| Belt conveyor is the main equipment of coal conveying system in mine,and its driving motor usually has enough power margin.However,in the actual production process,the underground belt conveyor mostly works under light load or no load,and it is difficult to reach the full load state.The high speed operation under light or no load condition not only intensifies the mechanical wear of the belt conveyor’s rotating parts and transport belt,but also significantly increases the operation energy consumption.Therefore,detecting the coal flow and automatically adjusting the running speed of the belt conveyor according to the coal flow is an effective way to realize the energy saving and consumption reduction of the mine coal conveying system.Aiming at the existing problems,this paper takes the underground coal conveying system of Yaoqiao Coal Mine as the background,and proposes an energy-saving optimization control system of mine belt conveyor based on laser-assisted vision technology.The main research work is as follows:According to the international standard ISO5048,the resistance analysis and power calculation of the belt conveyor are carried out.It is determined that the coal flow and the belt speed are the main factors affecting the power consumption of the belt conveyor.Based on this,the overall control scheme for energy saving and optimal operation of the belt conveyor in Yaoqiao Coal Mine is constructed.The intelligent analysis of underground coal mine image is affected by more dust and fog and poor illumination condition.In order to accurately obtain coal flow information in underground coal mine images,a fast multi-scale Retinex coal flow image enhancement algorithm based on illumination correction was proposed.By illuminating the dark and high light areas in the coal flow image,more detailed information can be obtained.The three times fast mean filter is used to replace Gaussian filter to estimate the incident component,which can effectively improve the image quality of underground coal flow and improve the running speed of the algorithm.A method of coal flow detection of belt conveyor based on laser-assisted vision technology is proposed to transform the actual task of coal flow detection into image processing work.The laser fringes in the enhanced coal flow image are segmented,and an algorithm for extracting laser fringes center is proposed,which integrates shape and gray level information.The linear interpolation method is used to repair the laser stripe center quickly.According to the area of the closed envelope curve formed by the laser stripe center,the coal flow of the belt conveyor is calculated.The frequency conversion speed control system of belt conveyor with speed control device as the core is designed,and the energy-saving optimization model of belt conveyor is constructed.Through the design of fuzzy controller and PLC control program,the running speed of belt conveyor can be adjusted automatically according to the size of coal flow.Finally,based on C# programming language and My SQL database technology,the software of ground control management platform of mine coal conveying system is developed to realize visual monitoring and scientific management of mine coal conveying system.The system has been put into practical operation in Yaoqiao Coal Mine in June 2020,and has achieved good energy-saving control effect.The paper has 65 figures,19 tables,and 77 references. |
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