Method for evaluating furnace roller precision and related apparatus

Abstract

The application discloses a furnace roller precision evaluation method and related equipment, and relates to the field of industrial manufacturing and automation, and mainly aims to solve the problem that the evaluation result of the existing furnace roller precision evaluation method is difficult to quantify. The method comprises the following steps: acquiring a strip steel deviation amount of a furnace roller in a strip steel conveying process based on an image acquisition device; calculating a deviation statistical value based on the strip steel deviation amount, wherein the deviation statistical value is used to represent the severity of the deviation of the strip steel in the conveying process; and determining a furnace roller precision score based on the deviation statistical value, wherein the furnace roller precision score is used to evaluate the furnace roller precision. The application is used for the evaluation process of the furnace roller precision.

Description

Technical Field

[0001] This invention relates to the field of industrial manufacturing and automation, and in particular to a method and related equipment for evaluating the accuracy of furnace rollers. Background Technology

[0002] In cold-rolled strip steel production, the continuous annealing furnace, as a key process equipment, directly determines the stability of the strip's operation within the furnace due to its complex roller system consisting of dozens to hundreds of furnace rolls. However, furnace rolls are prone to precision deterioration under long-term high-temperature and high-load environments. If any individual furnace roll malfunctions, it can easily lead to serious accidents such as strip misalignment, scraping, or even strip breakage, causing significant production losses and equipment damage. Currently, the industry's assessment and maintenance of furnace roll precision mainly relies on manual inspections and periodic maintenance after furnace shutdown. This method not only fails to achieve online monitoring but also lacks real-time understanding of the precision status. Although some improvement technologies attempt to improve inspection efficiency, such as installing vibration sensors to collect vibration signals from the fixed and free ends of the furnace rolls, the assessment results still heavily rely on pre-set sensor deployment, have high hardware costs, and only provide discrete qualitative level judgments, failing to provide continuous and quantifiable precision indicators. This results in assessment results lacking refined guidance and failing to support accurate predictive maintenance decisions, highlighting the difficulty in quantifying the assessment results of existing furnace roll precision assessment methods. Summary of the Invention

[0003] In view of the above problems, the present invention provides a method and related equipment for evaluating the accuracy of furnace rollers, the main purpose of which is to solve the problem that the evaluation results of existing furnace roller accuracy evaluation methods are difficult to quantify.

[0004] To address at least one of the aforementioned technical problems, in a first aspect, the present invention provides a method for evaluating the accuracy of furnace rollers, the method comprising: The amount of strip deviation during the conveying process of the furnace roll is obtained based on image acquisition equipment; Based on the strip deviation amount, a deviation statistical value is calculated, wherein the deviation statistical value is used to characterize the severity of the strip deviation during the conveying process; The furnace roll accuracy score is determined based on the deviation statistics, wherein the furnace roll accuracy score is used to evaluate the accuracy of the furnace roll.

[0005] Optionally, the acquisition of strip deviation during the conveying process using the image acquisition device includes: The initial image of the furnace roller during the strip conveying process is obtained based on the image acquisition device; The edge contour of the strip is located based on the initial image; The instantaneous offset data of the strip is determined based on the comparison between the edge profile of the strip and the ideal centerline of the strip, wherein the ideal centerline is the theoretical center trajectory of the strip as it is conveyed in the furnace.

[0006] Optionally, the acquisition of strip deviation during the conveying process using the image acquisition device includes: Acquire the first initial image of the first target furnace roll during the conveying of the steel strip; Acquire a second initial image of the second target furnace roll during the strip steel conveying process; Based on the first initial image, the first instantaneous offset data of the first target furnace roll during the strip conveying process is obtained; Based on the second initial image, the second instantaneous offset data of the second target furnace roll during the strip conveying process is obtained; The strip deviation amount generated by the first target furnace roll and the second target furnace roll during the strip conveying process is determined based on the first instantaneous offset data and the second instantaneous offset data.

[0007] Optionally, the above methods also include: Acquire all initial images of the target furnace roll during the strip steel conveying process; Based on all the initial images, obtain all instantaneous offset data of the target furnace roll during the strip conveying process; The maximum value is selected from all the instantaneous offset data as the maximum instantaneous offset data, wherein the maximum instantaneous offset data is used to calculate the strip deviation.

