基于机器视觉的储煤仓群智能监控系统OA

In order to improve the production management efficiency and information management level of the coal bunker cluster,and reduce manual operation and maintenance costs,based on machine vision and YOLOv5 object detection algorithm,this article designs the intelligent monitoring system for the coal bunker cluster and introduces system architecture design scheme and main task objectives function implementation.Based on the task objectives of safety prevention and efficiency improvement,the article analyzes the algorithm framework of system's intelligent detection functions for personnel location,personnel behavior,personal protective equipment wearing,production identification signs,fireworks,water accumulation,scraper machine faults,etc.The results indicate that monitoring system improves the safety and efficiency of production activities in the coal bunker cluster,enhances the level of information management in the production site,and promotes the intelligence level of the industrial structure.