Method for monitoring deformation of vertical shaft of coal mine
By combining 3D laser scanning and sensor monitoring, the monitoring target area was determined and a virtual model was constructed, which solved the problem of real-time and comprehensive monitoring of shaft deformation in coal mines, and realized accurate early warning and reliable monitoring of shaft deformation.
Patent Information
- Application Number
- CN202610323926.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-17
- Publication Date
- 2026-05-15
AI Technical Summary
Existing technologies are insufficient for real-time and comprehensive monitoring of coal mine shafts. Three-dimensional laser scanning methods cannot achieve real-time monitoring, and online sensors have limited monitoring range, resulting in fragmented data and difficulty in taking into account the overall deformation of the shaft.
By combining 3D laser scanning and sensor monitoring, the monitoring target area is determined through pre-morphological scanning, sensor groups are deployed to obtain information on anchor stress and spacing between guide beams, a virtual model is constructed to set deformation early warning thresholds, and collaborative data analysis and early warning are achieved.
It enables real-time and comprehensive monitoring of wellbore deformation, improves the accuracy and reliability of early warning, and avoids the problems of blind sensor deployment and data isolation.
Smart Images
Figure CN122041748A_ABST
Abstract
Description
Technical Field
[0001] This application relates to a method for monitoring the deformation of coal mine vertical shafts, belonging to the field of mine surveying and safety engineering technology. Background Technology
[0002] Vertical shafts are crucial passageways connecting mines to the surface, and their long-term safe and stable operation directly impacts the mine's production capacity, economic benefits, and personnel safety. With increasing mining depth and more complex geological conditions, the shafts are subjected to intensified asymmetric ground pressure, mining-induced stress, freeze-thaw cycles, and groundwater seepage, which can easily lead to shaft tilting, concrete cracking in the shaft walls, and deformation of the hoisting beams, threatening the safety of the hoisting system.
[0003] For detecting deformation in vertical shafts, current technologies often employ precision measurement methods such as 3D laser scanning and online sensor monitoring. However, while precision measurement methods like 3D laser scanning can acquire full-section, high-precision point cloud models, the measurement results are offline and delayed, making real-time monitoring of changes impossible. Furthermore, point cloud models are easily affected by downhole fog or water spray. Online sensor monitoring methods have limited monitoring range and struggle to cover the entire shaft. Overall, current technologies are often isolated, either performing only periodic detection or only continuous monitoring. The data from these two approaches are fragmented and difficult to coordinate, resulting in a lack of comprehensive and reliable detection of shaft deformation. Summary of the Invention
[0004] This application discloses a method for monitoring the deformation of coal mine vertical shafts.
[0005] The method for monitoring the deformation of coal mine vertical shafts in this application includes the following steps:
[0006] Multiple morphological scans are performed on the wellbore to be measured in advance to determine the monitoring target area of the wellbore; According to the shape of the well shaft to be measured, a sensor group with preset attributes is arranged in the monitoring target area to obtain anchor stress information and guide beam spacing information in the monitoring target area. The sensor group includes multiple first sensors for monitoring anchor stress and multiple second sensors for monitoring guide beam spacing. Based on the actual geological conditions and attribute parameters of the wellbore to be measured, determine the deformation early warning threshold group of the wellbore to be measured; Based on the anchor bolt stress information and the tank beam spacing information, a correlation analysis is performed to determine the fusion analysis data. Based on the fusion analysis data and the deformation early warning threshold group, early warning and handling are performed on the deformation of the well shaft to be measured.
[0007] In some implementations, the step of performing multiple morphological scans on the wellbore to determine the monitoring target area of the wellbore includes: Using a preset time period, a preset 3D laser scanner is used to measure the well shaft to be measured, thereby constructing a 3D point cloud model of the well shaft to be measured. A morphological analysis is performed on the three-dimensional point cloud model to determine the quantitative results of the morphological changes of the wellbore to be measured; Based on the quantitative results of the morphological changes, the geological conditions of the well shaft to be measured, and the maintenance history of the mining area where the well shaft to be measured is located, the monitoring target area is determined, wherein the monitoring target area is the weak and vulnerable section of the well shaft to be measured.
[0008] In some implementations, performing morphological analysis on the three-dimensional point cloud model to determine the quantification result of the morphological changes of the wellbore to be measured includes: Based on the three-dimensional point cloud model, the wellhead or bottom cross-section of the well shaft to be measured is fitted to determine the quantitative result of the inclination degree of the well shaft to be measured; Based on the three-dimensional point cloud model, the Xingtian of the well to be measured is fitted along the depth direction of the well to determine the quantification results of the significant offset well section of the well to be measured; Based on the three-dimensional point cloud model, an ideal plumb bob cylinder is fitted with the bottom of the well to be measured as a reference to determine the quantification result of the well wall deformation of the well to be measured. The quantification result of the shape change includes the quantification result of the inclination degree, the quantification result of the significantly offset well section and / or the quantification result of the well wall deformation.
