A method, system and storage medium for calculating coal quantity

Abstract

This application discloses a method, apparatus, and system for calculating coal quantity. The method includes: acquiring a binocular overhead video corresponding to a scraper conveyor; determining a three-dimensional image of the coal material on the scraper conveyor based on the binocular overhead video; and calculating the coal quantity based on the three-dimensional image of the coal material on the scraper conveyor. Using the solution provided in this application, an automatic method for calculating coal quantity is provided, eliminating the need for manual calculation of the coal quantity on the scraper conveyor and realizing automatic calculation of the coal quantity on coal mine scraper conveyors.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of scraper conveyor operation monitoring, in particular to a coal quantity calculation method and system and a storage medium. BACKGROUND

[0002] The scraper machine is a conveying device of a fully-mechanized coal mining face in a coal mine. In the process of transporting the coal mine by using the scraper conveyor, the coal quantity monitoring is not only a basis for yield statistics, but also an important link in safety production and process control. At present, the coal quantity monitoring mainly depends on manual calculation. Therefore, the staff needs to continuously calculate, which causes waste of human cost, and the calculation result is affected by the subjective will of the staff, and the accuracy is poor.

[0003] Therefore, it is urgent to provide a coal quantity calculation method to automatically calculate the coal quantity of the coal mine scraper conveyor, which is an urgent technical problem to be solved. SUMMARY

[0004] The application provides a coal quantity calculation method and system and a storage medium to automatically calculate the coal quantity of the coal mine scraper conveyor.

[0005] The application provides a coal quantity calculation method, which comprises the following steps:

[0006] Obtaining a binocular overhead video corresponding to the scraper conveyor;

[0007] Determining a three-dimensional image of the coal material on the scraper conveyor according to the binocular overhead video;

[0008] Calculating the coal quantity of the coal material according to the three-dimensional image of the coal material on the scraper conveyor.

[0009] The application has the beneficial effects that the three-dimensional image of the coal material on the scraper conveyor is determined according to the binocular overhead video corresponding to the scraper conveyor, the coal quantity of the coal material is calculated based on the three-dimensional image of the coal material on the scraper conveyor, and a method for automatically calculating the coal quantity is provided, so that the coal quantity of the scraper conveyor does not need to rely on manual calculation, the automatic calculation of the coal quantity of the coal mine scraper conveyor is realized, the human cost is saved, and the accuracy of the calculation result is improved.

[0010] In one embodiment, the three-dimensional image of the coal material on the scraper conveyor is determined according to the binocular overhead video, which comprises the following steps:

[0011] Obtaining a global binocular overhead image corresponding to the binocular overhead video;

[0012] Preprocessing the global binocular overhead image;

[0013] The pre-processed binocular top view image is recognized to determine a region where the coal material is located in the binocular top view image;

[0014] A three-dimensional image of the coal material on the scraper conveyor is determined according to the region where the coal material is located in the binocular top view image.

[0015] In one embodiment, the acquiring the global binocular top view image corresponding to the binocular top view video comprises:

[0016] The transport speed of the scraper conveyor is acquired.

[0017] The extraction frequency for extracting the image from the binocular top view video is determined according to the transport speed of the scraper conveyor, and the extraction frequency is used to ensure that the extracted image can completely and non-repeatedly contain the coal material information in the binocular top view video.

[0018] The global binocular top view image corresponding to the binocular top view video is acquired according to the extraction frequency.

[0019] The embodiment has the beneficial effects that the transport speed of the scraper conveyor is acquired, the extraction frequency for extracting the image from the binocular top view video is determined according to the transport speed of the scraper conveyor, and the global binocular top view image corresponding to the binocular top view video is acquired according to the extraction frequency. By monitoring the transport speed of the scraper conveyor, the extraction frequency of the image is automatically adjusted, without manual operation, so that the extracted image can completely and non-repeatedly contain the coal material information in the binocular top view video, and the global binocular top view image is acquired.

[0020] In one embodiment, the pre-processing the global binocular top view image comprises:

[0021] The global binocular top view image is denoised.

[0022] The denoised image is binarized to obtain the pre-processed binocular top view image.

