Construction of multi-factor identification model for real-time monitoring and early warning of mine water inrush

International Journal of Mining Science and Technology

Yajun Sun¹  Chenghang Zhang²  Zhongwen Duan³  Xin Wang³  Zhimin Xu³  Jieming Zheng³ 

[1] Corresponding author.;General Prospecting Institute China National Administration of Coal Geology, Beijing 100039, China;School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China;

关键词: Mine water inrush;    Automatic monitoring;    Real-time warning;    Recognition model;   

DOI  :  

来源: DOAJ

【 摘 要 】

As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning, the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years. Due to the many factors affecting water inrush and the complicated water inrush mechanism, many factors close to water inrush may have precursory abnormal changes. At present, the existing monitoring and early warning system mainly uses a few monitoring indicators such as groundwater level, water influx, and temperature, and performs water inrush early warning through the abnormal change of a single factor. However, there are relatively few multi-factor comprehensive early warning identification models. Based on the analysis of the abnormal changes of precursor factors in multiple water inrush cases, 11 measurable and effective indicators including groundwater flow field, hydrochemical field and temperature field are proposed. Finally, taking Hengyuan coal mine as an example, 6 indicators with long-term monitoring data sequences were selected to establish a single-index hierarchical early-warning recognition model, a multi-factor linear recognition model, and a comprehensive intelligent early-warning recognition model. The results show that the correct rate of early warning can reach 95.2%.

【 授权许可】

Unknown