Research on Mine Disaster Risk Monitoring Based on Dual-Driven Fiber Optic Sensing and Data Retrieval

With the depletion of energy sources at shallow, and the increasing intensity and depth of mining. Increasing difficulty of mining and disaster risk. Especially in the complex geological environment for mining, once the risk is not properly monitored, they often directly induce all kinds of mining disasters. Being limited to the existence of existing mine disaster monitoring technology has a limited monitoring range, insufficient deformation sensitivity, a high degree of data discretization and other problems. It is often difficult to accurately and in real-time monitor disaster risks and their causative effects throughout the mining process. Aiming at the above problems, this paper proposes a dual-driven mining disaster risk monitoring method based on fiber optic sensing and data retrieval. In other words, it is based on the actual monitoring needs of disaster risks in mining projects. First, the fiber optic sensing technology is used to construct a joint vertical and horizontal fiber optic neural perception network. Accordingly, real-time sensing of disaster risks in mine engineering is realized; Second, crawler techniques were used to obtain information about the data in tweets about concrete mining disasters in microblogs. The visual analysis of disaster accidents using data retrieval techniques. Providing scientific references for decision-making on the dynamic regulation of mine disaster risks. Integration of the above dual drivers, achieving precise oversight and dependable forecasting of all kinds of potential mine disaster hazards.