Method and device for identifying blanking blockage of sintering round roller

Abstract

The invention relates to a sintering round roller blanking blockage identification method. The method comprises the following steps: acquiring a section of image data of a fixed frame number through a camera lens directly facing a blanking area; marking the exposed part of the round roller in each frame of image data through a target detection model; identifying edge position information of a gate in each frame of image data through image processing; according to the gate edge position information, screening an exposed part of a round roller so as to calculate the probability of gate blockage; if the probability is larger than a set threshold value, it is judged that the gate is blocked. The invention further provides a corresponding sintering round roller discharging blockage recognition device. The sintering round roller blanking identification method is easy and convenient to install and maintain, small in calculated amount, small in environmental interference and high in accuracy.

Description

Technical Field

[0001] The present application relates to a technical field related to material transmission, and in particular to a method and device for identifying a blockage in a sintering round roller. Background Art

[0002] The round roller is a component used to guide materials, adjust the feeding speed, and ensure the smooth operation of the production line during the feeding process. It is usually used in metallurgy, chemical industry, building materials and other industries. In sintering operations, the round roller is usually installed in the feeding system of the sintering machine and used in conjunction with the feeding gate. When the feeding gate is blocked, it may cause material accumulation, increase safety hazards, and cause production interruptions, equipment damage and other problems. Therefore, the feeding position where the round roller is located should be monitored and regularly inspected.

[0003] Existing methods for identifying sintering roller blockage include manual inspection, sensor monitoring, and video monitoring. However, the existing methods have the following limitations and disadvantages in practical applications:

[0004] On the one hand, manual inspections rely on the operator’s experience and judgment, which can easily lead to misjudgments or missed inspections, and result in low recognition accuracy and efficiency.

[0005] On the other hand, the use of sensors for monitoring requires the installation of multiple sensors at key locations. The detection range of a single sensor is limited and may not cover all key areas. Wiring and installation are more complicated and require regular calibration and maintenance. Some sensors, such as pressure sensors, may be affected by environmental factors, resulting in false alarms or missed alarms.

[0006] On the other hand, when using traditional video algorithms for monitoring, there may be problems such as large amount of calculation, inaccurate recognition, low robustness, and excessive sensitivity.

[0007] Therefore, in view of the current sintering round roller material blockage identification technology's low accuracy, low efficiency, complex installation and maintenance, environmental interference, large algorithm calculation amount, and excessive sensitivity, how to provide a sintering round roller material blockage identification method that is easy to install and maintain, has low calculation amount, is less affected by the environment, and has high accuracy, is a technical problem to be solved. Summary of the invention

[0008] In view of the above problems in the prior art, the present application provides a method for identifying blockage in sintering round roller feeding, so as to provide a method which is easy to install and maintain, has a small amount of calculation, is less affected by the environment, and has a high accuracy.

[0009] To achieve the above-mentioned purpose, the first aspect of the present application provides a method for identifying a blockage in a sintering round roller feed, characterized in that a gate is provided above the round roller, and the gate and the round roller together constitute a feed area;

[0010] include:

[0011] Acquire a fixed number of frames of image data through a camera lens facing the material unloading area;

[0012] Marking the exposed portion of the roller in each frame of the image data by using a target detection model;

[0013] Identifying edge position information of the gate in each frame of the image data through image processing;

[0014] Screening the exposed portion of the round roller according to the gate edge position information;

[0015] The probability of the gate being blocked is calculated based on the exposed portion of the round roller after screening; if the probability is greater than a set threshold, it is determined that the gate is blocked.

[0016] As mentioned above, the image data is obtained through the camera lens, and the installation and maintenance are relatively simple; the target detection model is used to identify the exposed part of the round roller and the probability of blockage is calculated based on the exposed part, which has both recognition efficiency and accuracy; the exposed part of the round roller is screened through the gate edge information to prevent interference, which can improve the recognition accuracy.

[0017] As a possible implementation of the first aspect, the gate is a multi-section gate, and the corresponding round roller and the exposed part of the round roller are obtained by segmenting and classifying the position information of the gate edge;

[0018] The probability of gate blockage of each section is calculated to determine whether the gate of each section is blocked.

[0019] From the above, by identifying multiple sections of gates, it can be more adapted to the working environment in actual operations; dividing the exposed range of the round roller according to the edge of the gate can reduce the amount of calculation and improve the calculation efficiency.