[0008] Optionally, the calculation of deviation statistics based on the strip deviation amount includes: The strip deviation amount is weighted by a first preset weighting coefficient to obtain a weighted strip deviation amount, wherein the first preset weighting coefficient is used to correct the proportion of the strip deviation amount in evaluating the furnace roll accuracy. The instantaneous offset data is obtained by weighting the instantaneous offset data using a second preset weighting coefficient, wherein the second preset weighting coefficient is used to correct the proportion of the instantaneous offset data in evaluating the accuracy of the furnace roller; The deviation statistics are determined based on the absolute value of the sum of the weighted strip deviation and the weighted instantaneous offset data.

[0009] Optionally, determining the furnace roll accuracy score based on the deviation statistics includes: The deviation statistics are converted based on the scaling factor to obtain the furnace roller accuracy score.

[0010] Optionally, the above methods also include: The accuracy of the furnace rollers is evaluated based on the comparison between the accuracy score and the preset deviation threshold.

[0011] Secondly, embodiments of the present invention also provide an evaluation device for furnace roller accuracy, comprising: The acquisition unit is used to acquire the strip deviation of the furnace roll during the strip conveying process based on the image acquisition device; A calculation unit is used to calculate a deviation statistical value based on the deviation amount of the strip steel, wherein the deviation statistical value is used to characterize the severity of the deviation of the strip steel during the conveying process; A determining unit is used to determine the furnace roll accuracy score based on the deviation statistics, wherein the furnace roll accuracy score is used to evaluate the furnace roll accuracy.

[0012] To achieve the above objectives, according to a third aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium comprising a stored program, wherein, when the program is executed by a processor, the steps of the above-described method for evaluating the accuracy of furnace rollers are implemented.

[0013] To achieve the above objectives, according to a fourth aspect of the present invention, an electronic device is provided, comprising at least one processor and at least one memory connected to the processor; wherein the processor is configured to invoke program instructions in the memory to execute the steps of the above-described method for evaluating the accuracy of furnace rollers.

[0014] By employing the above technical solution, the furnace roll accuracy evaluation method and related equipment provided by this invention address the problem of difficulty in quantifying the evaluation results of existing furnace roll accuracy assessment methods. This invention acquires the strip deviation amount during the strip conveying process using image acquisition equipment; calculates a deviation statistical value based on the deviation amount, where the deviation statistical value characterizes the severity of the deviation during conveying; and determines a furnace roll accuracy score based on the deviation statistical value, where the furnace roll accuracy score is used to evaluate the furnace roll accuracy. In the above scheme, firstly, an image acquisition device deployed in a continuous annealing furnace is used as a sensing unit to acquire strip deviation data during conveying. This transforms the basis of evaluation from relying on manual inspection after furnace shutdown or vibration sensors installed on specific furnace rolls to the reuse of existing visual information, achieving online evaluation and universality of the basic data acquisition method. Secondly, an intermediate step of "calculating the deviation statistical value" is designed. This step extracts and fuses features from the original observation data to generate a single index that can more stably and comprehensively characterize the severity of deviation. This data processing reduces oversensitivity to single instantaneous data points and improves the model's robustness. Finally, a continuous mapping relationship was established from "deviation statistics" to "furnace roll accuracy scores." A pre-defined algorithm normalizes the statistical values ​​representing the severity of physical phenomena into a quantitative score range. This allows the output to move beyond limited qualitative levels such as "good," "qualified," "deteriorated," and "faulty," providing a continuous and finely comparable quantitative scale. This achieves a transformation from qualitative to quantitative assessment results, providing a direct and clear basis for accurate condition judgment and maintenance decisions.

[0015] Correspondingly, the furnace roller accuracy evaluation device, equipment, and computer-readable storage medium provided in the embodiments of the present invention also have the above-mentioned technical effects.

