Method and system for dynamic evaluation of passability of monorail hoist in underground coal mine roadway

Abstract

A method and system for dynamic evaluation of the passability of a monorail hoist in an underground coal mine roadway. The method comprises acquiring roadway video information by means of a video capture device, and analyzing and identifying a location having rock damage or deformation in a roadway; for the location having damage or deformation, reducing the travel speed of a monorail hoist in advance, and using three-dimensional laser point cloud technology to analyze the amount of deformation; by referring to a range of critical dimensions of the monorail hoist, preliminarily assessing the passability of the monorail hoist in a current roadway, and if it is determined to be impassable, performing multi-point cloud offline fitting for precise determination; on the basis of a determination result, evaluating the passability of the monorail hoist, and providing a travel recommendation. The described method and system can achieve dynamic evaluation of the passability of a monorail hoist in an underground coal mine roadway, ensuring safe operation of the monorail hoist.

Description

A method and system for dynamic evaluation of the mobility of monorail cranes in underground coal mine roadways Technical Field

[0001] This invention belongs to the technical field of underground auxiliary transportation equipment in coal mines, specifically relating to a dynamic evaluation method for the mobility of a monorail crane in underground coal mine roadways under deep confined spaces. Background Technology

[0002] Monorail cranes, as crucial transportation equipment in underground coal mine auxiliary transportation systems, play a vital role in coal mine production and transportation. The assessment of the drivability of monorail cranes in underground coal mine roadways is an important aspect of coal mine safety management and the intelligentization of mining equipment, aiming to ensure the safe operation of underground auxiliary transportation equipment.

[0003] Currently, the assessment of the accessibility of monorail cranes in underground coal mine roadways mainly relies on traditional manual inspections and visual checks. These methods have many problems and limitations, including:

[0004] Traditional manual inspections rely primarily on the driver's experience and visual observation, which has low accuracy and is severely limited in frequency. Coal mines have complex underground environments, frequently experiencing special conditions such as anchor bolt detachment, roof subsidence, sidewall shifting, and surrounding rock deformation. In these situations, manual inspections struggle to detect the type of damage in a timely manner, leading to significant safety risks. For example, anchor bolt detachment can cause the roof to lose support, resulting in dangerous situations like roof subsidence, which manual inspections often fail to detect promptly.

[0005] Visual inspection methods primarily acquire cross-sectional shape information of roadways using sensors such as cameras. However, due to the deep, confined spaces of coal mine roadways, the environment differs significantly from surface roads, with issues such as uneven lighting and insufficient illumination. This results in incomplete and indistinct cross-sectional shape features obtained from visual images, making it impossible to accurately predict and assess roadway risks and failing to meet the needs of assessing the drivability of monorail cranes in underground coal mine roadways. Furthermore, existing methods are mostly based on static measurement and assessment, making it difficult to rapidly detect deformation and drivability along the entire roadway route.

[0006] LiDAR sensors can measure details on the surface of roadways and are unaffected by ambient light, thus they are widely used in environmental perception. For example, a method for extracting feasible regions of structured roads based on three-dimensional LiDAR, published in application number CN 201810169285 X, takes single-line point clouds as the research object, uses K-means clustering to optimize the extraction of obstacles, and combines the DBSCAN clustering algorithm to extract the road edges to obtain the feasible region. However, this method is designed for structured roads. The working conditions of underground roadways are very different from those of structured roads on the ground. There are a large number of special obstacle types and factors that have unique effects on the passability of monorails underground. These factors make this method not universal in road conditions such as underground roadways in coal mines, and it is difficult to effectively assess the passability of monorails.

[0007] The application publication number CN 116929363 A describes an autonomous navigation method for mining vehicles based on a passable map. It uses lidar data to conduct a feasibility analysis of mining transport vehicles. However, this method is mostly used to identify obstacles on the mining ground and cannot identify the passability of monorail cranes under special working conditions such as the approach of the two sides of the roadway and roof deformation.