[0020] As a possible implementation of the first aspect, the target detection model uses a yolov5s pre-trained model; after the target detection model detects the image data, it returns the exposed part of the round roller, including the position and size information P of the minimum circumscribed rectangle of the exposed part of the round roller, where P is expressed as follows:

[0021] P=(X lt , Y lt , Width, Height)

[0022] Among them, X lt , Y lt is the coordinate of one corner of the minimum bounding rectangle; Width and Height are the width and height of the minimum bounding rectangle.

[0023] From the above, using the yolov5s pre-trained model for target detection can improve recognition efficiency and is suitable for real-time systems. At the same time, the position information of the exposed part of the roller is described by the size of the points and rectangles to facilitate analysis and further calculation.

[0024] As a possible implementation manner of the first aspect, the image processing algorithm includes:

[0025] Using a slicing method on the image data to concentrate the target area at the edge of the gate, and using Gaussian filtering to eliminate interference caused by image noise;

[0026] Using morphological opening operation to eliminate the influence of light and noise and compensate for the image loss caused by the Gaussian filter;

[0027] The sobel edge detection algorithm is used to extract the gate edge slope in the image data in the horizontal direction to obtain a gate edge point set.

[0028] From the above, the accuracy and computational efficiency can be improved by reducing the scope of the target area through the slicing method; the image noise can be eliminated by using Gaussian filtering, which has strong noise reduction ability, can retain edges, and has high computational efficiency; the boundaries of larger objects can be smoothed by using morphological opening operations, and the area of ​​foreground objects can be restored while removing smaller objects and small extensions; finally, the Sobel edge detection algorithm can be used to exclude results that are far away from the gate edge, thereby improving detection accuracy.

[0029] As a possible implementation manner of the first aspect, the gate edge point set is fitted using Hough line detection to obtain a unique straight line at the gate edge, and the straight line is expressed by the following formula:

[0030] ρ=x i ·cos(mortar)+y i ·sin(mortar)

[0031] Where ρ is the vertical distance from the origin to the straight line; θ is the angle between the normal of the straight line and the positive direction of the x-axis; xi, y i are the x-axis and y-axis coordinates of the edge point respectively.

[0032] From the above, by using Hough line detection for fitting, the only straight line at the edge of the gate can be obtained, which is convenient for subsequent processing and improves recognition accuracy.

[0033] As a possible implementation of the first aspect, the screening includes:

[0034] The distance between the minimum circumscribed rectangle of each exposed part of the round roller and the only straight line at the edge of the gate is calculated respectively, and the result is obtained according to the following formula:

[0035] d=|x lt ·cos(θ)+yl t ·sin(θ)-ρ|

[0036] Wherein, d is the distance; x lt ,y lt is the coordinate of the upper left corner of the minimum circumscribed rectangle of the exposed part of the roller;

[0037] For each exposed part of the round roller, if the distance d is greater than the threshold value T1 or the height Height of the minimum circumscribed rectangle is less than the threshold value T2, the exposed part of the round roller does not meet the standard and is removed.

[0038] As described above, by removing the exposed part of the round roller that is far away from the gate or smaller, irrelevant interference can be reduced and the accuracy of recognition can be improved.

[0039] As a possible implementation of the first aspect, the probability of the gate being blocked in each section is calculated by calculating the ratio of the number of frames in which the exposed portion of the round roller corresponding to each section of the gate appears to the fixed number of frames, and the total probability of the gate being blocked is obtained according to the following formula:

[0040]

[0041] Among them, γ is the probability of each gate section being blocked; n is the number of frames in which the round roller of a corresponding gate section has an exposed part; and m is the fixed number of frames.

[0042] From the above, by calculating the ratio of the number of frames with exposed parts of each section of the round roller to the fixed number of frames, the blockage situation within a period of time can be checked while reducing the amount of calculation, preventing the problem of over-sensitivity to the results due to real-time inspection, and improving the accuracy and robustness of recognition.

[0043] The second aspect of the present application provides a sintering round roller feed blockage identification device, comprising:

[0044] An image collection module is used to obtain a fixed number of frames of image data through a camera lens facing the material unloading area;

[0045] An image processing module is used to mark the exposed part of the round roller in each frame of the image data through a target detection model; identify the edge position information of the gate in each frame of the image data through image processing; and screen the exposed part of the round roller according to the gate edge position information;

[0046] The calculation output module is used to calculate the probability of the gate being blocked according to the exposed part of the round roller after screening; if the probability is greater than a set threshold, it is determined that the gate is blocked.

