Detection method and device for tundish nozzle, electronic equipment and storage medium

Abstract

The invention discloses a tundish nozzle detection method and device, electronic equipment and a storage medium, and belongs to the technical field of ferrous metallurgy automation, and the method comprises the steps: determining the resolution of a target image based on the target image of any to-be-detected target tundish nozzle and the basic parameter information of the target tundish nozzle; based on the target image and a preset threshold segmentation algorithm, determining a target section pixel area at a tundish nozzle of the target; determining target slag line pixel information and target necking pixel information at a target tundish nozzle based on the target image and a trained tundish nozzle feature recognition model; and based on the resolution, the target contour pixel area, the target slag line pixel information and the target necking pixel information, respectively determining a target section physical area, target slag line physical information and target necking physical information at the target tundish nozzle. According to the method, the accuracy of parameter measurement at the tundish nozzle can be improved, and the measurement efficiency is improved while the measurement error is reduced.

Description

Technical Field

[0001] The present application relates to the field of iron and steel metallurgical automation technology, and in particular to a method, device, electronic equipment and storage medium for detecting a tundish water outlet. Background Art

[0002] At present, the tundish water inlet is the protective casting channel for molten steel between the tundish and the crystallizer. During the steelmaking process, the cross-section of the tundish water inlet is controlled by a stopper rod, thereby controlling the flow rate and flow field of the molten steel inside the crystallizer. The stopper rod can effectively prevent secondary oxidation and splashing of the molten steel.

[0003] However, during the steel pouring process, the molten steel flushes the inner wall of the tundish nozzle, causing the inclusions in the molten steel to adhere to and gather on the inner wall of the nozzle to form nodules, and at the same time, slag is formed on the outside of the nozzle and near the steel spout. Nodules and slag at the nozzle can easily cause fluctuations in the flow field of the crystallizer, leading to unstable casting, nodule shedding, slag rolling, nozzle blockage and other accidents, which seriously affect the quality of the ingot. Therefore, after the tundish nozzle is offline, it is necessary to effectively detect the usage of the tundish nozzle to provide reliable protection for the nozzle material, structure and casting process.

[0004] Since the working temperature of the tundish nozzle is high and the shape of the nozzle is irregular after slag erosion, quantitative detection of the nozzle is very difficult. Therefore, the use of the nozzle is currently mainly evaluated through manual visual inspection, tape measure measurement, and rubbing. However, manual measurement has large measurement errors, low accuracy and low efficiency. Summary of the invention

[0005] The embodiments of the present application provide a method, device, electronic device and storage medium for detecting a water outlet of a middle bag. The embodiments provided in the present application can improve the accuracy of parameter measurement at the water outlet of the middle bag, thereby reducing measurement errors and improving measurement efficiency.

[0006] In a first aspect of the embodiments of the present application, the embodiments of the present application provide a method for detecting a water outlet of a middle package, and the method for detecting a water outlet of a middle package comprises:

[0007] Determine the resolution of the target image based on a target image at a water-inlet opening in any target to be detected and basic parameter information of the water-inlet opening in the target;

[0008] Based on the target image and a preset threshold segmentation algorithm, determining the target cross-sectional pixel area at the water inlet of the target;

[0009] Based on the target image and the trained middle ladle water inlet feature recognition model, target slag line pixel information and target necking pixel information at the target middle ladle water inlet are determined, wherein the trained middle ladle water inlet feature recognition model is used to characterize a model for identifying slag line features and necking features;

[0010] Based on the resolution, the target contour pixel area, the target slag line pixel information and the target neck pixel information, the target cross-sectional physical area, the target slag line physical information and the target neck physical information at the target water inlet are determined respectively.

[0011] In a feasible implementation manner, the step of determining the resolution of the target image based on the target image at the water inlet of any target to be detected and the basic parameter information of the water inlet of the target includes:

[0012] Based on a target image at a water inlet of any target to be detected, determining a reference scale pixel length of the target image, wherein the reference scale is used to represent any physical unit size at the water inlet of the target in the target image;

[0013] Based on the basic parameter information of the target water-enclosing outlet, determining the reference scale physical length of the target water-enclosing outlet;

[0014] The resolution of the target image is determined according to the pixel length of the reference scale and the physical length of the reference scale.

[0015] In a feasible implementation manner, a target image at a water outlet of any target to be detected is determined by the following method, and the method for detecting the water outlet of the target includes:

[0016] Determine an initial image at the water inlet of any target to be detected;

[0017] Based on the initial image and the trained middle bag water outlet recognition model, a target image at any target middle bag water outlet to be detected is determined, wherein the trained middle bag water outlet recognition model is used to characterize a model for identifying the middle bag water outlet.

