An underground roadway deformation monitoring device

Abstract

The present application relates to mine safety equipment technical field, especially in an underground roadway deformation monitoring equipment, including host computer and lower computer, the lower computer includes main frame, drive equipment, acquisition equipment, power equipment, the lower computer includes acquisition module, analysis module, the main frame includes equipment support, the equipment support is divided into multiple models according to the diameter size, the outside annular arrangement of the equipment support has multiple chutes, the drive equipment includes multiple connecting plates set up in the outside of the equipment support, the middle part of the connecting plate is rotatably connected with bidirectional screw rod through rotating stand, the both sides of the bidirectional screw rod are screw connected with extension rod, in the scheme, through self-adapting drive and autonomous movement technology, the unmanned monitoring coverage of high-risk, narrow roadway is realized, through high-precision laser scanning and three-dimensional modeling technology, the full-dimension accurate detection of the deformation of the inner wall of roadway is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mine safety equipment, in particular to an underground roadway deformation monitoring device. BACKGROUND

[0002] The underground roadway is a passageway excavated for the purpose of ventilation, transportation, drainage, pedestrian, etc. in the process of underground mining, and the underground roadway deformation monitoring is a key link to ensure the safety in production of mines, which is directly related to the safety of personnel and the service life of the roadway. At present, the traditional roadway deformation monitoring method mainly relies on artificial periodic patrol or fixed sensor single-point monitoring. The artificial patrol needs personnel to enter the roadway, which has great safety hazards for high-risk areas (such as gas leakage, roof falling hazards). In addition, the artificial observation has low efficiency and limited data coverage, and it is difficult to capture the overall deformation trend of the roadway. Although the fixed sensor can realize real-time monitoring of some areas, the equipment deployment cost is high and the flexibility is poor. Especially for the roadway where ventilation and drainage are impossible for people to pass due to narrow space and harsh environment (such as high humidity, dust, and toxic gas accumulation), the traditional monitoring method faces three technical bottlenecks:

[0003] Significant monitoring blind area: artificial personnel cannot enter the roadway, which leads to a long-term lack of effective monitoring of such roadway, and the deformation hidden danger cannot be found in time, which may cause chain accidents such as failure of ventilation system and rupture of drainage pipeline;

[0004] Low degree of automation: the existing equipment cannot adapt to the complex structure of different diameter roadways, and needs to be adjusted manually. In addition, it is difficult to complete the autonomous movement scanning of the whole roadway without human intervention, and the monitoring efficiency is low;

[0005] Limited data precision and analysis capability: the traditional sensor can only obtain single-point displacement data, lacks global perception of the three-dimensional shape of the inner wall of the roadway, cannot accurately identify local defects such as cracks and depressions, and lacks dynamic risk prediction and intelligent early warning function, which cannot meet the real-time and intelligent needs of mine safety management.

[0006] Therefore, the present application provides an underground roadway deformation monitoring device, which realizes unmanned autonomous monitoring, accurate capture of three-dimensional deformation of the whole inner wall, and dynamic risk early warning in a complex roadway environment through adaptive driving structure design, high-precision laser scanning modeling and intelligent data analysis technology, breaks through the bottleneck of low monitoring efficiency, insufficient data precision and poor degree of automation in the existing technology in high-risk and narrow roadways, and provides an efficient and reliable technical solution for mine roadway safety management. SUMMARY

[0007] The technical problems solved are the problems of significant monitoring blind area, insufficient degree of automation, and limited data precision and analysis capability.

[0008] In view of the deficiencies of the prior art, the present application provides a mine roadway deformation monitoring device, thereby solving the technical problems mentioned in the background art.