[0023] In one embodiment, the coal amount of the coal material is calculated according to the three-dimensional image of the coal material on the scraper conveyor, comprising:

[0024] A discrete voxel on the three-dimensional image of the coal material is acquired as a coal material surface point.

[0025] The depth of the coal material surface point is determined.

[0026] The height of the coal material surface point is determined according to the depth of the coal material surface point.

[0027] The coal material surface point is classified according to the height of the coal material surface point, wherein the coal material surface points in the same height interval are classified into one category.

[0028] calculate the ratio of the coal surface points of each category to all voxels in the three-dimensional image of the coal;

[0029] According to the ratio of the coal surface points of each category to all voxels in the three-dimensional image of the coal, the bottom area corresponding to the coal flow in the binocular overhead video, and the height of the coal surface points of each category, the coal quantity of the coal is calculated.

[0030] In one embodiment, the depth of the coal surface point is determined, comprising:

[0031] The depth of the coal surface point is determined according to the following formula:

[0032]

[0033] wherein z i is the depth of the coal surface point; B is the camera baseline distance; f is the camera focal length; d i is the parallax of the binocular camera for acquiring the binocular overhead video.

[0034] In one embodiment, the height of the coal surface point is determined according to the depth of the coal surface point, comprising:

[0035] The height of the coal surface point is determined according to the following formula:

[0036] l i =h-z i ;

[0037] wherein l i is the height of the coal surface point; h is the distance from the binocular camera for acquiring the binocular overhead video to the surface of the chute part of the scraper conveyor; z i is the depth of the coal surface point.

[0038] In one embodiment, the ratio of the coal surface points of each category to all voxels in the three-dimensional image of the coal is calculated, comprising:

[0039] The ratio of the coal surface points of each category to all voxels in the three-dimensional image of the coal is calculated according to the following formula:

[0040]

[0041] wherein p i is the ratio of the coal surface points of the i-th category to all voxels in the three-dimensional image of the coal; n i is the number of the coal surface points of the i-th category; N is the number of all voxels in the three-dimensional image of the coal.

[0042] In one embodiment, the coal quantity of the coal material is calculated according to the ratio of the surface points of the coal material of different categories to all voxels in the three-dimensional image of the coal material, the bottom area corresponding to the coal flow in the binocular overhead video, and the height of the surface points of each category of coal material, and the coal quantity calculation method comprises the following steps:

[0043] The volume of the coal material is calculated according to the following formula:

[0044]

[0045] Wherein, V is the volume of the coal material; pi is the ratio of the surface points of the coal material of the i-th category to all voxels in the three-dimensional image of the coal material; hi is the height of the surface points of the coal material; and s is the bottom area corresponding to the coal flow in the binocular overhead video. i i

[0046] The present application also provides a coal quantity calculation system, comprising:

[0047] at least one processor; and

[0048] a memory in communication connection with the at least one processor; wherein

[0049] the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to implement the coal quantity calculation method involved in any one of the above embodiments.

[0050] The present application also provides a computer readable storage medium, when the instructions in the storage medium are executed by the processor corresponding to the coal quantity calculation system, the coal quantity calculation system can implement the coal quantity calculation method involved in any one of the above embodiments.

[0051] Other features and advantages of the present application will be described in the following description, and some will become apparent from the description, or will be understood by those skilled in the art. The purpose and other advantages of the present application can be achieved and obtained by the structure specifically pointed out in the written description, claims, and drawings.

[0052] The technical solutions of the present application will be further described in detail below with the help of the drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0053] The accompanying drawings are used to provide further understanding of the present application, and constitute a part of the specification. They are used to explain the present application together with the embodiments of the present application, and do not constitute a limitation to the present application. In the drawings:

[0054] Figure 1 is a flow chart of a coal quantity calculation method in one embodiment of the present application;

[0055] Figure 2 ​​A flow chart of a coal quantity calculation method in another embodiment of the present application;

[0056] Figure 3 A flow chart of a coal quantity calculation method in another embodiment of the present application;

[0057] Figure 4 A structure schematic diagram of a coal quantity calculation system in an embodiment of the present application;

[0058] Figure 5 A structure schematic diagram of a binocular stereo imaging system in an embodiment of the present application. DETAILED DESCRIPTION

[0059] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings, which should be understood as merely illustrative and explanatory, and not limiting the present application.

