Mine dumping site safety monitoring system and monitoring method

Abstract

The invention discloses a mine dumping site safety monitoring system and monitoring method, and relates to the technical field of mine safety monitoring. The system comprises a four-layer architecture including a front-end sensing layer, a data transmission layer, a data analysis layer and an early warning layer, integrates displacement, osmotic pressure, stress, weather and video multi-dimensional monitoring modules, and introduces a multi-source data fused dynamic safety coefficient correction model and a self-adaptive early warning threshold adjustment mechanism. The technical problems of safety coefficient calculation staticization, early warning threshold immobilization and poor multi-source data collaboration of a traditional monitoring device are solved. According to the invention, real-time accurate evaluation and dynamic early warning of the safety state of the mine dump can be realized, the intelligent level and early warning reliability of safety monitoring of the dump are obviously improved, countermeasures can be conveniently and timely taken, and the probability of occurrence of safety accidents caused by disasters such as landslide and collapse is effectively reduced.

Description

Technical Field

[0001] This invention relates to the field of mine safety monitoring technology, and in particular to a mine spoil heap safety monitoring system and monitoring method. Background Technology

[0002] Mine spoil heaps are important sites for storing stripping materials and waste during mining operations, and their safety and stability directly affect mine production and operation as well as the safety of personnel and property. As the scale of mining expands, the height of spoil heaps continues to increase. Affected by factors such as topography, meteorological conditions, and changes in the physical and mechanical properties of the spoil heap, spoil heaps are prone to safety accidents such as landslides, collapses, and debris flows.

[0003] Existing safety monitoring technologies for mine spoil heaps mostly employ single or a few monitoring methods, such as relying solely on GNSS for displacement monitoring or using only piezometers to monitor pore water pressure. This results in incomplete monitoring dimensions and poor data coordination. Furthermore, the safety factor calculations of traditional monitoring devices are often based on static limit equilibrium theory, failing to consider the impact of real-time dynamic factors such as displacement change rate and rainfall on the safety status. This leads to discrepancies between safety assessment results and actual conditions. Warning thresholds are often fixed values, unable to be dynamically adjusted according to changes in spoil heap height or seasonal meteorological characteristics (such as a surge in rainfall during the rainy season), making false alarms or missed alarms likely and reducing the reliability of warnings.

[0004] Therefore, existing technologies need to be improved. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a safety monitoring system and method for mine spoil heaps. By designing a dynamic safety factor correction model and an adaptive early warning threshold adjustment mechanism, the system can achieve real-time and accurate assessment and dynamic early warning of the safety status of spoil heaps, thereby improving the level of monitoring intelligence and the reliability of early warning.

[0006] This invention is achieved through the following technical solution: In a first aspect, the present invention provides a safety monitoring system for mine spoil heaps, which includes a front-end sensing layer, a data transmission layer, a data analysis layer and an early warning layer; The front-end sensing layer includes a displacement monitoring module, a seepage pressure and water level monitoring module, a stress and strain monitoring module, an environmental and meteorological monitoring module, and a video monitoring and infrared detection module. The data transmission layer includes a "wireless + wired" hybrid transmission architecture, which includes a 4G / 5G transmission unit, a LoRa transmission unit, and an optical fiber transmission unit, used to enable bidirectional data interaction between the front-end sensing layer and the data analysis layer. The data analysis layer includes a data cleaning unit, a dual-mode storage unit, a dynamic safety factor calculation unit, and an intelligent prediction unit. The dynamic safety factor calculation unit has a built-in dynamic safety factor correction model based on multi-source data fusion. The model is based on the limit equilibrium theory and uses displacement change rate, pore water pressure increment, and real-time rainfall data as correction factors to dynamically correct the initial safety factor. The early warning layer includes a multi-level early warning unit, a visualization platform unit, and an emergency command unit. The multi-level early warning unit adopts an adaptive early warning threshold adjustment mechanism, which automatically adjusts the trigger thresholds for different early warning levels based on changes in the height of the spoil heap, seasonal meteorological characteristics, and historical accident data.

[0007] Furthermore, in this invention, the displacement monitoring module mentioned above includes a GNSS displacement monitoring station and an inclination sensor. The GNSS displacement monitoring station is installed at intervals from top to bottom on the surface of the spoil heap slope. The inclination sensor is installed in the middle and lower part of the spoil heap slope and on key structures to supplement the monitoring of local small-scale displacement changes.

[0008] Furthermore, in this invention, the bottom of the aforementioned GNSS displacement monitoring station is provided with an adaptive vibration damping and protection base, and the bottom of the adaptive vibration damping and protection base is provided with a fixed pile. The adaptive vibration damping and protection base includes an outer protective shell connected to the fixed pile and an inner fixed support connected to the GNSS displacement monitoring station. The outer protective shell and the inner fixed support are provided with transverse vibration damping components and longitudinal vibration damping components.

