Research and Application of A Comprehensive Monitoring Platform for Coal Conveyor Gallery Based on Multi-Dimensional Information Fusion

In response to the demand for constructing an intelligent coal conveyor gallery that features virtual digitization, comprehensive perception, intelligent control, and full state monitoring, covering the coal conveyor gallery production and operation activities and elements of a specific power plant, this paper presents the development of a comprehensive monitoring platform for this coal conveyor gallery based on multi-dimensional information fusion. This platform constructs a multi-layer perception sensor system, utilizing rail-mounted intelligent inspection robots, belt monitoring equipment, coal flow monitoring instruments, environmental monitoring instruments, fixed-point cameras, and other devices attached the coal conveyor gallery. It encompasses functions such as accessing multi-source heterogeneous data, load balancing, intelligent analysis, and decision fusion based on multiple data models. These functions were designed through an analysis of key technologies such as multi-source transmission, intelligent scheduling engine, fault diagnosis, and augmented reality (AR), while leveraging industrial digital twin and multi-dimensional data fusion technologies. Subsequent on-site applications demonstrated that the platform facilitated unmanned patrol inspection, intelligent alarming, and visual management at the coal conveyor gallery site, thereby improving the operational safety and enhancing the efficiency of operation and maintenance. During this implementation period, the number of patrol inspection personnel was reduced by five, and the average number of inspections per month was reduced by 20. Achieving the goal of reducing personnel and increasing efficiency, as well as elevating the level of operation management, the proposed platform offers an effective solution for the intelligent and full-state comprehensive monitoring of coal conveyor galleries.