| In recent years,with the continuous cost reduction and efficiency increase of'coal enterprises,it is imperative to reduce staff and increase efficiency in the coal industry.In order to promote the construction of Shangwan Intelligent Coal Preparation Plant,we actively explore a new management model of the Coal Preparation industry to reduce costs and increase efficiency,with the development of intelligent technology,this paper analyses the current situation and existing problems of Shangwan Coal Preparation Plant.According to the demand of intelligent coal preparation plant,the overall structure of intelligent coal preparation plant is designed.Emphasis is laid on the design of the intellectualized transformation scheme.On the basis of the existing intelligent transformation of Shangwan Coal Preparation Plant,the structure of the intelligent coal preparation plant is improved through coal particle size identification,personnel positioning,digital power distribution and on-line monitoring of equipment.By comparing the detection methods of super-granularity recognition of coal blocks,the recognition system of large coal blocks based on video image processing is determined.Edge detection algorithm is used to detect the lateral and vertical edges of coal blocks,and finally the image recognition of coal blocks is realized.Using gray'algorithm,coal and gangue have different gray levels,so as to achieve the recognition of coal and gangue.rThe structure of super-granularity recognition system and the pre-selection system of large Gangue Based on super-granularity recognition technology are described.Finally,the function of coal block super-granularity recognition system is tested.Testing in different time and the change of raw coal particle size can effectively identify and alarm the particle size of'large coal,and record and analyze the particle size curve.Based on the analysis of personnel positioning characteristics in coal preparation plant,the intelligent lighting personnel positioning system based on ZigBee is determined.By using TOA and TDOA algorithm,the personnel positioning and lighting control functions are realized through the structure and function design of the intelligent lighting personnel positioning system.The system function test and the personnel positioning system of Shangwan Coal Preparation Plant are carried out.Shangwan Intelligent Coal the personnel positioning and lighting control functions achieve the location of coal preparation plant personnel,historical track,intelligent lighting combined with the location of coal preparation plant personnel.According to the normal power cut and send process of Shangwan Coal Preparation Plant,the overall structure of the digital distribution system of the Coal Preparation Plant is designed,the basic model of each level of the system is built,and the business attributes are configured.According to the nomal process of power cut and send,the outage operation is tested under different scenarios.Testing under different conditions,the system can accurately deliver power outage tasks.Through the design of on-line monitoring system structure,data flow and software architecture of Shangwan Coal Preparation Plant,the location of monitoring points and the limit of alarm value are configurated,and the functions of vibration and temperature monitoring of equipment under different conditions are emphatically tested.The test data can effectively reflect the temperature and vibration data of each monitoring point.The results show that:the recognition system of large coal blocks can monitor the coal particle size in real time,detect and warn in time,and control the coal product particle size effectively?The personnel positioning system can achieve the accurate positioning of personnel well.The digital power distribution system can effectively improve the efficiency and accuracy of power outage tasks under different conditions,and reduce the work intensity of personnel.he online monitoring system can be very effective,Good realization of equipment condition monitoring,early warning. |
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