Intelligent monitoring method for surface mine slope stability
By constructing an intelligent monitoring system in open-pit coal mine slopes, the shortcomings in monitoring internal displacement and stress fields of slopes have been addressed, enabling multi-source data fusion and real-time early warning, thereby improving the accuracy and predictive capability of slope stability analysis.
Patent Information
- Application Number
- CN202511466978.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-14
- Publication Date
- 2026-01-09
AI Technical Summary
Existing technologies lack universal monitoring methods for accurately sensing the internal displacement and stress fields of open-pit coal mine slopes, resulting in severe data silos and an inability to achieve multi-source data fusion analysis and effective early warning. In particular, slope stability monitoring in water-rich areas suffers from blindness and uncertainty.
By determining the location of the drainage well group, conducting geological surveys, rationally designing drainage well parameters and drilling rig well completion processes, and combining intelligent deep displacement and stress monitoring, an intelligent joint monitoring system is constructed to achieve multi-parameter correlation analysis and real-time data transmission, and to establish a slope stability prediction model.
It achieves deep integration of drainage wells and monitoring, providing accurate monitoring of internal slope displacement and stress field, supporting slope safety early warning and long-term planning, and improving the accuracy and predictive ability of slope stability analysis.
Smart Images
Figure CN121297939A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of mine slope monitoring technology, specifically to an intelligent monitoring method for the stability of open-pit mine slopes. Background Technology
[0002] In open-pit coal mining, slope stability is a crucial factor affecting safe production and represents the greatest risk source. With the continuous development of mining and stripping operations, the depth and area of open-pit mines are gradually increasing. As a natural sinkhole, the surrounding groundwater converges and seeps into the mine, affecting not only mining activities but also seriously threatening the safety and stability of the slopes.
[0003] Existing technical solutions mainly include standalone dewatering well technology, deep displacement monitoring technology, and deep borehole stress monitoring technology. These solutions suffer from limitations in providing single monitoring parameters. Furthermore, current open-pit coal mine slope deformation monitoring systems are self-contained, with independent monitoring data, hindering information fusion and data mining, and easily creating "data silos." This hinders multi-source data fusion analysis and integrated early warning. For open-pit mine slopes with complex terrain, numerous gullies, and complex groundwater distribution, and for areas affected by groundwater in water-rich regions, which are highly susceptible to groundwater seepage and landslides, existing monitoring and analysis methods for water-rich open-pit mine slopes still have significant limitations. Firstly, in open-pit mines with dewatering well clusters, the dewatering well cluster system lacks universally applicable monitoring methods and systems for accurately sensing the internal displacement and stress fields of the slope. GNSS and slope radar are both surface deformation monitoring methods, while sliding borehole inclinometers have been limited in application due to drawbacks such as cracking of the inclinometer tube and borehole failure caused by large deformations of the coal and rock mass. Second, in open-pit mines with dewatering well clusters, there is a lack of analytical methods that integrate monitoring data on the effects of dewatering wells with deformation and failure mechanisms. Traditional slope stability management models are static and do not consider the continuous improvement of coal and rock mass mechanical parameters as dewatering conditions change, making it impossible to integrate and analyze with on-site dewatering monitoring information. Currently, slope disaster risk assessment under open-pit mine dewatering conditions still relies on mathematical deduction from monitoring data, resulting in subjective, blind, and uncertain assessments. There is an urgent need for universal monitoring methods and means that can accurately perceive internal slope displacement. Third, facing the influence of groundwater on slopes in water-rich open-pit coal mines, which is a highly complex nonlinear system, slope monitoring data are independent, hindering information fusion and data mining, easily forming "data silos," and impeding multi-source data fusion analysis and integrated early warning. Summary of the Invention
[0004] To address the shortcomings of existing technologies, this invention provides an intelligent monitoring method for the stability of open-pit mine slopes, solving the problem of the lack of universal monitoring methods and systems that accurately perceive the internal displacement and stress fields of slopes.