[0047] A third aspect of the present application provides a computing device, comprising: a processor, and a memory, on which program instructions are stored, and when the program instructions are executed by the processor, the processor executes the method for identifying a blockage in the unloading of a sintered round roller as described in any one of the first aspects.

[0048] A fourth aspect of the present application provides a computer-readable storage medium having program instructions stored thereon, wherein when the program instructions are executed by a computer, the computer executes the method for identifying a blockage in the unloading of a sintered round roller as described in any one of the first aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a flow chart of the first embodiment of the method for identifying blockage in sintering round roller feeding of the present application;

[0050] Figure 2 This is a flow chart of a second embodiment of the method for identifying blockage in sintering round roller feeding of the present application;

[0051] Figure 3 is a schematic diagram of camera setting positions provided in the second embodiment of the present application;

[0052] Figure 4 It is a schematic diagram of a method and device for identifying a blockage in a sintering round roller feeding provided in an embodiment of the present application;

[0053] Figure 5 It is a structural schematic diagram of a computing device provided in an embodiment of the present application.

[0054] It should be understood that the size and shape of each block diagram in the above structural diagram are for reference only and should not constitute an exclusive interpretation of the embodiment of the present invention. The relative position and inclusion relationship between the blocks presented in the structural diagram are only schematic representations of the structural association between the blocks, and do not limit the physical connection method of the embodiment of the present invention. DETAILED DESCRIPTION

[0055] The technical solution provided by the present application is further described below with reference to the accompanying drawings and examples. It should be understood that the system structure and business scenarios provided in the examples of the present application are mainly to illustrate the possible implementation methods of the technical solution of the present application and should not be interpreted as the only limitation on the technical solution of the present application. It is known to those of ordinary skill in the art that with the evolution of the system structure and the emergence of new business scenarios, the technical solution provided by the present application is also applicable to similar technical problems.

[0056] It should be understood that the sintering roller blanking blockage identification solution provided in the embodiment of the present application includes a sintering roller blanking blockage identification method, device, computing device and computer-readable storage medium. Since the principles of solving the problems in these technical solutions are the same or similar, some repetitions may not be repeated in the introduction of the following specific embodiments, but it should be regarded that these specific embodiments have been referenced to each other and can be combined with each other.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of this application. In the event of any inconsistency, the meaning described in this specification or the meaning derived from the contents recorded in this specification shall prevail. In addition, the terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application. In order to accurately describe the technical content in this application and to accurately understand the present invention, the following explanations or definitions are given to the terms used in this specification before describing the specific embodiments:

[0058] 1) You Only Look Once version 5 small model (YOLOv5s): It is a version in the YOLO model series of real-time target detection algorithm. It is fast and accurate. It can complete target detection and classification tasks in a single forward propagation. YOLOv5s provides an option that balances speed and accuracy.

[0059] 2) Edge Detection Algorithm: It is a key technology in image processing and computer vision. It determines the edge by detecting significant changes in pixel intensity in the image. Common edge detection algorithms include Sobel edge detection and Canny edge detection. These algorithms play a key role in many applications such as image segmentation, feature extraction, and target recognition.

[0060] The sintering round roller unloading blockage identification scheme provided in the embodiment of the present application can collect image data during the sintering unloading process, identify the exposed part of the round roller and the edge position of the gate in the data through the target detection model and image processing, and calculate the probability of the round roller being exposed in the unloading area, that is, the probability of the gate being blocked. This method addresses the problems of low accuracy, low efficiency, complex installation and maintenance, environmental interference, large algorithm calculation amount, and oversensitivity in the current sintering round roller unloading blockage identification technology, and provides a sintering round roller unloading identification method that is easy to install and maintain, has a small amount of calculation, is less affected by the environment, and has high accuracy. The embodiment of the present application can be applied to the monitoring and blockage identification of unloading operations in the fields of sintering operations, steel smelting, and material transportation. The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0061] The first embodiment of the present application provides a method for identifying a blockage in a sintered round roller feed, wherein a gate is provided above the round roller, and the gate and the round roller together constitute a feed area. Figure 1 , the implementation of each step of the method is specifically described, including steps S10-S50.

[0062] S10: Acquire a fixed number of frames of image data through a camera lens facing the material unloading area.