[0060] Figure 1 A flow chart of a coal quantity calculation method in an embodiment of the present application, which can be used to monitor the coal quantity of a coal mine scraper conveyor, as shown in Figure 1 The method can be implemented as the following steps S101-S103:

[0061] In step S101, the binocular overhead video corresponding to the scraper conveyor is acquired.

[0062] In step S102, the three-dimensional image of the coal material on the scraper conveyor is determined according to the binocular overhead video.

[0063] In step S103, the coal quantity of the coal material is calculated according to the three-dimensional image of the coal material on the scraper conveyor.

[0064] In the embodiment, the binocular overhead video corresponding to the scraper conveyor is acquired. Figure 5 A structure schematic diagram of a binocular stereo imaging system in the present application, specifically, as shown in Figure 5 The left and right two cameras at the same horizontal height above the chute of the scraper conveyor form the binocular stereo imaging system, which acquires the working images of the chute of the scraper conveyor in real time through the two cameras, and obtains the left and right overhead views of the chute of the scraper conveyor.

[0065] The three-dimensional image of the coal material on the scraper conveyor is determined according to the binocular overhead video.

[0066] In order to determine the three-dimensional image of the coal on the scraper conveyor, firstly, the global binocular top view image corresponding to the binocular top view video needs to be obtained. However, due to the running state of the scraper conveyor, the images captured by the camera may be repeated or missed. Therefore, the corresponding images need to be extracted according to the transportation speed of the scraper conveyor to ensure that the global binocular top view image of the scraper conveyor is complete. Specifically, in this embodiment, the transportation speed of the scraper conveyor is obtained, that is, the transportation speed and transportation time of the scraper conveyor are monitored in real time by a speed sensor; then, the extraction frequency when extracting images from the binocular top view video is determined according to the transportation speed of the scraper conveyor, wherein the extraction frequency is used to ensure that the extracted images can completely and repeatedly contain the coal information in the binocular top view video, for example, along the running direction of the conveyor, the length of the image captured by the camera is l, and the transportation speed of the conveyor is v, then l / v is used as the time interval for image extraction, thereby ensuring that the two images extracted before and after are complete and not repeated; finally, the global binocular top view image corresponding to the binocular top view video is obtained according to the extraction frequency.

[0067] Secondly, the global binocular top view image is preprocessed. The global binocular top view image is denoised, and the denoised image is binarized to obtain a preprocessed binocular top view image. Specifically, in this embodiment, after obtaining the global binocular top view image corresponding to the binocular top view video, the obtained coal image is scaled to improve the running speed of the entire system; then, an image enhancement algorithm of image morphology is used to remove image noise and eliminate isolated noise points; finally, the maximum inter-class variance method is used for binarization, and a preprocessed binocular top view image is obtained.

[0068] Thirdly, the preprocessed binocular top view image is identified to determine the region where the coal in the binocular top view image is located. In order to accurately determine the region where the coal in the binocular top view image is located, the threshold value in the image grayscale range is determined for the preprocessed binocular top view image; image segmentation is performed by threshold processing to separate the coal from the background and extract the target region, that is, the single chute part of the scraper conveyor.

[0069] Finally, the three-dimensional image of the coal on the scraper conveyor is determined according to the region where the coal in the binocular top view image is located.

[0070] The coal quantity of the coal on the scraper conveyor is calculated according to the three-dimensional image of the coal. There are various methods for calculating the coal quantity based on the three-dimensional image, such as integral operation based on the three-dimensional image of the coal volume, or obtaining the coal quantity cross-sectional area and combining the running time to determine the coal quantity. However, the above methods are relatively complex, have large calculation amount, and are not accurate. The present embodiment provides the following coal quantity calculation method based on binocular vision difference:

[0071] First, discrete voxels on the three-dimensional image of the coal are obtained as coal surface points. In this embodiment, discrete voxels in the image are regarded as coal surface points, and the total number of discrete voxels in the target area is set to i.