[0008] On the other hand, some current dynamic measurement methods mainly rely on point cloud data, but the amount of point cloud data is often very large, which places extremely high demands on computing power. In the actual underground environment of coal mines, excessive data volume and computing power requirements will seriously affect the timeliness and effectiveness of the assessment. Summary of the Invention

[0009] To overcome the shortcomings of the prior art, the present invention provides a method and system for dynamic evaluation of the accessibility of monorail cranes in underground coal mine roadways, which can realize dynamic evaluation of the accessibility of monorail cranes in underground coal mine roadways and assist in the safe operation of monorail cranes.

[0010] To achieve the above objectives, the present invention adopts the following technical solution:

[0011] A method for dynamically evaluating the mobility of monorail cranes in underground coal mine roadways includes the following steps:

[0012] S1: Visual information of the rock surface in the tunnel is obtained by video acquisition equipment installed on the monorail to identify the places where the rock in the tunnel is damaged or deformed;

[0013] S2. For areas where rock damage or deformation is identified, reduce the monorail travel speed to 30%-50% of the original speed in advance; at the same time, acquire point cloud data of the tunnel through point cloud data acquisition equipment installed on the monorail, and analyze the deformation of the tunnel rock using three-dimensional laser point cloud analysis method.

[0014] S3: Make a preliminary assessment of the maneuverability of the monorail in the current roadway, using the range of the monorail's height and width dimensions as a reference. If the preliminary assessment indicates that it is passable, the monorail will continue to travel at normal speed; if the preliminary assessment indicates that it is not passable, proceed to step S4.

[0015] S4. Accurately assess the mobility of the monorail in the current roadway, perform multi-point cloud offline fitting using the acquired point cloud data of the roadway, obtain the roadway cross-sectional contour data, and calculate the precise deformation of the roadway rock.

[0016] S5: Based on the precise deformation of the roadway rock calculated in step S4, the dimensions of the vehicle, and the provisions of the "Coal Mine Safety Regulations", provide travel suggestions for the monorail crane.

[0017] In step S2, for cases where there is no surface damage to the tunnel, the three-dimensional laser point cloud is sparsed to determine the amount of tunnel deformation.

[0018] In step S1, an object detection algorithm is used to identify areas where the rocks in the tunnel are damaged or deformed. Tunnel images containing both normal and damaged / deformed rocks are collected as a training set, and the rock areas and their states are labeled to train the object detection model.

[0019] In step S2, the three-dimensional laser point cloud analysis method adopts the point cloud registration method or the point cloud comparison method.

[0020] In step S3, the preliminary assessment of the passability of the monorail in the current roadway is made if the following two formulas are satisfied simultaneously, then the preliminary assessment is that it is passable; otherwise, the preliminary assessment is that it is not passable.

[0021] 0 < Δh ≤ 0.1h

[0022] 0 < Δw ≤ 0.05w

[0023] Where h is the height of the monorail crane body; w is the width of the monorail crane body.

[0024] In step S4, the method for offline fitting of multi-point clouds specifically includes the following steps:

[0025] S41. Extract the centerline data of the tunnel based on the ground and tunnel side projections, including the following sub-steps.

[0026] S411. Using the sensor of the point cloud acquisition device that collects the point cloud data of the roadway as the origin O, establish an XYZ three-axis coordinate system, where the X-axis is the axial direction of the roadway, the XOY plane is the ground, and the XOZ plane is the side of the roadway.

[0027] S412. Project the tunnel point cloud data onto the XOY plane and XOZ plane in the three-axis coordinate system respectively, and extract the two-dimensional boundary point set of the tunnel projection.