[0009] To achieve the above object, the present application is implemented by the following technical solutions:

[0010] A mine roadway deformation monitoring device, comprising an upper computer and a lower computer, the lower computer comprising a main frame, a driving device, a collection device and a power supply device, the lower computer comprising a collection module and an analysis module;

[0011] The main frame comprises a device support, which is divided into multiple types according to the diameter, and multiple chutes are arranged annularly on the outer side of the device support;

[0012] The driving device comprises multiple connecting plates arranged on the outer side of the device support, a bidirectional screw rod is rotatably connected to the middle part of the connecting plate through a rotating frame, two extension rods are threadedly connected to the two sides of the bidirectional screw rod, a rotating slide rod is rotatably connected to the end of each extension rod away from the bidirectional screw rod, a driving wheel is mounted on the end of each rotating slide rod away from the extension rod, a fixed frame is mounted on the two sides of the connecting plate, two rotating sliding blocks are rotatably connected to the top end of each fixed frame, and the rotating slide rod is slidably connected between the two rotating sliding blocks on the same side;

[0013] The collection device and the power supply device are respectively a collector and a storage battery arranged on the front and rear sides of the device support;

[0014] The upper computer is a mine shaft deformation analysis system, which comprises a collection module and an analysis module, the collection module is used for controlling the movement of the underground device and data collection, generating three-dimensional point cloud data of the inner wall of the mine shaft, and the analysis module is used for processing the three-dimensional point cloud and multi-sensor data generated by the collection module, identifying deformation characteristics and evaluating risk levels.

[0015] In a possible implementation, the side of each connecting plate close to the device support is provided with a sliding plate, the sliding plate is slidably connected to the inside of the sliding plate, and the number of chutes changes with the diameter of the device support, that is, the larger the diameter, the more chutes are set up, and the more driving devices can be installed.

[0016] In a possible implementation, a motor a is mounted on the middle part of the connecting plate, a belt pulley set a is mounted between the output end of the motor a and the middle part of the bidirectional screw rod, a motor b is mounted on the end of each rotating slide rod away from the extension rod, and a belt pulley set b is mounted between the output end of the motor b and the driving wheel.

[0017] In a possible implementation, the device support is provided with clamping grooves on both sides, and the outside of the battery and the collector is provided with clamping blocks close to the device support and the clamping grooves, so that the collector and the battery are installed on the device support through the clamping blocks and the clamping grooves.

[0018] In a possible implementation, the inside of the connecting plate is provided with a microcontroller, and the microcontroller is electrically connected with the motor a and the motor b, so as to control the start and stop of the motor a and the motor b.

[0019] In a possible implementation, the microcontroller, the motor a, the motor b and the collector are powered by the battery, and a self-connector terminal is arranged between the collector and the device support, between the device support and the battery and between the connecting plate and the device support, and is used for power supply and signal transmission between the microcontroller, the battery and the collector in the connecting plate.

[0020] In a possible implementation, the collection module includes a scanning control unit, a laser scanning unit and a three-dimensional modeling unit.

[0021] The scanning control unit includes device motion control and collector start-stop control.

[0022] The laser scanning unit includes a laser emission module, a signal receiving module and a scanning mechanism, and uses a distance measurement algorithm to obtain the data of the inner wall of the shaft.

[0023] The three-dimensional modeling unit uses model construction technology to construct a shaft inner wall model based on the distance, horizontal angle and vertical angle data obtained by the laser scanning unit.

[0024] In a possible implementation, the analysis module includes a deformation feature extraction unit, a risk assessment unit and a visualization labeling unit.

[0025] The deformation feature extraction unit uses a K=20 neighbor algorithm to fit a local quadratic surface and calculates the Gaussian curvature K and the average curvature H; K>0 represents a convex surface; K<0 represents a concave surface; and K≈0 represents a plane or a cylindrical surface.

[0026] The angle between the normal vectors of adjacent points is calculated, and if the angle is greater than 60 degrees, the candidate point is marked as a crack candidate point, the candidate points are connected into a crack line segment, and the length, width and extension direction are measured.

[0027] The distance difference AD=D 当前 -D 基准 between the current point cloud and the corresponding point of the reference model is compared, a positive value represents expansion, a negative value represents contraction, and the displacement rate (unit: mm / h); when v>2mm / h, it is determined as a rapid deformation area.