[0005] To achieve the above objectives, the present invention provides the following technical solution: an intelligent monitoring method for the stability of open-pit mine slopes, comprising the following steps:
[0006] Step 1: Determine the location of the slope dewatering well group. The location of the slope dewatering well group is determined based on the long-term planning, design and annual plan of the open-pit coal mine, the location of key projects, past hydrological parameters and slope stability.
[0007] Step 2: Geological exploration. High-density electrical resistivity tomography and transient electromagnetic methods are used to conduct geological exploration to determine the hydrogeological conditions and the distribution of aquifers.
[0008] Step 3: Design the location of the drainage wells in a reasonable manner. Based on the results of Step 2 and relevant hydrological parameters, scientifically and reasonably determine the parameters such as the depth, diameter, spacing and row spacing of the vertical drainage wells on the surface.
[0009] Step 4: Select the appropriate drilling rig well completion technology, taking into account factors such as the design results of the drainage well, the looseness of the formation, the hardness of the rock strata, and the deformation of the slope excavation.
[0010] Step 5: Ensure normal drainage requirements by using relevant theoretical algorithms and software to design and optimize the diameter of the drainage well, the diameter of the perforated pipe, the particle size and thickness of the filter media, and antifreeze measures.
[0011] Step 6: Design deep displacement monitoring boreholes and stress boreholes to achieve joint monitoring of slope pore water pressure and deep displacement results, based on the groundwater recharge direction and potential slip surface distribution.
[0012] Step 7: Construct an intelligent joint monitoring system that can be accessed remotely. Based on the intelligent deep displacement and borehole stress gauge measurement and monitoring instruments, conduct multi-parameter correlation analysis to study the slope sliding mechanism in depth.
[0013] Preferably, in step two, when using the high-density electrical resistivity tomography (EDT), the electrode spacing is set to 5-10 meters, the measurement depth is not less than 1.5 times the maximum possible slip surface depth of the slope, and at least three repeated measurements are required during data acquisition to ensure data stability. When using the transient electromagnetic method, the spacing between the transmitting coil and the receiving coil is controlled at 20-30 meters, the operating frequency range is set to 10Hz-10kHz, and the measurement data needs to be processed for terrain correction and electromagnetic interference removal.
[0014] Preferably, when determining the parameters of the vertical surface drainage wells in step three, it is necessary to combine the water-bearing level of the aquifer as determined in step two. When the aquifer is highly water-bearing, the spacing between drainage wells is reduced to 15-20 meters, and the well diameter is not less than 300 mm. When the aquifer is weakly water-bearing, the spacing can be increased to 30-40 meters, and the well diameter can be 200-250 mm. Furthermore, the depth of the drainage wells must penetrate at least 5 meters into the bottom plate of the target aquifer.
[0015] Preferably, in step four, when selecting the drilling rig well completion process, if the formation is loose and the rock hardness is less than 30 MPa, the impact rotary drilling process is preferred, equipped with mud wall protection measures; if the rock hardness is greater than 50 MPa, the diamond wireline coring drilling process is used, and a well inclination measurement is performed every 50 meters during the well completion process to ensure that the well inclination does not exceed 1%.
[0016] Preferably, the relevant theoretical algorithms used in step five include Darcy's law and hydraulic calculation formulas. The software simulates the inflow rate and head reduction rate under different pore sizes and filter media parameters. The filter media particle size is selected to be 5-10 times the particle size of the aquifer, and the filter media thickness is controlled at 100-150 mm. For areas with extreme winter temperatures below -10℃, antifreeze measures are adopted, using a wellhead insulation jacket combined with a well pipe heat tracing device. The power of the heat tracing device is set to 20-50 W / m according to the local lowest temperature.
[0017] Preferably, in step six, the number of deep displacement monitoring holes and stress holes is set at 3-5 per 100 meters of slope length. The depth of the monitoring holes needs to reach 20 meters below the potential slip surface. The pore water pressure monitoring points are arranged in the holes at intervals of 2-3 meters. The deep displacement monitoring uses a sliding inclinometer with a measurement accuracy of not less than 0.1 mm per meter. The stress measurement range needs to be greater than 1.2 times the maximum estimated stress of the slope.
