Method and system for eliminating clumps on the inner walls of coal transport vehicle compartments

Abstract

The application discloses a method for eliminating the clumps on the inner wall of a coal transport vehicle carriage, comprising the following steps: positioning the coal transport vehicle to a preset working position, so that the carriage to be cleaned keeps a standard position; scanning the inner wall of the carriage in the standard position, and obtaining a first space coordinate set of the calibrated actual space position; comparing the first space coordinate set with a pre-stored reference space coordinate set, and identifying a difference coordinate set, wherein the reference space coordinate set calibrates the space position of the inner wall of the carriage in the standard position in a clump-free state, and the difference coordinate set calibrates the actual space position of the clumps; and positioning the clumps on the inner wall of the carriage according to the difference coordinate set. The application can be adapted to railway vehicles and road transport vehicles, and greatly improves the coal transportation efficiency and economy.

Description

Technical Field

[0001] This invention relates to the field of coal transport vehicles, and more particularly to a method and system for eliminating clumps on the inner walls of coal transport vehicle compartments. Background Technology

[0002] During coal transportation, stubborn clumps easily form on the inner walls of coal trucks due to coal residue and moisture, leading to reduced loading capacity, decreased unloading efficiency, and increased transportation losses. Traditional removal methods rely on manual shoveling or mechanical scraping, which are risky, inefficient, and prone to damaging the truck's inner walls. Existing automation technologies lack the ability to accurately locate clumps and are ill-suited to complex truck structures, necessitating an efficient and non-destructive clump removal solution. Summary of the Invention

[0003] This invention proposes a method for eliminating clumps on the inner wall of a coal transport vehicle, comprising: S1. Position the coal transport vehicle to the preset work position, so that the car to be cleaned maintains the standard position; S2. Scan the inner wall of the carriage in a standard pose to obtain the first set of spatial coordinates for calibrating the actual spatial position; S3. Compare the first spatial coordinate set with the pre-stored reference spatial coordinate set to identify the difference coordinate set. The reference spatial coordinate set calibrates the spatial position of the inner wall of the carriage in the standard pose state without lumps, and the difference coordinate set calibrates the actual spatial position of the lumps. S4. Based on the difference coordinate set, locate and handle the clumps on the inner wall of the carriage.

[0004] Furthermore, the step of comparing the first spatial coordinate set with the pre-stored reference spatial coordinate set to identify the difference coordinate set includes: performing a coordinate alignment operation on the first spatial coordinate set and the reference spatial coordinate set to eliminate pose errors; calculating the spatial Euclidean distance between the two coordinate sets point by point to generate a distance mapping matrix; based on a preset distance threshold, selecting the points exceeding the standard in the distance mapping matrix as the initial difference set; performing a morphological closing operation on the initial difference set to connect adjacent difference points to form a continuous block region; and outputting the boundary coordinates of the continuous block region as the difference coordinate set.

[0005] Furthermore, S4 specifically includes: identifying multiple block region units based on the difference coordinate set; planning the optimal execution path of the execution mechanism based on the spatial distribution of the multiple block region units; and eliminating the block region units one by one according to the optimal execution path.

[0006] Furthermore, the step of identifying multiple clustered regional units based on the differential coordinate set includes: performing spatial clustering analysis on the differential coordinate set, aggregating spatially adjacent coordinate points into independent clustered units by using a preset distance threshold; filtering out pseudo-clustered units formed by discrete noise points based on the volume density distribution characteristics of each clustered unit; extracting the centroid coordinates and outer contour boundaries of the effective clustered units, and generating a clustered regional unit dataset containing spatial location and geometric features.

[0007] Furthermore, the optimal execution path of the spatial distribution planning execution mechanism based on multiple block region units includes: obtaining the centroid coordinates and outer contour boundary data of each block region unit; using the centroid coordinates as path nodes, solving the node access sequence with the minimum movement distance using the traveling salesman problem algorithm; generating the obstacle avoidance trajectory of the execution mechanism by combining the outer contour boundary data; and fusing the node access sequence and obstacle avoidance trajectory to generate the globally optimal execution path.