[0028] The risk assessment unit establishes a multi-level early warning model for risk warning: |ΔD|<5mm is safe, 5mm≤|ΔD|<10mm is a warning, and |ΔD|≥10mm is dangerous.

[0029] The visualization annotation unit enables mouse operation and picking / querying through 3D interactive functions, and provides dynamic annotation tools, including deformable vector graphics, risk heat maps, and historical comparison functions. It supports dual-window display of the current model and historical models, automatically calculates the difference, and highlights the changed areas.

[0030] Beneficial effects compared to existing technologies:

[0031] 1. This solution achieves unmanned monitoring coverage in high-risk and narrow tunnels through adaptive drive and autonomous movement technologies. For tunnels inaccessible to personnel, such as those for ventilation and drainage, the equipment uses motor a to drive a bidirectional screw to adjust the extension rod length, allowing the drive wheels to adaptively conform to the inner walls of tunnels with different diameters. A rotating slider allows the sliding rod to swing to adapt to irregular surfaces, enabling equipment fixation without manual intervention. Motor b drives multiple sets of drive wheels to rotate collaboratively, and differential speed control achieves minimum radius turning, allowing the equipment to move autonomously at a constant speed in horizontal, inclined, or curved tunnels. This overcomes the safety limitations of traditional manual inspections and the deployment limitations of fixed sensors, filling monitoring blind spots in high-risk areas and significantly improving monitoring coverage efficiency and safety in complex tunnel environments.

[0032] 2. In this solution, high-precision laser scanning and 3D modeling technology are used to achieve comprehensive and accurate detection of tunnel inner wall deformation. Addressing the limitations of traditional single-point monitoring data, the front-end data acquisition unit employs a 905nm near-infrared laser and a single-photon-level receiver, combined with a 100Hz high-speed galvanometer scan, to acquire 3D point cloud data of the tunnel inner wall with a 0.25° angular resolution. Environmental interference is eliminated through a temperature and humidity compensation algorithm, achieving millimeter-level ranging accuracy. After coordinate transformation, point cloud filtering, and surface reconstruction, the raw data generates a high-precision 3D model containing parameters such as curvature and stress. This model can accurately calculate global deformation indicators such as radial displacement and cross-sectional contraction rate, and can also locate local defects such as millimeter-level cracks and depressions through normal vector analysis. This solves the problem of insufficient ability of traditional technologies to identify complex deformation features, providing comprehensive and reliable data support for tunnel disease diagnosis. Attached Figure Description

[0033] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0034] Figure 1 This is a schematic diagram of the overall structure of the present invention;

[0035] Figure 2 Figure is a schematic diagram of the device support of the present application;

[0036] Figure 3 Figure is a schematic diagram of the chute of the present application;

[0037] Figure 4 Figure is a schematic diagram of the bidirectional screw of the present application;

[0038] Figure 5 Figure is a schematic diagram of the extension rod of the present application;

[0039] Figure 6 Figure is a schematic diagram of the driving wheel of the present application;

[0040] Figure 7 Figure is a schematic diagram of the rotating slider of the present application;

[0041] Figure 8 Figure is a schematic diagram of the collector of the present application;

[0042] Figure 9 Figure is a schematic diagram of the battery of the present application.

[0043] Legend: 1, device support; 2, chute; 3, connecting plate; 4, sliding plate; 5, rotating frame; 6, bidirectional screw; 7, motor a; 8, pulley set a; 9, extension rod; 10, rotating slide rod; 11, driving wheel; 12, motor b; 13, pulley set b; 14, fixed frame; 15, rotating slider; 16, battery; 17, collector; 18, clamping block; 19, clamping groove. DETAILED DESCRIPTION

[0044] The preferred embodiments of the present application will be described in detail with reference to the accompanying drawings, however the present application can be realized in various different forms, therefore the present application is not limited to the embodiments described below, in addition, in order to more clearly describe the present application, components not connected with the invention will be omitted from the accompanying drawings;