[0009] Furthermore, in this invention, the aforementioned lateral damping element is configured as a rubber block, and the longitudinal damping element is configured as a spring. Both ends of the transverse damping member are respectively inserted into the grooves of the outer protective shell and the inner fixing bracket. The inner fixing bracket is provided with an electric push rod connected to the transverse damping member. Both ends of the longitudinal damping member are respectively fixed to the outer protective shell and the inner fixing bracket by bolts. A thin-film pressure sensor is provided on the inner side of the transverse damping member for real-time monitoring of the pressure on the transverse damping member. According to the pressure data of the thin-film pressure sensor, the electric push rod adjusts the compression of the transverse damping member. A deformation cavity is provided inside the transverse damping member, and the deformation cavity is located in the gap between the outer protective shell and the inner fixing bracket.

[0010] Furthermore, in this invention, the aforementioned seepage pressure and water level monitoring module includes a vibrating wire piezometer and an immersion water level gauge; the vibrating wire piezometer is buried in aquifers at different depths in the spoil heap; the immersion water level gauge is installed in the water accumulation pits and groundwater level observation wells around the spoil heap.

[0011] Furthermore, in this invention, the calculation expression for the dynamic safety factor correction model described above is: in: F′s is the dynamically adjusted safety factor; Fs is the initial safety factor calculated based on the limit equilibrium theory; α, β, and γ are the displacement correction factor, seepage pressure correction factor, and rainfall correction factor, respectively, with values ​​ranging from 0.1 to 0.3. They were obtained through training with historical monitoring data and accident cases. v is the real-time displacement rate (mm / d), and v0 is the displacement rate threshold (mm / d). Δu is the real-time pore water pressure increment (kPa), and u0 is the pore water pressure increment threshold (kPa). R is the 24-hour cumulative rainfall (mm), and R0 is the rainfall threshold (mm). min(1,x) is the minimum value function, which ensures that each correction factor does not exceed 1 and avoids over-correction of the safety factor.

[0012] Furthermore, in this invention, the aforementioned adaptive early warning threshold adjustment mechanism includes a threshold initial setting module, a dynamic adjustment module, and a threshold verification module; the threshold initial setting module sets an initial early warning threshold based on the spoil heap design parameters; the dynamic adjustment module adjusts the threshold according to the following rules: For every 5-meter increase in the height of the spoil heap, the safety factor thresholds corresponding to yellow, orange, and red alerts will be reduced by 0.02, 0.03, and 0.04, respectively. When the rainy season begins (monthly rainfall ≥ 100mm), the warning threshold triggered by rainfall will be reduced by 20%. If a localized landslide has occurred in a monitoring area within the past 3 years, the overall warning threshold for that monitoring area will be reduced by 15%. The threshold verification module verifies the rationality of the adjusted threshold by backtesting historical data. If the false alarm rate exceeds 5%, the adjustment parameters are re-optimized.

[0013] Furthermore, in this invention, the aforementioned front-end sensing layer also includes a temperature and humidity monitoring component disposed inside the reactor body. The temperature and humidity monitoring component includes an encapsulated outer tube, a temperature sensing unit, a humidity sensing unit, a data acquisition module, and a wireless transmission module. The outer tube of the package has water-permeable and air-permeable holes evenly distributed on its sidewall. A PTFE filter membrane is installed inside the water-permeable and air-permeable holes. A measuring tube communicating with the water-permeable and air-permeable holes is installed inside the outer tube of the package. The humidity sensing unit is integrated in the measuring tube. The temperature sensing unit extends outside the outer tube of the package.

[0014] Furthermore, in this invention, the LoRa transmission unit of the aforementioned data transmission layer adopts a star network topology and deploys a LoRa gateway. The video monitoring and infrared detection module includes a 4K high-definition dome camera and an infrared thermal imaging camera. The 4K high-definition dome camera has 360° rotation and supports motion detection. The infrared thermal imaging camera is used to identify areas with abnormal surface temperatures at the spoil heap.

[0015] Secondly, the present invention also provides a method for safety monitoring of mine spoil heaps, which employs the mine spoil heap safety monitoring system as described in claim 1.