[0008] Furthermore, the process of eliminating the agglomerated region units one by one according to the optimal execution path also includes: real-time detection of the elimination status of the current agglomerated region unit; if residual agglomerated region unit is detected, the geometric structural parameters of the residual agglomerated ...

[0009] Furthermore, the scanning process uses a 3D laser scanner to acquire surface topography data of the interior wall of the carriage.

[0010] Furthermore, the process of removing the clumps from the inner wall of the carriage is carried out by physically peeling them off using a high-pressure water jet removal device.

[0011] Furthermore, the present invention also proposes a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method for eliminating caking on the inner wall of the coal transport vehicle.

[0012] Furthermore, the present invention also proposes a system for eliminating clumps on the inner wall of a coal transport vehicle, comprising: The positioning unit is used to fix the coal transport vehicle and keep the car body in a standard position. The scanning unit is used to collect spatial coordinate data of the inner wall of the carriage in a standard pose. The processing unit is used to compare the actual coordinates with the reference coordinates and identify the coordinates of the clumped area; The execution unit is used to perform block clearing operations based on the coordinates of the block region.

[0013] This invention utilizes automated positioning and 3D scanning technology to accurately identify the spatial distribution of coal clumps, combined with high-pressure water jet directional removal, significantly improving operational safety and preventing damage to the transport vehicle. The system intelligently plans the optimal path for the robotic arm, achieving efficient cleaning; real-time monitoring and dynamic adjustment ensure complete removal of clumps while reducing energy and water consumption. This method is adaptable to both rail and road transport vehicles, greatly improving the efficiency and economy of coal transportation. Attached Figure Description

[0014] Figure 1 This is a flowchart illustrating a method for eliminating clumps on the inner wall of a coal transport vehicle, as proposed in this invention. Detailed Implementation

[0015] refer to Figure 1 This invention proposes a method for eliminating clumps on the inner wall of a coal transport vehicle, comprising: S1. Position the coal transport vehicle to the preset work position to ensure that the car body to be cleaned maintains a standard position.

[0016] S2. Scan the inner wall of the carriage in a standard pose to obtain the first set of spatial coordinates for calibrating the actual spatial position.

[0017] S3. Compare the first spatial coordinate set with the pre-stored reference spatial coordinate set to identify the difference coordinate set. The reference spatial coordinate set calibrates the spatial position of the inner wall of the carriage in the standard pose state without lumps, and the difference coordinate set calibrates the actual spatial position of the lumps.

[0018] S4. Based on the difference coordinate set, locate and handle the clumps on the inner wall of the carriage.

[0019] Among them, the coal transport vehicle specifically refers to rail or road transport vehicles for transporting coal; the preset work station specifically refers to a dedicated work area equipped with automated cleaning equipment; the standard pose specifically refers to a fixed spatial posture in which the plane of the inner wall of the carriage is vertically aligned with the scanning equipment; the first spatial coordinate set specifically refers to the set of point cloud data of the inner wall surface of the carriage obtained through 3D scanning; the reference spatial coordinate set specifically refers to the standard geometric structure data model of the inner wall of the carriage in the state of no coal block adhesion; and the difference coordinate set specifically refers to the set of 3D coordinate data in which the actual surface morphology deviates significantly from the reference model. Specifically, the coal transport vehicle is first precisely moved to a preset workstation and fixed with mechanical clamps to ensure that the inner wall of the carriage is in a standard pose that is vertically aligned with the scanning equipment. Then, the 3D scanning equipment is started to perform a comprehensive scan of the inner wall of the carriage, collect surface point cloud data, and construct a first spatial coordinate set. This coordinate set is then spatially registered and compared with a pre-stored non-caking reference coordinate set. After eliminating pose errors through a feature point matching algorithm, the spatial offset of each corresponding point is calculated, and abnormal coordinate points that exceed the preset tolerance range are selected to form an initial difference set. Then, regional clustering analysis is performed on the discrete abnormal points to identify coordinate abnormal areas within a continuous spatial range, and finally, the difference coordinate set of the calibrated agglomeration area is output. Finally, based on the spatial distribution characteristics of this coordinate set, the high-pressure water jet device is driven to perform targeted removal of the agglomeration area.