[0018] In a feasible implementation manner, determining the target cross-sectional pixel area at the water inlet of the target based on the target image and a preset threshold segmentation algorithm includes:

[0019] Performing grayscale processing on the target image to determine the coordinates of the target point in the target image;

[0020] Based on the target point coordinates and a preset threshold segmentation algorithm, the target cross-sectional pixel area at the water inlet in the target is determined from the target image.

[0021] In a feasible implementation, based on the target point coordinates and a preset threshold segmentation algorithm, determining the target cross-sectional pixel area at the water inlet in the target from the target image includes:

[0022] Based on the target point coordinates and the preset point division rules, the candidate area image of the middle package water outlet is determined from the target image;

[0023] Based on the candidate area image and a preset threshold segmentation algorithm, the target cross-sectional pixel area at the water inlet in the target is determined.

[0024] In a feasible implementation manner, after determining the target cross-sectional physical area, target slag line physical information and target neck physical information at the target middle ladle water outlet respectively based on the resolution, the target contour pixel area, the target slag line pixel information and the target neck pixel information, the middle ladle water outlet detection method further includes:

[0025] Based on the target cross-sectional physical area at the target middle ladle water inlet, the target slag line physical information, the target necking physical information and the continuous casting process equipment data of the target middle ladle water inlet, a middle ladle water inlet database is constructed for query by operators.

[0026] In a feasible implementation manner, after constructing a mid-bag water inlet database based on the target cross-sectional physical area at the target mid-bag water inlet, the target slag line physical information, the target necking physical information and the continuous casting process equipment data of the target mid-bag water inlet for query by operators, the mid-bag water inlet detection method further includes:

[0027] Based on the target cross-sectional physical area, target slag line physical information and target necking physical information at the target middle water inlet, it is determined whether the structure and casting process of the target middle water inlet need to be optimized.

[0028] In a second aspect of the embodiment of the present application, the embodiment of the present application provides a detection device for a water outlet of a middle package, and the detection device for the water outlet of the middle package includes:

[0029] A first determination module is used to determine the resolution of the target image based on a target image at a water-inlet in any target to be detected and basic parameter information of the water-inlet in the target;

[0030] A second determination module is used to determine the target cross-sectional pixel area at the water inlet of the target based on the target image and a preset threshold segmentation algorithm;

[0031] A third determination module is used to determine the target slag line pixel information and the target necking pixel information at the target middle ladle water inlet based on the target image and the trained middle ladle water inlet feature recognition model, wherein the trained middle ladle water inlet feature recognition model is used to characterize the model for identifying the slag line feature and the necking feature;

[0032] The fourth determination module is used to determine the target cross-sectional physical area, target slag line physical information and target neck physical information at the target water inlet based on the resolution, the target contour pixel area, the target slag line pixel information and the target neck pixel information.

[0033] According to a third aspect of the embodiments of the present application, an electronic device is provided, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the memory through the bus, and the machine-readable instructions are executed by the processor when running, such as the steps of the above-mentioned water outlet detection method.

[0034] In a fourth aspect of the embodiments of the present application, the embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the water outlet detection method as described above are executed.

[0035] The detection method, device and electronic device for the water inlet provided in the embodiments of the present application, compared with the prior art, the embodiments provided in the present application determine the resolution of the target image based on the target image at any target water inlet to be detected and the basic parameter information of the target water inlet, and determine the target cross-sectional pixel area at the target water inlet based on the target image and a preset threshold segmentation algorithm, and then determine the target slag line pixel information and target necking pixel information at the target water inlet based on the target image and a trained water inlet feature recognition model, and determine the target cross-sectional physical area, target slag line physical information and target necking physical information at the target water inlet based on the resolution, target contour pixel area, target slag line pixel information and target necking pixel information, respectively, which can improve the accuracy of parameter measurement at the water inlet, and improve measurement efficiency while reducing measurement errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 One of the flow charts of a method for detecting a water outlet of a middle package provided in an embodiment of the present application is shown;

[0037] Figure 2 The second flowchart of a method for detecting a water outlet of a middle package provided in an embodiment of the present application is shown;

[0038] Figure 3 A structural block diagram of a detection device for a middle bag water outlet provided in an embodiment of the present application is shown;

[0039] Figure 4 A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown.