[0072] Next, the depth of the coal surface point is determined. There are many methods for determining the depth of the coal surface point, such as determining the depth based on the height of a reference object in the image. In this embodiment, the parallax of a binocular camera is used to determine the depth of the coal surface. Specifically, the depth of the coal surface point is determined according to the following formula:

[0073]

[0074] Among them, z i B is the depth of the point on the coal surface; f is the distance from the camera baseline; d is the camera focal length; i Parallax of a binocular camera used to acquire binocular overhead video.

[0075] After obtaining the depth of the coal surface point, the height of the coal surface point can then be determined. Specifically, the height of the coal surface point is determined according to the following formula:

[0076] l i =hz i ;

[0077] Among them, l i denoted by z, where z is the height of the point on the coal surface; h is the distance from the binocular camera used to acquire the binocular top-down video to the surface of the scraper conveyor chute; z is the distance from the point on the coal surface to the surface of the scraper conveyor chute. i The depth of the point on the surface of the coal.

[0078] Then, the coal surface points are classified according to their height, with coal surface points within the same height range grouped into one category. Furthermore, the ratio of each category of coal surface points to all voxels in the 3D coal image is calculated; specifically, the ratio of each category of coal surface points to all voxels in the 3D coal image is calculated using the following formula:

[0079]

[0080] Where, p i Let n be the ratio of the surface points of coal of category i to all voxels in the 3D image of the coal; i denoted as the number of surface points of coal in category i; N is the total number of voxels in the three-dimensional image of the coal.

[0081] Finally, the coal quantity is calculated based on the ratio of different types of coal surface points to all voxels in the 3D image of the coal, the base area corresponding to the coal flow in the binocular top-down video, and the height of the surface points of each type of coal. The coal volume is calculated using the following formula:

[0082]

[0083] Where V is the volume of the coal; p i Let be the ratio of the surface points of coal of category i to all voxels in the 3D image of the coal; l i denoted as , and s as the base area corresponding to the coal flow in the binocular overhead video. The base area s corresponding to the coal flow can be determined based on the width of the chute, the travel speed of the scraper conveyor, and the duration of the binocular overhead video.

[0084] The beneficial effects of this application are as follows: by using the binocular overhead video corresponding to the scraper conveyor, a three-dimensional image of the coal material on the scraper conveyor is determined, and the amount of coal material is calculated based on the three-dimensional image of the coal material on the scraper conveyor. This provides a method for automatically calculating the amount of coal, so that the amount of coal on the scraper conveyor does not need to be calculated manually. This realizes the automatic calculation of the amount of coal on the scraper conveyor in the coal mine, saves labor costs, and improves the accuracy of the calculation results.

[0085] In one embodiment, step S102 can be implemented as steps S201-S204, as follows: Figure 2 The flowchart shown is for determining the three-dimensional image of the coal on the scraper conveyor in this embodiment:

[0086] In step S201, the global binocular top-view image corresponding to the binocular top-view video is obtained;

[0087] In step S202, the global binocular top-view image is preprocessed;

[0088] In step S203, the preprocessed binocular top-view image is identified to determine the area where the coal is located in the binocular top-view image;

[0089] In step S204, a three-dimensional image of the coal on the scraper conveyor is determined based on the area where the coal is located in the binocular top-view image.

[0090] Obtain the global binocular top-view image corresponding to the binocular top-view video. Since the scraper conveyor is in operation, the images captured by the camera may contain duplicates or omissions. Therefore, it is necessary to extract the corresponding images based on the conveyor's transport speed to ensure a complete global binocular top-view image of the scraper conveyor. Specifically, in this embodiment, the transport speed of the scraper conveyor is obtained by real-time monitoring of the conveyor's transport speed and transport time using a speed sensor. Then, the extraction frequency for extracting images from the binocular top-view video is determined based on the conveyor's transport speed. This extraction frequency ensures that the extracted images completely and non-repeatingly contain the coal information from the binocular top-view video. For example, if the length captured by the camera along the conveyor's travel direction is l, and the conveyor's transport speed is v, then images are extracted at a time interval of l / v, thus ensuring that the two extracted images are complete and non-repeating. Finally, the global binocular top-view image corresponding to the binocular top-view video is obtained based on the extraction frequency.

