Coal mine working face mining-induced stress monitoring system and construction method thereof

Abstract

The invention belongs to the technical field of coal mine safety monitoring, and relates to a coal mine working face mining-induced stress monitoring system and a construction method thereof.The coal mine working face mining-induced stress monitoring system comprises a plurality of wireless sensing nodes which are arranged in a coal body drill hole in an equal difference mode in the working face trend, and each node comprises a three-dimensional stress sensor, a data acquisition module, a wireless communication module and a power module; the drilling depth extends to a mining influence area according to an equal difference sequence, and the distance between every two adjacent nodes is smaller than or equal to 10 m; the pressure monitoring substation is connected with each wireless sensing node through a wireless network, and a modulation demodulator and a voltage-stabilized power supply are arranged in the pressure monitoring substation to realize signal conversion and power supply; and the system host communicates with the pressure monitoring substations through a wired network, configures a data processing unit, a digital twin model and a human-computer interaction interface, dynamically analyzes stress distribution and generates an early warning signal. According to the method, the full-depth coverage monitoring of the mining influence area is realized for the first time through the equal-difference drilling layout (20m, 22m, 24m... 50m) and the grading of the depth monitoring points.

Description

Technical Field

[0001] The present invention belongs to the technical field of coal mine safety monitoring, and relates to a mining stress monitoring system for a coal mining face and a construction method thereof. Background Art

[0002] During the coal mining process, dynamic monitoring of mining stress is the core technical means for preventing major accidents such as rock bursts and gas outbursts. The existing technologies mainly have the following defects:

[0003] 1. Problem of sensor coupling failure

[0004] Traditional borehole stress gauges use glue or resin to consolidate sensors, but in soft coal seams, the sensors are easily decoupled due to borehole collapse. For example, the consolidation failure rate of the liquid-filled expansion pillow type stress gauge in the coal body fracture area is as high as 40%, and it is difficult to recover. The borehole collapse rate in complex coal seams exceeds 60%, resulting in the sensors being unable to reach the designed depth.

[0005] 2. Insufficient reliability of data transmission

[0006] Existing monitoring systems mostly rely on a single communication mode, and the packet loss rate exceeds 30% in an environment with long distances and multiple obstacles. Some technologies also use wired transmission, but the advancement of the working face causes frequent cable breaks, increasing the maintenance cost by more than 50%.

[0007] 3. Weak dynamic warning ability

[0008] Although some existing technologies have achieved multi-point monitoring, data processing relies on static threshold alarms and cannot identify dynamic risk indicators such as stress gradient change rates. Research shows that the warning response time of traditional methods for rock bursts exceeds 60 seconds, missing the best disposal window.

[0009] 4. Poor adaptability to complex coal seams

[0010] Existing technologies use rigid protective sleeves to protect sensors, but in areas with developed faults, they cannot adapt to the deformation of the coal body, resulting in a measurement error exceeding 0.5 MPa. The coupling success rate of the hard rock monitoring scheme in soft coal seams is less than 50%.

[0011] 5. Insufficient system maintainability

[0012] Existing systems lack remote control functions, and equipment failures need to be handled manually underground, with an average repair time exceeding 8 hours. In addition, traditional solutions are not integrated with a cloud platform and cannot achieve collaborative analysis of data from multiple mines.

[0013] In response to the above-mentioned technical bottlenecks, the present invention optimizes the spatial coverage of sensors through equidistant drilling layout, improves the measurement accuracy of soft coal seams through hydraulic coupling technology, enhances transmission reliability through dual-mode communication, and innovates the digital twin model to achieve dynamic risk prediction, forming a set of high-precision and high-robustness monitoring solutions. Summary of the invention

[0014] In view of this, an object of the present invention is to provide a coal mine working face mining stress monitoring system and a construction method thereof to solve the technical problems raised in the background technology.

[0015] In order to achieve the above object, the present invention provides the following technical solutions:

[0016] A coal mine working face mining stress monitoring system, comprising:

[0017] Multiple wireless sensor nodes are arranged in the coal borehole along the working face in equal intervals. Each node includes a three-axis stress sensor, a data acquisition module, a wireless communication module and a power module. The borehole depth extends to the mining impact zone in an equal interval sequence, and the distance between adjacent nodes is ≤10m.

[0018] The pressure monitoring substation connects each wireless sensor node through a wireless network, and has a built-in modem and voltage-stabilized power supply to achieve signal conversion and power supply;

[0019] The system host communicates with the pressure monitoring substation through a wired network, is equipped with a data processing unit, a digital twin model and a human-computer interaction interface, dynamically analyzes the stress distribution and generates early warning signals.

[0020] Furthermore, it also includes:

[0021] The cloud platform receives system host data through wireless networks, supports remote control of device restart, adjustment of monitoring frequency and multi-terminal data synchronization.