[0028] S413. Set a certain step size Δx along the roadway axis in the XOY and XOZ planes, and sample the boundary point set at equal intervals to extract x. i The maximum value of the boundary point set along the y-axis corresponding to (i = 1, 2, 3, ..., n) is y. i(max) With minimum value y i(min) The maximum value z of the boundary point set corresponding to the z-axis direction i(max) With minimum value z i(min) ;

[0029] S414. Using the midpoint formula and Calculate the set values ​​of boundary points along the y-axis and z-axis to obtain the midpoint set M = {m1, m2, m3, ..., m} in the XOY plane. n The set of points N in the XOZ plane is N = {n1, n2, n3, ..., n}. n The tunnel centerline is obtained by fitting the midpoint set of the XOY plane and the midpoint set of the XOZ plane.

[0030] S42. Using a RANSAC-based roadway cross-section profile separation model, obtain the roadway cross-section profile data and calculate the deformation, including the following sub-steps:

[0031] S421. Calculate the angle α between the tunnel centerline and the XOY plane and the angle β between the tunnel centerline and the XOZ plane extracted in step S414.

[0032] S422. Based on the included angles α and β, transform the coordinates of the roadway point cloud data so that the central axis of the transformed roadway point cloud data is parallel to the X-axis. The calculation formulas before and after the transformation are:

[0033]

[0034] Among them [XYZ] T The original coordinates of the tunnel point cloud are [X'Y'Z']. T The coordinates of the converted tunnel point cloud;

[0035] S423. The adjusted roadway point cloud data is sliced ​​along the X-axis at certain intervals δ and thickness d according to the point cloud processing speed. The sliced ​​point cloud data is then projected and fitted based on the RANSAC algorithm to obtain the roadway cross-sectional contour data and calculate the precise deformation.

[0036] In step S423, the adjusted roadway point cloud data is sliced ​​along the X-axis at certain intervals δ and thickness d according to the point cloud processing speed. To achieve continuous processing of the slices, the vehicle is still located before the processed slice after all slices have been processed. The time required to process the point cloud of one slice is denoted as T. 计Let the monorail's travel speed be V, its braking time be t, and the distance between the monorail and the processed slice section be denoted as δ1. Then, the determination of δ1 satisfies the formula: The interval between the two slice sections is δ2. To ensure that the monorail can brake in time when identifying impassable areas, δ2 must satisfy the following formula: and

[0037]

[0038] Step S5 specifically involves: the monorail needs to consider the swaying that occurs during the operation of the equipment, and its maximum swing amplitude needs to be considered as 10°. In addition to the maximum swing amplitude, a safety distance of at least 200mm should be set between the monorail and the tunnel wall, a safety distance of 500mm should be set between the monorail and the top of the tunnel, and a safety distance of 400mm should be set between the bottom of the monorail and the bottom of the tunnel. Based on these regulations, a safe passage area model for transport vehicles should be designed.

[0039] The specific travel advice provided to the monorail is: to brake in a timely manner or change the travel route.

[0040] This invention further discloses a dynamic evaluation system for the mobility of monorail cranes in underground coal mine roadways, comprising:

[0041] The video acquisition module is used to acquire video information from the tunnel.

[0042] The video analysis module is used to perform frame extraction analysis on video information to identify areas where the rocks in the tunnel are damaged or deformed.

[0043] The point cloud acquisition module is used to acquire point cloud data of the tunnel.

[0044] The point cloud processing module is used to process 3D laser point clouds and analyze the precise deformation of tunnel rocks.

[0045] The accessibility assessment module is used to accurately assess the accessibility of a monorail crane based on the precise deformation of the rock in the tunnel.

[0046] The decision suggestion module is used to provide travel suggestions for monorails based on the evaluation results.

[0047] The beneficial effects of this invention are:

[0048] First, the present invention provides a dynamic assessment method for the traversability of a monorail in an underground coal mine roadway. Compared with existing traditional static measurement and assessment, the present invention utilizes on-board sensors to achieve rapid detection of moving deformation, enabling dynamic assessment of deformation and traversability of the entire roadway.