[0009] In some embodiments, the step of arranging a sensor group with preset attributes in the monitoring target area according to the shape of the wellbore to be measured includes: According to the shape of the well shaft to be measured, multiple holes are drilled in the well wall of the monitoring target area to install the corresponding first sensor at each of the drill holes, wherein the first sensor is an intrinsically safe anchor bolt stress sensor for mining. According to the shape of the well shaft to be measured, multiple prefabricated fixtures are set on the guide beam of the monitoring target area to install the corresponding second sensor at each prefabricated fixture, wherein the second sensor is an intrinsically safe laser rangefinder for mining.
[0010] In some embodiments, obtaining the anchor stress information and the spacing information of the guide beams in the monitoring target area includes: Based on a preset intrinsically safe junction box for mining, the first sensor and the second sensor are connected to a preset intrinsically safe data monitoring station for mining, wherein the first sensor sends the anchor stress information to the intrinsically safe data monitoring station for mining, and the second sensor sends the track beam spacing information to the intrinsically safe data monitoring station for mining; The anchor stress information and the spacing information of the guide beam in the monitoring target area are obtained from the intrinsically safe data monitoring station in the mine through a preset mine industrial ring network and sent to the local data server. The mine industrial ring network includes an intrinsically safe explosion-proof power supply and an intrinsically safe gateway.
[0011] In some embodiments, determining the deformation early warning threshold set of the wellbore to be measured based on the actual geological conditions and property parameters of the wellbore to be measured includes: Based on the actual geological conditions and support parameters of the well shaft to be measured, a virtual model of the well shaft to be measured is constructed to simulate the quantitative information of the stress and deformation of the well shaft to be measured. The virtual model is used to quantitatively analyze the stress concentration and deformation mechanism of the monitoring target area. Based on the design information of the well shaft to be measured, a concrete specimen of the inner wall of the well shaft to be measured is prepared to determine the stress-strain simulation and quantitative information of the inner wall of the well shaft to be measured. Based on the virtual model and the stress-strain quantification information, the deformation early warning threshold group is calculated and determined, wherein the deformation early warning threshold group includes multiple anchor stress early warning thresholds, and the property parameters of the wellbore to be measured include the support parameters and the design information.
[0012] In some implementations, multiple anchor stress warning thresholds divide the value of anchor stress into multiple value ranges, each value range corresponds to a warning level, and each warning level is associated with one or more preset response measures.
[0013] In some embodiments, constructing a virtual model of the wellbore to be measured based on the actual geological conditions and support parameters of the wellbore to be measured includes: Based on the actual geological conditions and support parameters of the well shaft to be measured, the stress and deformation of the well shaft to be measured are simulated under the coupled action of the original ground stress field, the mining influence field and / or the groundwater pressure field, so as to construct a virtual model of the well shaft to be measured.
[0014] In some implementations, the step of performing correlation analysis based on the anchor bolt stress information and the track beam spacing information to determine the fusion analysis data includes: Based on the actual location information of the well shaft to be measured, the stress information of the anchor bolt and the spacing information of the guide beam are associated to determine the stress-deformation coupling information of the well shaft to be measured. The fusion analysis data includes the stress-deformation coupling information of the well shaft to be measured.
[0015] In some implementations, the step of performing early warning and handling of the deformation of the wellbore under test based on the fused analysis data and the deformation early warning threshold group includes: Based on the stress-deformation coupling information, the early warning level corresponding to the wellbore to be measured is determined by comparing it with the deformation early warning threshold group. Based on the warning level, a warning message is issued through a preset reminder method, and the response measures associated with the warning level are executed, wherein the preset reminder method includes at least an interface pop-up, an audible and visual alarm, and / or a short message reminder.