[0040] Figure 3 and Figure 4 The corresponding relationship between the reference numerals and the names of the drawings is as follows:

[0041] 300 includes a detection device for a water outlet; 310 a first determination module; 320 a second determination module; 330 a third determination module; 340 a fourth determination module; 350 a construction module; 360 a fifth determination module; 400 an electronic device; 410 a processor; 420 a memory; and 430 a bus. DETAILED DESCRIPTION

[0042] In order to better understand the technical solutions provided by the embodiments of this specification, the technical solutions of the embodiments of this specification are described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of this specification and the specific features in the embodiments are detailed descriptions of the technical solutions of the embodiments of this specification, rather than limitations on the technical solutions of this specification. In the absence of conflict, the embodiments of this specification and the technical features in the embodiments can be combined with each other.

[0043] In this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or equipment. In the absence of more restrictions, the elements limited by the statement "comprise one..." do not exclude the existence of other identical elements in the process, method, article or equipment including the elements. The term "more than two" includes two or more than two situations.

[0044] First, the applicable application scenarios of the present application are introduced. The embodiments provided in the present application are applicable to the field of iron and steel metallurgical automation technology.

[0045] At present, due to the high working temperature of the tundish nozzle and the irregular shape of the nozzle after slag erosion, quantitative detection of the water nozzle has caused great difficulties. Therefore, the use of the nozzle is currently mainly evaluated through manual visual inspection, tape measure measurement, and rubbing. However, manual measurement has large measurement errors, low accuracy and low efficiency.

[0046] Moreover, the traditional manual measurement method cannot obtain the accurate steel-passing area at the sprue, which affects the subsequent evaluation of the sprue usage. The manually measured slag line of the sprue has certain high-temperature operation risks, and the measurement results are easily affected by the operator. At the same time, the manually measured sprue steel-passing data cannot record the offline sprue usage and the continuous casting process equipment data when the sprue is working in real time, thus affecting the subsequent use and optimization of the sprue.

[0047] Based on this, the embodiments of the present application provide a method, device, electronic device and storage medium for detecting the water outlet of the middle package. The embodiments provided by the present application can improve the accuracy of parameter measurement at the water outlet of the middle package, thereby reducing measurement errors and improving measurement efficiency.

[0048] See also Figure 1 , Figure 1 One of the flow charts of a method for detecting a water outlet of a middle package provided in an embodiment of the present application is as follows: Figure 1 As shown in the figure, the method for detecting the water outlet of the middle package provided in the embodiment of the present application comprises the following steps:

[0049] S101, determining the resolution of the target image based on a target image at a water-containing outlet of any target to be detected and basic parameter information of the water-containing outlet of the target.

[0050] In this step, the embodiment provided by the present application, under the premise of wanting to evaluate the usage of the water outlet of the target to be detected, first needs to collect the target image at the water outlet of the target and the basic parameter information corresponding to the water outlet of the target, and then determine the resolution of the target image based on the collected pixel information of the target image and the basic parameter information of the water outlet of the target, wherein the resolution in the embodiment provided by the present application is characterized by θ.

[0051] The basic parameter information corresponding to the water-included outlet in the target includes but is not limited to information such as the actual length of the water-included outlet in the target.

[0052] It can be understood that the target image in the embodiments provided in the present application can be captured by an artificial camera, an industrial camera image acquisition device, an industrial camera system, etc., to complete the storage of the target image at the water inlet of the target package. It is assumed that the target image in the embodiments provided in the present application is represented by image(w1,h1).

[0053] S102, determining a target cross-sectional pixel area at a water inlet in the target based on the target image and a preset threshold segmentation algorithm.

[0054] In this step, after the target image at the target water inlet is acquired, it is necessary to determine the through-steel area that affects the molten steel flow rate at the target water inlet. The through-steel area in the embodiment provided in the present application is determined based on the target cross-sectional pixel area at the target water inlet.

[0055] It is assumed that the embodiment provided in the present application is specific but not limited to determining the target cross-sectional pixel area at the water outlet of the target according to a preset threshold segmentation algorithm or semantic segmentation method and the corresponding target image. It is assumed that the target cross-sectional pixel area in the embodiment provided in the present application can be specifically represented by Sp.

[0056] Among them, the embodiments provided in the present application specifically but not limitingly use a preset threshold segmentation algorithm, and may also use semantic segmentation or manual labeling and the like.

[0057] S103. Determine the target slag line pixel information and target necking pixel information at the target middle ladle water outlet based on the target image and the trained middle ladle water outlet feature recognition model, wherein the trained middle ladle water outlet feature recognition model is used to characterize the model for identifying slag line features and necking features.