[0063] In some embodiments, industrial cameras are used as image data acquisition tools; wherein the industrial cameras may include area array cameras, line array cameras, and other cameras that can acquire images containing visual information.

[0064] In some embodiments, the camera lens should be placed horizontally facing the unloading area and the influence of lens distortion should be reduced by setting a reasonable distance; the image data collected by the camera should include the entire roller area and the complete gate edge.

[0065] In some embodiments, a camera lens can be used to obtain a fixed number of frames of image data for subsequent processing, or the required data can be obtained by quickly taking multiple static images; a video segment and its duration can also be obtained for subsequent processing.

[0066] In some embodiments, the unloading area includes a plurality of segmented gates, and the blockage status of each segmented gate can be determined by identifying the blockage of the segmented gates and the corresponding roller areas below them.

[0067] In some embodiments, the acquired images can be processed in real time with the PLC system via a communication protocol; they can also be sent to a suitable processing device via a communication protocol or other data transmission methods for subsequent processing and feedback.

[0068] S20: Marking the exposed part of the round roller in each frame of the image data by using a target detection model.

[0069] In some embodiments, a deep learning target detection algorithm is used to detect the exposed part of the round roller, such as yolov5s can be used as the algorithm used for target detection; wherein, pre-trained models such as yolov5s can be directly used for position detection of the exposed part of the round roller; the result can also be verified and fine-tuned by collecting position information data of the exposed part during the blanking process; the training and verification data can also be re-collected, and deep learning, machine learning, statistical learning and other models can be built for training and adjustment to obtain a target detection model.

[0070] In some embodiments, the position information of the exposed part of the circular roller can be represented by the minimum circumscribed rectangle of the exposed part and the coordinates of the upper left corner of the minimum circumscribed rectangle; it can also be represented by a set of contour points of the exposed part or other data that can represent the position and size of the exposed part; wherein the position information is the result returned by the target detection model or the result obtained after further calculation.

[0071] S30: Identify the edge position information of the gate in each frame of the image data through image processing.

[0072] In some embodiments, the image processing algorithm first preprocesses the input image; wherein the preprocessing may include steps such as median filtering, morphological opening, graying, normalization, Gaussian filtering, local enhancement, etc.; the target area may be concentrated at the edge of the gate by slicing; and the area of ​​the lost foreground object may be restored by further using morphological opening after using Gaussian filtering to eliminate fine noise in the image.

[0073] In some embodiments, edge detection is used to obtain the position of the gate edge in the image; wherein, the edge detection algorithm can use the Sobel operator, Canny operator, Laplacian operator, Prewitt operator, Roberts operator, etc.; by detecting all edges in the image, the edge point coordinates of the gate edge are screened, and the straight line formula of the position of the gate edge is obtained by methods such as Hough line detection and straight line fitting; wherein, the edge point coordinates of the gate edge can be screened by using the Sobel operator to extract the edge information in the lateral direction or near the lateral direction in the image to improve the detection accuracy; a unique edge straight line can be obtained by setting the threshold of the Hough line detection algorithm; a unique track straight line can also be obtained by screening possible edge lines using probability distribution and other methods; wherein the edge straight line can be represented in the form of polar coordinates or rectangular coordinates.

[0074] In some embodiments, the gate edge position can also be obtained using target detection algorithms such as deep learning.

[0075] S40: Screening the exposed portion of the round roller according to the gate edge position information.

[0076] In some embodiments, the exposed part of the round roller can be screened according to the distance between the exposed part of the round roller and the edge of the gate. If the exposed part is far away from the edge of the gate, the exposed part may be a normal phenomenon and should be removed from the set of exposed parts.

[0077] In some embodiments, the exposed parts with smaller sizes can be eliminated by limiting the height or width of the exposed parts of the round roller, such as ignoring the exposed parts of the round roller whose height is less than a set threshold.

[0078] S50: Calculate the probability of the gate being blocked according to the exposed portion of the round roller after screening; if the probability is greater than a set threshold, determine that the gate is blocked.

[0079] In some embodiments, the probability of gate blockage is calculated by calculating the ratio of the number of frames or duration in which the exposed part of the round roller appears to the total number of frames and duration of the material unloading process; wherein, by recording the existence of the exposed part in each frame, the total number of frames in which the exposed part appears is obtained; the exposed part of each frame can also be further limited to count the number of frames in which the exposed part appears, such as using the distribution probability statistics method to limit the number and area size of the exposed parts.

[0080] In some embodiments, whether the gate is blocked is determined by setting a threshold.