[0091] The global binocular top-down image is preprocessed. The global binocular top-down image is denoised; the denoised image is then binarized to obtain the preprocessed binocular top-down image. Specifically, in this embodiment, after acquiring the global binocular top-down image corresponding to the binocular top-down video, the acquired coal image is first scaled to improve the overall system speed; then, image morphology algorithms are used for image enhancement to remove image noise and eliminate isolated noise points; finally, the maximum inter-class variance method is used for binarization to obtain the preprocessed binocular top-down image.

[0092] The preprocessed binocular top-view image is identified to determine the area where the coal is located. To accurately determine the area where the coal is located in the binocular top-view image, a threshold is determined within the image grayscale range of the preprocessed binocular top-view image; threshold processing is used for image segmentation to separate the coal from the background, and the target area, namely the single chute section of the plate conveyor, is extracted.

[0093] A three-dimensional image of the coal on the scraper conveyor is determined based on the area where the coal is located in the binocular top-view image.

[0094] In one embodiment, step S201 above can be implemented as steps A1-A3 as follows:

[0095] In step A1, the conveying speed of the scraper conveyor is obtained;

[0096] In step A2, the extraction frequency for extracting images from the binocular top-view video is determined based on the transport speed of the scraper conveyor. The extraction frequency is used to ensure that the extracted images can completely and non-repeatedly contain the coal information in the binocular top-view video.

[0097] In step A3, a global binocular top-down image corresponding to the binocular top-down video is obtained according to the extraction frequency.

[0098] Since the scraper conveyor is in operation, the images captured by the camera may contain duplicates or omissions. Therefore, it is necessary to extract the corresponding images based on the conveyor's transport speed to ensure a complete binocular top-view image of the entire scraper conveyor. In this embodiment, the conveyor's transport speed is obtained by real-time monitoring of the conveyor's speed and transport time using a speed sensor.

[0099] The extraction frequency for extracting images from the binocular top-down video is determined based on the conveying speed of the scraper conveyor. This extraction frequency ensures that the extracted images completely and non-repeatingly contain the coal information from the binocular top-down video. For example, if the length captured by the camera along the conveyor's direction of travel is l, and the conveyor's speed is v, then images are extracted at time intervals of l / v, thus ensuring that the two extracted images are complete and non-repeating. Finally, a global binocular top-down image corresponding to the binocular top-down video is obtained based on the extraction frequency.

[0100] The beneficial effects of this embodiment are as follows: It obtains the transport speed of the scraper conveyor; determines the extraction frequency for extracting images from the binocular top-down video based on the transport speed of the scraper conveyor; and obtains a global binocular top-down image corresponding to the binocular top-down video based on the extraction frequency. By monitoring the transport speed of the scraper conveyor and automatically adjusting the image extraction frequency, without manual operation, it ensures that the extracted images completely and non-repeatingly contain the coal information in the binocular top-down video, thus obtaining a global binocular top-down image.

[0101] In one embodiment, step S202 above can be implemented as steps B1-B2 as follows:

[0102] In step B1, the global binocular top-view image is denoised;

[0103] In step B2, the denoised image is binarized to obtain a preprocessed binocular top-view image.

[0104] The global binocular top-view image is denoised. In this embodiment, in order to improve the overall system speed, after acquiring the global binocular top-view image corresponding to the binocular top-view video, the acquired coal image is first scaled, and then image enhancement is performed using image morphology algorithms to remove image noise and eliminate isolated noise points;

[0105] The denoised image is binarized to obtain a preprocessed binocular top-view image. Specifically, in this embodiment, the maximum inter-class variance method is used for binarization to obtain the preprocessed binocular top-view image.

[0106] Figure 3 This is a flowchart of a coal quantity calculation method according to an embodiment of this application, as shown below. Figure 3 As shown, step S103 above can be implemented as steps S301-S306:

[0107] In step S301, discrete voxels on the three-dimensional image of the coal are obtained as points on the coal surface.

[0108] In step S302, the depth of the point on the coal surface is determined;

[0109] In step S303, the height of the coal surface point is determined based on the depth of the coal surface point.

