An image forming system and method for a three-dimensional dynamic stockpile

Abstract

The present application relates to the field of granular material processing, and particularly to a kind of image forming system and method of three-dimensional dynamic stockpile, image forming system, comprising: feed channel, discharge gate, stock bin, image forming device and data processing center;The stock bin side is provided with several longitudinal arrangement height baseline, wherein the topmost height baseline is bin top line, the feed channel with the discharge gate is set in the bin top line, the image forming device includes, height line identifier and laser scanning device.Forming method is by the way of multiple scanning imaging, the imaging results of two times are compared, whether the stockpile is in stable state is determined by the comparison of similarity, until the accurate grid map of stable state stockpile is finally obtained.Compared with ordinary scanning system, after scanning, directly modeling calculation coordinates, the data reliability obtained in the present application is higher, and the real state of stockpile can be more reflected.

Description

Technical Field

[0001] This invention relates to the field of particulate material processing, and specifically to an image forming system and method for a three-dimensional dynamic stockpile. Background Technology

[0002] With rapid economic development, large quantities of waste, scrap steel, nuclear waste, biomass, and other bulk particulate matter require harmless treatment or reuse. This process necessitates loading and unloading these materials into processing equipment using grab cranes. Currently, the traditional loading and unloading process is widely employed, involving manual observation of the materials and manual operation of the grab crane. However, this traditional method is inefficient, physically demanding, and prone to safety accidents during prolonged operation. To transform this traditional process, improve automation, increase efficiency and safety, and reduce worker fatigue, many research institutions and manufacturers both domestically and internationally are increasingly focusing on the research and development of intelligent grab cranes.

[0003] The research and development of intelligent grab cranes requires the use of computational image processing technology, which is organically combined with the control of the central control room. The goal is to realize unmanned loading and unloading processes in bulk material yards, and on this basis, to achieve the integration of yard management, central control, and unmanned control of stacker-reclaimers. In order to ensure that the grab can operate well, it is necessary to design a system and method that can reliably obtain three-dimensional dynamic images of the material pile. Summary of the Invention

[0004] The purpose of this invention is to solve the problems in the background art and provide a three-dimensional dynamic material stack image forming system and method.

[0005] The above-mentioned technical objective of the present invention is achieved through the following technical solution:

[0006] A three-dimensional dynamic material pile image forming system includes: a feeding channel, a discharge gate, a material pile bin, an image forming device, and a data processing center; the side of the material pile bin is provided with several longitudinally arranged height baselines, wherein the topmost height baseline is the top line of the bin, the feeding channel and the discharge gate are located above the top line of the bin, and the image forming device includes a height line recognizer and a laser scanning device.

[0007] Preferably, the height baseline is provided with a reflective surface to facilitate identification by the height line identifier.

[0008] Preferably, the top line of the silo protrudes inward from the side of the silo to form a top line boss, so that the laser scanning device can scan the top line of the silo into the imaging model together during scanning, which facilitates the subsequent fitting of the graphic.

[0009] A method for image formation of a three-dimensional dynamic material pile, using the above-mentioned imaging system, involves the following steps to image the material pile:

[0010] S1. Establish coordinate axes and set image shaping boundaries;

[0011] S2. Deformation judgment of material pile: After the material is fed into the material pile silo from the feeding channel and the unloading is completed, the deformation of the material pile is judged and the material pile forming measurement is carried out.

[0012] S3. Image forming: Use a laser scanning device to acquire an image of the top surface of the material pile containing the top line of the silo, and obtain the height data of the top surface of the material pile through a height line recognizer.

[0013] S4. Data gridding: In the data processing center, the image outside the boundary is removed, and the remaining top surface image of the material pile is gridded. The position coordinate data of each grid is recorded to obtain the basic material pile grid data A.

[0014] S5. Data verification: After a period of time T, repeat steps S3-S4 to obtain verification stockpile grid data B. Compare the basic stockpile grid data A with the verification stockpile grid data B and calculate the similarity P.

[0015] S6. If the similarity P is greater than or equal to the set value Px, the verification passes; if the similarity P is less than the set value Px, the verification fails. Delete the basic material pile grid data A and write the verification material pile grid data B into the basic material pile grid data A. Repeat step S5 to obtain the new verification material pile grid data B and compare it again until the verification passes.

[0016] After S7 and S6 are verified, the basic material pile grid data A and the verification material pile grid data B are overlaid to obtain the final grid data C.

[0017] Preferably, in step S1, the horizontal plane where the top line of the silo is located is taken as the X-axis and Y-axis plane, the height direction of the silo is taken as the Z-axis, the length and width of the silo are taken as the image boundaries of the X-axis and Y-axis, and the height from the top line of the silo to the bottom of the silo is taken as the boundary of the Z-axis.