[0081] The second embodiment of the present application provides a method for identifying a blockage in a sintering roller feed, wherein a gate is provided above the roller, and the gate and the roller together constitute a feed area; the gate is a multi-stage gate. Figure 2 The method provided by the second embodiment includes the following steps S200-S250.

[0082] S200: Acquire image data to be detected through a camera lens.

[0083] Set the camera lens to face the edge of the roller and the gate. Figure 3 As shown; when the gate is opened and the round roller is unloading, a fixed frame number m of image data is collected through the camera lens for analysis.

[0084] S210: Acquire the position information of the exposed part of the round roller through the YOLO target detection algorithm.

[0085] The exposed part in the roller blanking area is identified frame by frame using the YOLO target detection algorithm for the acquired images, and the minimum circumscribed rectangle information P of the exposed part is returned. The format is as follows:

[0086] P=(X lt , Y lt , Width, Height)

[0087] Among them, X lt , Y lt is the coordinate of the upper left corner of the minimum bounding rectangle; Width and Height are the width and height of the minimum bounding rectangle.

[0088] S220: Identify the gate edge through image processing.

[0089] The collected images are processed frame by frame, including the following steps:

[0090] First, the image is preprocessed by using the slicing method to concentrate the target area near the edge of the gate to reduce the amount of recognition calculation; then Gaussian filtering is used to eliminate the interference caused by image noise to the greatest extent.

[0091] Through morphological opening operation, the influence of materials and other small noises in the feeding process is eliminated.

[0092] By using the Sobel edge detection algorithm and the horizontal convolution kernel to extract the edges in the horizontal direction of the image, the accuracy of gate edge detection is improved, and finally the edge point set of the gate edge is obtained.

[0093] Since the gate is multi-segmented, the edge points need to be segmented to represent the gate information at different locations. The set of edge position coordinate points at each location is represented as l i , then l i (x i ,y i )∈f(x,y);x i ,y i are the x-axis and y-axis coordinates of the edge points, and f(x, y) is the coordinates of all detected edge points.

[0094] S230: Calculate the only straight line at the gate edge.

[0095] For each gate edge point set l i (x i ,y i ) Use Hough line detection to fit and obtain a unique edge segment; the edge of a multi-segment gate is obtained based on the combination of multiple segments. The straight line where the unique edge segment of each segment is located can be expressed as follows:

[0096] ρ=x i ·cos(mortar)+y i ·sin(mortar)

[0097] Wherein, ρ is the vertical distance from the origin to the straight line; θ is the angle between the normal of the straight line and the positive direction of the x-axis.

[0098] S240: Calculate the distance from the exposed part of the round roller to the edge of the gate, and screen the exposed part of the round roller.

[0099] The distance from the exposed part of each roller to the edge of the corresponding segmented gate can be calculated according to the following formula:

[0100] d=|x lt ·cos(θ)+y lt ·sin(θ)-ρ|

[0101] Wherein, d is the distance; xlt , y lt is the upper left corner coordinate of the minimum circumscribed rectangle of the exposed part of the round roller.

[0102] It is normal during the blanking process that the exposed part of the round roller is too far from the edge of the gate or the exposed part of the round roller is too small. Therefore, it should be excluded during the recognition and judgment process. Therefore, distance thresholds T1 and T2 are set. For the exposed part P of the round roller where d > T1 or Height < T2, it will be excluded from the results of the exposed part of the round roller.

[0103] S250: Calculate the probability of gate blockage and judge whether the gate is blocked.

[0104] Based on the probability of the exposed part of the round roller appearing within a period of time collected by the camera lens, judge whether there is a blockage phenomenon in the gate corresponding to the exposed part of the round roller. Specifically, calculate the ratio of the number of frames in which the exposed part of the round roller appears in each segment to the fixed number of frames, as shown in the following formula:

[0105]

[0106] where γ is the probability of gate blockage in each segment; n is the number of frames in which the exposed part of the round roller appears in each segment; m is the fixed number of frames.

[0107] When γ is greater than the set threshold, it is determined that this segment of the gate is blocked and feedback to relevant staff and equipment for further processing. Different monitoring and recognition requirements can be met by adjusting and setting the threshold.