[0020] Furthermore, the step of comparing the first spatial coordinate set with the pre-stored reference spatial coordinate set to identify the difference coordinate set includes: performing a coordinate alignment operation on the first spatial coordinate set and the reference spatial coordinate set to eliminate pose errors; calculating the spatial Euclidean distance between the two coordinate sets point by point to generate a distance mapping matrix; based on a preset distance threshold, selecting the points exceeding the standard in the distance mapping matrix as the initial difference set; performing a morphological closing operation on the initial difference set to connect adjacent difference points to form a continuous block region; and outputting the boundary coordinates of the continuous block region as the difference coordinate set.

[0021] Specifically, the coordinate alignment operation is the process of solving the spatial transformation matrix through the iterative nearest point algorithm; the spatial Euclidean distance is the measure of the straight-line distance between two points in a three-dimensional coordinate system; the distance mapping matrix is ​​a two-dimensional data table storing the distance values ​​between the actual coordinates of each scan point and the reference coordinates; the preset distance threshold is the minimum spatial offset for determining the existence of a block; the initial difference set is the set of discrete abnormal coordinate points that exceed the distance threshold; the morphological closing operation is an image processing method of first dilation and then erosion; and the continuous block region is the spatially connected region formed after the closing operation. Specifically, in the coordinate comparison stage, the iterative nearest point algorithm is first used to spatially align the actual scan coordinate set with the reference coordinate set through rotation and translation transformation matrices, eliminating systematic errors caused by carriage pose deviations. After registration, the Euclidean distance between the actual coordinate point and the corresponding reference point is calculated point by point to generate a mapping matrix containing all distance data. A reasonable distance threshold parameter is set according to the material characteristics, and coordinate points exceeding the threshold in the mapping matrix are selected to form an initial difference set. Morphological closing operations are performed on this initial set. First, the neighborhood range of the difference points is expanded by dilation to fill the small gaps, and then the boundary contour is smoothed by erosion, finally forming a spatially continuous blocky region model. Finally, the boundary vertex coordinate sequence of this region is extracted as the difference coordinate set output.

[0022] Furthermore, S4 specifically includes: identifying multiple block region units based on the difference coordinate set; planning the optimal execution path of the execution mechanism based on the spatial distribution of the multiple block region units; and eliminating the block region units one by one according to the optimal execution path.

[0023] Specifically, the agglomeration area unit is an independent, contiguous coal seam space region; the optimal execution path is the trajectory planning scheme that minimizes the total movement distance of the cleaning device; and the execution mechanism is a multi-axis robotic arm device equipped with a high-pressure water gun. Specifically, based on the spatial distribution characteristics of the difference coordinate set, a density clustering algorithm is used to aggregate spatially adjacent abnormal coordinate points into independent agglomeration area units; a structured dataset containing geometric features is established by calculating the centroid coordinates and outer contour boundary parameters of each unit; based on this dataset, a traveling salesman problem algorithm is used, with the minimization of the robotic arm's movement distance as the objective function, combined with the centroid position of each unit to generate the optimal access sequence; simultaneously, a three-dimensional obstacle avoidance trajectory is constructed based on the unit's outer contour data to ensure that the high-pressure water gun nozzle maintains a constant working distance from the inner wall of the carriage; finally, the path sequence and obstacle avoidance trajectory are fused to generate a global execution path, driving the robotic arm to move sequentially to the location of each agglomeration unit to carry out the cleaning operation.

[0024] Furthermore, the step of identifying multiple clustered regional units based on the differential coordinate set includes: performing spatial clustering analysis on the differential coordinate set, aggregating spatially adjacent coordinate points into independent clustered units by using a preset distance threshold; filtering out pseudo-clustered units formed by discrete noise points based on the volume density distribution characteristics of each clustered unit; extracting the centroid coordinates and outer contour boundaries of the effective clustered units, and generating a clustered regional unit dataset containing spatial location and geometric features.