[0016] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0017] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A flowchart illustrating a method for evaluating the accuracy of furnace rollers according to an embodiment of the present invention is shown. Figure 2A schematic block diagram of the composition of a furnace roller accuracy evaluation device provided in an embodiment of the present invention is shown; Figure 3 This diagram illustrates the composition of an electronic device for evaluating the accuracy of furnace rollers, as provided in an embodiment of the present invention. Detailed Implementation

[0018] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0019] To address the difficulty in quantifying the evaluation results of existing furnace roll precision assessment methods, this invention provides a method for evaluating furnace roll precision, such as... Figure 1 As shown, the method includes: S101. Obtain the strip deviation during the conveying process of the furnace roll based on the image acquisition equipment; In one embodiment, acquiring the strip deviation amount during the strip conveying process using an image acquisition device includes: The initial image of the furnace roller during the strip conveying process is obtained based on the image acquisition device; The edge contour of the strip is located based on the initial image; The instantaneous offset data of the strip is determined based on the comparison between the edge profile of the strip and the ideal centerline of the strip, wherein the ideal centerline is the theoretical center trajectory of the strip as it is conveyed in the furnace.

[0020] For example, the image acquisition equipment specifically refers to industrial cameras arranged inside the continuous annealing furnace, used to capture images of the furnace rolls and strip steel in operation. These devices provide raw visual data for subsequent image processing and are the data source foundation for the entire evaluation method. The initial image refers to the raw visual data of the furnace rolls during the strip steel conveying process captured by the image acquisition equipment. The edge contour of the strip steel refers to the boundary features of the strip steel extracted from the initial image through image processing technology. The ideal centerline refers to the theoretical center trajectory of the strip steel conveyed in the furnace, serving as a comparison benchmark. The instantaneous offset data refers to the instantaneous deviation of the strip steel calculated based on the comparison results between the edge contour of the strip steel and the ideal centerline.

[0021] In this embodiment, the strip deviation during the conveying process of the furnace rolls is obtained based on image acquisition equipment. First, an image acquisition device, such as an industrial camera, deployed within the continuous annealing furnace, captures initial images of the strip conveying the furnace rolls in real time. For example, cameras are placed at key locations such as the heating or cooling sections to capture the strip's running status. Then, an image recognition algorithm is used to process the initial image, accurately locating the strip's edge contour to ensure accurate capture of its actual position. Further, the extracted edge contour is compared with a preset ideal center line, and the instantaneous offset data is obtained by calculating the deviation between the two, thereby quantifying the degree of strip deviation. For example, in practical applications, initial images can be acquired for adjacent furnace rolls, and after locating the edge contour, the instantaneous offset data for each roll position can be obtained by comparing it with the ideal center line, providing a basis for subsequent evaluation.

[0022] By employing the above technical solutions, the strip deviation amount is obtained through image acquisition and processing technology, and the visual information is transformed into quantifiable offset data, realizing online real-time monitoring of furnace roll accuracy. This reduces the lag and cost caused by traditional manual inspection and reliance on dedicated sensors, improves the universality and objectivity of data acquisition, provides continuous and accurate input for furnace roll accuracy evaluation, and supports refined maintenance decisions.

[0023] In one embodiment, acquiring the strip deviation amount during the strip conveying process using an image acquisition device includes: Acquire the first initial image of the first target furnace roll during the conveying of the steel strip; Acquire a second initial image of the second target furnace roll during the strip steel conveying process; Based on the first initial image, the first instantaneous offset data of the first target furnace roll during the strip conveying process is obtained; Based on the second initial image, the second instantaneous offset data of the second target furnace roll during the strip conveying process is obtained; The strip deviation amount generated by the first target furnace roll and the second target furnace roll during the strip conveying process is determined based on the first instantaneous offset data and the second instantaneous offset data.

[0024] For example, the first target furnace roll and the second target furnace roll refer to specific furnace roll instances arranged adjacent to each other in a continuous annealing furnace; the first initial image and the second initial image are respectively visual data of strip running captured by an image acquisition device for the first target furnace roll and the second target furnace roll; the first instantaneous offset data and the second instantaneous offset data are instantaneous deviations of the strip calculated based on their respective initial images; the strip deviation amount is a comprehensive deviation index determined based on the two instantaneous offset data.