[0108] The third embodiment of the present application provides a sintering round roller blanking recognition device, which can be used to implement the sintering round roller blanking recognition method in the above embodiment, such as Figure 4 shown, the sintering round roller blanking recognition device includes:

[0109] An image collection module for obtaining image data of a fixed number of frames through a camera lens facing the blanking area; specifically, this image collection module can be used to implement step S10 and its optional embodiments in the first embodiment.

[0110] An image processing module for marking the exposed part of the round roller in each frame of the image data through a target detection model; identifying the edge position information of the gate in each frame of the image data through image processing; screening the exposed part of the round roller according to the gate edge position information; specifically, this image processing module can be used to implement steps S20 - S40 and their optional embodiments in the first embodiment.

[0111] The calculation output module is used to calculate the probability of the gate being blocked based on the exposed part of the round roller after screening; if the probability is greater than the set threshold, it is determined that the gate is blocked; specifically, the calculation output module can be used to implement step S50 in the first embodiment and its optional embodiments.

[0112] Figure 5 900 is a schematic structural diagram of a computing device 900 provided in an embodiment of the present application. The computing device can execute each optional embodiment of the above method, and the computing device can be a terminal, or a chip or chip system inside the terminal. Figure 5 As shown, the computing device 900 includes: a processor 910 , a memory 920 , and a communication interface 930 .

[0113] It should be understood that Figure 5 The communication interface 930 in the computing device 900 shown may be used to communicate with other devices, and may specifically include one or more transceiver circuits or interface circuits.

[0114] The processor 910 may be connected to a memory 920. The memory 920 may be used to store the program code and data. Therefore, the memory 920 may be a storage unit inside the processor 910, or an external storage unit independent of the processor 910, or a component including a storage unit inside the processor 910 and an external storage unit independent of the processor 910.

[0115] Optionally, the computing device 900 may further include a bus. The memory 920 and the communication interface 930 may be connected to the processor 910 via the bus. The bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 A line without an arrow is used to represent the bus, but this does not mean that there is only one bus or one type of bus.

[0116] It should be understood that in the embodiment of the present application, the processor 910 may adopt a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. Alternatively, the processor 910 may adopt one or more integrated circuits to execute relevant programs to implement the technical solutions provided in the embodiment of the present application.

[0117] The memory 920 may include a read-only memory and a random access memory, and provides instructions and data to the processor 910. A portion of the processor 910 may also include a nonvolatile random access memory. For example, the processor 910 may also store information on the device type.

[0118] When the computing device 900 is running, the processor 910 executes the computer-executable instructions in the memory 920 to perform any operation step of the above method and any optional embodiment thereof.

[0119] It should be understood that the computing device 900 according to the embodiment of the present application can correspond to the corresponding subjects in the methods according to the embodiments of the present application, and the above-mentioned and other operations and / or functions of each module in the computing device 900 are respectively for implementing the corresponding processes of each method of the present embodiment. For the sake of brevity, they will not be repeated here.

[0120] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0121] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0122] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0123] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0124] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0125] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0126] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, it is used to execute the above method, which includes at least one of the solutions described in the above embodiments.

[0127] The computer storage medium of the embodiment of the present application can adopt any combination of one or more computer-readable media. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples (non-exhaustive lists) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, computer-readable storage media can be any tangible medium containing or storing programs, which can be used by instruction execution systems, devices or devices or used in combination with them.

[0128] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0129] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0130] Computer program code for performing the operation of the present application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0131] In addition, the words "first, second, third, etc." or module A, module B, module C and other similar terms in the specification and claims are only used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that the specific order or sequence can be interchanged where permitted so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0132] In the above description, the numbers representing the steps, such as S110, S120, etc., do not necessarily mean that the steps will be executed in this manner. If permitted, the order of the steps can be interchanged or they can be executed simultaneously.

[0133] The term "comprising" as used in the description and claims should not be interpreted as being limited to what is listed thereafter; it does not exclude other elements or steps. Therefore, it should be interpreted as specifying the presence of the features, integers, steps or components mentioned, but does not exclude the presence or addition of one or more other features, integers, steps or components and groups thereof. Therefore, the expression "a device comprising means A and B" should not be limited to a device consisting of components A and B only.

[0134] References to "one embodiment" or "an embodiment" in this specification mean that a particular feature, structure, or characteristic described in conjunction with the embodiment is included in at least one embodiment of the present application. Therefore, the phrases "in one embodiment" or "in an embodiment" appearing in various places in this specification do not necessarily refer to the same embodiment, but may refer to the same embodiment. In addition, in one or more embodiments, the particular features, structures, or characteristics can be combined in any appropriate manner, as would be apparent to one of ordinary skill in the art from this disclosure.