[0049] Secondly, unlike existing dynamic measurement point cloud methods, which involve large amounts of data and high computational requirements, this invention combines vision and point cloud, using visual information to assist in point cloud data processing. This effectively reduces the amount of data computation, increases data processing speed, and is more conducive to timely and accurate assessment of the maneuverability of monorail cranes in complex underground coal mine environments.

[0050] Third, this invention is mainly based on point cloud sensors. For underground vehicles with existing lidar sensors, the software can be directly upgraded, and for underground vehicles without lidar sensors, only the addition of lidar sensors is needed to upgrade the hardware. Attached Figure Description

[0051] Figure 1 is a flowchart of a method for dynamic evaluation of the mobility of a monorail in an underground roadway of a coal mine according to the present invention.

[0052] Figure 2 is a module diagram of a dynamic evaluation system for the mobility of a monorail crane in an underground roadway of a coal mine according to the present invention.

[0053] Figure 3 is a schematic diagram of the structure of the present invention;

[0054] Figure 4 is a schematic diagram of the cross-sectional spacing selection rules of the present invention;

[0055] Figure 5 is a schematic diagram of the safe passable area of ​​the present invention. Detailed Implementation

[0056] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0057] Please refer to Figure 1. This invention discloses a method for dynamically evaluating the mobility of a monorail crane in an underground coal mine roadway, including the following steps:

[0058] S1: Visual information of the rock surface in the tunnel is obtained by video acquisition equipment installed on the monorail to identify the places where the rock in the tunnel is damaged or deformed;

[0059] S2. For areas where rock damage or deformation is identified, reduce the monorail travel speed to 30%-50% of the original speed in advance; at the same time, acquire point cloud data of the tunnel through point cloud data acquisition equipment installed on the monorail, and analyze the deformation of the tunnel rock using three-dimensional laser point cloud analysis method.

[0060] S3: Make a preliminary assessment of the maneuverability of the monorail in the current roadway, using the range of the monorail's height and width dimensions as a reference. If the preliminary assessment indicates that it is passable, the monorail will continue to travel at normal speed; if the preliminary assessment indicates that it is not passable, proceed to step S4.

[0061] S4. Accurately assess the mobility of the monorail in the current roadway, perform multi-point cloud offline fitting using the acquired point cloud data of the roadway, obtain the roadway cross-sectional contour data, and calculate the precise deformation of the roadway rock.

[0062] S5: Based on the precise deformation of the roadway rock calculated in step S4, the dimensions of the vehicle, and the provisions of the "Coal Mine Safety Regulations", provide travel suggestions for the monorail crane.

[0063] The video acquisition devices in step S1 include, but are not limited to, cameras and video cameras, and the point cloud acquisition devices include, but are not limited to, lidar and binocular cameras.

[0064] The identification of rock damage or deformation in the tunnel can be achieved using target detection algorithms, such as Faster R-CNN and YOLO series algorithms. A large number of tunnel images containing normal and damaged / deformed rocks can be collected as a training set, and the rock areas and states can be labeled to train the target detection model.

[0065] The methods for analyzing deformation using three-dimensional laser point cloud technology in step S2 include, but are not limited to, point cloud matching and point cloud comparison.

[0066] In step S3, the initial assessment of passability is made by referring to the range of key dimensions of the monorail. Considering the height h of the monorail, when the spatial change Δh caused by the deformation of the top of the roadway meets the condition of 0 < Δh ≤ 0.1h, and the width w of the monorail, when the deformation Δw on both sides of the roadway meets the condition of 0 < Δw ≤ 0.05w, it can be initially assessed as passable; otherwise, it is initially assessed as impassable.

[0067] The method for offline fitting of multi-point clouds in step S4 includes the following steps:

[0068] S41. Extract the centerline data of the tunnel based on the ground and tunnel side projections.

[0069] S411. Using the sensor of the point cloud acquisition device that collects the point cloud data of the roadway as the origin O, establish an XYZ three-axis coordinate system, where the X-axis is the axial direction of the roadway, the XOY plane is the ground, and the XOZ plane is the side of the roadway.