[0025] Specifically, spatial clustering analysis is a point cloud segmentation algorithm based on Euclidean distance; volume density distribution features are the distribution density of effective coordinate points within a unit volume; pseudo-cluster units are non-real cluster regions formed by scanning noise; centroid coordinates are the average position coordinates of the geometric center of the cluster unit; and outer contour boundaries are the set of outermost three-dimensional coordinate points defining the cluster region. Specifically, a density-based spatial clustering algorithm is used to process the differential coordinate set, using a preset neighborhood radius as the criterion to group coordinate points with a distance smaller than this radius into independent cluster units; for the initially clustered unit set, the volume density value of the coordinate points within each unit is calculated, and discrete pseudo-units formed by scanning noise are filtered out by setting a density threshold; geometric modeling is performed on the effective cluster units, and the outer contour boundary point set of the unit is extracted using the convex hull algorithm, and the three-dimensional spatial coordinates of the unit centroid are calculated; finally, a structured dataset of cluster region units containing centroid positions, outer contour vertex coordinates, and volume parameters is generated.

[0026] Furthermore, the optimal execution path of the spatial distribution planning execution mechanism based on multiple block region units includes: obtaining the centroid coordinates and outer contour boundary data of each block region unit; using the centroid coordinates as path nodes, solving the node access sequence with the minimum movement distance using the traveling salesman problem algorithm; generating the obstacle avoidance trajectory of the execution mechanism by combining the outer contour boundary data; and fusing the node access sequence and obstacle avoidance trajectory to generate the globally optimal execution path.

[0027] Specifically, the node access sequence is a list of the order in which the robotic arm visits each block unit; the obstacle avoidance trajectory is a safe movement path that bypasses the block contour. Specifically, firstly, the three-dimensional coordinates of the centroid of each unit are extracted from the block region unit dataset as key nodes for path planning; then, an improved traveling salesman problem solving algorithm is applied, with the optimization objective of minimizing the energy consumption of the robotic arm joint movement, to calculate the optimal access sequence for traversing all centroid nodes; simultaneously, a three-dimensional obstacle model is constructed based on the outer contour boundary data of each unit, and the artificial potential field method is used to generate a safe obstacle avoidance trajectory between the robotic arm end effector and the inner wall of the carriage; finally, the path node sequence and obstacle avoidance trajectory are fused using a spline curve interpolation algorithm to form a smooth and continuous global execution path, ensuring that the high-pressure water gun nozzle moves along the optimal trajectory and always maintains the optimal working distance from the block surface.

[0028] Furthermore, the process of eliminating the agglomerated region units one by one according to the optimal execution path also includes: real-time detection of the elimination status of the current agglomerated region unit; if a residue is detected in the current agglomerated region unit, the geometric structure parameters of the residual agglomerated units are obtained through three-dimensional scanning; a fluid dynamics model is established based on the geometric structure parameters to calculate the optimal water pressure adjustment amount and scouring angle deflection amount; and the spray parameters of the high-pressure water gun are dynamically adjusted to perform a re-elimination operation.

[0029] Specifically, the geometric parameters include the surface curvature distribution characteristics and thickness gradient data of the residual agglomerates; the fluid dynamics model is a numerical simulation system describing the impact of high-pressure water flow on the agglomerates; and the scouring angle deflection is the adjustment value of the angle between the water jet nozzle axis and the normal to the agglomerate surface. Specifically, during the high-pressure water jet removal process, the agglomerate removal status is determined by real-time monitoring of the reaction force changes of the water jet; when residual agglomerates are detected, a local three-dimensional scan is immediately initiated to obtain the surface curvature distribution, thickness gradient, and porosity characteristic parameters of the residual agglomerates; based on these parameters, a computational fluid dynamics model is established to simulate the removal effect under different water pressures and impact angles; the optimal water pressure adjustment and nozzle angle deflection are obtained through numerical iteration calculations; the output pressure of the high-pressure water pump and the end-effector posture are dynamically adjusted to ensure the water jet impacts the weak areas of the residual agglomerates at the optimal incident angle; this process is repeated until the residual agglomerates are completely removed.

[0030] Furthermore, the scanning process uses a 3D laser scanner to acquire surface topography data of the interior wall of the carriage.