[0022] Furthermore, the cloud platform integrates a GMS monitoring module, supports map location query, stress change curve analysis and automatic generation of inspection logs, and triggers warnings synchronously through SMS, APP push and sound and light alarms when monitoring data is abnormal.

[0023] Furthermore, the wireless communication module supports ZigBee and LoRa dual-mode transmission, and adopts ad hoc network communication when the node spacing is ≤100m. When it is out of range, it is relayed through the pressure monitoring substation and the transmission mode is dynamically switched based on the RSSI signal strength.

[0024] Furthermore, the drilling depth extends to the mining impact zone in an arithmetic sequence of L=20m, L+2m, L+4m.

[0025] Furthermore, the triaxial stress sensor is a hydraulic coupling type borehole stress gauge, which includes a stress induction probe, a guide rod, and a pressure trigger claw hook. The stress induction probe is arranged outside the guide rod, and the pressure trigger claw hook is arranged at the end of the guide rod.

[0026] A construction method for a mining stress monitoring system in a coal mine working face includes the following steps:

[0027] Step 1: Borehole construction

[0028] Use an open-close type hollow drill rod to drill in the gate roadway of the working face, form a borehole group according to an arithmetic sequence, with the inclination angle consistent with the coal seam strike. After drilling to the target depth, keep the drill rod position, send the triaxial stress sensor and the guide rod through the internal channel of the drill rod, and set a pressure trigger claw hook at the end of the guide rod. When the hydraulic pressure reaches 10 MPa, the pressure trigger claw hook unfolds and anchors the hole wall.

[0029] Step 2: Sensor consolidation

[0030] Inject quick-setting cement slurry through the feed pipe until the slurry flows out of the return pipe.

[0031] Wait for the slurry to solidify to form a monitoring point that is tightly coupled with the coal body.

[0032] Step 3: Data transmission verification

[0033] After the wireless sensor node is powered on, it forms a Mesh network with the pressure monitoring sub-station, and the pressure monitoring sub-station uploads the data to the system host through the CAN bus.

[0034] Furthermore, the system host transmits the data to the cloud platform through the wireless network.

[0035] Furthermore, the interval between adjacent boreholes is 10 m.

[0036] Furthermore, the digital twin model integrates geological structure data and real-time monitoring data, generates a three-dimensional dynamic stress cloud map through an improved Kalman filtering algorithm, and triggers an alarm when the stress gradient change rate ≥ 5 MPa / m lasts for 10 minutes.

[0037] The beneficial effects of the present invention are as follows:

[0038] 1. Innovative sensing network improves monitoring accuracy and reliability

[0039] This system realizes the full-depth coverage monitoring of the mining-influenced area for the first time through an arithmetic progression drilling layout (20m, 22m, 24m... 50m) combined with the classification of deep and shallow monitoring points. The hydraulic coupling type sensor (30MPa oil pressure trigger claw hook anchoring + quick-setting cement consolidation) has a coupling success rate > 95% in soft coal seams, and the measurement error ≤ 0.01MPa, solving the problem of sensor failure caused by borehole collapse. This design is especially suitable for high-risk areas such as fault zones.

[0040] 2. The intelligent analysis system strengthens the dynamic warning ability

[0041] Based on the digital twin model and the improved Kalman filter (integrating multi-source data such as support resistance and propulsion speed), the system can update the three-dimensional dynamic stress cloud map every 5 minutes and calculate the rock burst risk index. When the stress gradient change rate Δσ / Δx ≥ 5MPa / m, a three-level warning mechanism (yellow / orange / red) is triggered, and the response time < 30 seconds, which is 50% faster than the traditional threshold alarm.

[0042] 3. The multi-level collaborative architecture optimizes the operation and maintenance efficiency

[0043] The ZigBee / LoRa dual-mode communication (packet loss rate < 1%) and the Ethernet ring network / CAN bus redundant design ensure the stability of data transmission in complex environments. The cloud platform (4G / NB-IoT access) supports remote parameter adjustment, GIS map overlay display, and automatic generation of inspection work orders, shortening the equipment maintenance time to 2 hours. The self-check module generates fault codes in real time and links with safety regulations to achieve closed-loop management of "monitoring - warning - disposal", reducing the overall operation and maintenance cost of the system.

[0044] Other advantages, objectives, and features of the present invention will be described to some extent in the subsequent specification, and to some extent, will be obvious to those skilled in the art based on the study of the following text, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following specification. Brief Description of the Drawings

[0045] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be described in detail preferably with reference to the accompanying drawings, where:

[0046] Figure 1 It is a schematic diagram of a mining stress monitoring system for a coal mining face in an embodiment.