[0110] In step S304, the coal surface points are classified according to their height, and coal surface points in the same height range are classified into one category.

[0111] In step S305, the ratio of each type of coal surface point to all voxels in the three-dimensional image of the coal is calculated.

[0112] In step S306, the amount of coal is calculated based on the ratio of different types of coal surface points to all voxels in the three-dimensional image of the coal, the bottom area corresponding to the coal flow in the binocular top-view video, and the height of each type of coal surface point.

[0113] In this embodiment, discrete voxels on a 3D image of the coal are obtained as points on the coal surface. Specifically, discrete voxels in the image are considered as points on the coal surface, and the target region is defined as having a total of i discrete voxels.

[0114] Determine the depth of points on the coal surface. There are many methods for determining the depth of points on the coal surface using 3D images, such as determining the depth of points based on the height of reference objects in the image. In this embodiment, the parallax of a binocular camera is used to determine the depth of the coal surface. Specifically, the depth of points on the coal surface is determined according to the following formula:

[0115]

[0116] Among them, z i B is the depth of the point on the coal surface; f is the distance from the camera baseline; d is the camera focal length; i Parallax of a binocular camera used to acquire binocular overhead video.

[0117] The height of the coal surface point is determined by the depth of the point on the coal surface. After obtaining the depth of the coal surface point, its height can then be determined. Specifically, the height of the coal surface point is determined using the following formula:

[0118] l i =hz i ;

[0119] Among them, l i denoted by z, where z is the height of the point on the coal surface; h is the distance from the binocular camera used to acquire the binocular top-down video to the surface of the scraper conveyor chute; z is the distance from the point on the coal surface to the surface of the scraper conveyor chute. i The depth of the point on the surface of the coal.

[0120] The coal surface points are classified according to their height, with points within the same height range grouped together. After calculating the height of each coal surface point, the points are classified based on this height value, with points at the same height grouped together.

[0121] Calculate the ratio of each category of coal surface points to all voxels in the 3D coal image. In other words, determine the proportion of coal surface points at each height in the 3D coal image. Specifically, calculate the ratio of each category of coal surface points to all voxels in the 3D coal image using the following formula:

[0122]

[0123] Where, p i Let n be the ratio of the surface points of coal of category i to all voxels in the 3D image of the coal; i denoted as the number of surface points of coal in category i; N is the total number of voxels in the three-dimensional image of the coal.

[0124] The amount of coal is calculated based on the ratio of different types of coal surface points to all voxels in the 3D image of the coal, the base area corresponding to the coal flow in the binocular top-down video, and the height of the surface points of each type of coal. The volume of the coal is calculated using the following formula:

[0125]

[0126] Where V is the volume of the coal; p i Let be the ratio of the surface points of coal of category i to all voxels in the 3D image of the coal; l i s is the height of the point on the coal surface; s is the area of ​​the bottom of the scraper conveyor chute.

[0127] The beneficial effects of this embodiment are as follows: Discrete voxels on the three-dimensional image of the coal are obtained as coal surface points; the depth of the coal surface points is determined based on binocular visual aberration, thereby obtaining the coal height; the coal surface points are classified according to their heights; the ratio of coal surface points of each height category to all voxels in the three-dimensional coal image is calculated; the coal quantity is calculated based on the ratio of different categories of coal surface points to all voxels in the three-dimensional coal image, the base area corresponding to the coal flow in the binocular top-down video, and the height of each category of coal surface points. Through this embodiment, a method for analyzing three-dimensional coal images based on binocular vision can be used to determine the coal quantity.

[0128] In one embodiment, the depth of the point on the coal surface can be determined by the following formula in step S302:

[0129]

[0130] Among them, z i B is the depth of the point on the coal surface; f is the distance from the camera baseline; d is the camera focal length; i Parallax of a binocular camera used to acquire binocular overhead video.

[0131] In one embodiment, step S303 above can be used to determine the height of the coal surface point using the following formula:

[0132] l i =hz i ;

[0133] Among them, l i denoted by z, where z is the height of the point on the coal surface; h is the distance from the binocular camera used to acquire the binocular top-down video to the surface of the scraper conveyor chute; z is the distance from the point on the coal surface to the surface of the scraper conveyor chute. i The depth of the point on the surface of the coal.