[0016] The beneficial effects of this application are as follows: The coal mine vertical shaft deformation monitoring method in this application can coordinate the results of periodically executed three-dimensional laser scanning with the data acquisition results of continuously executed networked sensors, enabling the deformation monitoring of the shaft to take into account both historical deformation and current conditions. Furthermore, by using two different sensors to perform continuous monitoring, the information on stress and deformation is complementary and verified, making the monitoring process and results more comprehensive and reliable. In addition, the above method also constructs a virtual model and produces concrete specimens to determine the stress-strain performance of the shaft, thereby establishing an early warning threshold rooted in the specific rock and soil environment and material properties of the mine, thus improving the accuracy of shaft deformation early warning. Attached Figure Description
[0017] Figure 1 This is one of the flowcharts of the coal mine vertical shaft deformation monitoring method in the embodiments of this application; Figure 2 This is the second flowchart illustrating the coal mine vertical shaft deformation monitoring method in the embodiments of this application; Figure 3 This is the third flowchart illustrating the coal mine vertical shaft deformation monitoring method in the embodiments of this application; Figure 4 This is one of the application scenarios of the coal mine vertical shaft deformation monitoring method in the embodiments of this application; Figure 5 This is the second schematic diagram of the application scenario of the coal mine vertical shaft deformation monitoring method in the embodiments of this application; Figure 6 This is the fourth flowchart of the coal mine vertical shaft deformation monitoring method in the embodiments of this application; Figure 7This is the third schematic diagram of the application scenario of the coal mine vertical shaft deformation monitoring method in the embodiments of this application.
[0018] The components include: 1. Remote control room; 2. Local data server; 3. Gateway equipment; 4. Data monitoring main station; 5. Data monitoring substation; 6. Communication cable; 7. Wellhead; 8. Second sensor; 9. First sensor; 10. Cage beam; 11. Cage; 12. Cage beam. Detailed Implementation
[0019] Please see Figure 1 The method for monitoring the deformation of a coal mine vertical shaft in this application includes the following steps: Step 01: Perform multiple morphological scans on the wellbore to be measured in advance to determine the monitoring target area of the wellbore.
[0020] Specifically, the coal mine vertical shaft deformation monitoring method in this application requires the combination of offline but periodically performed morphological scanning results of the shaft to be measured and online and continuously performed status detection results of the shaft to be measured through deployed sensors. Only by combining the two can the historical deformation and current status of the shaft to be measured be taken into account, thereby improving the comprehensiveness and reliability of deformation monitoring.
[0021] For offline but periodically performed morphological scanning, its main function is to, on the one hand, to conduct a comprehensive survey of the historical deformation of the wellbore to be measured, and on the other hand, to screen out the local areas in the wellbore to be measured that have deformed or damaged, so as to determine the specific area (i.e. the corresponding monitoring target area) for subsequent sensor deployment to perform continuous monitoring. This can avoid the situation of having no clear target in the wellbore.
[0022] Further, please refer to Figure 2 In some embodiments, step 01 further includes: Step 011: Using a preset time period, perform measurements on the well shaft to be measured based on a preset 3D laser scanner to construct a 3D point cloud model of the well shaft to be measured; Step 012: Perform morphological analysis on the 3D point cloud model to determine the quantitative results of the morphological changes of the wellbore to be measured; Step 013: Based on the morphological change quantification results, the geological conditions of the wellbore to be measured, and the maintenance history of the mining area where the wellbore is located, determine the monitoring target area. The monitoring target area is the weak and vulnerable section of the wellbore to be measured.
[0023] Specifically, for offline but periodically executed morphological scans, the execution method can be implemented according to the following example.
[0024] For example, for mine A of a coal mine, the shaft of mine A is scanned twice with a 25-month interval, using the same set of 3D laser scanners. This results in a prior 3D point cloud model and a subsequent 3D point cloud model of the shaft of mine A (corresponding to the shaft to be measured). The prior 3D point cloud model and the subsequent 3D point cloud model are then compared to achieve morphological analysis of the 3D point cloud model.
[0025] Furthermore, in some implementations, please refer to Figure 3 Step 012 specifically includes: Step 0121: Based on the three-dimensional point cloud model, fit the wellhead or bottom cross section of the well to be measured to determine the quantitative result of the inclination degree of the well to be measured; Step 0122: Based on the 3D point cloud model, fit the wellbore to be measured along the wellbore depth direction to determine the quantification results of the significant offset wellbore section to be measured; Step 0123: Based on the 3D point cloud model, fit an ideal plumb bob cylinder with the bottom of the well to be measured as the reference to determine the quantification result of the well wall deformation of the well to be measured. The morphological change quantification results include the tilt degree quantification results, the significant displacement well section quantification results, and / or the well wall deformation quantification results.
[0026] Specifically, after obtaining the prior 3D point cloud model and the subsequent 3D point cloud model, the point cloud is first fitted to form a 3D fitting model of each part of the wellbore, such as the wellhead, well bottom and well wall. Then, based on the above 3D fitting model, the deformation, defects and other conditions of each part of the wellbore are further quantitatively analyzed.