[0070] S412. Project the tunnel point cloud data onto the XOY plane and XOZ plane in the three-axis coordinate system respectively, and extract the two-dimensional boundary point set of the tunnel projection.

[0071] S413. Set a certain step size Δx along the roadway axis in the XOY and XOZ planes, and sample the boundary point set at equal intervals to extract x. i The maximum value of the boundary point set along the y-axis corresponding to (i = 1, 2, 3, ..., n) is y. i(max) With minimum value y i(min)The maximum value z of the boundary point set corresponding to the z-axis direction i(max) With minimum value z i(min) ;

[0072] S314. Calculate the set values ​​of boundary points along the y-axis and z-axis using the midpoint formula to obtain the midpoint set M = {m1, m2, m3, ..., m} in the XOY plane. n The set of points N in the XOZ plane is N = {n1, n2, n3, ..., n}. n The tunnel centerline is obtained by fitting the midpoint set of the XOY plane and the midpoint set of the XOZ plane.

[0073] S42. Using a RANSAC-based tunnel cross-section profile separation model, tunnel cross-section profile data is obtained and deformation is calculated.

[0074] S421. Calculate the angles between the tunnel centerline extracted in S1 and the ground (XOY plane) and the tunnel side (XOZ plane), and denote them as α and β, respectively.

[0075] S422. Based on the angle between the tunnel centerline and the ground and tunnel sides, transform the tunnel point cloud data coordinates so that the centerline of the transformed tunnel point cloud data is parallel to the X-axis. The calculation formulas before and after the transformation are:

[0076]

[0077] Among them [XYZ] T The original coordinates of the tunnel point cloud are [X'Y'Z']. T The coordinates of the converted tunnel point cloud;

[0078] S423. The adjusted roadway point cloud data is sliced ​​along the X-axis at a certain interval δ and thickness d. The sliced ​​point cloud data is then projected and fitted based on the RANSAC algorithm to obtain the roadway cross-sectional contour data and calculate the deformation.

[0079] Please refer to Figure 4. In S423, the adjusted roadway point cloud data is sliced ​​along the X-axis at certain intervals δ and thickness d according to the point cloud processing speed. To achieve continuous processing of the slices, ensuring that the vehicle is still in the position before the processed slice after all slices have been processed, the time required for the industrial control computer to process one slice of point cloud is denoted as T. 计 The monorail's travel speed is V, its braking time is t, and the distance between the monorail and a section being treated is denoted as δ1. The determination of δ1 requires satisfying the formula: The distance between the two sections is δ2. To ensure that the monorail can brake in time when identifying impassable areas, the determination of δ2 must simultaneously satisfy the following formula: and

[0080]

[0081] Please refer to Figure 5. The basis for accurately assessing the passability of the monorail in S4 includes, but is not limited to, the deformation of the roadway, the size and performance of the vehicle, and safety regulations. The "Coal Mine Safety Regulations" stipulate that the monorail must take into account the swaying and other conditions that occur during the operation of the equipment. It is necessary to consider its maximum swing amplitude ±10°. In addition to the maximum swing amplitude, a safety distance of at least 200mm is required, and a safety distance of 500mm is required at the top and 400mm is required at the bottom. The safe passability area model of the monorail should be designed according to this regulation.

[0082] The implementation process for providing travel suggestions to the monorail in step S5 is as follows: when the assessment result is that it is passable, the monorail maintains its normal speed and travels along the original route; when the preliminary assessment result is that it is not passable, the monorail reduces its speed and waits for the industrial control computer to output the accurate assessment result; when the accurate assessment result is that it is not passable, the monorail needs to brake in time or change its travel route.

