Technol.,2020
2. Development direction of intelligent coal mine and intelligent mining technology;Wang;Coal Sci. Technol.,2019
3. Key technology and engineering practice of intelligent rapid heading in coal mine;Wang;J. China Coal Soc.,2021
4. Numerical characterization for rock mass integrating GSI/Hoek-Brown system and synthetic rock mass method;Zhang;J. Struct. Geol.,2019
5. Improving the GSI Hoek-Brown criterion relationships;Bertuzzi;Int. J. Rock. Mech. Min.,2016
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