[0027] For example, in some cases, after obtaining a subsequent 3D point cloud model through scanning, comparing the 3D fitting model corresponding to the previous 3D point cloud model and the 3D fitting model corresponding to the subsequent 3D point cloud model reveals that the geometric center of the wellhead of mine A has shifted by 0.045m in the direction of 76° north-northeast compared to 25 months ago (corresponding to the quantification result of inclination). By slicing the 3D fitting model along the depth of the well shaft, the offset of the center of each section at different depths of the well shaft can be determined using the center of each slice, thus identifying the depth range requiring key monitoring. For instance, for mine A, the local offsets in the soft rock layer development sections at depths of 50m, 150m, and 300m are significantly greater than the offset at the wellhead (corresponding to the quantification result of significantly offset well sections). Simultaneously, by fitting an ideal plumb bob cylinder with the well bottom as a reference, the unevenness and defects of the well wall can be detected, such as multiple localized defects on the well wall including well wall damage and water inrush (corresponding to the quantification result of well wall deformation). The above analysis results constitute the quantification result of the morphological changes of the well shaft of mine A.
[0028] Therefore, based on the above-mentioned quantitative results of morphological changes, combined with the geological conditions of the area where the coal mine corresponding to Mine A is located and the recent maintenance records of Mine A, the areas near the shaft depths of 50m, 150m and 300m in Mine A are identified as monitoring target areas with prominent deformation, weak rock, and vulnerability. This area needs to be continuously monitored by deploying sensor groups.
[0029] In this way, through the above-mentioned means, the coal mine vertical shaft deformation monitoring method in the embodiments of this application can quantitatively identify the spatial distribution pattern of deformation (overall tilt, local twisting, radial expansion and contraction) and the location of apparent defects in the entire shaft area from massive point cloud data, thereby providing irrefutable data basis for the precise targeted deployment of sensor groups and avoiding the blindness of sensor deployment.
[0030] Please continue reading. Figure 1 The coal mine vertical shaft deformation monitoring method in this application embodiment further includes: Step 02: Based on the shape of the wellbore to be measured, deploy a sensor group with preset attributes in the monitoring target area to obtain information on anchor bolt stress and guide beam spacing in the monitoring target area. The sensor group includes multiple first sensors for monitoring anchor bolt stress and multiple second sensors for monitoring the spacing between the track beams.
[0031] Specifically, based on the above implementation method, the next step is to install sensor groups at the determined monitoring target areas according to the actual shape of the wellbore to be measured, so as to achieve continuous monitoring of each monitoring target area. The sensor group includes multiple sensors. Generally, the sensors are divided into two categories: one is a first sensor for measuring the stress of the anchor bolts in the wellbore, and the other is a second sensor for measuring the spacing of the guide beams in the wellbore. The second sensor generally uses the laser reflection principle to measure the spacing. There are generally multiple first and second sensors. After installation in the wellbore, a continuous monitoring network can be formed for the stress and deformation of the well wall, anchor bolts, and guide beams in the entire monitoring target area.
[0032] Furthermore, in some embodiments, step 02 specifically includes: Based on the shape of the wellbore to be measured, multiple holes are drilled in the well wall of the monitoring target area to install a corresponding first sensor at each hole. The first sensor is an intrinsically safe anchor stress sensor for mining applications; Based on the shape of the wellbore to be measured, multiple prefabricated fixtures are set on the guide beam of the monitoring target area to install a corresponding second sensor at each prefabricated fixture. The second sensor is an intrinsically safe laser rangefinder for mining applications.
[0033] Specifically, based on the above implementation method, for the specific installation method of the first sensor and the second sensor, for example, for the first sensor, based on relevant safety regulations and laws, it is necessary to use an intrinsically safe anchor stress sensor for mining. The main way to install the first sensor is to drill multiple blind holes in the well wall of the monitoring target area, drive an anchor into each blind hole and install a first sensor on the anchor, so as to form a continuous monitoring network for anchor stress in the monitoring target area, thereby detecting the radial or circumferential stress and the uniformity of stress distribution borne by the concrete lining of the well wall in real time and continuously.
[0034] Similarly, for the second sensor, based on relevant safety regulations and laws, an intrinsically safe laser ranging sensor for mining is required. The main method for installing the second sensor is to customize and install multiple special clamps on the guide beams in the monitoring target area according to the structure of the guide beams. A second sensor is fixedly installed at each clamp, thereby forming a continuous monitoring network for the spacing of the guide beams in the monitoring target area. This allows for real-time and continuous detection of changes in the horizontal and vertical spacing of the guide beams, indirectly reflecting the convergence deformation of the shaft and the geometric stability of the guide system.