[0058] In this step, the main factors affecting the flow rate of molten steel at the target middle ladle water outlet in the embodiment provided by the present application include, in addition to the through steel area determined based on the target cross-sectional pixel area, the width and height of the target middle ladle water outlet. The embodiment provided by the present application determines the height and width of the target middle ladle water outlet based on the determined target slag line pixel information and target necking pixel information at the target middle ladle water outlet. In addition to automatically and / or manually determining the target slag line pixel information and target necking pixel information in the target image, the embodiment provided by the present application can also identify the target slag line pixel information and target necking pixel information at the target middle ladle water outlet in the target image through a trained middle ladle water outlet feature recognition model.

[0059] In the above, the embodiment provided in the present application uses a trained middle bag water outlet feature recognition model to determine the target slag line pixel information and target necking pixel information at the target middle bag water outlet. However, in actual application scenarios, manual selection can also be used to determine the target slag line pixel information and target necking pixel information at the target middle bag water outlet.

[0060] It can be understood that the target slag line pixel information in the embodiment provided in the present application can be specifically the target slag line pixel height, specifically expressed as h. p The target necking pixel information in the embodiment provided in the present application may be specifically the target necking pixel width, specifically w p To express.

[0061] Among them, the trained middle ladle nozzle feature recognition model in the embodiment provided in the present application is obtained by training an initial neural network model based on a large number of sample images and sample feature labels in the sample images.

[0062] S104, based on the resolution, the target contour pixel area, the target slag line pixel information and the target necking pixel information, respectively determine the target cross-sectional physical area, target slag line physical information and target necking physical information at the target water inlet.

[0063] In this step, the embodiments provided in this application are respectively based on the resolution θ and the target contour pixel area S p , determine the target cross-sectional physical area at the target water inlet, where the target cross-sectional physical area is expressed by S k Characterization, and S k =Spθ 2 ; According to the resolution θ and the target slag line pixel information h p , determine the physical information of the target slag line at the target sluice gate, where the physical information of the target slag line is expressed by h k Characterization, and h k =h p θ; According to the resolution θ and the target necking pixel information w p , determine the target necking physical information at the target water inlet, where the target necking physical information is expressed by w k Characterize, and w k =w p θ.

[0064] The method for detecting the water inlet provided in the embodiment of the present application, compared with the prior art, determines the resolution of the target image based on the target image at any target water inlet to be detected and the basic parameter information of the target water inlet, and determines the target cross-sectional pixel area at the target water inlet based on the target image and a preset threshold segmentation algorithm, and then determines the target slag line pixel information and target necking pixel information at the target water inlet based on the target image and a trained water inlet feature recognition model, and determines the target cross-sectional physical area, target slag line physical information and target necking physical information at the target water inlet based on the resolution, target contour pixel area, target slag line pixel information and target necking pixel information, respectively, which can improve the accuracy of parameter measurement at the water inlet, and improve measurement efficiency while reducing measurement errors.

[0065] In one embodiment, the step S101 includes the following sub-steps:

[0066] Sub-step 1011, based on a target image at a water inlet of any target to be detected, determine a reference scale pixel length of the target image, wherein the reference scale is used to represent any physical unit size at the water inlet of the target in the target image.

[0067] In this step, if the resolution of the target image is to be determined, the embodiment provided in the present application first determines any physical unit size of the water inlet of the target in the target image, that is, the pixel length of the reference ruler, which can be specifically expressed as wa mm.

[0068] Sub-step 1012: determining the reference scale physical length of the target water-containing outlet based on the basic parameter information of the target water-containing outlet.

[0069] In this step, the embodiment provided by the present application determines the reference scale physical length of the target water outlet according to the target water outlet and the reference scale pixel length in the above sub-step 1011, and the basic parameter information of the target water outlet, which can be specifically expressed as La mm.

[0070] Sub-step 1013: determining the resolution of the target image according to the pixel length of the reference scale and the physical length of the reference scale.

[0071] In this step, the resolution of the target image may be specifically θ=La / wa.

[0072] In one embodiment, determining a target image at a water inlet in any target to be detected by the following sub-steps specifically includes:

[0073] Sub-step 1: Determine an initial image at the water inlet of any target to be detected.

[0074] In this step, a target image acquisition device is used to acquire an initial image of the target water outlet to be detected, wherein the initial image needs to include at least a panoramic image of the target water outlet.

[0075] Sub-step 2: determining a target image at any target middle bag water outlet to be detected based on the initial image and the trained middle bag water outlet recognition model, wherein the trained middle bag water outlet recognition model is used to characterize a model for identifying the middle bag water outlet.

[0076] In this step, the embodiment provided in the present application needs to input the initial image into the trained middle bag water outlet recognition model, determine the target image at the target middle bag water outlet, and remove the more obvious and large background image.

[0077] Among them, the trained middle-package water nozzle recognition model in the embodiment provided in the present application is trained based on the sample initial image and the initial image label.