[0016] Compared with the prior art, the present invention has the following advantages and beneficial effects: The mine spoil heap safety monitoring device and method of this invention integrates five major monitoring modules—displacement, seepage pressure, stress, meteorology, and video—in its front-end sensing layer. This avoids misjudgments caused by relying on a single monitoring method and enables comprehensive analysis of the spoil heap's safety status. Through a dynamic safety factor correction model, three correction factors—displacement, seepage pressure, and rainfall—are introduced, along with a minimum value function constraint. This ensures that the safety factor calculation reflects actual dynamic values, achieving real-time, accurate assessment and dynamic early warning of the spoil heap's safety status, thus improving the intelligence level of monitoring and the reliability of early warnings. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 This is a schematic diagram of the displacement monitoring module according to an embodiment of the present invention; Figure 2 This is an internal schematic diagram of the adaptive shock absorption and protection base according to an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the cooperation between the lateral shock absorber and the electric push rod in an embodiment of the present invention; Figure 4 This is a schematic diagram of the temperature and humidity monitoring component according to an embodiment of the present invention.

[0018] The attached diagram shows the markings and corresponding component names: 1-GNSS displacement monitoring station, 2-adaptive vibration damping and protection base, 201-outer protective shell, 202-inner fixed bracket, 3-fixed pile, 4-lateral vibration damping component, 401-electric push rod, 402-deformation cavity, 5-longitudinal vibration damping component, 6-temperature and humidity monitoring component, 601-encapsulation outer tube, 6011-water and air permeable hole, 602-temperature sensing unit, 603-humidity sensing unit, 604-data acquisition module, 605-wireless transmission module, 606-measuring tube. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments and accompanying drawings. The illustrative embodiments and descriptions of this invention are for explanation only and are not intended to limit the invention. The following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without inventive effort are within the scope of protection of this invention.

[0020] It should be noted that similar reference numerals and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In the description of the embodiments of the present invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," and "connect" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0021] Example 1 Taking an open-pit coal mine spoil heap as an example, the spoil heap has a height of 90m and the main body is a mixture of sandy clay and rock.

[0022] When installing GNSS displacement monitoring station 1, several foundation monitoring points are set up along the slope of the spoil heap at certain intervals (e.g., 50m intervals), and monitoring points are densely arranged above the potential sliding surface (e.g., 30m intervals). Combined with... Figure 1 As shown, each monitoring point is constructed with a C30 concrete observation pier as a fixed pile 3. An adaptive vibration damping and protection base 2 is installed on the top of the fixed pile 3. The GNSS displacement monitoring station 1 is connected to the adaptive vibration damping and protection base 2.

[0023] Because there are a large number of heavy equipment (such as excavators and dump trucks) in the mining spoil heap area, the vibration generated by the operation of the equipment will affect the precision equipment of GNSS displacement monitoring station 1 and reduce the accuracy of displacement monitoring; long-term vibration will also cause the internal components of the equipment to loosen and shorten the service life of the equipment. Therefore, an adaptive vibration damping and protection base 2 is designed to reduce vibration.

[0024] Combination Figure 1 , Figure 2 and Figure 3 As shown, the adaptive vibration damping and protection base 2 includes an outer protective shell 201 connected to the fixed pile 3 and an inner fixed support 202 connected to the GNSS displacement monitoring station 1. Both the outer protective shell 201 and the inner fixed support 202 are sleeve-shaped, and a transverse damping component 4 and a longitudinal damping component 5 are provided between the outer protective shell 201 and the inner fixed support 202.

[0025] The transverse damping component 4 is configured as a nitrile rubber block, and the longitudinal damping component 5 is configured as a spring. Both ends of the transverse damping component 4 are inserted into the grooves of the outer protective shell 201 and the inner fixing bracket 202, respectively. The inner fixing bracket 202 is equipped with an electric push rod 401 connected to the transverse damping component 4. Both ends of the longitudinal damping component 5 are fixed to the outer protective shell 201 and the inner fixing bracket 202 by bolts. A thin-film pressure sensor is installed inside the transverse damping component 4 to monitor the pressure on it in real time. Based on the pressure data from the thin-film pressure sensor, the electric push rod 401 adjusts the compression of the transverse damping component 4. A deformation cavity 402 is provided inside the transverse damping component 4, located within the gap between the outer protective shell 201 and the inner fixing bracket 202. The deformation cavity 402 ensures that the deformed portion of the transverse damping component 4 remains within the gap between the outer protective shell 201 and the inner fixing bracket 202 when deformed.

[0026] A thin-film pressure sensor monitors the pressure on the damping pad during vibration in real time. The controller can be integrated inside the inner fixed bracket 202. The controller drives the electric push rod 401 to adjust the compression of the transverse damping component 4 according to the pressure data to adapt to different vibration intensities. For example, when heavy equipment is close, the damping effect needs to be enhanced; when heavy equipment is far away, the damping effect needs to be reduced to avoid the equipment from shaking due to insufficient rigidity.