[0031] Specifically, the 3D laser scanner is a precision measuring device that acquires the three-dimensional coordinates of an object's surface using the principle of laser ranging. Specifically, under standard pose conditions, the 3D laser scanner performs a panoramic scan of the interior wall of the carriage. This device calculates the spatial three-dimensional coordinates of each measuring point on the carriage's interior wall surface by emitting a laser beam and receiving reflected signals, combined with the horizontal azimuth and vertical pitch angles recorded by a precision angle encoder. A two-dimensional deflection scan of the laser beam is achieved through a high-speed rotating mirror, and a fully covered scanning path is formed in conjunction with the uniform movement of the vehicle. Finally, a millimeter-precision point cloud dataset of the carriage's interior wall surface topography is generated, providing basic spatial data for subsequent cluster identification.

[0032] Furthermore, the process of removing the clumps from the inner wall of the carriage is carried out by physically peeling them off using a high-pressure water jet removal device.

[0033] The high-pressure water jet removal device is specifically a caking removal device that generates a high-speed water jet through a pressurization system. Specifically, the high-pressure water jet removal device consists of a multi-stage plunger pump, an accumulator, high-pressure pipelines, and special nozzles. The plunger pump pressurizes atmospheric water to a set pressure value and stores it in the accumulator. High-pressure water is then transported to the nozzles via pipelines controlled by a digitally controlled valve. The nozzles employ a jewel-like throttling orifice structure to convert pressure energy into kinetic energy, forming a continuous water jet with a speed exceeding the speed of sound. When this jet impacts the caking surface, it generates impact stress exceeding the compressive strength of the coal block. Simultaneously, the water flow penetrates the micro-cracks in the caking, creating a water wedge effect, thus physically peeling the caking off from the inner wall of the truck bed. By adjusting the pump station pressure and flow parameters, the device can adapt to the removal needs of caking blocks of varying hardness.

[0034] The present invention also proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for eliminating caking on the inner wall of the coal transport vehicle.

[0035] Specifically, the computer-readable storage medium is a solid-state memory or a disk array device. Specifically, the computer program stored in the storage medium includes a positioning control module, a scanning drive module, a coordinate processing module, and an execution control module. The positioning control module generates positioning instructions for the coal transport vehicle and transmits them to the workstation conveying system. The scanning drive module controls a 3D laser scanner to complete data acquisition of the inner wall of the truck bed. The coordinate processing module implements coordinate alignment, difference analysis, and agglomeration area identification algorithms. The execution control module plans the robotic arm's motion trajectory based on the agglomeration distribution characteristics and dynamically adjusts the high-pressure water jet parameters. All modules work together to achieve full-process control of automatic agglomeration identification and removal.

[0036] The present invention also proposes a system for eliminating clumps on the inner wall of a coal transport vehicle, comprising: a positioning unit for fixing the coal transport vehicle and maintaining the vehicle in a standard position; a scanning unit for collecting spatial coordinate data of the inner wall of the vehicle in the standard position; a processing unit for comparing the actual coordinates with the reference coordinates and identifying the coordinates of the clump area; and an execution unit for performing a clump removal operation based on the coordinates of the clump area.

[0037] The system comprises a positioning unit, a hydraulically driven rail clamping system, a scanning unit, a 3D laser scanning device, a processing unit, an industrial control computer system, and an execution unit, a six-degree-of-freedom high-pressure water jet robotic arm. Specifically, the positioning unit uses a hydraulically driven rail clamping device to fix the wheels of the coal transport vehicle and, in conjunction with a leveling mechanism, adjusts the carriage to a standard position. The scanning unit uses a line laser scanner to move along the longitudinal axis of the carriage, collecting high-density point cloud data of the inner wall surface. The processing unit uses a spatial registration algorithm to compare the actual point cloud with a reference model, identifying agglomeration areas through distance threshold segmentation and morphological processing. The execution unit controls the movement of the six-degree-of-freedom robotic arm based on the agglomeration coordinates, ensuring precise positioning of the high-pressure water jet nozzle along the planned path. Simultaneously, it dynamically adjusts the water pressure and spray angle based on the residual agglomeration detection results to achieve efficient agglomeration removal.