[0078] Here, it is assumed that the target image in the embodiment provided in the present application can be specifically represented by image(w1,h1), and the initial image can be specifically represented by image(w,h).

[0079] In one embodiment, step S103 includes the following sub-steps:

[0080] Sub-step 1031 : performing grayscale processing on the target image to determine the coordinates of the target point in the target image.

[0081] In this step, the embodiment provided by the present application performs grayscale processing on the target image image(w1,h1) to obtain the maximum brightness point in the target image, that is, the target point P h 、The target point P h The brightness value T h and the target point P h The target point coordinates (x h ,y h ).

[0082] Sub-step 1032: Based on the target point coordinates and a preset threshold segmentation algorithm, determine the target cross-sectional pixel area at the water inlet in the target from the target image.

[0083] In this step, the embodiment provided in the present application first determines the candidate area image of the middle water outlet from the target image based on the target point coordinates and the preset point division rules, and then determines the target cross-sectional pixel area at the target middle water outlet based on the candidate area image and the preset threshold segmentation algorithm.

[0084] It is assumed that the embodiment provided by the present application first takes the target point coordinates (x h ,y h ) as the center, and the candidate region image imaget(x h -w1 / 4,y h -w1 / 4,w1 / 2,w1 / 2), and based on the preset threshold segmentation algorithm, extract the brightness of the candidate area image [T h -10,T h +10], and after filtering out the contour, the sum of the remaining contour pixel areas is calculated, that is, the target cross-sectional pixel area S at the target water inlet p .

[0085] In the above, the preset point division rule is specifically based on the target point coordinates (x h ,y h ) as the center, and the candidate region image imaget(x h -w1 / 4,y h-w1 / 4,w1 / 2,w1 / 2).

[0086] The method for detecting the water inlet provided in the embodiment of the present application, compared with the prior art, determines the resolution of the target image based on the target image at any target water inlet to be detected and the basic parameter information of the target water inlet, determines the target cross-sectional pixel area at the target water inlet based on the target image and a preset threshold segmentation algorithm, and then determines the target slag line pixel information and the target necking pixel information at the target water inlet based on the target image and the trained water inlet feature recognition model, and determines the target cross-sectional physical area, target slag line physical information and target necking physical information at the target water inlet based on the resolution, target contour pixel area, target slag line pixel information and target necking pixel information, respectively, so as to improve the accuracy of parameter measurement at the water inlet, reduce measurement errors and improve measurement efficiency, and the present application introduces image recognition technology to realize contactless quantitative detection of the steel outlet through-steel area, target slag line physical height and target necking physical width at the target water inlet, providing effective support for the optimization of the material, structure and casting process of the target water inlet.

[0087] See also Figure 2 , Figure 2 The second flowchart of a method for detecting a water outlet of a middle package provided in an embodiment of the present application is as follows: Figure 2 As shown in the figure, the method for detecting the water outlet of the middle package provided in the embodiment of the present application comprises the following steps:

[0088] S201. Determine the resolution of the target image based on a target image at a water-containing outlet of any target to be detected and basic parameter information of the water-containing outlet of the target.

[0089] S202: Determine the target cross-sectional pixel area at the water inlet of the target based on the target image and a preset threshold segmentation algorithm.

[0090] S203. Determine the target slag line pixel information and target necking pixel information at the target middle ladle water inlet based on the target image and the trained middle ladle water inlet feature recognition model, wherein the trained middle ladle water inlet feature recognition model is used to characterize the model for identifying slag line features and necking features.

[0091] S204, based on the resolution, the target contour pixel area, the target slag line pixel information and the target necking pixel information, respectively determine the target cross-sectional physical area, target slag line physical information and target necking physical information at the target water inlet.

[0092] S205, constructing a tundish water inlet database based on the target cross-sectional physical area at the target tundish water inlet, the target slag line physical information, the target necking physical information and the continuous casting process equipment data of the target tundish water inlet for query by operators.

[0093] In this step, the embodiment provided in the present application collects core continuous casting process equipment data (including steel type, temperature, composition, pulling speed, width, taper, and crystallizer vibration parameters, etc.) from the external casting machine L2 system, and stores the target cross-sectional physical area at the target ladle water inlet, target slag line physical information, target necking physical information, and the above-mentioned continuous casting process equipment data in a corresponding database, so as to facilitate subsequent operators to trace and track the technology when problems occur.

[0094] S206: Determine whether it is necessary to optimize the structure and casting process of the target middle ladle water inlet based on the target cross-sectional physical area, target slag line physical information and target necking physical information at the target middle ladle water inlet.

