Water inrush sources monitoring and identification based on mine IoT. (3rd October 2018)

• Record Type: Journal Article
• Authors: Yan, Zhigang; Han, Jiazheng; Yu, Jieqing; Yang, Yuanxuan
• Other Names: Manogaran Gunasekaran guestEditor.; Chilamkurti Naveen guestEditor.; Hsu Ching‐Hsien guestEditor.; Vijayakumar V. guestEditor.
• Is Part Of: Concurrency and computation. Volume 31:Number 10(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-10-03
• Subjects: identification of water source -- IOT -- SVM -- water inrush in mine; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4843
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Internet of things (IoT) is applied to water inrush source monitoring network for overcoming complexity and uncertainty of coal mines in monitoring. This study starts from the idea of sensory mines and the architecture of IoT, and describes key techniques in IoT‐based mine water inrush source sensing. In the sensing layer, networked and intelligent sensors are employed for constructing the distributed monitoring system; in the network service layer, data mining, 3D geoscience simulation system and cloud computing are combined for establishing the cloud service platform so as to comprehensively analyze water inrush sources; in the application layer, a novel maximum/minimum‐margin‐based hierarchical‐SVM model for the identification of water‐inrush sources is proposed. Test results demonstrate that, owing to the application of mine IoT, both information collection efficiency and processing capability of water‐inrush source monitoring can be effectively enhanced, and the established water source identification system exhibits low false alarm rate and mis‐detection ratio, thereby significantly improving the prediction reliability.