[0045] The technical solutions in the embodiments of the present application are to solve the problems in the above background art, and the general idea is as follows:

[0046] Embodiment:

[0047] Please refer to Figures 1 to 9 As shown in the figure, the present embodiment introduces a kind of underground roadway deformation monitoring equipment, the equipment includes host computer and lower computer, the lower computer includes main frame, driving device, acquisition device, power supply equipment, the main frame includes device support 1, the device support 1 is designed as cylindrical shape, as shown in Figure 1 And Figure 9 As shown in the figure, Figure 9For another model of the equipment support 1, the specific model is divided according to the diameter, and the model is selected according to the diameter of the shaft, the equipment support 1 is made of light material, so as to reduce the equipment load in size;

[0048] The equipment support 1 is arranged with a plurality of sliding grooves 2 on the outer side, the number of the sliding grooves 2 changes with the diameter of the equipment support 1, and the more the diameter is, the more the sliding grooves 2 are arranged;

[0049] The driving equipment includes a plurality of connecting plates 3 arranged on the outer side of the equipment support 1, the number of the connecting plates 3 is arranged according to the number of the sliding grooves 2 on the outer side of the equipment support 1, and the plurality of connecting plates 3 are arranged with sliding plates 4 close to one side of the equipment support 1, the sliding plates 4 are slidingly connected in the sliding plates 4, and the sliding grooves 2 and the sliding plates 4 are used for connecting the equipment support 1 and the connecting plates 3;

[0050] The middle part of the connecting plate 3 is rotationally connected with a bidirectional screw rod 6 through a rotating frame 5, a motor a 7 is installed in the middle part of the connecting plate 3, a belt pulley set a 8 is installed between the output end of the motor a 7 and the middle part of the bidirectional screw rod 6, the two sides of the bidirectional screw rod 6 are threadedly connected with extension rods 9, the two extension rods 9 are slidingly connected on the two sides of the connecting plate 3, the extension rods 9 are designed in an elliptical shape, the rotation of the extension rods 9 is limited through the elliptical design of the connecting plate 3 and the extension rods 9, and then the extension rods 9 on the two sides are extended to the two sides through the threaded connection design between the bidirectional screw rod 6 and the extension rods 9 when the bidirectional screw rod 6 rotates;

[0051] The two extension rods 9 are rotationally connected with rotating sliding rods 10 away from the bidirectional screw rod 6, the two rotating sliding rods 10 are installed with driving wheels 11 away from the extension rods 9, the two rotating sliding rods 10 are installed with motors b 12 away from the extension rods 9, and the belt pulley set b 13 is installed between the output end of the motor b 12 and the driving wheel 11;

[0052] The two sides of the connecting plate 3 are installed with fixing frames 14, the top ends of the two fixing frames 14 are rotationally connected with two rotating sliding blocks 15, and the rotating sliding rods 10 are slidingly connected between the two rotating sliding blocks 15 on the same side;

[0053] Specifically, the connecting plate 3 is arranged in an annular shape on the outer side of the equipment support 1, a starting motor a7 drives a double-way screw rod 6 to rotate through a transmission belt of a belt pulley set a8, the double-way screw rod 6 drives the extension rods 9 on both sides to extend to both sides, when the extension rods 9 on both sides extend, the rotating slide rods 10 on both sides are pushed to extend, since the rotating slide rods 10 on both sides are slidably connected between the two rotating slide blocks 15 on the same side, the rotating slide rods 10 on both sides will drive the driving wheels 11 to extend to the outer side, until the driving wheels 11 are pushed to press the inner wall of the shaft, then a starting motor b12 drives the driving wheels 11 to rotate through a transmission belt of a belt pulley set b13, thereby driving the whole equipment to move in the shaft;

[0054] Please refer to Figure 8 As shown in the drawings, the collecting device and the power supply device are a collector 17 and a storage battery 16 arranged on the front and rear sides of the equipment support 1, the equipment support 1 is provided with a clamping groove 19 on both sides, the storage battery 16 and the collector 17 are provided with a clamping block 18 near the junction of the equipment support 1 and the clamping groove 19 on the outer side, the clamping block 18 and the clamping groove 19 are clamped to install the collector 17 and the storage battery 16 on the equipment support 1;