[0095] In this step, the embodiment provided in the present application determines that if the target cross-sectional physical area at the target center water inlet, the target slag line physical information, and the target necking physical information exceed the corresponding preset specification threshold data, it is necessary to optimize the structure and casting process of the target center water inlet, or adjust one or several parameter data.

[0096] The following is a specific example to illustrate the application process of the detection method of the middle bag water outlet:

[0097] First, the embodiment provided in the present application uses a manual photography acquisition method to collect the initial image imageo(4000,3000) of the water outlet of the target package, manually selects the rectangular frame, and determines the target image image(674,1824) in the initial image. The pixel length of the reference ruler is 381, and based on the physical length of the reference ruler of 125 mm, the resolution of the target image is calculated to be θ=0.3281 mm / pix.

[0098] Then, the target image image(674,1824) at the water inlet of the target is gray-processed to obtain the brightness value 249 and the target point coordinates (355,1492) corresponding to the maximum brightness point (target point) Ph in the image, and the candidate area image imaget(187,1305,337,337) is intercepted with the target point coordinates (355,1492) as the center and 337 pixels as the side length; the threshold segmentation method is used to extract the area contour with a brightness of [239,255] in the candidate area image imaget. After filtering the contour, the area of ​​the remaining contour is 6198, and the pixel area of ​​the target cross-section is calculated to be 667.21 mm2.

[0099] Next, the target slag line pixel height 745 and the target neck image pixel width 274 were obtained by the manual selection method, and the target slag line physical height was calculated to be 244.43 mm, and the target neck physical width was calculated to be 89.90 mm.

[0100] The core continuous casting process equipment data such as steel type S, temperature T, composition C, pulling speed V, width H, taper R and crystallizer vibration parameter K are collected from the external casting machine system, and the target cross-sectional pixel area is 667.21mm2, the target slag line physical height is 244.43mm, the target neck physical width is 89.90mm and other core continuous casting process equipment data are recorded.

[0101] The method for detecting the water inlet provided in the embodiment of the present application, compared with the prior art, determines the resolution of the target image based on the target image at the water inlet of any target to be detected and the basic parameter information of the water inlet of the target, and determines the target cross-sectional pixel area at the water inlet of the target based on the target image and a preset threshold segmentation algorithm, and then determines the target slag line pixel information and the target necking pixel information at the water inlet of the target based on the target image and the trained water inlet feature recognition model, and determines the target water inlet of the target based on the resolution, the target contour pixel area, the target slag line pixel information and the target necking pixel information. The target cross-sectional physical area, target slag line physical information and target necking physical information at the mouth can improve the accuracy of parameter measurement at the middle ladle water inlet, while reducing measurement errors and improving measurement efficiency. The application introduces image recognition technology to achieve contactless quantitative detection of the steel-spouting area, target slag line physical height and target necking physical width at the target middle ladle water inlet, providing effective support for the optimization of the target middle ladle water inlet material, structure and casting process. The application automatically records the above parameters at the target middle ladle water inlet, providing detection and data support for the subsequent optimization of the target middle ladle water inlet material, structure and casting process.

[0102] See also Figure 3 , Figure 3 The structural block diagram of a detection device for a water outlet of a middle package provided in an embodiment of the present application is shown as follows: Figure 3 As shown, the detection device 300 of the middle bag water outlet includes:

[0103] The first determination module 310 is used to determine the resolution of the target image based on the target image at any target water-containing outlet to be detected and the basic parameter information of the target water-containing outlet.

[0104] The second determination module 320 is used to determine the target cross-sectional pixel area at the water inlet of the target based on the target image and a preset threshold segmentation algorithm.

[0105] The third determination module 330 is used to determine the target slag line pixel information and target necking pixel information at the target middle ladle water outlet based on the target image and the trained middle ladle water outlet feature recognition model, wherein the trained middle ladle water outlet feature recognition model is used to characterize the model for identifying slag line features and necking features.

[0106] The fourth determination module 340 is used to determine the target cross-sectional physical area, target slag line physical information and target neck physical information at the target water inlet based on the resolution, the target contour pixel area, the target slag line pixel information and the target neck pixel information.

[0107] Construction module 350 is used to construct a middle ladle water inlet database based on the target cross-sectional physical area at the target middle ladle water inlet, the target slag line physical information, the target necking physical information and the continuous casting process equipment data of the target middle ladle water inlet for query by operators.

[0108] The fifth determination module 360 ​​is used to determine whether it is necessary to optimize the structure and casting process of the target middle water inlet based on the target cross-sectional physical area, target slag line physical information and target neck physical information at the target middle water inlet.