[0018] Preferably, the intelligent joint monitoring system in step seven has real-time data transmission function, with a transmission frequency of not less than once per hour. The system has a built-in data anomaly early warning module, which automatically issues an early warning when the monitored parameters exceed a preset threshold of 10%. The multi-parameter correlation analysis includes the temporal variation correlation between pore water pressure and deep displacement, and the spatial distribution correlation of data from different monitoring holes. By establishing a slope stability prediction model, the stability trend prediction for the next 72 hours can be achieved.
[0019] An intelligent monitoring system for the stability of open-pit mine slopes includes:
[0020] The acquisition module is used to acquire the width of each plate above each weak layer, the safety reserve coefficient and the stability coefficient of each weak layer in the soil-rock mixed slope.
[0021] The first determining module is used to determine the average flat plate width of each weak layer based on the flat plate width of each flat plate above each weak layer.
[0022] The first optimization module is used to optimize the width of each plate above each weak layer in the soil-rock mixed slope based on the average plate width of each weak layer, the safety reserve coefficient and the stability coefficient of each weak layer, so as to obtain the first optimized width of each plate above each weak layer in the soil-rock mixed slope.
[0023] The second optimization module is used to optimize the bottom width of each weak layer of the soil-rock mixed slope according to the three-dimensional support effect. Based on the bottom width of each weak layer, the first optimized width of each plate is optimized a second time to obtain the optimal width of each plate in each weak layer of the slope.
[0024] An electronic device includes a memory and a processor, wherein when the processor executes the intelligent monitoring system of claim 8, it implements an intelligent monitoring method.
[0025] A computer-readable storage medium on which an intelligent monitoring system is stored.
[0026] This invention provides an intelligent monitoring method for the stability of open-pit mine slopes. It has the following beneficial effects:
[0027] 1. This invention achieves deep integration of dewatering well construction and monitoring, possessing both efficient dewatering and precise monitoring functions. Through preliminary high-density electrical resistivity tomography (EDT) or transient electromagnetic reconnaissance (TEM), information on aquifer strata is accurately obtained. Combined with theoretical algorithms, dewatering well parameters are optimized, ensuring drainage needs are met while laying the foundation for joint monitoring. The well-forming process, tailored to geological conditions and monitoring equipment requirements, ensures effective equipment installation and survival. Coupled with an intelligent system, it enables automated dewatering operation and real-time monitoring of water pressure and deep displacement, reliably acquiring data and providing precise support for slope safety prevention.
[0028] 2. This invention innovatively constructs a correlation system between dewatering and slope monitoring, providing a novel technical approach for slope research. The system integrates relevant modules to capture the real-time impact of dewatering on pore water pressure and deep displacement, overcoming the limitations of traditional monitoring and dewatering separation. Its data can directly serve slope stability analysis and evaluation, and, combined with long-term and annual planning, determine well locations, closely aligning with actual mining conditions. This ensures current slope safety while accumulating data for subsequent design optimization, demonstrating both practical value and research significance in the safety management of slopes in water-rich open-pit mines. Attached Figure Description
[0029] Figure 1 This is a schematic diagram of step one of the present invention;
[0030] Figure 2 This is a schematic diagram of step two of the present invention;
[0031] Figure 3 This is a schematic diagram of step three of the present invention. Figure 1 ;
[0032] Figure 4 This is a schematic diagram of step three of the present invention. Figure 2 ;
[0033] Figure 5 This is a schematic diagram of step three of the present invention. Figure 3 ;
[0034] Figure 6 This is a schematic diagram of step five of the present invention. Figure 1 ;
[0035] Figure 7 This is a schematic diagram of step five of the present invention. Figure 2 ;
[0036] Figure 8 This is a schematic diagram of step six of the present invention;
[0037] Figure 9 This is a schematic diagram of step seven of the present invention. Figure 1 ;
[0038] Figure 10 This is a schematic diagram of step seven of the present invention. Figure 2 ;
[0039] Figure 11 The system of the present invention Figure 1 ;
[0040] Figure 12 The system of the present invention Figure 2 ;
[0041] Figure 13 This is a flowchart of the present invention. Detailed Implementation
[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0043] Example: Take a slope of a water-rich open-pit coal mine (slope length 1200 meters, maximum slope height 150 meters, potential sliding surface depth about 50 meters, aquifer mainly consisting of Quaternary water-bearing gravel sand layer and mudstone interlayer, with moderate to strong water-bearing capacity) as an example.