[0055] Specifically, the side where the collector 17 is located is the front direction side, the collector 17 scans the inner wall of the shaft, then transmits the host computer for analysis, and then judges the deformation of the shaft from the inner wall of the shaft;

[0056] The microcontroller is installed in the connecting plate 3, the microcontroller is electrically connected with the motor a7 and the motor b12, and the microcontroller controls the start and stop of the motor a7 and the motor b12;

[0057] The microcontroller, the motor a7, the motor b12 and the collector 17 are powered by the storage battery 16, and the collector 17 and the equipment support 1, the equipment support 1 and the storage battery 16, and the connecting plate 3 and the equipment support 1 are provided with self-connector terminals for power supply and signal transmission between the microcontroller in the connecting plate 3, the storage battery 16 and the collector 17;

[0058] The host computer should bear the functions of data receiving, processing, analysis, storage and control instruction sending, the host computer is a shaft deformation analysis system, which includes a collecting module and an analysis module, and specifically as follows:

[0059] I. The collecting module controls the movement of the underground equipment and data collection, generates three-dimensional point cloud data of the inner wall of the shaft, and provides original input for analysis.

[0060] 1. Scanning control unit

[0061] 1.1. Equipment movement control

[0062] Through the instruction regulation of the lower computer motor a7 and motor b12, the length of the extension rod 9 is adjusted by the control of the bidirectional screw rod 6, so that the driving wheel 11 is attached to the well tunnel with different diameters, the driving wheel rotates synchronously, the equipment moves at a constant speed along the central axis of the well tunnel, the differential control inside driving wheel is triggered to slow down, the outside is accelerated, and the minimum radius turning is realized by cooperating with the rotating sliding block 15;

[0063] 1.2, collector start-stop control

[0064] Send pulse signals to the collector 17 to activate / close the laser emitter, sensor array; Support timed collection (such as automatically starting scanning every hour) and event-triggered collection (such as automatically scanning when the lower computer detects a sudden vibration);

[0065] 2, laser scanning unit (i.e. collector 17)

[0066] 2.1, hardware composition

[0067] Laser emission module, 905nm near-infrared pulse laser, the laser beam divergence angle is compressed to within 0.5°, which improves the measurement accuracy.

[0068] Signal receiving module, avalanche photodiode receiver, detection sensitivity reaches single photon level, band-pass filter, center wavelength 905nm, filter environmental light interference;

[0069] Scanning mechanism: high-speed galvanometer, scanning frequency 100Hz, realizing fast scanning in horizontal direction 0°-360°, angle resolution 0.25°, vertical direction through device movement to realize data superposition, forming spiral scanning track;

[0070] 2.2, distance measurement algorithm

[0071] Where, c is the speed of light in vacuum (3x108m / s), t is the round-trip time of laser (measured by high-precision timer, resolution 1ns), n(T) is the air refractive index, which is calculated in real time based on temperature and humidity sensor data (temperature compensation formula P is the air pressure, T is the temperature);

[0072] 3, three-dimensional modeling unit

[0073] 3.1, point cloud generation process

[0074] Raw data collection: laser scanning to obtain distance (D), horizontal angle (θ), vertical angle

[0075] Coordinate conversion: Z = device odometer data;

[0076] Timestamp synchronization: Add nanosecond-level timestamp to each point cloud, associate with device moving trajectory (get position information through drive wheel encoder).

