Research on charge location method of main fracture source in coal and rock failure

Existing coal-rock charge induction monitoring technology relies solely on signal time-series characteristics for disaster early warning, which suffers from the shortcoming of insufficient spatial positioning capability for disaster-prone areas, making it difficult to deploy prevention and control measures accurately. To address the problems of the lack of a theoretical model for charge positioning of the main fracture source in coal-rock failure and the absence of verification experiments for positioning methods, and to achieve the technological leap from “judging the possibility of disaster occurrence” to “spatial positioning of disaster-prone areas”, a new path is provided for the precise prevention and control of dynamic disasters in intelligent mines. This study systematically studies the charge positioning method for the main fracture source in coal-rock failure, analyzes the charge induction monitoring mechanism of coal-rock failure, and clarifies the charge signal characteristics of the four stages of coal-rock mass deformation and failure (compaction, linear elasticity, accelerated inelastic deformation, and instability failure). The core mechanisms of charge generation are revealed, including the piezoelectric effect, crack tip discharge, fault plane friction, and ejection of charged coal fragments. A laboratory charge induction monitoring system for coal-rock loading (including an industrial control computer, high-speed camera, and other components) and a field portable coal-rock charge induction monitoring device (capable of accessing 4 channels of sensors simultaneously and displaying data in real time) are developed. Based on the principles of electrostatic shielding and electric field intensity superposition, a theoretical model for charge positioning of the main fracture source in coal-rock failure is established, and the relationship between the induced charge quantity Q, the charge source q, and the sensor distance r is established (Q is proportional to q and inversely proportional to r). Experiments on the detection distance of charge sensors (using a charged rubber rod to simulate the charge source, with test points set at equal intervals along the sensor axis) and verification experiments of the positioning method (setting 4 sensor measuring points and 3 point charge source points, collecting 4 000 groups of induced charge data, solving distances via Excel, and calculating coordinates by simultaneous equations in MATLAB) are carried out. This study systematically explores the laws of charge generation and transmission during coal-rock failure, breaks through the limitations of traditional single-point low-frequency monitoring, and constructs a multi-sensor collaborative charge positioning technology system. The correlation between charge signals and the spatial position of fracture sources is quantified through theoretical modeling, filling the theoretical gap in charge positioning. With the help of two types of monitoring devices (laboratory and field), the effective detection distance of sensors and the rationality of the positioning model are verified respectively, forming a collaborative monitoring mode of “regional (microseismic) + local (charge)”. The effective detection distances of charge sensors for the laboratory coal-rock loading monitoring system and the portable monitoring device are 2 m and 4 m, respectively. The difference in the induced charge energy coefficient K solved by the two devices at each test point is small (for the laboratory system, the deviation of K values is ≤0.000 137 except for test point 1^#; for the portable device, the deviation of K values is ≤0.000 400), verifying the correctness and rationality of the positioning theoretical model. In the positioning experiments of 3 point charge source points, the overall positioning accuracy of 12 000 groups of spatial coordinates and source points reaches 80.3% (average accuracy of point 1^#: 76.3%, point 2^#: 84.3%, point 3^#: 80.3%), and the positioning accuracy is within a reasonable range.