[0044] Please see the appendix Figure 1 - Appendix Figure 13 This invention provides an intelligent monitoring method for the stability of open-pit mine slopes, comprising the following steps:
[0045] Step 1: Determine the location of the slope dewatering well group. The location of the slope dewatering well group is determined based on the long-term planning, design and annual plan of the open-pit coal mine, the location of key projects, past hydrological parameters and slope stability.
[0046] Based on the coal mine's 5-year mining plan (planned excavation to -100m elevation), annual mining and stripping engineering plan (key mining area located in the middle section of the slope), and historical data (two small landslides occurred in the middle section of the slope in the past 3 years, and groundwater recharge mainly comes from the gully on the east side), the drainage well group was ultimately divided into three sections for layout:
[0047] Eastern section (gully recharge area): Deployed within 50m along the slope boundary line, focusing on highly water-rich gravelly sand layers;
[0048] Middle section (historical landslide area): Intensive deployment 30m above the mining platform, covering the potential slip surface area;
[0049] Western section (weakly water-rich area): Evenly distributed along the non-working slope, taking into account long-term stability monitoring.
[0050] Step 2: Geological exploration. Geological exploration is conducted using high-density electrical resistivity tomography (EDS) and transient electromagnetic methods to determine hydrogeological conditions and aquifer distribution. When using EDS, the electrode spacing should be 5-10 meters, and the measurement depth should be no less than 1.5 times the maximum possible slip surface depth of the slope. At least three repeated measurements are required during data acquisition to ensure data stability. When using transient electromagnetic methods, the distance between the transmitting and receiving coils should be controlled at 20-30 meters, and the operating frequency range should be set to 10Hz-10kHz. The measurement data needs to be corrected for topography and processed to remove electromagnetic interference.
[0051] 1. High-density electrical resistivity tomography: Using a Wenner device with an electrode spacing of 8 meters to balance resolution and efficiency, three survey lines were laid out along the slope direction, one each in the east, middle, and west sections. Each survey line covered the entire width of the slope, approximately 300 meters. The measurement depth was set at 80 meters, which is 1.6 times the potential slip surface depth of 50 meters. During data acquisition, a forward-backward reciprocating measurement mode was used, repeated 3 times. Outliers with an error greater than 5% were removed, and a resistivity profile was finally generated, clearly distinguishing between the gravel and sand layer (low resistivity zone, ρ < 50 Ω·m) and the mudstone layer (high resistivity zone, ρ > 200 Ω·m).
[0052] 2. Supplementary exploration using transient electromagnetic method: A 50m×50m transmitting coil and a 20m×20m receiving coil were selected, spaced 25 meters apart, with the operating frequency switched in three ranges (10Hz, 1kHz, 10kHz): the 10Hz band was used to detect the boundaries of the deep (50-100m) aquifer; the 1kHz band was used to identify the water-bearing capacity of the middle (20-50m) gravel and sand layers; and the 10kHz band was used to refine the distribution of the shallow (0-20m) loose overburden layer. During data processing, the influence of slope gradient (average 25°) was first eliminated through topographic correction, and then wavelet transform was used to remove power frequency (50Hz) electromagnetic interference. Finally, three strong water-bearing anomaly zones were delineated (two in the middle section and one in the eastern section).
[0053] Step 3: Design the location of the drainage wells reasonably. Based on the results of Step 2 and relevant hydrological parameters, scientifically and reasonably determine the depth, diameter, spacing, and row spacing of the surface vertical drainage wells. When determining the parameters of the surface vertical drainage wells, it is necessary to consider the water-bearing level of the aquifer as determined in Step 2. When the aquifer is highly water-bearing, the spacing between drainage wells should be reduced to 15-20 meters, and the diameter should not be less than 300 mm. When the aquifer is weakly water-bearing, the spacing can be increased to 30-40 meters, and the diameter can be 200-250 mm. The depth of the drainage wells must penetrate at least 5 meters into the bottom plate of the target aquifer.