[0035] Furthermore, in some embodiments, step 02 further includes: Based on a pre-designed intrinsically safe junction box for mining, the first sensor and the second sensor are connected to a pre-designed intrinsically safe data monitoring station for mining. The first sensor sends anchor bolt stress information to the intrinsically safe data monitoring station for mining, and the second sensor sends track beam spacing information to the intrinsically safe data monitoring station for mining. The anchor stress information and guide beam spacing information in the monitoring target area are obtained from the intrinsically safe data monitoring station in the mine via a pre-set mine industrial ring network and sent to the local data server. The mine industrial ring network includes mine-use explosion-proof and intrinsically safe power supplies and mine-use intrinsically safe gateways.
[0036] Specifically, based on the above implementation method, the information acquired by each sensor in the above sensor group can be collected, for example, by using junction boxes, data monitoring stations and constructing a mine industrial ring network, to automatically transmit the information acquired by each sensor directly to the local data server, thereby realizing the automatic acquisition of anchor bolt stress and chute beam spacing data.
[0037] Exemplarily, for each monitored target area, a junction box is set up. The transmission lines of each sensor in the monitored target area are integrated at the junction box, and then each junction box is connected to the same data monitoring station by a two-wire communication cable, thereby achieving the preliminary summary of sensor data. Among them, based on relevant safety regulations and laws and regulations, the junction boxes set in each monitored target area need to use intrinsically safe junction boxes for mines, and the data monitoring station also needs to use an intrinsically safe data monitoring station for mines. The above-mentioned data monitoring station is generally set outside the well, such as in the winch house or a dedicated information machine room.
[0038] Further exemplarily, the data monitoring station can be arranged in a two-level layout of sub-station and main-station, or in a single-level layout of a single main-station. In the case where the data monitoring station is arranged in a two-level layout of sub-station and main-station, the main function of the sub-station is to access the incoming data lines of all junction boxes and further transmit the data to the main-station. The main function of the main-station is to summarize the bolt stress information and the spacing information of the cage guide beam transmitted by the sub-station, and transmit the above data to the local data server through the mine industrial ring network constructed by the gateway device, thereby achieving the automatic acquisition of the bolt stress and the spacing information of the cage guide beam based on the sensor group to the local data server. In the above-mentioned mine industrial ring network, based on relevant safety regulations and laws and regulations, the gateway device needs to use an intrinsically safe gateway device for mines, and the power supply device supporting the gateway device needs to use an explosion-proof and intrinsically safe power supply.
[0039] Regarding the arrangement and connection methods of the sensor group, junction box, gateway device in the mine industrial ring network, and the server in the above embodiments, please refer to Figure 4 , in the figure, it shows that in the shaft of Mine A, monitoring target areas are respectively set at 50m, 150m, and 300m underground. In each monitored target area, three customized fixtures are set on two groups of cage guide beams 10, and a second sensor 8 is set on each fixture. And blind holes are drilled every 90° along the circumference on the shaft wall, and a bolt is driven into each blind hole. Further, a first sensor 9 is installed on each bolt. The communication cable 6 passes through all monitored target areas, extends out of the wellhead 7 and is connected to the data monitoring sub-station 5. The data monitoring sub-station 5 receives the data and further transmits it to the data monitoring main-station 4. The data monitoring main-station 4 summarizes the acquired data and further transmits the data to the local data server 2 via the gateway device 3. The above data monitoring sub-station 5, data monitoring main-station 4, gateway device 3, and local data server 2 are all set in the remote control machine room 1.
[0040] Further, please refer to Figure 5 , Figure 5This is a cross-sectional view of a certain monitoring target area. For example, in addition to the tank guide beam 10, the second sensor 8 can also be set on the tank beam 12 by a clamp, and the tank cage 11 runs on the tank guide formed by the tank guide beam 10 and the tank beam 12.
[0041] In this way, based on the above deployment method, a real-time monitoring network for coordinated force-deformation sensing can be constructed in the target area. The first sensor perceives the cause of the wellbore stress from a mechanical perspective, while the second sensor monitors the deformation of the guide beam from a geometric perspective. The corresponding data from the two sensors are synchronized in time and space, and can mutually verify and supplement each other. This overcomes the shortcomings of single stress sensors being insensitive to deformation or single distance sensors being unclear about mechanical mechanisms, and also utilizes automated industrial ring networks to transmit information, thereby avoiding the high risks and low efficiency of manual data collection in the well.
[0042] Please continue reading. Figure 1 The coal mine vertical shaft deformation monitoring method in this application embodiment further includes: Step 03: Determine the deformation early warning threshold group for the wellbore to be measured based on the actual geological conditions and attribute parameters of the wellbore to be measured.