[0077] 3.2 Model construction technology

[0078] Point cloud filtering:

[0079] Statistical filtering: Remove outliers (such as dust reflection points);

[0080] Voxel filtering: Reduce point cloud density to improve rendering efficiency (regular area point spacing 10mm, key area 2mm);

[0081] Surface reconstruction:

[0082] Based on the greedy projection triangulation algorithm, the point cloud is fitted into a continuous triangular mesh;

[0083] Texture mapping: If equipped with a high-definition camera, the shaft image can be textured to the three-dimensional model to enhance the visualization effect;

[0084] II. Analysis module, process the three-dimensional point cloud and multi-sensor data generated by the acquisition module, identify deformation features and evaluate risk level;

[0085] 1. Deformation feature extraction unit

[0086] 1.1 Curvature calculation:

[0087] For each point cloud, fit a local quadratic surface through the K-nearest neighbor algorithm (K=20), calculate the Gaussian curvature (K) and the average curvature (H):

[0088] K>0: Convex surface (such as shaft wall protrusions);

[0089] K<0: Concave surface (such as cracks or depressions);

[0090] K≈0: Plane or cylinder (normal shaft wall);

[0091] 1.2 Crack detection:

[0092] Based on the discontinuity of point cloud normal vector: Calculate the angle between adjacent point normal vectors, if >60°, mark as a crack candidate point;

[0093] Morphological dilation processing: Connect candidate points into crack line segments, measure length (L), width (W) and extension direction (μ).

[0094] 1.3 Deformation calculation

[0095] Radial displacement: Compare the distance difference (ΔD=D 当前 -D 基准Positive value indicates expansion, negative value indicates contraction;

[0096] Displacement rate: (unit: mm / h); when v> 2 mm / h, it is determined as a fast deformation region;

[0097] 2, risk assessment unit

[0098] Multi-level early warning model

[0099] Risk level Decision condition Visual identification Safe |ΔD| < 5 mm Green Warning 5 mm < |ΔD| < 10 mm Yellow Danger |ΔD|≥10mm Red

[0100] Trend prediction

[0101] Adopt long short-term memory network (LSTM) modeling, input historical displacement data (past 7 days), output future 3 days deformation prediction value;

[0102] Confidence evaluation: if the prediction value confidence interval exceeds ±2mm, trigger encryption monitoring (scan frequency is increased to 200Hz).

[0103] 3, visual labeling unit

[0104] Three-dimensional interaction function

[0105] Mouse operation: left button rotates the model, right button pans, and scroll wheel zooms in and out;

[0106] Pickup query: click on any point of the model, and a pop-up window will display the distance, curvature, stress value and other parameters of the point.

[0107] Dynamic labeling tool

[0108] Deformation vector diagram: use arrows to mark displacement direction and size (arrow length is proportional to |ΔD|);

[0109] Risk heat map: render color gradient on the surface of the three-dimensional model to intuitively display deformation distribution (green-yellow-red corresponds to displacement from small to large);

[0110] History comparison: support double window display of current model and historical model (such as 1 month ago), automatically calculate the difference and highlight the change area.

[0111] In summary, the specific operation process of the device is as follows:

[0112] 1, device operation process

[0113] Drive wheel adaptive stretching

[0114] Start motor a (7), bidirectional screw (6) rotation push extension rod (9) to stretch out, drive rotating slide bar (10) and drive wheel (11) extrude the inner wall of roadway; Rotating slide block (15) allows the slide bar to swing slightly, ensuring that the drive wheel is tightly attached to the irregular inner wall, completing the device fixation and support;

[0115] Autonomous movement in the roadway

[0116] After the drive wheel is attached to the inner wall, start motor b (12) to drive the drive wheel to rotate through belt pulley set b (13), driving the device to move along the axial direction of the roadway; Multiple sets of drive wheels rotate in coordination to provide stable driving force, adapting to horizontal or inclined roadways;

[0117] Dynamic data acquisition

[0118] The collector (17) located at the front end of the device moves in real time to scan the inner wall of the roadway, obtaining point cloud data, surface texture, and geometric size information of the inner wall through three-dimensional laser scanning;

[0119] 2、Data analysis process

[0120] 2.1、Original data acquisition

[0121] The collector (17) collects three-dimensional coordinate data (X, Y, Z), distance information, and image texture (if equipped with a visual sensor) of the inner wall of the roadway at a set frequency (such as 10 frames per second), forming original point cloud data or mesh models;