[0054] Based on the exploration results, parameters were determined for different regions:
[0055]
[0056] The spacing between rows is set at 20 meters (along the slope) to form an "interlaced grid" layout, ensuring uniform rainfall.
[0057] Step 4: Select the appropriate drilling rig well completion technology, taking into account factors such as the design results of the drainage well, the looseness of the formation, the hardness of the rock strata, and the deformation of the slope excavation. When selecting the drilling rig well completion technology, if the formation is loose and the rock strata hardness is less than 30MPa, the impact rotary drilling technology should be given priority, equipped with mud wall protection measures. If the rock strata hardness is greater than 50MPa, the diamond wireline coring drilling technology should be used. During the well completion process, the well inclination should be measured every 50 meters to ensure that the well inclination does not exceed 1%.
[0058] Eastern and central sections (loose gravelly sand layer, rock hardness 20MPa): An XY-4 rotary percussion drill was used with the following drilling parameters: impact frequency 40 times / minute, rotation speed 150 r / min, and bentonite mud (density 1.2 g / cm³) applied simultaneously. 3 ) Protect the wall to prevent the hole wall from collapsing.
[0059] West section (mudstone interlayer, local hardness 60MPa): Replace with diamond wireline coring rig, core recovery rate ≥90%, use inclinometer (accuracy 0.1°) every 50 meters of drilling to check the well deviation, and finally control the well deviation within 0.8% to ensure the smooth installation of subsequent monitoring equipment.
[0060] Step 5: To ensure normal drainage requirements, relevant theoretical algorithms and software are used to design and optimize the wellbore diameter, perforated pipe diameter, filter media particle size and thickness, and antifreeze measures. The relevant theoretical algorithms used include Darcy's law and hydraulic calculation formulas. Software is used to simulate the inflow rate and head reduction rate under different pore diameters and filter media parameters. The filter media particle size is selected to be 5-10 times the aquifer particle size, and the filter media thickness is controlled at 100-150 mm. For areas with extreme winter temperatures below -10℃, antifreeze measures are used, such as wellhead insulation jackets combined with well pipe heat tracing devices. The power of the heat tracing device is set to 20-50 W / m according to the local lowest temperature.
[0061] 1. Parameter Calculation: Calculate the single-well water yield based on Darcy's law:
[0062] Q = 1.366K(2H-S)S / (lgR-lgr), where the permeability coefficient K (gravel layer) is taken as 20 m / d, and the calculated single-well yield in the eastern section is approximately 80 m³ / d. 3 / h; The filter media is graded quartz sand (particle size 5-10mm, which is 5-10 times the particle size of the aquifer (1mm)), with a thickness of 120mm, and the perforated tube aperture is set to 15mm (to prevent filter media loss).
[0063] 2. Anti-freezing measures: The extreme low temperature in this area during winter is -15℃. The following measures are taken: a polyurethane insulation sleeve (50mm thick) is installed at the wellhead; a heating cable (30W / m power) is wrapped around the outside of the well pipe and connected to a temperature controller (automatically starts below -5℃).
[0064] Step Six: Design deep displacement monitoring boreholes and stress boreholes. Based on the groundwater recharge direction and potential slip surface distribution, achieve joint monitoring of pore water pressure and deep displacement results on the slope. The number of deep displacement monitoring boreholes and stress boreholes should be 3-5 per 100 meters of slope length. The monitoring borehole depth should reach 20 meters below the potential slip surface. Pore water pressure monitoring points should be arranged in the boreholes at intervals of 2-3 meters. Deep displacement monitoring should use a sliding inclinometer with a measurement accuracy of not less than 0.1 mm per meter. The stress measurement range should be greater than 1.2 times the maximum estimated stress of the slope.