[0083] This invention also discloses a dynamic assessment system for the drivability of a monorail crane in an underground coal mine roadway, comprising: a video acquisition module, a video analysis module, a point cloud acquisition module, a point cloud processing module, a drivability assessment module, and a decision suggestion module; the video acquisition module includes video acquisition equipment installed in the monorail crane or roadway for acquiring video information of the roadway; the video analysis module is used to perform frame extraction analysis on the video information to identify areas of rock damage or deformation in the roadway; the point cloud acquisition module includes point cloud acquisition equipment installed in the monorail crane or roadway for acquiring point cloud data of the roadway; the point cloud processing module is used to process the three-dimensional laser point cloud, analyze the deformation amount, and determine drivability; the drivability assessment module is used to assess the drivability of the monorail crane based on the deformation amount and the drivability assessment results; and the decision suggestion module is used to provide travel suggestions for the monorail crane based on the assessment results.

Claims

1. A method for dynamically evaluating the mobility of a monorail crane in an underground coal mine roadway, characterized in that, Includes the following steps: S1: Visual information of the rock surface in the tunnel is obtained by video acquisition equipment installed on the monorail to identify the places where the rock in the tunnel is damaged or deformed; S2. For areas where rock damage or deformation is identified, reduce the monorail travel speed to 30%-50% of the original speed in advance; at the same time, acquire point cloud data of the tunnel through point cloud data acquisition equipment installed on the monorail, and analyze the deformation of the tunnel rock using three-dimensional laser point cloud analysis method. S3: Make a preliminary assessment of the maneuverability of the monorail in the current roadway, using the range of the monorail's height and width dimensions as a reference. If the preliminary assessment indicates that it is passable, the monorail will continue to travel at normal speed; if the preliminary assessment indicates that it is not passable, proceed to step S4. S4. Accurately assess the mobility of the monorail in the current roadway, perform multi-point cloud offline fitting using the acquired point cloud data of the roadway, obtain the roadway cross-sectional contour data, and calculate the precise deformation of the roadway rock. S5: Based on the precise deformation of the roadway rock calculated in step S4, the dimensions of the vehicle, and the provisions of the "Coal Mine Safety Regulations", provide travel suggestions for the monorail crane.

2. The method for dynamic evaluation of the traversability of monorail cranes in underground coal mine roadways according to claim 1, characterized in that, In step S2, for cases where there is no surface damage to the tunnel, the three-dimensional laser point cloud is sparsed to determine the amount of tunnel deformation.

3. The method for dynamic evaluation of the traversability of monorail cranes in underground coal mine roadways according to claim 1, characterized in that, In step S1, an object detection algorithm is used to identify areas where the rocks in the tunnel are damaged or deformed. Tunnel images containing both normal and damaged / deformed rocks are collected as a training set, and the rock areas and their states are labeled to train the object detection model.

4. The method for dynamic evaluation of the traversability of monorail cranes in underground coal mine roadways according to claim 1, characterized in that, In step S2, the three-dimensional laser point cloud analysis method adopts the point cloud registration method or the point cloud comparison method.

5. The method for dynamic evaluation of the traversability of monorail cranes in underground coal mine roadways according to claim 1, characterized in that, In step S3, the preliminary assessment of the monorail's passability within the current roadway is performed. If both of the following two formulas are satisfied, the preliminary assessment deems it passable; otherwise, it is preliminarily deemed impassable: 0 < Δh ≤ 0.1h 0 < Δw ≤ 0.05w Where h is the height of the monorail crane body; w is the width of the monorail crane body.

