Industrial Internet of Things-enabled monitoring and maintenance mechanism for fully mechanized mining equipment. (October 2022)

• Record Type: Journal Article
• Authors: Zhang, Geng; Chen, Chun-Hsien; Cao, Xiangang; Zhong, Ray Y.; Duan, Xinyu; Li, Pengfei
• Is Part Of: Advanced engineering informatics. Volume 54(2022)
• Publication Date: 2022-10
• Subjects: Industrial Internet of Things -- Fully mechanized mining equipment -- Smart mine -- Monitoring and maintenance; Computer-aided engineering -- Periodicals; Engineering -- Data processing -- Periodicals; 620.00285
• DOI: 10.1016/j.aei.2022.101782
• Languages: English
• ISSNs: 1474-0346

Abstract

Highlights: IIoT-based mechanism is proposed for mining equipment monitoring and maintenance. A novel description model is constructed to perform real-time monitoring. A knowledge-enabled method is designed to execute efficient maintenance. The effectiveness of the proposed framework is illustrated by a case study. Abstract: Under the support of advanced information technologies, smart mine is proposed to meet the demands of green, safe, and automated coal mining. Due to the potential advantages in promoting the automation of coal mining, smart mine has attracted wide attention from industry and academia. Current studies related to the smart mine mainly focus on the macro framework and up-level architecture, and rarely investigate the improvement of basic mining equipment to satisfy the raised automation requirements in smart mine. However, the accurate monitoring and timely maintenance of mining equipment have become the prerequisite issue for constructing the smart mine and efficient management of coal mining operations. To address the above issue, this paper proposes an Industrial Internet of Things (IIoT)-enabled mechanism to achieve the monitoring and maintenance of fully mechanized mining equipment (FMME) and promote the automation of smart mine. A smart sensing module of FMME is designed to upgrade traditional FMME and acquire meaningful real-time information from FMME. Then, a description model is constructed to implement the real-time monitoring of FMME. An event-driven and knowledge-enabled mechanism is designed to perform the efficient maintenance of FMME based on the acquired real-time information. A case study is further employed to verify the effectiveness of the proposed IIoT-enabled monitoring and maintenance mechanism for FMME, which can then promote sustainable and automated coal mining.