[0027] It should be noted that during the initialization of GNSS displacement monitoring station 1, a 48-hour static connection test was conducted with a GNSS reference station 3km away from the mining area to complete coordinate calibration. The positioning accuracy reached ±2mm+1PPm horizontally and ±5mm+1PPm vertically, and the data output frequency was set to 5Hz.

[0028] Furthermore, several tilt sensors were installed in the lower part of the slope of the spoil heap, with a measurement range of ±30°, an accuracy of ±0.1°, and a data acquisition frequency of 1 time / minute.

[0029] In this embodiment, a geological drilling rig was used to drill boreholes in different areas of the spoil heap. The borehole diameter was 150mm, and the depths were 15m, 30m, and 45m, respectively. A layer of vibrating wire piezometers was installed at each depth, with 5 piezometer monitoring points per layer, for a total of 15 vibrating wire piezometers. When burying the vibrating wire piezometers, a 5cm thick layer of fine sand was first laid at the bottom of the borehole. After placing the piezometer, bentonite and fine sand were mixed in a 1:3 ratio and backfilled to ensure close contact between the vibrating wire piezometer and the spoil heap. Finally, a concrete protective cap was installed at the borehole opening. During equipment initialization, calibration was performed three times using a standard pressure source (0.2MPa, 0.5MPa, 0.8MPa), with the range set to 0-1MPa.

[0030] One submersible water level gauge was installed in each of the four water accumulation pits and three groundwater level observation wells around the spoil heap. The submersible water level gauges were suspended by steel wire ropes, with the bottom of the gauge 1m above the bottom of the pit / well. The data update frequency was set to once every 5 minutes. During initialization, the water level height was manually measured and compared with the equipment reading, with an error ≤0.2mm. The measurement range was set to 0-10m.

[0031] In this embodiment, earth pressure gauges are installed at depths of 20m and 35m inside the spoil heap, with six monitoring points in each layer, for a total of 12 earth pressure gauges. The earth pressure gauges are installed using a sleeve method: a 120mm diameter sleeve is first inserted into the spoil heap, the earth pressure gauge is placed in, the sleeve is then removed, and fine sand is backfilled to ensure uniform pressure transmission. During equipment initialization, pressures of 0.1MPa, 0.3MPa, and 0.5MPa are applied for calibration, and the measurement range is set to 0-2MPa.

[0032] Two fiber optic strain gauges were attached to the surface of each of the 10 retaining wall sections and 8 anti-slide piles on the slope of the spoil heap. Special adhesive was used for the attachment, and the surface of the attachment area was ground smooth. The data acquisition frequency was set to once every 2 minutes. During initialization, strains of 100με, 200με, and 300με were applied using a strain calibrator for verification, achieving a resolution of 1με.

[0033] The front-end sensing layer also includes a temperature and humidity monitoring component 6 disposed inside the reactor body. The temperature and humidity monitoring component 6 includes an encapsulated outer tube 601, a temperature sensing unit 602, a humidity sensing unit 603, a data acquisition module 604, and a wireless transmission module 605. Water and air perforations 6011 are evenly distributed on the sidewall of the encapsulated outer tube 601. A PTFE filter membrane is installed inside each water and air perforation 6011. A measuring tube 606 communicating with the water and air perforations 6011 is disposed inside the encapsulated outer tube 601. The humidity sensing unit 603 is integrated into the measuring tube 606, and the temperature sensing unit 602 extends outside the encapsulated outer tube 601. The water and air perforations 6011 on the sidewall, combined with the PTFE filter membrane, allow water vapor from inside the reactor body to enter the shell and contact the sensors, while blocking soil particles and impurities to prevent sensor clogging and failure. The shell ends adopt a threaded sealing structure and are equipped with fluororubber sealing rings, achieving an IP68 protection rating to prevent moisture from seeping into the interior and damaging electronic components. The temperature sensing unit 602 uses a platinum resistance sensor, which is in direct contact with the material in the stack, making the measurement more direct and accurate.

[0034] After the temperature and humidity monitoring component 6 is embedded in the reactor body, the humidity sensing unit 603 converts the humidity signal into an electrical signal; the temperature sensing unit 602 senses the reactor body temperature and converts it into an electrical signal; the data acquisition module 604 converts the electrical signal into a digital signal, which is then sent to the LoRa gateway via the wireless transmission module 605, and then uploaded to the data processing and analysis layer via the data transmission layer. The data processing and analysis layer analyzes the temperature and humidity data. For example, when the temperature in a certain area continues to rise (e.g., an increase of ≥2℃ within 24 hours) and the humidity is >85%RH, it is determined that the cohesion of the reactor body particles in that area may be reduced, and it is necessary to focus on monitoring in conjunction with displacement data; if the abnormal temperature and humidity area coincides with a potential sliding surface, the warning level is promptly upgraded.