[0018] Preferably, the specific steps of image meshing in step S4 are as follows:

[0019] 1. Within the boundary area of ​​the graphic, divide the X-axis and Y-axis equally by a distance L to form several grids. Each grid records data (xi, yi, zi), where (xi, yi) represents the grid position of the X-axis and Y-axis, and zi represents the height of the material pile within that grid.

[0020] 2. The height line identifier identifies a set of parallel lines representing the height baseline of the silo top line; the laser scanning device scans the curved surface image of the top of the material pile, which includes the silo top line image; the two sets of images are fitted using the silo top line as a reference to obtain a grid map.

[0021] 3. The height baseline spacing is a known fixed value. Therefore, the height data zi corresponding to each (xi, yi) coordinate is calculated by measuring the surface image using the height baseline as a scale, and written into the grid record data (xi, yi, zi).

[0022] Preferably, in step S5, the similarity P calculation step is as follows:

[0023] 1. Calculate the difference between ziA and ziB at the same position point of each (xi, yi) coordinate in the basic material pile grid data A and the verification material pile grid data B;

[0024] 2. Record the number of grids n with a difference less than or equal to a, and record the number of grids m with a difference greater than a, where a is the set accuracy parameter;

[0025] 3. Similarity P = n / (n+m).

[0026] Preferably, in step S6, the data for each grid point in the final grid data C is (xi, yi, ziC), and the data overlay processing algorithm is ziC = (ziA + ziB) / 2, where ziA and ziB are the height values ​​of the pile at the same coordinates (xi, yi) in the basic pile grid data A and the verification pile grid data B. By overlaying the results multiple times, the accuracy of the data is improved.

[0027] In summary, this invention employs a multi-scan imaging method, comparing the results of two consecutive scans to determine whether the material pile is in a stable state, until a precise mesh map of the stable material pile is obtained. Compared to conventional scanning systems that directly model and calculate coordinates after scanning, this approach yields more reliable data that better reflects the true state of the material pile. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the image forming system structure in this invention. Detailed Implementation

[0029] The following specific embodiments are merely illustrative of the present invention and are not intended to limit the invention. After reading this specification, those skilled in the art can make modifications to these embodiments without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of the present invention.

[0030] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0031] Example 1

[0032] according to Figure 1 As shown, a three-dimensional dynamic material pile image forming system includes: a feeding channel 1, a discharge gate 2, a material silo 3, an image forming device 4, and a data processing center; the material silo 3 has several longitudinally arranged height baselines 31 on its side, wherein the topmost height baseline 31 is the silo top line 32, the feeding channel 1 and the discharge gate 2 are located above the silo top line 32, the image forming device 4 includes a height line recognizer 41 and a laser scanning device 42, the height baselines 31 are provided with reflective surfaces, and the silo top line 32 protrudes inward from the side of the material silo 3 to form a top line boss.

[0033] A method for image formation of a three-dimensional dynamic material pile, using the above-mentioned imaging system, involves the following steps to image the material pile:

[0034] S1. Establish coordinate axes and set image forming boundaries: Take the horizontal plane where the top line 32 of the silo is located as the X-axis and Y-axis plane, take the height direction of the silo 3 as the Z-axis, take the length and width of the silo 3 as the image boundaries of the X-axis and Y-axis, and take the height from the top line 32 of the silo to the bottom of the silo 3 as the boundary of the Z-axis.

[0035] S2. Deformation judgment of material pile: The material is fed into the material pile 3 from the feeding channel 1. After the material is unloaded, the material pile deformation is judged after the unloading gate 2 is closed, and the material pile forming measurement is carried out.

[0036] S3. Image forming: Use laser scanning device 42 to acquire an image of the top surface of the material pile containing the image of the top line 32 of the silo, and obtain the height data of the top surface of the material pile through height line recognizer 41.

[0037] S4. Data gridding: The image outside the boundary is removed in the data processing center, and the remaining top surface image of the material pile is gridded. The position coordinate data of each grid is recorded to obtain the basic material pile grid data A. The specific steps of gridding are as follows: 1. In the boundary area of ​​the graphic, the X-axis and Y-axis are evenly divided by a distance L to form several grids. Each grid records data (xi, yi, zi), where (xi, yi) represents the grid position of the X-axis and Y-axis, and zi represents the height of the material pile in the grid; 2. The height line recognizer identifies the height baseline parallel line group graphic with the top of the silo top line (32); the top surface image of the material pile obtained by the laser scanning device contains the silo top line image; the two sets of images are fitted by the silo top line as the reference to obtain the grid map; 3. The height baseline spacing is a known fixed value, so the height baseline is used as the scale to calculate the corresponding height data zi under each (xi, yi) coordinate through the surface image and write it into the grid record data (xi, yi, zi).

[0038] S5. Data Verification: After an interval of time T (0.05s≤T≤1s), repeat steps S3-S4 to obtain verification stockpile grid data B. Compare the basic stockpile grid data A with the verification stockpile grid data B and calculate the similarity P. The similarity P calculation steps are as follows: 1. Calculate the difference between ziA and ziB at the same position point of each (xi, yi) coordinate in the basic stockpile grid data A and the verification stockpile grid data B; 2. Record the number of grids n with a difference less than or equal to a, and record the number of grids m with a difference greater than a, where a is the set accuracy parameter (0.1cm≤a≤50cm); 3. Similarity P=n / (n+m).