[0043] Specifically, based on the above implementation method, while continuously monitoring the target area using a sensor array, exemplarily, simulation experiments can also be performed based on the actual geological conditions of the wellbore to be measured and the wellbore's own property parameters to determine the early warning threshold for the deformation of the wellbore to be measured. The aforementioned early warning threshold is generally expressed as an anchor bolt stress early warning threshold. There are multiple anchor bolt stress early warning thresholds, which divide the reasonable range of anchor bolt stress values into multiple early warning value ranges. Each early warning value range corresponds to an early warning level, and each early warning level corresponds to a description of a wellbore deformation state, as well as one or more preset response measures.
[0044] For example, in some cases, please refer to Table 1, which shows a set of anchor stress warning thresholds and corresponding warning levels, deformation state descriptions and response measures. In the case shown in Table 1, the theoretical yield load of the corresponding anchor is 126kN. Based on the relevant design information and safety regulations, a set of anchor stress warning thresholds as shown in Table 1 can be obtained.
[0045] Table 1. Early Warning Classification and Response Measures
[0046] Furthermore, in some implementations, please refer to Figure 6 Step 03 specifically includes: Step 031: Based on the actual geological conditions and support parameters of the wellbore to be measured, construct a virtual model of the wellbore to simulate the quantification information of its stress and deformation. The virtual model is used to quantitatively analyze and monitor the stress concentration and deformation mechanism of the target area. Step 032: Based on the design information of the well shaft to be measured, prepare concrete specimens of the inner wall of the well shaft to determine the stress-strain simulation and quantitative information of the inner wall of the well shaft to be measured. Step 033: Based on the virtual model and stress-strain quantification information, calculate and determine the deformation early warning threshold group. The deformation early warning threshold group includes multiple anchor stress early warning thresholds, and the property parameters of the well barrel to be measured include support parameters and design information.
[0047] Specifically, in some examples, the method for determining the anchor stress warning threshold mentioned above generally starts from three aspects: the geological conditions of the well location, the property parameters of the well itself, and the mechanical properties of the inner wall material of the well. The anchor stress warning threshold of the entire well to be measured is estimated, thereby determining the anchor stress warning threshold as accurately as possible.
[0048] For example, based on the above example, and considering the actual geological conditions of the location of mine A and the support parameters of mine A's own structure, a refined virtual model of the mine A shaft can be established using current three-dimensional numerical simulation software (such as FLAC3D, ANSYS, etc.). This model mainly simulates the possible stress and deformation of the shaft under the coupled action of the original geostress field, the influence field, and the groundwater pressure field. The virtual model can then be used to quantitatively analyze the stress concentration and deformation mechanism of each monitoring target area section, thus providing a theoretical reference for the preliminary setting of the anchor bolt stress early warning threshold.
[0049] The aforementioned virtual model primarily covers two aspects: the geological conditions of the wellbore's location and the wellbore's own property parameters. Regarding the mechanical properties of the wellbore's inner wall material, for example, concrete samples can be collected from the well wall, or identical concrete specimens can be fabricated according to the well wall's design information. Then, axial compressive strength tests can be performed on these concrete samples or specimens using strain gauges. During the test, the strain gauges continuously acquire the stress-strain curves of the test piece from the application of external force to deformation failure, thereby accurately determining key stress-strain simulation and quantification information such as the upper limit of the linear elastic stage, yield strain, and failure limit strain. This stress-strain simulation and quantification information provides a factual basis for accurately setting the anchor bolt stress warning threshold. For example, please refer to... Figure 7 , Figure 7The stress-strain curves of concrete specimens made from the material of the sidewall of mine A shaft are shown in the axial compressive strength test. According to the curves, the rated crack initiation strain threshold of the concrete specimens from the sidewall of mine A shaft is approximately 1780 μm. µ ε.
[0050] Next, based on the possible stress and deformation conditions known from the virtual model analysis and the stress-strain simulation quantification information obtained from stress-strain tests, combined with industry laws, regulations, and technical specifications such as the "Code for Design of Concrete Structures" and the "Technical Specification for Anchor Bolt Support in Coal Mine Roadways," the aforementioned multi-level anchor bolt stress warning thresholds are accurately calculated. For example, the percentage of the anchor bolt's design working load (e.g., 33%, 50%, 67%, 95%) is used as the quantification standard for the anchor bolt stress warning threshold, and the percentage of the ultimate yield load is used as the classification (e.g., observation level, ultimate level, dangerous level, failure level) as the quantification standard for the warning level, thus setting the warning levels as shown in Table 1.