[0035] The environmental and meteorological monitoring module is deployed by setting up an automatic weather station in an open area (unobstructed, 2.5m above the ground) in a certain direction (e.g., the east side) of the spoil heap. The station integrates a rain gauge, wind speed sensor, wind direction sensor, and temperature and humidity sensor. The data acquisition frequency is set to once every 10 minutes. The automatic weather station is fixed to the concrete base below with expansion bolts during installation.

[0036] One 4K high-definition dome camera was installed at each of the four highest points around the spoil heap. The cameras were fixed with galvanized steel pipe brackets. The cameras have 360° rotation, 20x optical zoom, and an effective infrared night vision range of 80m. The software is configured with motion detection function (sensitivity set to medium level) and crack recognition algorithm (can identify surface cracks ≥5mm in width). The video frame rate is set to 25fps and the image resolution is 3840×2160.

[0037] One infrared thermal imaging camera is installed on each slope area of ​​the spoil heap that is prone to landslides. The temperature measurement range is -20℃ to 150℃, the accuracy is ±2℃, the installation height is 10m, the lens is facing the slope surface, and the data acquisition frequency is 1 time / 30 seconds.

[0038] The data transmission layer includes 4G / 5G and LoRa transmission units. Both the GNSS displacement monitoring station 1 and the tilt sensor have built-in 4G / 5G modules (supporting China Mobile, China Unicom, and China Telecom networks). Each device is equipped with a 10000mAh lithium battery and a 10W solar panel to ensure battery life in cloudy or rainy weather. The devices transmit data to the cloud server via TCP / IP protocol.

[0039] Piezometers, soil pressure gauges, and strain gauges all utilize LoRa modules. Three LoRa gateways (covering a 2km radius, each capable of connecting 200 devices) are deployed, located in the east, west, and central areas of the spoil heap. The gateways are connected to the nearest 4G router via Ethernet cables, uploading the collected data to the cloud. The gateway devices are powered by lithium batteries.

[0040] High-definition dome cameras, infrared thermal imaging cameras, and automatic weather stations are connected to the local monitoring center of the mine via optical fiber (single-mode optical fiber, transmission distance ≤20km). The optical fiber is laid in PE pipe (50mm in diameter) at a depth of 0.8m, avoiding the spoil heap operation area and transportation roads. The transmission rate is set to 100Mbps to ensure smooth transmission of video data (delay ≤200ms).

[0041] The data processing and analysis layer includes local servers and cloud databases, a dynamic security coefficient calculation unit, and an intelligent prediction unit.

[0042] Local servers and cloud databases: Two industrial servers are deployed in the mine monitoring center to store real-time monitoring data for nearly one year; Alibaba Cloud or Huawei Cloud servers are used in the cloud to store more than five years of historical data, and data management is carried out through a MySQL database, supporting data query, export and backup functions.

[0043] Dynamic safety factor calculation unit configuration: Dynamic safety factor correction model software is deployed on a local server. Through training with historical monitoring data (last 3 years) and landslide accident cases, correction coefficients α=0.2, β=0.15, γ=0.25, displacement change rate threshold v0=5mm / d, pore water pressure increment threshold u0=50kPa, and rainfall threshold R0=80mm / 24h are determined. The initial safety factor Fs is calculated using the simplified Bishop method. Input parameters include bulk density (20kN / m³), internal friction angle (30°), cohesion (15kPa), and stockpile height (90m). The calculated Fs... s =1.35.

[0044] Intelligent prediction unit configuration: The LSTM neural network model is built based on Python. The training dataset consists of monitoring data from the past two years (with a time interval of 10 minutes, totaling approximately 100,000 data points). Input features include displacement, seepage pressure, stress, rainfall, and temperature. The output is the predicted safety factor for the next 1-3 days. The model prediction error is ≤5%, and the prediction results are updated once per hour.

[0045] The early warning layer includes a multi-level early warning unit configuration. One audible and visual alarm and one LED display screen are installed in the mine monitoring center. The initial safety factor thresholds corresponding to the early warning levels are set as follows: blue warning (F′s≥1.2), yellow warning (1.1≤F′s<1.2), orange warning (1.05≤F′s<1.1), and red warning (F′s<1.05).