[0122] 2.2、Coordinate conversion

[0123] Convert the data in the collector coordinate system to the global coordinate system of the roadway (such as taking the wellhead as the origin and the axial direction of the roadway as the Z axis), facilitating the splicing of multiple segments of data;

[0124] 2.3、Data splicing and registration

[0125] If the device is moved in segments for collection (such as multiple deployments for long-distance roadways), use ICP (iterative closest point) algorithm or feature matching technology to splice multiple segments of point cloud data into a complete three-dimensional model of the inner wall of the roadway;

[0126] 2.4、Reference model comparison

[0127] Establish an initial reference model of the roadway (design drawings or historical monitoring data), and perform point-to-point matching or mesh superposition between the current three-dimensional model and the reference model to calculate the displacement deviation (ΔX, ΔY, ΔZ) of each point;

[0128] Focus on analyzing key indicators such as roadway roof and floor subsidence (Z-axis deviation) and two-side convergence (X / Y-axis deviation) to generate a deformation cloud chart (color-coded to represent deformation);

[0129] 2.5, Feature parameter calculation

[0130] Extracting the cross-section shrinkage of the roadway: calculating the difference ratio of the current cross-section area and the reference cross-section area to determine whether the roadway has a reduced traffic or ventilation capacity due to deformation;

[0131] Identifying local defects such as cracks, protrusions, and depressions: positioning abnormal areas through curvature analysis and edge detection algorithm, and measuring defect size (length, depth);

[0132] 2.6, Time series trend analysis

[0133] If it is periodic monitoring (such as once a month), compare multiple periods of data to analyze the development trend of deformation over time and predict potential risks (such as accelerated deformation rate indicating the need for reinforcement);

[0134] 2.7, Visual report

[0135] Generate a three-dimensional visualization model of roadway deformation, a deformation amount statistical table, and a trend curve graph, support interactive operations such as zooming and rotating, and facilitate intuitive analysis by engineers;

[0136] 2.8, Early warning mechanism

[0137] Set a deformation threshold (such as roof and floor subsidence > 50 mm, two-way convergence > 30 mm), when the measured value exceeds the threshold, the system automatically triggers an audible and visual alarm, and sends a short message and an email to the manager;

[0138] Output risk level assessment results (such as safe, attention, and dangerous) to provide a basis for roadway maintenance plans (such as local support and overall reinforcement).

[0139] Finally, it should be noted that: obviously, the above embodiments are only examples for clearly illustrating the present application, and are not limited to the implementation. For ordinary skilled in the art, on the basis of the above description, other different forms of changes or variations can also be made. Here, it is not necessary and impossible to exhaust all the implementation. The obvious changes or variations derived therefrom are still within the scope of the present application.

