Shen Yan, Li Yu, Li Zengping
Art School, Northwest University, Xi'an, China.
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China.
Front Neurorobot. 2022 Jun 23;16:865146. doi: 10.3389/fnbot.2022.865146. eCollection 2022.
This study is developed to explore the role of intelligent inspection robot in the protection and utilization of coal mine industrial heritage. Based on the actual situation of the coal mine, the underground planning protection scope is analyzed. Aiming at the problems of imperfect fire early warning detection technology, management mechanism, high labor cost and low work efficiency in underground protection, the intelligent inspection robot technology is proposed to realize safety tour, underground intelligent management and early warning of underground security, fire protection facilities construction, and intelligent early warning system. This paper analyzes the key technology of intelligent inspection robot in coal mine industrial heritage protection, introduces the composition, structure and implementation method, and proposes its construction path and method. Besides, the path planning, motion obstacle avoidance and sensing detection of the robot are studied. The research shows that the intelligent inspection robot has comprehensive functions and stable performance, and can realize the scientific, intelligent and refined management of industrial heritage protection, which provides a guiding basis for the intelligent protection of coal mine industrial heritage.
本研究旨在探讨智能巡检机器人在煤矿工业遗产保护与利用中的作用。基于煤矿实际情况,分析了井下规划保护范围。针对井下保护中火灾预警检测技术不完善、管理机制不健全、劳动成本高和工作效率低等问题,提出采用智能巡检机器人技术实现安全巡检、井下智能管理以及井下安全、消防设施建设和智能预警系统的预警。本文分析了智能巡检机器人在煤矿工业遗产保护中的关键技术,介绍了其组成、结构及实现方法,并提出了其建设路径和方法。此外,还研究了机器人的路径规划、运动避障和传感检测。研究表明,智能巡检机器人功能全面、性能稳定,能够实现工业遗产保护的科学化、智能化和精细化管理,为煤矿工业遗产的智能化保护提供了指导依据。