Research on intelligent control system for scraper conveyor in coal mining working face - FAN Baodong; MA Kaide; CUI Weixiu; LI Zhiyuan (Gong-kuang zidonghua)
Scraper conveyor is the core equipment for coal transportation in underground mining, and its level of intelligence directly impacts the overall automation in the working face. Analysis indicates that current intelligent technology of scraper conveyor still faces several issues: inadequate management of operating condition sensing data, lack of top-level control in data interaction and multi-machine collaborative control, insufficient equipment maintenance and care, and insufficient application of intelligent technologies. Based on the advantages of the Kuanghong operating system, such as unified system architecture, standards, and protocols, an intelligent control system for scraper conveyor in coal mining working faces was developed. The system architecture was introduced, focusing on two key technologies: operating condition sensing and adaptive control for scraper conveyor. Taking dumbbell state monitoring and chain break fault monitoring as examples, the implementation methods of operating condition sensing technology for scraper conveyor were detailed. By analyzing the current data of the scraper conveyor’s driving motor and integrating collected data such as cutting height, cutting depth, travel speed, and position of the coal shearer, a formula for calculating the coal transportation volume of the scraper conveyor was derived. This led to the design of an intelligent speed control strategy for the scraper conveyor based on load conditions. Additionally, the relationship between the scraper conveyor's chain and tension was analyzed. By calculating the chain elongation and comparing it to a set value, the extension (or retraction) of hydraulic cylinders was controlled to achieve automatic chain tension control. Industrial tests of the intelligent control system for scraper conveyor based on the Kuanghong operating system were conducted at coal mine sites. The results showed that the system could collect and analyze key parameters such as the operating status, fault information, and load of the scraper conveyor in real time. It demonstrated high data accuracy, strong stability, and high precision in fault diagnosis. Furthermore, the system achieved interconnection and collaboration between the scraper conveyor and other equipment such as coal shearer and hydraulic supports, with a data transmission delay of only 5 to 10 ms.