[0038] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for eliminating clumps on the inner wall of a coal transport vehicle, characterized in that, include: S1. Position the coal transport vehicle to the preset work position, so that the car to be cleaned maintains the standard position; S2. Scan the inner wall of the carriage in a standard pose to obtain the first set of spatial coordinates for calibrating the actual spatial position; S3. Compare the first spatial coordinate set with the pre-stored reference spatial coordinate set to identify the difference coordinate set. The reference spatial coordinate set calibrates the spatial position of the inner wall of the carriage in the standard pose state without lumps, and the difference coordinate set calibrates the actual spatial position of the lumps. S4. Based on the difference coordinate set, locate and handle the clumps on the inner wall of the carriage.

2. The method for eliminating clumps on the inner wall of a coal transport vehicle according to claim 1, characterized in that, The step of comparing the first spatial coordinate set with the pre-stored reference spatial coordinate set to identify the difference coordinate set includes: performing a coordinate alignment operation on the first spatial coordinate set and the reference spatial coordinate set to eliminate pose errors; calculating the spatial Euclidean distance between the two coordinate sets point by point to generate a distance mapping matrix; selecting points exceeding the standard in the distance mapping matrix as the initial difference set based on a preset distance threshold; performing a morphological closing operation on the initial difference set to connect adjacent difference points to form a continuous block region; and outputting the boundary coordinates of the continuous block region as the difference coordinate set.

3. The method for eliminating clumps on the inner wall of a coal transport vehicle according to claim 1, characterized in that, S4 specifically includes: identifying multiple block region units based on the difference coordinate set; planning the optimal execution path of the execution mechanism based on the spatial distribution of the multiple block region units; and eliminating the block region units one by one according to the optimal execution path.

4. The method for eliminating clumps on the inner wall of a coal transport vehicle according to claim 3, characterized in that, The process of identifying multiple clustered regional units based on the differential coordinate set includes: performing spatial clustering analysis on the differential coordinate set, aggregating spatially adjacent coordinate points into independent clustered units using a preset distance threshold; filtering out pseudo-clustered units formed by discrete noise based on the volume density distribution characteristics of each clustered unit; extracting the centroid coordinates and outer contour boundaries of the effective clustered units, and generating a clustered regional unit dataset containing spatial location and geometric features.

5. The method for eliminating clumps on the inner wall of a coal transport vehicle according to claim 4, characterized in that, The optimal execution path of the spatial distribution planning execution mechanism based on multiple block region units includes: obtaining the centroid coordinates and outer contour boundary data of each block region unit; using the centroid coordinates as path nodes, solving the node access sequence with the minimum movement distance using the traveling salesman problem algorithm; generating the obstacle avoidance trajectory of the execution mechanism by combining the outer contour boundary data; and fusing the node access sequence and obstacle avoidance trajectory to generate the globally optimal execution path.

6. The method for eliminating clumps on the inner wall of a coal transport vehicle according to claim 5, characterized in that, The process of eliminating the agglomerated region units one by one according to the optimal execution path also includes: real-time detection of the elimination status of the current agglomerated region unit; if residual agglomerated region unit is detected, the geometric structural parameters of the residual agglomerated ...

7. The method for eliminating clumps on the inner wall of a coal transport vehicle according to claim 1, characterized in that, The scanning process uses a 3D laser scanner to acquire surface topography data of the interior wall of the carriage.

8. The method for eliminating clumps on the inner wall of a coal transport vehicle according to claim 1, characterized in that, The process of removing clumps from the inner wall of the carriage is carried out by physically peeling them off using a high-pressure water jet removal device.

9. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for eliminating caking on the inner wall of a coal transport vehicle as described in any one of claims 1-8.

10. A system for eliminating clumps forming on the inner wall of a coal transport vehicle, characterized in that, include: The positioning unit is used to fix the coal transport vehicle and keep the car body in a standard position. The scanning unit is used to collect spatial coordinate data of the inner wall of the carriage in a standard pose. The processing unit is used to compare the actual coordinates with the reference coordinates and identify the coordinates of the clumped area; The execution unit is used to perform block clearing operations based on the coordinates of the block region.

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