CN-122014354-A - Deep mine hidden water hazard dangerous source detection robot and working method thereof

Abstract

The invention relates to the field of mine disaster prevention and control, and particularly discloses a deep mine hidden water hazard dangerous source detection robot and a working method thereof. The robot body structure integrates a high-precision geophysical sensor, a water quality analyzer, a microseism monitor and an AI data processing unit, the travelling mechanism adopts a crawler and wheel type composite design and adapts to the topography of a complex bottom plate, the detection module realizes the omnibearing analysis from a macroscopic geological structure to microscopic pore water flow through a multi-scale data fusion technology, and the intelligent control module generates water damage risk early warning in real time based on a deep learning algorithm. The robot automatically navigates to a target area, performs a detection task, and transmits data to a ground monitoring center through a wireless network. The invention solves the problems of limited detection range and poor real-time property in the prior art, and obviously improves the water damage prevention and control capability of the deep mine.

Inventors

• LI BO
• CHE LULU
• WU QIANG
• ZHANG XIN
• Ren dongxing
• MENG HAILUN
• PENG TAO
• He Bomin

Assignees

• 贵州大学

Dates

Publication Date

20260512

Application Date

20260408

Claims (8)

1. 1. The robot for detecting the hidden water hazard dangerous source of the deep mine is characterized by comprising a robot body, a multi-mode detection module, an intelligent control module, an autonomous traveling mechanism, an energy system and a communication module, wherein the robot body comprises a pressure-resistant explosion-proof shell, and the inside of the robot body is divided into a detection cabin, a control cabin and an energy cabin.
2. 2. The deep mine hidden water hazard dangerous source detection robot according to claim 1, wherein the multi-mode detection module is integrated with a high-resolution resistivity imaging instrument, a microseismic sensor array, a laser-induced breakdown spectroscopy LIBS, a multi-parameter water quality sensor, a pore water pressure sensor and a three-dimensional sonar imaging unit, wherein the laser-induced breakdown spectroscopy LIBS is integrated in a detection cabin, sample spectra are collected through a sapphire glass optical window at the front end of the detection cabin, the robot further comprises a telescopic mechanical arm arranged at the outer side of the front end of the detection cabin, the pore water pressure sensor is embedded into the tail end of the mechanical arm of the robot and used for directly measuring the pore water pressure of a rock stratum, and the three-dimensional sonar imaging unit is arranged at the top of the detection cabin and used for constructing a three-dimensional structural model of a bottom plate stratum.
3. 3. The deep mine hidden water hazard source detection robot of claim 1, wherein the intelligent control module is internally provided with an AI processor for real-time data fusion and risk modeling.
4. 4. The robot for detecting hidden water hazard dangerous sources in deep mines according to claim 1, wherein the autonomous traveling mechanism adopts a crawler and multi-degree-of-freedom wheel set composite structure and is provided with a terrain self-adaptive algorithm.
5. 5. The robot for detecting hidden water hazard dangerous sources in deep mines according to claim 1, wherein the autonomous traveling mechanism further comprises a terrain identification camera, a laser radar and a hydraulic lifting chassis, wherein the terrain identification camera and the laser radar are used for generating traveling paths in real time, and the hydraulic lifting chassis adjusts a ground clearance to adapt to a concave-convex bottom plate.
6. 6. The deep mine hidden water hazard source detection robot and the working method thereof according to claim 1, wherein the energy source system comprises a high-density lithium battery and a wireless charging interface.
7. 7. The deep mine hidden water hazard source detection robot of claim 1, wherein the communication module supports 5G/fiber hybrid transmission for real-time interaction with a ground monitoring center.
8. 8. A working method of a robot for detecting hidden water hazard dangerous sources of a deep mine, which is characterized by comprising the following specific steps of: S1, after a robot receives a detection task, automatically navigating to a target area based on a preset map and a real-time positioning system RTK; S2, starting a multi-mode detection module, and synchronously collecting resistivity, micro seismic waves, water quality and pore water pressure data; s3, carrying out data fusion by using an AI processor, generating a water damage risk probability map and marking potential hazard sources; And S4, transmitting the early warning information and the three-dimensional geological model to a monitoring center, and triggering an emergency response mechanism.