[0109] Optionally, the first determining module 310 is specifically configured to:

[0110] Based on a target image at a water inlet in any target to be detected, a reference scale pixel length of the target image is determined, wherein the reference scale is used to represent any physical unit size at the water inlet in the target image.

[0111] Based on the basic parameter information of the target water-containing outlet, a reference scale physical length of the target water-containing outlet is determined.

[0112] The resolution of the target image is determined according to the pixel length of the reference scale and the physical length of the reference scale.

[0113] Optionally, a target image at a water outlet of any target to be detected is determined by the following method, and the method for detecting the water outlet of the target includes:

[0114] Determine the initial image at the water inlet of any target to be detected.

[0115] Based on the initial image and the trained middle bag water outlet recognition model, a target image at any target middle bag water outlet to be detected is determined, wherein the trained middle bag water outlet recognition model is used to characterize a model for identifying the middle bag water outlet.

[0116] Optionally, the second determining module 320 is specifically configured to:

[0117] Grayscale processing is performed on the target image to determine the coordinates of the target point in the target image.

[0118] Based on the target point coordinates and a preset threshold segmentation algorithm, the target cross-sectional pixel area at the water inlet in the target is determined from the target image.

[0119] Optionally, based on the target point coordinates and a preset threshold segmentation algorithm, determining the target cross-sectional pixel area at the water inlet in the target from the target image includes:

[0120] Based on the target point coordinates and preset point division rules, the candidate area image of the middle package water outlet is determined from the target image.

[0121] Based on the candidate area image and a preset threshold segmentation algorithm, the target cross-sectional pixel area at the water inlet in the target is determined.

[0122] The detection device 300 for the middle bag water outlet provided in the embodiment of the present application, compared with the prior art, determines the resolution of the target image based on the target image at any target middle bag water outlet to be detected and the basic parameter information of the target middle bag water outlet, and determines the target cross-sectional pixel area at the target middle bag water outlet based on the target image and a preset threshold segmentation algorithm, and then determines the target slag line pixel information and the target necking pixel information at the target middle bag water outlet based on the target image and a trained middle bag water outlet feature recognition model, and determines the target middle bag water outlet based on the resolution, the target contour pixel area, the target slag line pixel information and the target necking pixel information, respectively. The target cross-sectional physical area, target slag line physical information and target necking physical information at the water inlet of the middle ladle can improve the accuracy of parameter measurement at the water inlet of the middle ladle, while reducing measurement errors and improving measurement efficiency. The present application introduces image recognition technology to achieve contactless quantitative detection of the steel-spouting area at the target water inlet of the middle ladle, the target slag line physical height and the target necking physical width, providing effective support for the optimization of the target water inlet of the middle ladle, structure and casting process. The present application automatically records the above parameters at the target water inlet of the middle ladle, providing detection and data support for the subsequent optimization of the material, structure and casting process of the target water inlet of the middle ladle.

[0123] See also Figure 4 , Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown in FIG. Figure 4 As shown in , the electronic device 400 includes a processor 410 , a memory 420 , and a bus 430 .

[0124] The memory 420 stores machine-readable instructions executable by the processor 410. When the electronic device 400 is running, the processor 410 communicates with the memory 420 via the bus 430. When the machine-readable instructions are executed by the processor 410, the above-mentioned Figure 1 to Figure 2 The steps of the method for detecting the water outlet of the middle package in the method embodiment shown in the figure, and the specific implementation method can be referred to the method embodiment, which will not be repeated here.

[0125] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the computer program can execute the above-mentioned Figure 1 to Figure 2 The steps of the method for detecting the water outlet of the middle package in the method embodiment shown in the figure, and the specific implementation method can be referred to the method embodiment, which will not be repeated here.

[0126] 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.

[0127] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0128] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-readable program code.

[0129] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0130] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0131] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0132] An embodiment of the present application also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device executes the process of a method for detecting a middle package water outlet of a solid-state hard disk controller.

[0133] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or a data center that includes one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

[0134] 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.

[0135] In the several embodiments provided in the present application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and 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 an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0136] 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.

[0137] 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. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0138] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable 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 various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program codes.

[0139] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

[0140] Although the preferred embodiments of this specification have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of this specification.

[0141] Obviously, those skilled in the art can make various changes and modifications to this specification without departing from the spirit and scope of this specification. Thus, if these modifications and variations of this specification fall within the scope of the claims of this specification and their equivalents, this specification is also intended to include these modifications and variations.