[0065] 1. Monitoring hole density: 4 monitoring holes are set up for every 100 meters of slope (5 holes in the middle section), for a total of 48 holes (12 in the east section, 20 in the middle section and 16 in the west section);
[0066] 2. Hole depth and monitoring points: Hole depth 70 meters (20 meters below the potential slip surface), pore water pressure monitoring points are arranged at 2.5-meter intervals (28 layers in total), using vibrating wire pore water pressure gauges (range 0-1MPa);
[0067] 3. Deep displacement monitoring: A φ76mm PVC inclinometer tube (5mm wall thickness) is embedded in the borehole and fixed at the bottom to a stable rock layer. A sliding inclinometer (accuracy 0.05mm / m) is used to measure a data point every 3 meters.
[0068] 4. Stress monitoring: Four sets of borehole stress gauges (range 0-50MPa, which is 1.67 times the estimated maximum stress of 30MPa) are installed on the potential slip surface (30-50 meters deep).
[0069] Step 7: Construct a remotely accessible intelligent joint monitoring system. Based on intelligent deep displacement and borehole stress gauge measurement and monitoring instruments, conduct multi-parameter correlation analysis to deeply study the slope sliding mechanism. The intelligent joint monitoring system has real-time data transmission capabilities, with a transmission frequency of no less than once per hour. The system has a built-in data anomaly early warning module, which automatically issues an early warning when the monitored parameters exceed a preset threshold of 10%. The multi-parameter correlation analysis includes the temporal variation correlation between pore water pressure and deep displacement, and the spatial distribution correlation of data from different monitoring boreholes. By establishing a slope stability prediction model, the stability trend can be predicted for the next 72 hours.
[0070] 1. System Architecture: Field Layer: Monitoring equipment (pressure gauges, inclinometers, stress gauges) transmits data in real time via 4G modules (once every 30 minutes); Base Station Layer: Two signal relay base stations are set up in the middle section to receive and cache data and upload it synchronously to the cloud; Cloud Layer: Edge computing servers are deployed to run multi-parameter correlation models (such as Pearson correlation analysis of pore water pressure and displacement rate).
[0071] 2. Early Warning and Prediction: Preset thresholds: sudden change in pore water pressure > 10 kPa / hour, displacement rate > 5 mm / day; mid-October 2023 monitoring showed that the pore water pressure at a depth of 35 meters (slippery surface position) in a certain borehole increased by 12 kPa within 2 hours, and the synchronous displacement rate reached 6.2 mm / day. The system automatically issued an orange warning. Combined with the 72-hour prediction model (based on LSTM neural network), it was predicted that a local landslide might occur. Emergency drainage measures were taken on site in a timely manner to avoid an accident.
[0072] An intelligent monitoring system for the stability of open-pit mine slopes includes:
[0073] The acquisition module is used to obtain the width of each platform above each weak layer in a soil-rock mixed slope, as well as the safety reserve coefficient and stability coefficient of each weak layer. Its functions include: collecting the width of the platform above each weak layer (i.e., the horizontal projection width of each step), the corresponding safety reserve coefficient, and the overall stability coefficient. Data sources include: aerial surveys by UAVs, lidar, slope monitoring sensors, historical mining plans, and geological exploration reports.
[0074] The first determining module is used to determine the average width of each weak layer based on the width of each pantograph above each weak layer. Function: Based on the acquired pantograph width data above each weak layer, calculate the "average pantograph width" corresponding to each weak layer. Method: Take the average width of all mining pantographs above a certain weak layer to reflect the overall influence of the bench distribution on that weak layer.
[0075] The second optimization module optimizes the bottom width of each weak layer in a soil-rock mixed slope based on the three-dimensional retaining effect. Based on the bottom width of each weak layer, it performs a secondary optimization of the first optimized width of each leveling plate to obtain the optimal width of each leveling plate within each weak layer of the slope. Function: Introduces the "three-dimensional retaining effect" to optimize and adjust the width of the bottom of the weak layer; based on the optimized bottom width, it performs a secondary optimization of the "first optimized width" of the leveling plate, ultimately obtaining the optimal width configuration of each leveling plate within each weak layer. Purpose: To achieve a balance between the economy and safety of slope excavation while ensuring that the safety reserve coefficient meets the requirements.