Claims

1. A deformation monitoring device for underground roadways, characterized in that, It includes a host computer and a slave computer. The slave computer includes a main frame, a drive device, a data acquisition device, and a power supply device. The slave computer also includes a data acquisition module and an analysis module. The main frame includes an equipment support (1); The driving device includes multiple connecting plates (3) set on the outside of the device bracket (1). A bidirectional screw (6) is rotatably connected to the middle of the connecting plate (3) via a rotating frame (5). Extension rods (9) are threaded to both sides of the bidirectional screw (6). Rotating slide rods (10) are rotatably connected to the ends of the two extension rods (9) away from the bidirectional screw (6). Drive wheels (11) are installed at the ends of the two rotating slide rods (10) away from the extension rods (9). Fixing frames (14) are installed on both sides of the connecting plate (3). Two rotating sliders (15) are rotatably connected to the top of the two fixing frames (14). The rotating slide rods (10) are slidably connected between the two rotating sliders (15) on the same side. The equipment bracket (1) is divided into various models according to its diameter. Multiple sliding grooves (2) are arranged in a ring on the outer side of the equipment bracket (1). Multiple connecting plates (3) are provided with sliding plates (4) on the side near the equipment bracket (1). The sliding plates (4) are slidably connected to the inside of the sliding grooves (2). The number of sliding grooves (2) varies with the diameter of the equipment bracket (1). The larger the diameter, the more sliding grooves (2) are provided. The more sliding grooves (2) there are, the more drive devices can be installed. The data acquisition device and the power supply device are respectively the data acquisition device (17) and the battery (16) installed on the front and rear sides of the equipment bracket (1). The host computer is a wellbore deformation analysis system, which includes an acquisition module and an analysis module. The acquisition module is used to control the movement of downhole equipment and data acquisition, and generate three-dimensional point cloud data of the wellbore inner wall. The analysis module is used to process the three-dimensional point cloud and multi-sensor data generated by the acquisition module, identify deformation features and assess the risk level. The analysis module includes a deformation feature extraction unit, a risk assessment unit, and a visualization annotation unit; The deformation feature extraction unit uses a nearest neighbor algorithm. Fit a local quadratic surface and calculate the Gaussian curvature. With mean curvature ; Convex surface; concave surface; Plane or cylindrical surface; Calculate the angle between the normal vectors of adjacent points. If it is greater than 60°, mark it as a candidate crack point. Connect the candidate points to form a crack line segment and measure its length, width and extension direction. Compare the distance difference between the current point cloud and the corresponding points in the baseline model. , The raw distance values ​​obtained from laser scanning; positive values ​​indicate expansion, and negative values ​​indicate contraction; displacement rate. , For the laser round trip time; when At that time, it was determined to be a rapid deformation zone; The risk assessment unit conducts risk warnings by establishing a multi-level early warning model. Safety, Warning, Danger; The visualization annotation unit enables mouse operation and picking / querying through 3D interactive functions, and provides dynamic annotation tools, including deformable vector graphics, risk heat maps, and historical comparison functions. It supports dual-window display of the current model and historical models, automatically calculates the difference, and highlights the changed areas.

2. The underground roadway deformation monitoring device as described in claim 1, characterized in that, A motor a (7) is installed in the middle of the connecting plate (3). A pulley set a (8) is installed between the output end of the motor a (7) and the middle of the bidirectional screw (6). A motor b (12) is installed at the end of each of the two rotating slide rods (10) away from the extension rod (9). A pulley set b (13) is installed between the output end of the motor b (12) and the drive wheel (11).

3. The underground roadway deformation monitoring device as described in claim 1, characterized in that, The device bracket (1) has slots (19) on both sides. The battery (16) and the collector (17) are provided with blocks (18) near the junction of the device bracket (1) and the slots (19). The blocks (18) engage with the slots (19) to install the collector (17) and the battery (16) on the device bracket (1).

4. The underground roadway deformation monitoring device as described in claim 1, characterized in that, The connecting plate (3) is equipped with a microcontroller, which is electrically connected to motor a (7) and motor b (12). The microcontroller controls the start and stop of motor a (7) and motor b (12).

5. The underground roadway deformation monitoring device as described in claim 1, characterized in that, The microcontroller, motor a (7), motor b (12), and data acquisition device (17) are all powered by the battery (16). The data acquisition device (17) and the equipment bracket (1), the equipment bracket (1) and the battery (16), and the connecting plate (3) and the equipment bracket (1) are all provided with self-connecting terminals, which are used for power and signal transmission between the microcontroller, the battery (16), and the data acquisition device (17) inside the connecting plate (3).

6. The underground roadway deformation monitoring device as described in claim 1, characterized in that, The acquisition module includes a scanning control unit, a laser scanning unit, and a 3D modeling unit; The scanning control unit includes device motion control and collector (17) start / stop control. The laser scanning unit includes a laser emitting module, a signal receiving module, and a scanning mechanism, and uses a distance measurement algorithm to acquire data of the inner wall of the well. The three-dimensional modeling unit uses the distance, horizontal angle, and vertical angle data obtained by the laser scanning unit to construct a model of the wellbore inner wall using model building technology.

Images