[0039] S6. If the similarity P is greater than or equal to the set value Px (70%≤Px≤100%), the verification passes; if the similarity P is less than the set value Px, the verification fails. Delete the basic material pile grid data A and write the verification material pile grid data B into the basic material pile grid data A. Repeat step S5 to obtain the new verification material pile grid data B and compare it again until the verification passes.

[0040] After S7 and S6 are verified, the basic material pile grid data A and the verification material pile grid data B are superimposed to obtain the final grid data C (xi, yi, ziC). The data superposition processing algorithm is ziC=(ziA+ziB) / 2, where ziA and ziB are the material pile height values ​​of the points with the same coordinates (xi, yi) in the basic material pile grid data A and the verification material pile grid data B.

Claims

1. A method for image forming of a three-dimensional dynamic material pile, characterized in that, A three-dimensional dynamic material pile image forming system is used to image the material pile. The image forming system includes: a feeding channel (1), a discharge gate (2), a material silo (3), an image forming device (4), and a data processing center. The side of the material silo (3) is provided with several longitudinally arranged height baselines (31), of which the topmost height baseline (31) is the top line (32) of the silo. The feeding channel (1) and the discharge gate (2) are located above the top line (32) of the silo. The image forming device (4) includes a height line recognizer (41) and a laser scanning device (42). The height baselines (31) are provided with reflective surfaces. The top line (32) of the silo protrudes inward from the side of the material silo (3) to form a top line protrusion. The specific imaging steps include: S1. Establish coordinate axes and set image forming boundaries. Take the horizontal plane where the top line (32) of the silo is located as the X-axis and Y-axis plane, and the height direction of the stacking silo (3) as the Z-axis. Take the length and width of the stacking silo (3) as the image boundaries of the X-axis and Y-axis, and take the height from the top line (32) of the silo to the bottom of the stacking silo (3) as the boundary of the Z-axis. S2, Deformation judgment of material pile: The material is fed into the material pile silo (3) from the feeding channel (1). After the material is unloaded, the material pile deformation is judged after the unloading gate (2) is closed, and the material pile forming measurement is carried out. S3, Image Forming: Use a laser scanning device (42) to obtain an image of the top surface of the material pile containing the image of the top line (32) of the silo, and obtain the height data of the top surface of the material pile through the height line recognizer (41); S4. Data Gridding: In the data processing center, images outside the boundaries are removed, and the remaining top surface image of the material pile is gridded. The position coordinate data of each grid is recorded to obtain the basic material pile grid data A. The specific steps of image gridding are as follows: S4-1. Within the boundary area of ​​the graphic, the X-axis and Y-axis are evenly divided by a distance L to form several grids. Each grid records data (xi, yi, zi), where (xi, yi) represents the grid position of the X-axis and Y-axis, and zi represents the height of the material pile within the grid; S4-2. Height line recognizer (4 1) Identify the parallel line group of height baseline (31) with the top of the silo top line (32) as the top line; the curved surface image of the top of the material pile obtained by the laser scanning device (42) includes the image of the silo top line (32); fit the two sets of images with the silo top line (32) as the reference to obtain the grid map; S4-3, the spacing of the height baseline (31) is a known fixed value, so the height data zi corresponding to each (xi, yi) coordinate is calculated by measuring the curved surface image with the height baseline (31) as the scale, and written into the grid record data (xi, yi, zi); S5. Data Verification: After a time interval T, repeat steps S3-S4 to obtain verification stockpile grid data B. Compare the basic stockpile grid data A with the verification stockpile grid data B to calculate the similarity P. The similarity P calculation steps are as follows: S5-1. Calculate the difference between ziA and ziB at the same (xi, yi) coordinate point in the basic stockpile grid data A and the verification stockpile grid data B; S5-2. Record the number of grids n with a difference less than or equal to a, and record the number of grids m with a difference greater than a, where a is a set accuracy parameter; S5-3. Similarity P = n / (n+m). S6. If the similarity P is greater than or equal to the set value Px, the verification passes; if the similarity P is less than the set value Px, the verification fails. Delete the basic material pile grid data A and write the verification material pile grid data B into the basic material pile grid data A. Repeat step S5 to obtain the new verification material pile grid data B and compare it again until the verification passes. S7. After step S6 is verified, the basic material pile grid data A and the verification material pile grid data B are superimposed to obtain the final grid data C. The data of each grid point in the final grid data C is (xi, yi, ziC). The data superposition processing algorithm is ziC=(ziA+ziB) / 2, where ziA and ziB are the material pile height values ​​of the points with the same coordinates (xi, yi) in the basic material pile grid data A and the verification material pile grid data B.

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