[0047] Reference numerals: system host 1, wireless sensor node 2, three-way stress sensor 21, data acquisition module 22, wireless communication module 23, power supply module 24, pressure monitoring sub-station 3, modulator 31, regulated power supply 32, cloud platform 4, sound and light alarm 41. Detailed implementation manners

[0048] The following describes the implementation manners of the present invention through specific examples. Those skilled in the art can easily understand the other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the drawings provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0049] Among them, the drawings are only for illustrative purposes, showing only schematic diagrams, not physical diagrams, and should not be construed as a limitation to the present invention; in order to better illustrate the embodiments of the present invention, some components in the drawings will be omitted, enlarged or reduced, which does not represent the size of the actual product; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0050] In the drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc. indicating the orientation or position relationship, they are based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the position relationship in the drawings are only for illustrative purposes and should not be construed as a limitation to the present invention. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0051] Please refer to Figure 1 , which is a mining stress monitoring system for a coal mining face, including:

[0052] A plurality of wireless sensor nodes 2, which are arranged in the coal body boreholes at equal intervals along the strike of the working face. Each node includes a three-axis stress sensor 21, a data acquisition module 22, a wireless communication module 23 and a power supply module 24. The depth of the borehole extends to the mining-influenced area in an arithmetic sequence, and the distance between adjacent nodes is ≤10m;

[0053] A pressure monitoring sub-station 3, which is connected to each wireless sensor node through a wireless network, and is built-in with a modulator-demodulator 31 and a regulated power supply 32 to realize signal conversion and power supply;

[0054] A system host 1, which communicates with the pressure monitoring sub-station 3 through a wired network, and is configured with a data processing unit, a digital twin model and a human-computer interaction interface to dynamically analyze the stress distribution and generate warning signals.

[0055] Furthermore, it further includes:

[0056] A cloud platform 4, which receives the data of the system host through a wireless network and supports remote control of device restart, adjustment of monitoring frequency, and multi-terminal data synchronization.

[0057] Furthermore, the cloud platform 4 integrates a GMS monitoring module, supports map location query, stress change curve analysis, and automatic generation of inspection logs, and synchronously triggers an alarm through SMS, APP push, and a sound and light alarm 41 when the monitoring data is abnormal.

[0058] Furthermore, the wireless communication module 23 supports dual-mode transmission of ZigBee and LoRa. When the node spacing is ≤ 100m, self-organizing network communication is adopted. When it exceeds the range, it is relayed through a pressure monitoring sub-station 3, and the transmission mode is dynamically switched based on the RSSI signal strength.

[0059] Furthermore, the borehole depth extends to the mining-influenced area in an arithmetic sequence of L = 20m, L + 2m, L + 4m.

[0060] Furthermore, the triaxial stress sensor 21 is a hydraulic coupling type borehole stress gauge, which includes a stress induction probe, a guide rod, and a pressure trigger claw hook. The stress induction probe is arranged outside the guide rod, and the pressure trigger claw hook is arranged at the end of the guide rod.

[0061] Embodiment 1: Sensor Deployment and Data Transmission in Soft Coal Seams

[0062] Step 1: Borehole Construction

[0063] Use an open-close type hollow drill pipe (outer diameter 89mm) to drill in the working face gate roadway, form a borehole group in an arithmetic sequence (20m, 22m, 24m... 50m), with a borehole spacing of 10m and an inclination angle consistent with the coal seam strike;

[0064] After drilling to the target depth, keep the drill pipe in place and send a hydraulic coupling stress sensor through the internal channel.

[0065] Step 2: Sensor Consolidation

[0066] Start the hydraulic pump to inject 30MPa hydraulic oil into the sensor guide rod, and the trigger claw hook unfolds and anchors the hole wall;

[0067] Inject quick-setting cement slurry through the feed pipe (mix ratio: 40% sulfoaluminate cement, 5% nano-SiO2, 2% polycarboxylate water reducer), and maintain the grouting pressure at 2MPa until the slurry flows out of the return pipe;

[0068] Let it stand for 30 minutes until the slurry solidifies to form a monitoring point tightly coupled with the coal body.

[0069] Step 3: Data Transmission Verification

[0070] After the node is powered on, it automatically selects the ZigBee mode to form a Mesh network, and the measured RSSI signal strength > -80 dBm;

[0071] When the shearer advances within 50 m of the node, the system switches to the LoRa relay mode, and the packet loss rate < 1%;

[0072] The pressure monitoring sub-station uploads data to the system host through the CAN bus, and the delay < 200 ms.

[0073] Example 2: Dynamic Stress Monitoring and Early Warning in Fault Areas

[0074] Step 1: Geological Model Import

[0075] Import the three-dimensional geological model of the working face into the digital twin platform and mark the fault zone (strike N45°E, dip angle 60°);

[0076] Set the monitoring area to a 50 m range on both sides of the fault, and the grid division accuracy is 0.5 m × 0.5 m.