[0046] According to the adaptive early warning threshold adjustment mechanism, since the current stockpile height of the spoil heap is 90m (the threshold is lowered for every 5m increase), which is 40m higher than the initial design height (50m), the yellow, orange, and red warning thresholds are lowered by 0.16, 0.24, and 0.32 respectively. The adjusted thresholds are: blue warning (F′s≥1.2), yellow warning (0.94≤F′s<1.2), orange warning (0.81≤F′s<0.94), and red warning (F′s<0.81). Meanwhile, since the area is in its rainy season (with rainfall ≥120mm in the past 3 months), the warning threshold triggered by rainfall will be reduced by 20%, i.e., R0 will be adjusted to 80mm / 24h. In addition, due to two landslide accidents in the past 5 years, the overall warning threshold for the area will be reduced by 15%. The final warning thresholds are: blue warning (F′s≥1.02), yellow warning (0.799≤F′s<1.02), orange warning (0.6885≤F′s<0.799), and red warning (F′s<0.6885). Through backtesting of historical data, the false alarm rate is 3.2% (≤5%), which meets the requirements.

[0047] Visualization Platform Deployment: A web-based (supporting Chrome and Firefox browsers) and mobile (Android and iOS) visualization platform has been developed. The web-based platform is deployed on the mine monitoring center server, while the mobile platform is released through the App Store, Android app markets, and other channels. The platform uses a GIS map (Gaode Map API) to display the topography of the spoil heap and the location of monitoring points. Clicking on a monitoring point allows users to view real-time data and historical curves. It also features equipment status monitoring capabilities (displaying device online / offline status, battery level, and signal strength).

[0048] Emergency command unit configuration: The visualization platform has a built-in emergency response plan library, including personnel evacuation route maps (generating three optimal evacuation routes based on GIS maps to avoid potentially dangerous areas), equipment transfer plans (clearly specifying the location of transport vehicles and engineering machinery to be transferred and their destinations), and rescue team dispatch procedures (contact information and dispatch order for contacting the mine rescue team and local emergency management departments). The platform supports video conferencing (integrating Tencent Meeting API), allowing for one-click invitation of relevant personnel to join meetings and real-time sharing of monitoring data and on-site video.

[0049] Example 2 This embodiment provides a monitoring method, which adopts the mine spoil heap safety monitoring system of Embodiment 1.

[0050] Each monitoring device collects data at a preset frequency. GNSS displacement monitoring station 1 collects displacement data once every 5 Hz, tilt sensor collects tilt angle data once every 1 minute, piezometer and earth pressure gauge collect pressure data once every 10 minutes, strain gauge collects strain data once every 2 minutes, automatic weather station collects meteorological data once every 10 minutes, and high-definition camera and infrared thermal imaging camera collect video data in real time.

[0051] F′s (dynamically corrected safety factor): This is the output of the model, reflecting the actual safety status of the spoil heap under the influence of real-time monitoring data. The larger the value, the better the stability of the spoil heap; when the value is lower than the warning threshold, the corresponding level of warning is triggered.

[0052] Fs (Initial Safety Factor): The static safety factor calculated based on traditional limit equilibrium theory (such as the simplified Bishop method). Input parameters include physical and mechanical indicators such as bulk density, internal friction angle, cohesion, and stockpile height of the spoil heap, representing the theoretical safety level under ideal conditions.

[0053] α, β, and γ (correction coefficients): These are the displacement correction coefficient, seepage pressure correction coefficient, and rainfall correction coefficient, respectively, with values ​​ranging from 0.1 to 0.3. They are determined through training using historical monitoring data and accident case studies. For example, the larger the α value, the higher the weight of displacement changes on the safety factor (e.g., α for loose rock formations is usually greater than that for hard rock formations).

[0054] v and v0 (displacement rate of change and threshold): v is the real-time displacement rate of change (unit: mm / d) collected by the GNSS monitoring terminal, reflecting the movement trend of the spoil heap slope. v0 is the displacement rate threshold (unit: mm / d) set according to the stability requirements of the spoil heap; exceeding this value indicates abnormally active displacement.

[0055] Δu and u0 (pore water pressure increment and threshold): Δu is the pore water pressure increment per unit time monitored by the piezometer (unit: kPa), reflecting changes in the hydrodynamic conditions inside the reactor (increased water pressure reduces the shear strength of the reactor). u0 is the safe threshold for pore water pressure increment (unit: kPa), exceeding this value indicates a significant increase in the influence of water on the stability of the reactor.

[0056] R and R0 (Rainfall and Threshold): R is the 24-hour cumulative rainfall (in mm) monitored by the automatic weather station. Rainfall is a key factor inducing landslides at spoil heaps (rainwater infiltration increases the weight of the spoil heap and reduces soil strength). R0 is a rainfall threshold (in mm) set according to local climate characteristics. Exceeding this value indicates that rainfall poses a threat to the safety of the spoil heap.