[0135] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may also include more other equivalent embodiments without departing from the concept of the present application, all of which belong to the scope of protection of the present application.

Claims

1. A method for identifying a blockage in a round roller feeding, characterized in that: A gate is provided above the round roller, and the gate and the round roller together constitute a material unloading area; The method comprises: Acquire a fixed number of frames of image data through a camera lens facing the material unloading area; Marking the exposed portion of the roller in each frame of the image data by using a target detection model; Identifying edge position information of the gate in each frame of the image data through image processing; Screening the exposed portion of the round roller according to the gate edge position information; The probability of the gate being blocked is calculated based on the exposed portion of the round roller after screening; if the probability is greater than a set threshold, it is determined that the gate is blocked.

2. The method according to claim 1, characterized in that include: The gate is a multi-section gate, and the corresponding round roller and the exposed part of the round roller are obtained by segmenting and classifying the position information of the gate edge; The probability of gate blockage of each section is calculated to determine whether the gate of each section is blocked.

3. The method according to claim 2, characterized in that The target detection model uses the yolov5s pre-trained model; after the target detection model detects the image data, it returns the exposed part of the round roller, including the position and size information P of the minimum circumscribed rectangle of the exposed part of the round roller, where P is expressed as follows: P=(X lt ,Y lt ,Width,Height) Among them, X lt ,Y lt is the coordinate of one corner of the minimum bounding rectangle; Width and Height are the width and height of the minimum bounding rectangle.

4. The method according to claim 3, characterized in that The image processing algorithm includes: Using a slicing method to concentrate the target area on the edge of the gate for the image data, and using Gaussian filtering to eliminate interference caused by image noise; Using morphological opening operation to eliminate the influence of light and noise and compensate for the image loss caused by the Gaussian filter; The sobel edge detection algorithm is used to extract the gate edge slope in the image data in the horizontal direction to obtain a gate edge point set.

5. The method according to claim 4, characterized in that The gate edge point set is fitted using Hough line detection to obtain a unique straight line at the gate edge, which is expressed by the following formula: p=x i ·cos(θ)+y i ·sin(θ) Wherein, ρ is the vertical distance from the origin to the straight line; θ is the angle between the normal of the straight line and the positive direction of the x-axis; x i ,y i are the x-axis and y-axis coordinates of the edge point respectively.

6. The method according to claim 5, characterized in that The screening includes: The distance between the minimum circumscribed rectangle of each exposed part of the round roller and the only straight line at the edge of the gate is calculated respectively, and the result is obtained according to the following formula: d=|x lt ·cos(θ)+y lt ·sin(θ)-ρ| Wherein, d is the distance; x lt ,y lt is the coordinate of the upper left corner of the minimum circumscribed rectangle of the exposed part of the roller; For each exposed part of the round roller, if the distance d is greater than the threshold value T1 or the height Height of the minimum circumscribed rectangle is less than the threshold value T2, the exposed part of the round roller does not meet the standard and is removed.

7. The method according to claim 6, characterized in that The probability of the gate being blocked in each section is calculated by calculating the ratio of the number of frames in which the exposed portion of the round roller corresponding to each section of the gate appears to the fixed number of frames. The total probability of the gate being blocked is obtained according to the following formula: Among them, γ is the probability of each gate section being blocked; n is the number of frames in which the round roller of a corresponding gate section has an exposed part; and m is the fixed number of frames.

8. A device for identifying blockage of sintering round roller feeding, characterized in that: include: An image collection module is used to obtain a fixed number of frames of image data through a camera lens facing the material unloading area; An image processing module, used for marking the exposed part of the round roller in each frame of the image data by using a target detection model; Identifying edge position information of the gate in each frame of the image data through image processing; Screening the exposed portion of the round roller according to the gate edge position information; The calculation output module is used to calculate the probability of the gate being blocked according to the exposed part of the round roller after screening; if the probability is greater than a set threshold, it is determined that the gate is blocked.

9. A computing device, characterized in that include: processor, and A memory having program instructions stored thereon, wherein when the program instructions are executed by the processor, the processor executes the method for identifying a blockage in the unloading of a sintered round roller according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Program instructions are stored thereon, and when the program instructions are executed by a computer, the computer executes the method for identifying a blockage in the unloading of a sintered round roller according to any one of claims 1 to 7.

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