[0025] In this embodiment, the strip deviation during the conveying process of the furnace rolls is obtained based on image acquisition equipment. First, image acquisition equipment deployed within the continuous annealing furnace acquires a first initial image of the first target furnace roll and a second initial image of the second target furnace roll during the strip conveying process. These image acquisition devices are typically industrial cameras, positioned at key points within the furnace, such as the heating or cooling sections, to monitor the strip's operating status in real time. After acquiring the initial images, the edge contour of the strip is located using image processing technology. The first instantaneous offset data of the first target furnace roll and the second instantaneous offset data of the second target furnace roll are calculated by comparing the strip edge contour with the ideal centerline. The ideal centerline is the theoretical center trajectory of the strip conveyed within the furnace. Subsequently, the first and second instantaneous offset data are comprehensively processed, for example, through difference calculation or weighted fusion, to determine the strip deviation generated by the first and second target furnace rolls during the strip conveying process. This method allows for comparative analysis of the deviation in adjacent furnace roll areas, thereby more accurately pinpointing accuracy issues. In practical applications, the sixth and eighth rollers at the inlet of the heating section of the continuous annealing furnace can be selected as the first and second target furnace rollers, respectively. Their images are collected and instantaneous offset data is calculated to evaluate the accuracy status of the furnace rollers in this area.

[0026] By employing the aforementioned technical solution, the strip deviation is determined by acquiring image data from adjacent furnace rolls and calculating their instantaneous offsets. This achieves a localized and accurate evaluation of furnace roll precision, reducing the evaluation bias that may arise from data from a single furnace roll and improving the comprehensiveness and reliability of the evaluation. This method can effectively identify the precision degradation of furnace rolls in specific areas, providing targeted data support for predictive maintenance. Furthermore, the comparison of data from multiple points enhances the detail of furnace roll condition monitoring.

[0027] In one embodiment, the above method further includes: Acquire all initial images of the target furnace roll during the strip steel conveying process; Based on all the initial images, obtain all instantaneous offset data of the target furnace roll during the strip conveying process; The maximum value is selected from all the instantaneous offset data as the maximum instantaneous offset data, wherein the maximum instantaneous offset data is used to calculate the strip deviation.

[0028] For example, the target furnace roll refers to a specific furnace roll instance selected as the evaluation object in a continuous annealing furnace; all initial images refer to the set of all visual data captured by the image acquisition device for the target furnace roll during the strip conveying process; all instantaneous offset data are the sequence of instantaneous deviations of the strip calculated based on all initial images; the maximum instantaneous offset data is the maximum value selected from all instantaneous offset data, used to characterize the most severe situation of strip deviation.

[0029] In this embodiment, all initial images of the target furnace roll during the strip conveying process are acquired. First, image acquisition devices, such as industrial cameras, deployed within the furnace continuously capture images of the strip's movement within the target furnace roll area, ensuring coverage of various operating conditions throughout the conveying process. Based on all initial images, image processing techniques are used to locate the strip's edge contour in each image, and all instantaneous offset data are calculated by comparing the strip's edge contour with the ideal centerline. The ideal centerline is the theoretical center trajectory of the strip conveyed within the furnace. Subsequently, the maximum value is selected from all instantaneous offset data as the maximum instantaneous offset data. This data is used to subsequently calculate the strip deviation, ensuring that the evaluation process reflects the most extreme deviation conditions. For example, in practical applications, the sixth roll in the heating section of a continuous annealing furnace can be used as the target furnace roll. Multiple sets of initial images of it conveying strip are acquired, the instantaneous offset data for each set of images is calculated, and the maximum value is selected to assess the risk of accuracy degradation of the furnace roll. This method improves the reliability of the evaluation by comprehensively acquiring data and focusing on the worst-case scenario.

[0030] By employing the aforementioned technical solution, and through the acquisition of all initial images and the selection of the maximum instantaneous offset data, comprehensive coverage of furnace roll precision evaluation is achieved. This reduces evaluation bias caused by the limitations of single samples and improves the adaptability and robustness of the evaluation model to extreme operating conditions. This method can more accurately identify potential risks of furnace roll precision degradation, providing a more reliable data foundation for predictive maintenance. Furthermore, data maximization processing enhances the conservatism and security of the evaluation results.

[0031] S102. Calculate the deviation statistics based on the deviation amount of the strip steel, wherein the deviation statistics are used to characterize the severity of the deviation of the strip steel during the conveying process; In one embodiment, calculating the deviation statistics based on the strip deviation amount includes: The strip deviation amount is weighted by a first preset weighting coefficient to obtain a weighted strip deviation amount, wherein the first preset weighting coefficient is used to correct the proportion of the strip deviation amount in evaluating the furnace roll accuracy. The instantaneous offset data is obtained by weighting the instantaneous offset data using a second preset weighting coefficient, wherein the second preset weighting coefficient is used to correct the proportion of the instantaneous offset data in evaluating the accuracy of the furnace roller; The deviation statistics are determined based on the absolute value of the sum of the weighted strip deviation and the weighted instantaneous offset data.

