Study on Dust Migration Law and Spray Dedusting Technology in Parallel Double Belt Transportation

To effectively solve the problem of dust pollution caused by the parallel double-belt transportation of coal in a coal preparation plant, taking the Huangyuchuan coal preparation plant as an example, a numerical model of the air flow-dust distribution was established by means of simulation. The flow lines between the strips of tape and the tail of the tape machine will gather, and there will be backflow on the right side of the 3001 tape and left side of the 3002 tape. Under the action of wind current, most of the dust particles larger than 10 μm are distributed in the range of 0~5 m on both sides of the tape; dust particles smaller than 10 μm spread to the entire preparation workshop. Combined with field test verification, dust pollution is mainly concentrated at the guide trough, the feed inlet, the rear of the machine, and the joint of the belt corridor. Based on this, a targeted spray dust reduction treatment plan is proposed. By measuring the dust concentration before and after the treatment of dust-polluted areas, it is proven that the dust reduction efficiency of this plan can reach more than 90%.

Computer Big Data Technology in Internet Network Communication Video Monitoring of Coal Preparation Plant

The paper uses the control technology of computer big data and PLC, fieldbus communication technology and video monitoring technology to research, design and develop the monitoring system of the coal preparation plant’s production process. In this plan, the coal preparation plant’s video monitoring system, production centralized control system and other production support systems are fully integrated through network technology, to achieve the purpose of improving its safety guarantee function. The system improves the level of visual management, realizes unattended operation, and reduces potential safety hazards.

Digital Twin Based on 3D Visualization and Computer Image Recognition Technology in Coal Preparation Plant

The digital twin coal preparation plant is a potentially effective way to realize the intelligent interconnection and interactive integration of the manufacturing physical world and the information world. Aiming at the difficulty in predicting and maintaining the state of the shearer in a harsh working environment, combined with the high-fidelity behaviour simulation characteristics of the digital twin and the powerful data mining capabilities of deep learning, a coal shearer health prediction driven by the integration of the digital twin and deep learning is proposed. Method. The article builds an information management and integration platform composed of a real-time database and a comprehensive information platform, and realizes the unified management of data integration and application systems.

Computer Intelligent Cloud Server Platform of Coal Preparation Plant Based on Big Data Cloud Technology

This article combines the actual situation of the coal preparation plant and uses big data cloud technology to carry out detailed system requirements analysis and monitoring platform design. The entire design includes server framework design, database design, cloud service deployment and mobile client prototype design. According to the on-site working conditions of electromechanical equipment, the article uses ER model and 3NF method to abstract it and establishes a MySQL real-time database of equipment operating status. Finally, the ECS cloud server is used to complete the deployment, and the JSP technology is used to realize the display of the system’s man-machine interface, as well as remote monitoring services for equipment monitoring, information management, and user management. Practical application shows that the system can improve the comprehensive automation and information level of the enterprise, reduce the operating cost of the enterprise, and improve the production efficiency of the enterprise.