[0134] In one embodiment, step S305 above can calculate the ratio of each category of coal surface points to all voxels in the three-dimensional image of the coal using the following formula:

[0135]

[0136] Where, p i Let n be the ratio of the surface points of coal of category i to all voxels in the 3D image of the coal; i denoted as the number of surface points of coal in category i; N is the total number of voxels in the three-dimensional image of the coal.

[0137] In one embodiment, step S306 above calculates the volume of the coal according to the following formula:

[0138]

[0139] Where V is the volume of the coal; p i Let be the ratio of the surface points of coal of category i to all voxels in the 3D image of the coal; l i s is the height of the point on the coal surface; s is the area of ​​the bottom of the scraper conveyor chute.

[0140] Figure 4 This is a schematic diagram of a coal quantity calculation system according to this application. Figure 4 As shown, the coal quantity calculation system includes:

[0141] At least one processor 420; and,

[0142] Memory 404 communicatively connected to the at least one processor; wherein,

[0143] The memory stores instructions that can be executed by the at least one processor to implement the coal quantity calculation method involved in any of the above embodiments.

[0144] Reference Figure 4 The coal quantity calculation system 400 may include one or more of the following components: processing component 402, memory 404, power supply component 406, multimedia component 408, audio component 410, input / output (I / O) interface 412, sensor component 414, and communication component 416.

[0145] Processing component 402 typically controls the overall operation of the coal quantity calculation system 400. Processing component 402 may include one or more processors 420 to execute instructions to complete all or part of the steps of the method described above. Furthermore, processing component 402 may include one or more modules to facilitate interaction between processing component 402 and other components. For example, processing component 402 may include a multimedia module to facilitate interaction between multimedia component 408 and processing component 402.

[0146] Memory 404 is configured to store various types of data to support the operation of the coal quantity calculation system 400. Examples of this data include instructions for any application or method operating on the coal quantity calculation system 400, such as text, images, videos, etc. Memory 404 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0147] Power supply component 406 provides power to various components of the coal quantity calculation system 400. Power supply component 406 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the vehicle control system 400.

[0148] The multimedia component 408 includes a screen that provides an output interface between the coal quantity calculation system 400 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of touch or swipe actions but also the duration and pressure associated with the touch or swipe operation. In some embodiments, the multimedia component 408 may also include a front-facing camera and / or a rear-facing camera. When the coal quantity calculation system 400 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0149] Audio component 410 is configured to output and / or input audio signals. For example, audio component 410 includes a microphone (MIC) configured to receive external audio signals when the coal quantity calculation system 400 is in an operating mode, such as alarm mode, recording mode, voice recognition mode, and voice output mode. The received audio signals may be further stored in memory 404 or transmitted via communication component 416. In some embodiments, audio component 410 also includes a speaker for outputting audio signals.

[0150] I / O interface 412 provides an interface between processing component 402 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0151] Sensor assembly 414 includes one or more sensors for providing status assessments of various aspects of the coal quantity calculation system 400. For example, sensor assembly 414 may include a sound sensor. Additionally, sensor assembly 414 can detect the on / off state of the coal quantity calculation system 400, the relative positioning of components (e.g., the display and keypad of the coal quantity calculation system 400), and the operating status of the coal quantity calculation system 400 or one of its components, such as the operating status of the air distribution plate, structural status, the operating status of the discharge scraper, the orientation or acceleration / deceleration of the coal quantity calculation system 400, and temperature changes of the coal quantity calculation system 400. Sensor assembly 414 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 414 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 414 may also include an accelerometer, a gyroscope, a magnetic sensor, a pressure sensor, a material accumulation thickness sensor, or a temperature sensor.

[0152] Communication component 416 is configured to enable the coal quantity calculation system 400 to provide wired or wireless communication capabilities with other devices and cloud platforms. The coal quantity calculation system 400 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 416 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 416 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0153] In an exemplary embodiment, the coal quantity calculation system 400 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the coal quantity calculation method described in any of the above embodiments.