[0032] For example, the deviation statistics value refers to a single quantitative indicator used to characterize the severity of deviation of the strip steel during the conveying process; the first preset weighting coefficient is a weighting parameter used to correct the proportion of the strip steel deviation amount in the evaluation of the furnace roll accuracy; the second preset weighting coefficient is a weighting parameter used to correct the proportion of the instantaneous offset data in the evaluation of the furnace roll accuracy; the weighted strip steel deviation amount is the value obtained by weighting the strip steel deviation amount using the first preset weighting coefficient; the weighted instantaneous offset data is the value obtained by weighting the instantaneous offset data using the second preset weighting coefficient.

[0033] In this embodiment, the deviation statistics are calculated based on the strip deviation amount. First, the strip deviation amount is weighted using a first preset weighting coefficient to obtain a weighted strip deviation amount. Simultaneously, instantaneous offset data is weighted using a second preset weighting coefficient to obtain weighted instantaneous offset data. The instantaneous offset data is the deviation obtained by comparing the strip edge contour acquired by an image acquisition device with the ideal center line. Then, the deviation statistics are determined based on the absolute value of the sum of the weighted strip deviation amount and the weighted instantaneous offset data. This statistical value comprehensively reflects the severity of the strip deviation. For example, in practical applications, the maximum strip deviation amount can be obtained for adjacent furnace rolls in a continuous annealing furnace, such as roll number six and roll number eight. These values ​​are then weighted and fused using preset weighting coefficients to calculate the deviation statistics for that region of furnace rolls, thus providing input for furnace roll accuracy evaluation. This method adjusts the contribution of different data sources through weighting coefficients, ensuring the balance and adaptability of the evaluation model.

[0034] By employing the aforementioned technical solution, weighted calculations are used to integrate strip misalignment and instantaneous offset data to generate misalignment statistics. This achieves a comprehensive quantitative characterization of the severity of misalignment, reducing the risk of a single data type dominating the evaluation results and improving the stability and robustness of the evaluation model. This approach enables furnace roll accuracy evaluation to more comprehensively reflect the actual operating status, providing continuous and comparable quantitative evidence for precise maintenance decisions. Furthermore, weight adjustment enhances the model's adaptability to different operating conditions.

[0035] S103. Determine the furnace roll accuracy score based on the deviation statistics, wherein the furnace roll accuracy score is used to evaluate the furnace roll accuracy.

[0036] In one embodiment, determining the furnace roll accuracy score based on the deviation statistics includes: The deviation statistics are converted based on the scaling factor to obtain the furnace roller accuracy score.

[0037] In one embodiment, the above method further includes: The accuracy of the furnace rollers is evaluated based on the comparison between the accuracy score and the preset deviation threshold.

[0038] For example, the furnace roll accuracy score refers to the quantitative score used to evaluate the accuracy of the furnace roll; the scaling factor refers to the proportional factor used to convert the deviation statistics to the score range; and the preset deviation threshold refers to the pre-set benchmark value used to evaluate the accuracy level of the furnace roll.

[0039] In this embodiment, the furnace roll accuracy score is determined based on the deviation statistics. First, the deviation statistics are converted into a furnace roll accuracy score using a scaling factor. For example, the deviation statistics are linearly mapped to a preset score range to obtain a continuously comparable quantitative index. Then, the furnace roll accuracy is evaluated based on the comparison between the furnace roll accuracy score and a preset deviation threshold. For example, the score is compared with multiple threshold intervals to determine the evaluation level of the furnace roll accuracy. In practical applications, the deviation statistics of adjacent furnace rolls in a continuous annealing furnace, such as roll number six and roll number eight, can be converted to obtain the furnace roll accuracy score, referring to the furnace roll accuracy evaluation diagram. This method ensures the systematicness and repeatability of the evaluation process.

[0040] By employing the aforementioned technical solution, and converting the deviation statistics into a furnace roll accuracy score and comparing it with a preset threshold, a standardized and quantitative evaluation of furnace roll accuracy is achieved. This provides an intuitive and continuous score indicator, facilitating operators to quickly identify the furnace roll condition and formulate maintenance strategies. This method reduces the subjective reliance of traditional qualitative evaluation methods, improves the objectivity and comparability of evaluation results, provides reliable data support for predictive maintenance, and enhances the refinement and practicality of the evaluation through threshold grading.