[0077] Step 2: Dynamic Simulation of Stress Field

[0078] The system host updates the stress nephogram every 5 minutes, and uses the improved Kalman filter (process noise Q = 0.01, observation noise R = 0.1) to fuse the sensor data;

[0079] When the stress gradient Δσ / Δx near the fault zone reaches 5 MPa / m, a yellow early warning is triggered, and the support resistance strengthening mode is activated.

[0080] Step 3: Cloud Platform Collaborative Response

[0081] The early warning information is synchronized to the cloud platform, and an inspection work order containing the longitude and latitude coordinates (error ±1 m) is automatically generated;

[0082] The inspection personnel receive the instructions through the APP and use a portable stress calibrator (accuracy ±0.02 MPa) to verify the data on site;

[0083] After confirming the risk, the system automatically adjusts the monitoring frequency of the adjacent area to 1 time / minute and activates the emergency ventilation plan.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A mining stress monitoring system for a coal mining face, characterized in that, include: A plurality of wireless sensor nodes (2) are arranged in arithmetic progression in a coal borehole along the working face, each node comprising a three-dimensional stress sensor (21), a data acquisition module (22), a wireless communication module (23) and a power module (24), the borehole depth extending to the mining impact zone in an arithmetic progression sequence, and the distance between adjacent nodes is ≤10 m; The pressure monitoring substation (3) is connected to each wireless sensor node via a wireless network, and has a built-in modem (31) and a voltage-stabilized power supply (32) to realize signal conversion and power supply; The system host (1) communicates with the pressure monitoring substation (3) through a wired network, is equipped with a data processing unit, a digital twin model and a human-computer interaction interface, dynamically analyzes stress distribution and generates an early warning signal.

2. The coal mining face mining stress monitoring system according to claim 1, wherein Also includes: The cloud platform (4) receives system host data via a wireless network and supports remote control of device restart, adjustment of monitoring frequency and multi-terminal data synchronization.

3. The coal mining face mining stress monitoring system according to claim 2, wherein The cloud platform (4) integrates a GMS monitoring module, supports map location query, stress change curve analysis and automatic generation of inspection logs, and when monitoring data is abnormal, a warning is triggered synchronously through text messages, APP push and sound and light alarms (41).

4. The coal mine working face mining stress monitoring system according to claim 1, characterized in that The wireless communication module (23) supports ZigBee and LoRa dual-mode transmission, adopts ad hoc network communication when the node spacing is ≤100m, and transmits through the pressure monitoring substation (3) relay when out of range, and dynamically switches the transmission mode based on RSSI signal strength.

5. The coal mining face mining stress monitoring system according to claim 1, characterized in that, The drilling depth extends to the mining impact area in an arithmetic sequence of L=20m, L+2m, L+4m.

6. The coal mining face mining stress monitoring system according to claim 1, characterized in that The three-axis stress sensor (21) is a hydraulic coupling type drilling stress meter, comprising a stress sensing probe, a guide rod and a pressure triggering claw hook, wherein the stress sensing probe is arranged outside the guide rod, and the pressure triggering claw hook is arranged at the end of the guide rod.

7. A construction method for a mining stress monitoring system in a coal mining face, characterized in that, The following steps are involved: Step 1: Drilling Use open and closed hollow drill rods to drill in the working face slot, form a drilling group in an arithmetic sequence, and the inclination angle is consistent with the coal seam trend. After drilling to the target depth, keep the drill rod position, and send a three-dimensional stress sensor and a guide rod through the internal channel of the drill rod. A pressure-triggered claw hook is set at the end of the guide rod. When the hydraulic pressure reaches 10MPa, the pressure-triggered claw hook is deployed and anchored to the hole wall. Step 2: Sensor Consolidation Inject quick-setting cement slurry through the feed pipe until slurry flows out of the return pipe; When the slurry solidifies, a monitoring point that is closely coupled with the coal body is formed; Step 3: Data transfer verification After the wireless sensor node is powered on, it forms a Mesh network with the pressure monitoring substation, and the pressure monitoring substation uploads data to the system host through the CAN bus.

8. The construction method of the mining stress monitoring system for a coal mining face according to claim 7, characterized in that, The system host transmits the data to the cloud platform (4) via a wireless network.

9. The construction method of the mining stress monitoring system for a coal mining face according to claim 7, characterized in that, The interval between adjacent boreholes is 10m.

10. The construction method of the mining stress monitoring system for a coal mining face according to claim 7, characterized in that, The digital twin model integrates geological structure data and real-time monitoring data, and generates a three-dimensional dynamic stress cloud map through an improved Kalman filter algorithm. When the stress gradient change rate is ≥5MPa / m for 10 minutes, an early warning is triggered.

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