Description

Deep mine hidden water hazard dangerous source detection robot and working method thereof Technical Field The invention relates to the technical field of mine disaster prevention and control, in particular to a deep mine hidden water hazard dangerous source detection robot and a working method thereof. Background The water damage of the bottom plate of the deep mine is one of the core risks threatening the safe production of the mine. As mineral resource exploitation depth extends below 800 meters, complex hydrogeological conditions cause frequent water bursting accidents of the bottom plate, and about 65% of water bursting accidents of the Chinese coal mine are related to pressure-bearing water of the bottom plate according to statistics. The water damage has the characteristics of strong bursting property and high destructive power, on one hand, the deep rock stratum is subjected to the coupling effect of high ground stress and high osmotic pressure, tiny cracks can be evolved into a through water guide channel within a plurality of hours, the instant water inflow exceeding 1000m 3/h is caused to be a disastrous accident, on the other hand, the dynamic interaction between the hidden aquifer and the mining destruction area makes the water damage precursor characteristics difficult to capture, and the traditional prevention and treatment means such as advanced drilling, grouting reinforcement and the like have serious hysteresis. More seriously, the deep mine often faces multiple water damage coupling threats including karst water, old goaf ponding, fault water guiding and the like, the disaster causing mechanism of the deep mine relates to multidisciplinary intersection of geological structures, rock mass mechanics, seepage dynamics and the like, and the risk is difficult to comprehensively evaluate by the existing single monitoring means. According to industry reports, the direct economic loss caused by the water damage of the bottom plate in 2018-2023 is 120 hundred million yuan, and the serious casualties are caused, so that the defects of the prior art system in the prevention and control of the deep water damage are highlighted. The current stage of the bottom plate water hazard detection technology mainly relies on manual drilling sampling and off-line geophysical exploration. The method has the advantages that local hydrologic parameters are obtained through drilling holes with the interval of 50-100m, but the method has two major defects that single-hole data only reflect information within the range of 2-3m in diameter, large-scale seepage field abnormality is difficult to capture, and the drilling period is as long as 3-5 days, so that dynamic monitoring cannot be realized. The latter can be used for regional scanning by resistivity method and transient electromagnetic method, but the spatial resolution is limited by the detection precision of 10-20m, and the static aquifer and the active water guide channel cannot be distinguished. More importantly, the existing method has the common problem of data island that geophysical data, water quality parameters and stress strain monitoring data belong to independent systems, and a multisource information fusion mechanism is lacked, so that the false alarm rate of an early warning model is as high as 30% -40%. In recent years, although research attempts have been made to introduce a robot technology (such as the water quality detection robot described in CN 101234567 a), only a single sensor is provided, and the geological structure data cannot be obtained synchronously, and the autonomous obstacle avoidance and intelligent decision making capability are not provided. For example, the patent robot needs to rely on a preset track to move, cannot adapt to the relief topography of the bottom plate, and the data analysis completely relies on manual interpretation, so that the response delay exceeds 2 hours. Therefore, development of an intelligent detection device integrating multi-scale detection, real-time data fusion and autonomous operation is needed to break through the technical bottleneck of prevention and control of water damage of deep mines. Disclosure of Invention Aiming at the problems in the prior art, the invention provides a robot for detecting hidden water hazard dangerous sources in a deep mine and a working method thereof, which effectively solve the problems of poor real-time performance, low spatial resolution and insufficient data utilization rate in the prior art and effectively improve the identification precision of the hidden water hazard sources. In order to achieve the above purpose, the invention provides a deep mine hidden water hazard dangerous source detection robot and a working method thereof, comprising the following steps: robot body, multimode detection module, intelligent control module, independently advance mechanism, energy system and communication module, the robot body includes withstand voltage explosion-proof housi