[0041] It is important to note that the core of this application lies in using the strip's running results, i.e., the deviation amount, to infer the furnace roll accuracy. To ensure the accuracy of this reverse diagnosis, it is essential to first eliminate interference from other factors affecting the deviation phenomenon. Therefore, this application sets strict implementation prerequisites in the data acquisition and processing stage: the strip deviation data used for analysis should be collected under stable operating conditions where there are no raw material shape defects and the main process parameters such as tension, running speed, and furnace temperature are all maintained within the normal process window. By selecting historical data of typical steel grades for statistical analysis under these constraints, it is possible to maximize the assurance that the observed strip deviation is dominated by the equipment factor of furnace roll accuracy deterioration, thereby making the subsequently constructed correlation model and accuracy evaluation results more accurate and reliable.

[0042] In summary, this application utilizes the image acquisition equipment inherently configured within the continuous annealing furnace as a sensing means to acquire strip running images in a non-contact manner. This transforms the assessment basis from relying on manual inspection after furnace shutdown or dedicated sensors to reusing existing visual information, achieving online assessment and non-invasive acquisition of basic data. By locating the strip edge contour using image recognition technology and comparing it with the ideal centerline, visual information is transformed into quantifiable instantaneous offset data, solving the problem of insufficient data support for qualitative judgments in traditional methods. Furthermore, a weighted calculation of strip deviation is used to generate a deviation statistical value, which comprehensively characterizes the severity of deviation, reducing oversensitivity to single instantaneous data. Finally, a scaling factor maps the deviation statistical value to a continuous furnace roll accuracy score, which is compared with a preset threshold to derive the evaluation level. This makes the output no longer limited to a limited level but provides a quantitatively comparable scale. This method of transforming physical phenomena into quantitative indicators fundamentally changes the traditional assessment model, providing a direct and clear basis for predictive maintenance.

[0043] Furthermore, as a response to the above Figure 1 In addition to the implementation of the method shown, this embodiment of the invention also provides an evaluation device for furnace roller accuracy, used to evaluate the above-mentioned... Figure 1 The method shown is implemented accordingly. This device embodiment corresponds to the foregoing method embodiment. For ease of reading, this device embodiment will not repeat the details of the foregoing method embodiment, but it should be clear that the device in this embodiment can implement all the contents of the foregoing method embodiment. Figure 2 As shown, the device includes: an acquisition unit 21, a calculation unit 22, and a determination unit 23, wherein... The acquisition unit 21 is used to acquire the strip deviation of the furnace roll during the strip conveying process based on the image acquisition device; The calculation unit 22 is used to calculate the deviation statistics based on the deviation amount of the strip steel, wherein the deviation statistics are used to characterize the severity of the deviation of the strip steel during the conveying process; The determining unit 23 is used to determine the furnace roll accuracy score based on the deviation statistics, wherein the furnace roll accuracy score is used to evaluate the furnace roll accuracy.

[0044] The processor contains a kernel, which retrieves the corresponding program unit from memory. One or more kernels can be configured, and by adjusting the kernel parameters, a method for evaluating furnace roller accuracy can be implemented, solving the problem of the difficulty in quantifying the evaluation results of existing furnace roller accuracy assessment methods.

[0045] This invention provides a computer-readable storage medium including a stored program that, when executed by a processor, implements a method for evaluating the accuracy of furnace rollers.

[0046] This invention provides a processor for running a program, wherein the program executes a method for evaluating the accuracy of the furnace rollers.

[0047] This invention provides an electronic device comprising at least one processor and at least one memory connected to the processor; wherein the processor is configured to invoke program instructions in the memory to execute the furnace roller accuracy evaluation method described above. This invention provides an electronic device 30, such as... Figure 3 As shown, the electronic device includes at least one processor 301, and at least one memory 302 and bus 303 connected to the processor; wherein, the processor 301 and the memory 302 communicate with each other through the bus 303; the processor 301 is used to call program instructions in the memory to execute the above-mentioned method for evaluating the accuracy of the furnace roller.

[0048] The smart electronic devices mentioned in this article can be PCs, tablets, mobile phones, etc.