Claims

1. A method for detecting a tundish water outlet, characterized in that: The method for detecting the water outlet of the middle package comprises: Determine the resolution of the target image based on a target image at a water-inlet opening in any target to be detected and basic parameter information of the water-inlet opening in the target; Based on the target image and a preset threshold segmentation algorithm, determining the target cross-sectional pixel area at the water inlet of the target; Based on the target image and the trained middle ladle water inlet feature recognition model, target slag line pixel information and target necking pixel information at the target middle ladle water inlet are determined, wherein the trained middle ladle water inlet feature recognition model is used to characterize a model for identifying slag line features and necking features; Based on the resolution, the target contour pixel area, the target slag line pixel information and the target neck pixel information, the target cross-sectional physical area, the target slag line physical information and the target neck physical information at the target water inlet are determined respectively.

2. The method for detecting the tundish water outlet according to claim 1, characterized in that: The step of determining the resolution of the target image based on the target image at the water inlet of any target to be detected and the basic parameter information of the water inlet of the target includes: Based on a target image at a water inlet of any target to be detected, determining a reference scale pixel length of the target image, wherein the reference scale is used to represent any physical unit size at the water inlet of the target in the target image; Based on the basic parameter information of the target water-enclosing outlet, determining the reference scale physical length of the target water-enclosing outlet; The resolution of the target image is determined according to the pixel length of the reference scale and the physical length of the reference scale.

3. The method for detecting the tundish water outlet according to claim 1, characterized in that: The target image at the water outlet of any target to be detected is determined by the following method, wherein the detection method of the water outlet of the target includes: Determine an initial image at the water inlet of any target to be detected; Based on the initial image and the trained middle bag water outlet recognition model, a target image at any target middle bag water outlet to be detected is determined, wherein the trained middle bag water outlet recognition model is used to characterize a model for identifying the middle bag water outlet.

4. The method for detecting the tundish water outlet according to claim 1, characterized in that: The step of determining the target cross-sectional pixel area at the water inlet of the target based on the target image and a preset threshold segmentation algorithm comprises: Performing grayscale processing on the target image to determine the coordinates of the target point in the target image; Based on the target point coordinates and a preset threshold segmentation algorithm, the target cross-sectional pixel area at the water inlet in the target is determined from the target image.

5. The method for detecting the tundish water outlet according to claim 4, characterized in that: Based on the target point coordinates and a preset threshold segmentation algorithm, determining the target cross-sectional pixel area at the water inlet in the target from the target image, including: Based on the target point coordinates and the preset point division rules, the candidate area image of the middle package water outlet is determined from the target image; Based on the candidate area image and a preset threshold segmentation algorithm, the target cross-sectional pixel area at the water inlet in the target is determined.

6. The method for detecting the tundish water outlet according to claim 1, characterized in that: After respectively determining the target cross-sectional physical area, target slag line physical information and target neck physical information at the target middle ladle water outlet based on the resolution, the target contour pixel area, the target slag line pixel information and the target neck pixel information, the middle ladle water outlet detection method further includes: Based on the target cross-sectional physical area at the target middle ladle water inlet, the target slag line physical information, the target necking physical information and the continuous casting process equipment data of the target middle ladle water inlet, a middle ladle water inlet database is constructed for query by operators.

7. The method for detecting the tundish water outlet according to claim 6, characterized in that: After constructing a mid-bag water inlet database based on the target cross-sectional physical area at the target mid-bag water inlet, the target slag line physical information, the target necking physical information and the continuous casting process equipment data of the target mid-bag water inlet for query by operators, the mid-bag water inlet detection method further includes: Based on the target cross-sectional physical area, target slag line physical information and target necking physical information at the target middle water inlet, it is determined whether the structure and casting process of the target middle water inlet need to be optimized.

8. A device for detecting a water outlet of a middle package, characterized in that: The detection device of the middle bag water outlet comprises: A first determination module is used to determine the resolution of the target image based on a target image at a water-inlet in any target to be detected and basic parameter information of the water-inlet in the target; A second determination module is used to determine the target cross-sectional pixel area at the water inlet of the target based on the target image and a preset threshold segmentation algorithm; A third determination module is used to determine the target slag line pixel information and the target necking pixel information at the target middle ladle water inlet based on the target image and the trained middle ladle water inlet feature recognition model, wherein the trained middle ladle water inlet feature recognition model is used to characterize the model for identifying the slag line feature and the necking feature; The fourth determination module is used to determine the target cross-sectional physical area, target slag line physical information and target neck physical information at the target water inlet based on the resolution, the target contour pixel area, the target slag line pixel information and the target neck pixel information.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate via the bus, and the machine-readable instructions are executed by the processor to perform the steps of the method for detecting the water outlet of the middle package as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for detecting the water outlet of the middle package as described in any one of claims 1 to 7 are executed.

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