[0057] min(1,x) (Minimum function): This is a key constraint of the model. When the monitored parameter (such as v / v0) exceeds 1, this correction factor is forced to be 1 to avoid the safety factor being overcorrected due to a single parameter anomaly (such as a severe rainstorm), thus ensuring the rationality of the calculation results.

[0058] The dynamic safety factor calculation unit calls the correction model to calculate F′s every 10 minutes. The calculation parameters of the dynamic safety factor correction model are as follows: Initial safety factor F_s=1.35, displacement correction factor α=0.2, seepage pressure correction factor β=0.15, rainfall correction factor γ=0.25, real-time displacement change rate v=3.5mm / d, displacement change rate threshold v0=5mm / d, real-time pore water pressure increment Δu=30kPa, pore water pressure increment threshold u0=50kPa, 24-hour cumulative rainfall R=60mm, rainfall threshold R0=80mm (values ​​after adaptive adjustment).

[0059] Displacement rate ratio: , Since 0.7 < 1, therefore .

[0060] Pore ​​water pressure increment ratio: , Since 0.6 < 1, therefore .

[0061] Rainfall ratio: , Since 0.75 < 1, therefore .

[0062] Corrections for displacement, seepage pressure, and rainfall: , , .

[0063] Calculate the safety factor after dynamic correction: .

[0064] The intelligent prediction unit predicts the safety factor for the next 1-3 days every hour based on the LSTM model. For example, if F′s = 0.786 at the current time, it predicts that F′s will drop to 0.75 in the next 24 hours, 0.72 in the next 48 hours, and 0.69 in the next 72 hours, indicating that the safety risk continues to rise.

[0065] When F′s = 0.786 (orange alert) is calculated, the multi-level warning unit immediately triggers the warning: the local audible and visual alarm emits an orange light and intermittent alarm sound, and the LED display shows "Orange alert for spoil heap; landslide risk exists in some areas; immediately organize the evacuation of workers and prohibit vehicles from entering"; at the same time, the warning information is sent to relevant personnel via SMS and APP push, and the SMS content includes the warning level and the triggering reason (displacement change rate 3.5mm / d, pore water pressure increase 30kPa, 24-hour rainfall 60mm). Emergency rescue teams are dispatched, and emergency reinforcement materials such as sandbags and anti-slide piles are prepared. Simultaneously, changes in displacement, seepage pressure, and rainfall are closely monitored to provide data support for subsequent response.

[0066] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A mine waste dump safety monitoring system, characterised in that, The front-end perception layer, the data transmission layer, the data analysis layer, and the early warning layer are comprised; The front-end perception layer comprises a displacement monitoring module, a seepage pressure and water level monitoring module, a stress and strain monitoring module, an environment and weather monitoring module, and a video monitoring and infrared detection module; The data transmission layer comprises a "wireless + wired" hybrid transmission architecture, which comprises a 4G / 5G transmission unit, a LoRa transmission unit, and an optical fiber transmission unit, for interacting with the bidirectional data between the front-end perception layer and the data analysis layer; The data analysis layer comprises a data cleaning unit, a dual-mode storage unit, a dynamic safety factor calculation unit, and an intelligent prediction unit; the dynamic safety factor calculation unit is internally provided with a dynamic safety factor correction model of multi-source data fusion, which takes the limit equilibrium theory as the basis and uses the displacement change rate, the pore water pressure increment, and the real-time rainfall data as correction factors to dynamically correct the initial safety factor; The early warning layer comprises a multi-level early warning unit, a visualization platform unit, and an emergency command unit; the multi-level early warning unit adopts an adaptive early warning threshold adjustment mechanism to automatically adjust the trigger threshold of different early warning levels according to the dump storage height change, the seasonal weather characteristics, and the historical accident data.

2. The mine waste dump safety monitoring system according to claim 1, characterized in that, The displacement monitoring module comprises a GNSS displacement monitoring station (1) and an inclination sensor; the GNSS displacement monitoring station (1) is installed on the surface of the dump slope from top to bottom at intervals; the inclination sensor is installed in the middle and lower part of the dump slope and the key structure to supplement the monitoring of local small-range displacement changes.

3. The mine waste dump safety monitoring system according to claim 2, characterised in that, The bottom of the GNSS displacement monitoring station (1) is provided with an adaptive shock-absorbing protection base (2), and the bottom of the adaptive shock-absorbing protection base (2) is provided with a fixed pile (3); the adaptive shock-absorbing protection base (2) comprises an outer protective shell (201) connected with the fixed pile (3) and an inner fixed support (202) connected with the GNSS displacement monitoring station (1); the outer protective shell (201) and the inner fixed support (202) are provided with a transverse shock-absorbing piece (4) and a longitudinal shock-absorbing piece (5).