6. The method for dynamic evaluation of the traversability of monorail cranes in underground coal mine roadways according to claim 1, characterized in that, In step S4, the method for offline fitting of multi-point clouds specifically includes the following steps: S41. Extract the centerline data of the tunnel based on the ground and tunnel side projections, including the following sub-steps. S411. Using the sensor of the point cloud acquisition device that collects the point cloud data of the roadway as the origin O, establish an XYZ three-axis coordinate system, where the X-axis is the axial direction of the roadway, the XOY plane is the ground, and the XOZ plane is the side of the roadway. S412. Project the tunnel point cloud data onto the XOY plane and XOZ plane in the three-axis coordinate system respectively, and extract the two-dimensional boundary point set of the tunnel projection. S413. Set a certain step size Δx along the roadway axis in the XOY and XOZ planes, and sample the boundary point set at equal intervals to extract x. i The maximum value of the boundary point set along the y-axis corresponding to (i = 1, 2, 3, ..., n) is y. i(max) With minimum value y i(min) The maximum value z of the boundary point set corresponding to the z-axis direction i(max) With minimum value z i(min) ; S414. Using the midpoint formula and Calculate the set values ​​of boundary points along the y-axis and z-axis to obtain the midpoint set M = {m1, m2, m3, ..., m} in the XOY plane. n The set of points N in the XOZ plane is N = {n1, n2, n3, ..., n}. n The tunnel centerline is obtained by fitting the midpoint set of the XOY plane and the midpoint set of the XOZ plane. S42. Using a RANSAC-based roadway cross-section profile separation model, obtain the roadway cross-section profile data and calculate the deformation, including the following sub-steps: S421. Calculate the angle α between the tunnel centerline and the XOY plane and the angle β between the tunnel centerline and the XOZ plane extracted in step S414. S422. Based on the included angles α and β, transform the coordinates of the roadway point cloud data so that the central axis of the transformed roadway point cloud data is parallel to the X-axis. The calculation formulas before and after the transformation are: Among them [XYZ] T The original coordinates of the tunnel point cloud are [X'Y'Z']. T The coordinates of the converted tunnel point cloud; S423. The adjusted roadway point cloud data is sliced ​​along the X-axis at certain intervals δ and thickness d according to the point cloud processing speed. The sliced ​​point cloud data is then projected and fitted based on the RANSAC algorithm to obtain the roadway cross-sectional contour data and calculate the precise deformation.

7. The method for dynamic evaluation of the traversability of monorail cranes in underground coal mine roadways according to claim 4, characterized in that, In step S423, the adjusted roadway point cloud data is sliced ​​along the X-axis at certain intervals δ and thickness d according to the point cloud processing speed. To achieve continuous processing of the slices, the vehicle is still located before the processed slice after all slices have been processed. The time required to process the point cloud of one slice is denoted as T. 计 Let the monorail's travel speed be V, its braking time be t, and the distance between the monorail and the processed slice section be denoted as δ1. Then, the determination of δ1 satisfies the formula: The interval between the two slice sections is δ2. To ensure that the monorail can brake in time when identifying impassable areas, δ2 must satisfy the following formula: and 8. The method for dynamic evaluation of the traversability of monorail cranes in underground coal mine roadways according to claim 1, characterized in that, Step S5 specifically involves: the monorail needs to consider the swaying that occurs during the operation of the equipment, and its maximum swing amplitude needs to be considered as 10°. In addition to the maximum swing amplitude, a safety distance of at least 200mm should be set between the monorail and the tunnel wall, a safety distance of 500mm should be set between the monorail and the top of the tunnel, and a safety distance of 400mm should be set between the bottom of the monorail and the bottom of the tunnel. Based on these regulations, a safe passage area model for transport vehicles should be designed.

9. The method for dynamic evaluation of the traversability of monorail cranes in underground coal mine roadways according to claim 1, characterized in that, In step S5, providing travel suggestions for the monorail specifically involves the monorail braking or changing its travel route in a timely manner.

10. A dynamic evaluation system for the mobility of a monorail crane in an underground coal mine roadway, characterized in that, include: The video acquisition module is used to acquire video information from the tunnel. The video analysis module is used to perform frame extraction analysis on video information to identify areas where the rocks in the tunnel are damaged or deformed. The point cloud acquisition module is used to acquire point cloud data of the tunnel. The point cloud processing module is used to process 3D laser point clouds and analyze the precise deformation of tunnel rocks. The accessibility assessment module is used to accurately assess the accessibility of a monorail crane based on the precise deformation of the rock in the tunnel. The decision suggestion module is used to provide travel suggestions for monorails based on the evaluation results.

Images