[0051] In this way, the warning threshold can be set based on the logic of mechanism simulation-material testing-standard calibration, so that the warning threshold is consistent with the specific geological conditions of the specific mine and the actual engineering situation, thereby greatly improving the accuracy and reliability of the warning and avoiding false alarms and missed alarms.
[0052] Please continue reading. Figure 1 The coal mine vertical shaft deformation monitoring method in this application embodiment further includes: Step 04: Perform correlation analysis based on anchor bolt stress information and guide beam spacing information to determine fusion analysis data. Based on the fusion analysis data and deformation early warning threshold group, perform early warning and handling for the deformation of the well shaft to be measured.
[0053] Furthermore, in some embodiments, step 04 includes: Based on the force-deformation coupling information, compare it with the deformation early warning threshold group to determine the current early warning level of the wellbore to be measured; Based on the warning level, warning information is issued through preset reminder methods, and response measures associated with the warning level are implemented. The preset reminder methods include at least interface pop-ups, sound and light alarms, and / or SMS reminders.
[0054] Specifically, based on the above implementation method, after obtaining the anchor bolt stress information and the spacing information of the guide beam during continuous monitoring, data analysis software (such as CMPSES) set on a local data server can be used to correlate and merge the two, thereby constructing stress-deformation coupling state information in the data analysis software. Since the anchor bolt stress information and the guide beam spacing information are obtained in real time during continuous monitoring, the stress-deformation coupling state information is also updated in real time. During the real-time updating of the stress-deformation coupling state information, the data analysis software continuously compares this information with the determined anchor bolt stress warning threshold, triggers different warning levels based on the situation shown in Table 1, and further executes the corresponding alarm action to remind the user to take corresponding response measures.
[0055] For example, warning information can be provided to users by popping up windows or making sounds on the local data server based on the warning level, or by controlling other audio-visual devices (such as buzzers, alarm lights, alarm bells, and speakers) to make sounds and lights, or by controlling smartphones, tablets, and other mobile electronic devices to pop up windows, make sounds, vibrate, or send text message reminders through wireless networks, Bluetooth communication, or access communication.
[0056] In this way, the coal mine vertical shaft deformation monitoring method in this application can realize the automatic interpretation of continuous monitoring data, transform the raw data into safety status information that can directly guide subsequent actions, and also associate the early warning level with the response measures, so as to ensure that safety hazards can be detected in time, accurately assessed and immediately activated in a standardized response process, thereby greatly improving the efficiency and standardization of the handling of emergency situations in the shaft to be measured.
[0057] The above description is merely a preferred embodiment of this application and is not intended to limit this application in any way. Although this application has disclosed the preferred embodiment as above, it is not intended to limit this application. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the technical solution of this application. Any simple modifications, equivalent substitutions, and improvements made to the above embodiments without departing from the technical solution of this application, based on the technical essence of this application and within the spirit and principles of this application, shall still fall within the protection scope of the technical solution of this application.
Claims
1. A method for monitoring deformation of a coal mine vertical shaft, characterized in that, The method includes: Multiple morphological scans are performed on the wellbore to be measured in advance to determine the monitoring target area of the wellbore; According to the shape of the well shaft to be measured, a sensor group with preset attributes is arranged in the monitoring target area to obtain anchor stress information and guide beam spacing information in the monitoring target area. The sensor group includes multiple first sensors for monitoring anchor stress and multiple second sensors for monitoring guide beam spacing. Based on the actual geological conditions and attribute parameters of the wellbore to be measured, determine the deformation early warning threshold group of the wellbore to be measured; Based on the anchor bolt stress information and the tank beam spacing information, a correlation analysis is performed to determine the fusion analysis data. Based on the fusion analysis data and the deformation early warning threshold group, early warning and handling are performed on the deformation of the well shaft to be measured.
2. The method according to claim 1, characterized in that, The process of performing multiple morphological scans on the wellbore to determine the monitoring target area includes: Using a preset time period, a preset 3D laser scanner is used to measure the well shaft to be measured, thereby constructing a 3D point cloud model of the well shaft to be measured. A morphological analysis is performed on the three-dimensional point cloud model to determine the quantitative results of the morphological changes of the wellbore to be measured; Based on the quantitative results of the morphological changes, the geological conditions of the well shaft to be measured, and the maintenance history of the mining area where the well shaft to be measured is located, the monitoring target area is determined, wherein the monitoring target area is the weak and vulnerable section of the well shaft to be measured.