[0076] An electronic device includes a memory and a processor. When the processor executes an intelligent monitoring system, it implements an intelligent monitoring method. The memory stores the program code of the intelligent monitoring system, relevant monitoring data, slope geometric parameters, geotechnical parameters, platform width information, safety reserve coefficient, stability coefficient, optimization algorithm model, historical monitoring records, and intermediate calculation results. The memory can be a non-volatile storage medium, such as read-only memory, flash memory, solid-state drive, hard disk drive, etc., or it can be a volatile memory, such as random access memory, used for temporary storage of data and instructions during processor operation. The processor is connected to the memory and is used to load and execute the intelligent monitoring system program stored in the memory, thereby implementing the intelligent monitoring method. Specifically, the processor implements the following functions by calling program modules stored in the memory:
[0077] 1. Call the acquisition module to obtain the width of each mining platform above each weak layer in the soil-rock mixed slope, the safety reserve coefficient corresponding to each weak layer, and the overall slope stability coefficient.
[0078] 2. Call the first determination module to calculate and determine the average width of the flat plate above each weak layer based on the obtained flat plate width data above. This parameter can be used to evaluate the distribution characteristics and stability impact of the step load borne by the weak layer.
[0079] 3. The second optimization module is invoked to optimize and adjust the key geometric parameters at the bottom of each weak layer of the slope, taking into account the spatial layout of the three-dimensional retaining structure and its mechanical effects. Furthermore, based on the optimized bottom width, the initial or recommended width of each flat plate is calculated for secondary optimization. Finally, the optimal width configuration of each flat plate in each weak layer is output, which is suitable for the actual engineering project, so as to achieve a balance between safety and economy.
[0080] A computer-readable storage medium storing an intelligent monitoring system.
[0081] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.
Claims
1. An intelligent monitoring method for the stability of open-pit mine slopes, characterized in that, Includes the following steps: Step 1: Determine the location of the slope dewatering well group. The location of the slope dewatering well group is determined based on the long-term planning, design and annual plan of the open-pit coal mine, the location of key projects, past hydrological parameters and slope stability. Step 2: Geological exploration. High-density electrical resistivity tomography and transient electromagnetic methods are used to conduct geological exploration to determine the hydrogeological conditions and the distribution of aquifers. Step 3: Design the location of the drainage wells in a reasonable manner. Based on the results of Step 2 and relevant hydrological parameters, scientifically and reasonably determine the parameters such as the depth, diameter, spacing and row spacing of the vertical drainage wells on the surface. Step 4: Select the appropriate drilling rig well completion technology, taking into account factors such as the design results of the drainage well, the looseness of the formation, the hardness of the rock strata, and the deformation of the slope excavation. Step 5: Ensure normal drainage requirements by using relevant theoretical algorithms and software to design and optimize the diameter of the drainage well, the diameter of the perforated pipe, the particle size and thickness of the filter media, and antifreeze measures. Step 6: Design deep displacement monitoring boreholes and stress boreholes to achieve joint monitoring of slope pore water pressure and deep displacement results, based on the groundwater recharge direction and potential slip surface distribution. Step 7: Construct an intelligent joint monitoring system that can be accessed remotely. Based on the intelligent deep displacement and borehole stress gauge measurement and monitoring instruments, conduct multi-parameter correlation analysis to study the slope sliding mechanism in depth.
2. The intelligent monitoring method for slope stability in open-pit mines according to claim 1, characterized in that, In step two, when using the high-density electrical resistivity tomography (EDT), the electrode spacing is set to 5-10 meters, the measurement depth is not less than 1.5 times the maximum possible slip surface depth of the slope, and at least three repeated measurements are required during data acquisition to ensure data stability. When using the transient electromagnetic method, the distance between the transmitting coil and the receiving coil is controlled at 20-30 meters, the operating frequency range is set to 10Hz-10kHz, and the measurement data needs to be corrected for terrain and processed to remove electromagnetic interference.