4. The mine waste dump safety monitoring system according to claim 3, characterised in that, The transverse shock-absorbing piece (4) is configured as a rubber block, and the longitudinal shock-absorbing piece (5) is configured as a spring. Two ends of the transverse damping member (4) are respectively inserted into the grooves of the outer protective shell (201) and the inner fixed support (202), the inner fixed support (202) is provided with an electric push rod (401) connected with the transverse damping member (4), and two ends of the longitudinal damping member (5) are fixed with the outer protective shell (201) and the inner fixed support (202) through bolts; the inner side of the transverse damping member (4) is provided with a thin film pressure sensor for monitoring the pressure borne by the transverse damping member (4) in real time; according to the pressure data of the thin film pressure sensor, the electric push rod adjusts the compression amount of the transverse damping member (4), and the inside of the transverse damping member (4) is provided with a deformation cavity (402), and the deformation cavity (402) is located in the gap between the outer protective shell (201) and the inner fixed support (202).

5. The mine waste dump safety monitoring system according to claim 1, characterized in that, The osmotic pressure and water level monitoring module comprises a vibrating string osmotic pressure gauge and a submerged water level gauge; the vibrating string osmotic pressure gauge is buried in different depth aquifers of the dump site; and the submerged water level gauge is installed in a surrounding water accumulation pit and a groundwater level observation well of the dump site.

6. The mine waste dump safety monitoring system according to claim 1, characterized in that, The calculation expression of the dynamic safety factor correction model is: Wherein: F′s is the dynamic corrected safety factor; Fs is the initial safety factor calculated based on the limit equilibrium theory; α, β, γ are displacement correction coefficient, osmotic pressure correction coefficient and rainfall correction coefficient respectively, the value range of each is 0.1-0.3, and they are obtained by training historical monitoring data and accident cases; v is the real-time displacement change rate (mm / d), and v0 is the displacement change rate threshold (mm / d); Δu is the real-time pore water pressure increment (kPa), and u0 is the pore water pressure increment threshold (kPa); R is the 24-hour cumulative rainfall (mm), and R0 is the rainfall threshold (mm); min(1,x) is the minimum value function, which ensures that each correction factor does not exceed 1, so as to avoid excessive correction of the safety factor.

7. The mine waste dump safety monitoring system according to claim 1, characterized in that, The adaptive early warning threshold adjustment mechanism comprises a threshold initial setting module, a dynamic adjustment module and a threshold verification module; the threshold initial setting module sets the initial early warning threshold according to the design parameters of the dump site; the dynamic adjustment module adjusts the threshold according to the following rules: When the dump site storage height increases by 5 meters, the safety factor thresholds corresponding to yellow, orange and red early warnings are reduced by 0.02, 0.03 and 0.04 respectively; When it enters the rainy season (monthly rainfall ≥100mm), the early warning threshold triggered by rainfall is reduced by 20%; When a local landslide accident occurs in the monitoring area within 3 years, the early warning threshold of the monitoring area is reduced by 15% as a whole; The threshold verification module verifies the rationality of the adjusted threshold through historical data backtesting, and if the false positive rate exceeds 5%, the adjustment parameters are re-optimized.

8. The mine waste dump safety monitoring system according to claim 1, characterized in that, The front-end perception layer further comprises a temperature and humidity monitoring assembly (6) arranged inside the heap body, The temperature and humidity monitoring assembly (6) comprises an encapsulation outer tube (601), a temperature sensing unit (602), a humidity sensing unit (603), a data acquisition module (604) and a wireless transmission module (605). The packaging outer tube (601) is uniformly provided with water-permeable and air-permeable holes (6011) in the side wall, a PTFE filter film is arranged in the water-permeable and air-permeable holes (6011), the inside of the packaging outer tube (601) is provided with a measuring tube (606) in communication with the water-permeable and air-permeable holes (6011), the humidity sensing unit (603) is integrated in the measuring tube (606), and the temperature sensing unit (602) extends outside the packaging outer tube (601).

9. The mine waste dump safety monitoring system according to claim 1, characterized in that, The LoRa transmission unit of the data transmission layer adopts a star network topology, and a LoRa gateway is arranged, the video monitoring and infrared detection module comprises a 4K high-definition ball camera and an infrared thermal imaging camera; the 4K high-definition ball camera is capable of rotating by 360 degrees and supports mobile detection; and the infrared thermal imaging camera is used for identifying abnormal temperature areas on the surface of the dump.

10. A method of safety monitoring of a mine waste dump, characterized by, The mine dump safety monitoring system as claimed in claim 1 is adopted.

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