3. The method according to claim 2, characterized in that, The morphological analysis performed on the three-dimensional point cloud model to determine the quantified morphological changes of the wellbore to be measured includes: Based on the three-dimensional point cloud model, the wellhead or bottom cross-section of the well shaft to be measured is fitted to determine the quantitative result of the inclination degree of the well shaft to be measured; Based on the three-dimensional point cloud model, the wellbore to be measured is fitted along the wellbore depth direction to determine the quantification results of the significant offset wellbore section of the wellbore to be measured; Based on the three-dimensional point cloud model, an ideal plumb bob cylinder is fitted with the bottom of the well to be measured as a reference to determine the quantification result of the well wall deformation of the well to be measured. The quantification result of the shape change includes the quantification result of the inclination degree, the quantification result of the significantly offset well section and / or the quantification result of the well wall deformation.
4. The method according to claim 1, characterized in that, The step of arranging a sensor group with preset attributes in the monitoring target area according to the shape of the wellbore to be measured includes: According to the shape of the well shaft to be measured, multiple holes are drilled in the well wall of the monitoring target area to install the corresponding first sensor at each of the drill holes, wherein the first sensor is an intrinsically safe anchor bolt stress sensor for mining. According to the shape of the well shaft to be measured, multiple prefabricated fixtures are set on the guide beam of the monitoring target area to install the corresponding second sensor at each prefabricated fixture, wherein the second sensor is an intrinsically safe laser rangefinder for mining.
5. The method according to claim 4, characterized in that, The acquisition of anchor bolt stress information and guide beam spacing information in the monitoring target area includes: Based on a preset intrinsically safe junction box for mining, the first sensor and the second sensor are connected to a preset intrinsically safe data monitoring station for mining, wherein the first sensor sends the anchor stress information to the intrinsically safe data monitoring station for mining, and the second sensor sends the track beam spacing information to the intrinsically safe data monitoring station for mining; The anchor stress information and the spacing information of the guide beam in the monitoring target area are obtained from the intrinsically safe data monitoring station in the mine through a preset mine industrial ring network and sent to the local data server. The mine industrial ring network includes an intrinsically safe explosion-proof power supply and an intrinsically safe gateway.
6. The method according to claim 1, characterized in that, The step of determining the deformation early warning threshold group of the wellbore to be measured based on the actual geological conditions and attribute parameters of the wellbore to be measured includes: Based on the actual geological conditions and support parameters of the well shaft to be measured, a virtual model of the well shaft to be measured is constructed to simulate the quantitative information of the stress and deformation of the well shaft to be measured. The virtual model is used to quantitatively analyze the stress concentration and deformation mechanism of the monitoring target area. Based on the design information of the well shaft to be measured, a concrete specimen of the inner wall of the well shaft to be measured is prepared to determine the stress-strain simulation and quantitative information of the inner wall of the well shaft to be measured. Based on the virtual model and the stress-strain quantification information, the deformation early warning threshold group is calculated and determined, wherein the deformation early warning threshold group includes multiple anchor stress early warning thresholds, and the property parameters of the wellbore to be measured include the support parameters and the design information.
7. The method according to claim 6, characterized in that, The multiple anchor bolt stress warning thresholds divide the anchor bolt stress values into multiple value ranges, each value range corresponds to a warning level, and each warning level is associated with one or more preset response measures.
8. The method according to claim 6, characterized in that, The step of constructing a virtual model of the wellbore to be measured based on the actual geological conditions and support parameters of the wellbore to be measured includes: Based on the actual geological conditions and support parameters of the well shaft to be measured, the stress and deformation of the well shaft to be measured are simulated under the coupled action of the original ground stress field, the mining influence field and / or the groundwater pressure field, so as to construct a virtual model of the well shaft to be measured.
9. The method according to claim 7, characterized in that, The step of performing correlation analysis based on the anchor bolt stress information and the duct beam spacing information to determine the fusion analysis data includes: Based on the actual location information of the well shaft to be measured, the stress information of the anchor bolt and the spacing information of the guide beam are associated to determine the stress-deformation coupling information of the well shaft to be measured. The fusion analysis data includes the stress-deformation coupling information of the well shaft to be measured.
10. The method according to claim 9, characterized in that, The step of performing early warning and handling of the deformation of the wellbore under test based on the fused analysis data and the deformation early warning threshold group includes: Based on the stress-deformation coupling information, the early warning level corresponding to the wellbore to be measured is determined by comparing it with the deformation early warning threshold group. Based on the warning level, a warning message is issued through a preset reminder method, and the response measures associated with the warning level are executed, wherein the preset reminder method includes at least an interface pop-up, an audible and visual alarm, and / or a short message reminder.