3. The intelligent monitoring method for slope stability in open-pit mines according to claim 1, characterized in that, When determining the parameters of the vertical surface drainage wells in step three, it is necessary to combine the water-bearing capacity level of the aquifer as determined in step two. When the aquifer is highly water-bearing, the spacing between drainage wells should be reduced to 15-20 meters, and the well diameter should not be less than 300 mm. When the aquifer is weakly water-bearing, the spacing can be increased to 30-40 meters, and the well diameter can be 200-250 mm. In addition, the depth of the drainage wells should penetrate at least 5 meters into the bottom plate of the target aquifer.
4. The intelligent monitoring method for slope stability in open-pit mines according to claim 1, characterized in that, In step four, when selecting the drilling rig well completion process, if the formation is loose and the rock hardness is less than 30 MPa, the impact rotary drilling process should be given priority, and mud wall protection measures should be provided; if the rock hardness is greater than 50 MPa, the diamond wireline coring drilling process should be used. During the well completion process, the well inclination should be measured every 50 meters to ensure that the well inclination does not exceed 1%.
5. The intelligent monitoring method for slope stability in open-pit mines according to claim 1, characterized in that, The relevant theoretical algorithms used in step five include Darcy's law and hydraulic calculation formulas. The software simulates the inflow rate and head reduction rate under different pore sizes and filter media parameters. The filter media particle size is selected to be 5-10 times the particle size of the aquifer, and the filter media thickness is controlled at 100-150 mm. For areas with extreme winter temperatures below -10℃, antifreeze measures are taken by using a wellhead insulation jacket combined with a well casing heat tracing device. The power of the heat tracing device is set to 20-50 W / m according to the local lowest temperature.
6. The intelligent monitoring method for slope stability in open-pit mines according to claim 1, characterized in that, In step six, the number of deep displacement monitoring holes and stress holes should be 3-5 per 100 meters of slope length. The depth of the monitoring holes should reach 20 meters below the potential slip surface. The pore water pressure monitoring points should be arranged in the holes at intervals of 2-3 meters. The deep displacement monitoring uses a sliding inclinometer with a measurement accuracy of not less than 0.1 mm per meter. The stress measurement range should be greater than 1.2 times the maximum estimated stress of the slope.
7. The intelligent monitoring method for slope stability in open-pit mines according to claim 1, characterized in that, In step seven, the intelligent joint monitoring system has real-time data transmission capabilities, with a transmission frequency of no less than once per hour. The system has a built-in data anomaly early warning module that automatically issues an early warning when the monitored parameters exceed a preset threshold of 10%. The multi-parameter correlation analysis includes the temporal variation correlation between pore water pressure and deep displacement, and the spatial distribution correlation of data from different monitoring holes. By establishing a slope stability prediction model, the stability trend can be predicted for the next 72 hours.
8. An intelligent monitoring system for the stability of open-pit mine slopes, characterized in that, include: The acquisition module is used to acquire the width of each plate above each weak layer, the safety reserve coefficient and the stability coefficient of each weak layer in the soil-rock mixed slope. The first determining module is used to determine the average flat plate width of each weak layer based on the flat plate width of each flat plate above each weak layer. The first optimization module is used to optimize the width of each plate above each weak layer in the soil-rock mixed slope based on the average plate width of each weak layer, the safety reserve coefficient and the stability coefficient of each weak layer, so as to obtain the first optimized width of each plate above each weak layer in the soil-rock mixed slope. The second optimization module is used to optimize the bottom width of each weak layer of the soil-rock mixed slope according to the three-dimensional support effect. Based on the bottom width of each weak layer, the first optimized width of each plate is optimized a second time to obtain the optimal width of each plate in each weak layer of the slope.
9. An electronic device, characterized in that, include: The system includes a memory and a processor, wherein when the processor executes the intelligent monitoring system of claim 8, it implements the intelligent monitoring method as described in any one of claims 1-7.
10. A computer-readable storage medium, characterized in that, The intelligent monitoring system of claim 8 is stored on the readable storage medium.