[0154] This application also provides a computer-readable storage medium, which, when the instructions in the storage medium are executed by the processor corresponding to the coal quantity calculation system, enables the coal quantity calculation system to implement the coal quantity calculation method involved in any of the above embodiments.

[0155] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0156] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0157] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0158] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0159] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A coal amount calculation method characterized by comprising: The method comprises the following steps: acquiring a binocular overhead video corresponding to a scraper conveyor; determining a three-dimensional image of coal on the scraper conveyor according to the binocular overhead video; calculating the amount of coal on the scraper conveyor according to the three-dimensional image of coal on the scraper conveyor; the method for calculating the amount of coal on the scraper conveyor according to the three-dimensional image of coal on the scraper conveyor comprises the following steps: acquiring discrete voxels on the three-dimensional image of coal as coal surface points; determining the depth of the coal surface points; determining the height of the coal surface points according to the depth of the coal surface points; classifying the coal surface points according to the height of the coal surface points, wherein the coal surface points in the same height interval are classified into one category; calculating the ratio of the coal surface points in each category to all voxels in the three-dimensional image of coal; calculating the amount of coal according to the ratio of the coal surface points in different categories to all voxels in the three-dimensional image of coal, the bottom area corresponding to the coal flow in the binocular overhead video, and the height of the coal surface points in each category; the method for determining the depth of the coal surface points comprises the following steps: determining the depth of the coal surface points according to the following formula: ； wherein, is a depth of a point on the surface of the coal; is a camera baseline distance; is a camera focal length; is a disparity of a binocular camera that acquires the binocular overhead video; the method for determining the height of the coal surface points according to the depth of the coal surface points comprises the following steps: determining the height of the coal surface points according to the following formula: ； wherein, is the height of the surface point of the coal material; is the distance from the binocula camera to the surface of the trough section of the en masse conveyor to acquire the binocular overhead video; is the depth of the surface point of the coal material; the method for calculating the ratio of the coal surface points in each category to all voxels in the three-dimensional image of coal comprises the following steps: calculating the ratio of the coal surface points in each category to all voxels in the three-dimensional image of coal according to the following formula: ； wherein, is the ratio of the surface points of the i-th category of coal material to all voxels in the three-dimensional image of the coal material; is the number of surface points of the i-th category of coal material; is the number of all voxels in the three-dimensional image of the coal material. the method for calculating the amount of coal according to the ratio of the coal surface points in different categories to all voxels in the three-dimensional image of coal, the bottom area corresponding to the coal flow in the binocular overhead video, and the height of the coal surface points in each category comprises the following steps: calculating the volume of coal according to the following formula: ; wherein, is the volume of the coal material; is the ratio of the surface points of the i-th category of coal material to all voxels in the three-dimensional image of the coal material; is the height of the surface points of the coal material; is the bottom area corresponding to the coal flow in the binocular top-view video.

2. The method of claim 1, wherein, the method for determining the three-dimensional image of coal on the scraper conveyor according to the binocular overhead video comprises the following steps: acquiring a global binocular overhead image corresponding to the binocular overhead video; preprocessing the global binocular overhead image; identifying the preprocessed binocular overhead image to determine the region where the coal is located in the binocular overhead image; determining the three-dimensional image of coal on the scraper conveyor according to the region where the coal is located in the binocular overhead image.

3. The method of claim 2, wherein, the method for acquiring the global binocular overhead image corresponding to the binocular overhead video comprises the following steps: acquiring the transport speed of the scraper conveyor; determining the extraction frequency when extracting images from the binocular overhead video according to the transport speed of the scraper conveyor, so that the extracted images can completely and non-repeatedly contain the coal information in the binocular overhead video; acquiring the global binocular overhead image corresponding to the binocular overhead video according to the extraction frequency.

4. The method of claim 2, wherein, the method for preprocessing the global binocular overhead image comprises the following steps: denoising the global binocular overhead image; performing binaryzation processing on the denoised image to obtain the preprocessed binocular overhead image.

5. A coal amount calculation system characterized by comprising: The device comprises at least one processor and a memory connected in communication with the at least one processor. ​ ​ ​ The memory stores instructions executable by the at least one processor to implement the coal quantity calculation method as claimed in any one of claims 1-4.

Images