[0049] This application also provides a computer program product that, when executed on a process management electronic device, is suitable for executing a program that initializes the evaluation method steps for the aforementioned furnace roll accuracy.

[0050] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0051] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0052] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0053] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0054] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0055] This application also provides a computer program product, which includes computer software instructions that, when executed on a processing device, cause the processing device to perform actions such as... Figure 1 The control flow of the memory in the corresponding embodiment.

[0056] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0057] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0058] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between apparatuses or units, and may be electrical, mechanical, or other forms.

[0059] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0060] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0061] If the integrated unit is implemented as 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 this application, in essence, 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0062] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method of evaluating a furnace roller precision, characterized by, include: The amount of strip deviation during the conveying process of the furnace roll is obtained based on image acquisition equipment; Based on the strip deviation amount, a deviation statistical value is calculated, wherein the deviation statistical value is used to characterize the severity of the strip deviation during the conveying process; The furnace roll accuracy score is determined based on the deviation statistics, wherein the furnace roll accuracy score is used to evaluate the accuracy of the furnace roll.

2. The method of claim 1, wherein, The acquisition of strip deviation during the conveying process using furnace rollers based on image acquisition equipment includes: The initial image of the furnace roller during the strip conveying process is obtained based on the image acquisition device; The edge contour of the strip is located based on the initial image; The instantaneous offset data of the strip is determined based on the comparison between the edge profile of the strip and the ideal centerline of the strip, wherein the ideal centerline is the theoretical center trajectory of the strip as it is conveyed in the furnace.

3. The method of claim 2, wherein, The acquisition of strip deviation during the conveying process using furnace rollers based on image acquisition equipment includes: Acquire the first initial image of the first target furnace roll during the conveying of the steel strip; Acquire a second initial image of the second target furnace roll during the strip steel conveying process; Based on the first initial image, the first instantaneous offset data of the first target furnace roll during the strip conveying process is obtained; Based on the second initial image, the second instantaneous offset data of the second target furnace roll during the strip conveying process is obtained; The strip deviation amount generated by the first target furnace roll and the second target furnace roll during the strip conveying process is determined based on the first instantaneous offset data and the second instantaneous offset data.

4. The method according to claim 3, characterized in that, Also includes: Acquire all initial images of the target furnace roll during the strip steel conveying process; Based on all the initial images, obtain all instantaneous offset data of the target furnace roll during the strip conveying process; The maximum value is selected from all the instantaneous offset data as the maximum instantaneous offset data, wherein the maximum instantaneous offset data is used to calculate the strip deviation.

5. The method according to claim 1, characterized in that, The calculation of deviation statistics based on the strip deviation amount includes: The strip deviation amount is weighted by a first preset weighting coefficient to obtain a weighted strip deviation amount, wherein the first preset weighting coefficient is used to correct the proportion of the strip deviation amount in evaluating the furnace roll accuracy. The instantaneous offset data is obtained by weighting the instantaneous offset data using a second preset weighting coefficient, wherein the second preset weighting coefficient is used to correct the proportion of the instantaneous offset data in evaluating the accuracy of the furnace roller; The deviation statistics are determined based on the absolute value of the sum of the weighted strip deviation and the weighted instantaneous offset data.

6. The method according to claim 1, characterized in that, The determination of the furnace roller accuracy score based on the deviation statistics includes: The deviation statistics are converted based on the scaling factor to obtain the furnace roller accuracy score.

7. The method according to claim 1, characterized in that, Also includes: The accuracy of the furnace rollers is evaluated based on the comparison between the accuracy score and the preset deviation threshold.

8. A device for evaluating the precision of furnace rollers, characterized in that, Also includes: The acquisition unit is used to acquire the strip deviation of the furnace roll during the strip conveying process based on the image acquisition device; A calculation unit is used to calculate a deviation statistical value based on the deviation amount of the strip steel, wherein the deviation statistical value is used to characterize the severity of the deviation of the strip steel during the conveying process; A determining unit is used to determine the furnace roll accuracy score based on the deviation statistics, wherein the furnace roll accuracy score is used to evaluate the furnace roll accuracy.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed by a processor, it implements the steps of the method for evaluating the accuracy of the furnace rolls as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, The electronic device includes at least one processor and at least one memory connected to the processor; wherein the processor is configured to call program instructions in the memory to execute the steps of the method for evaluating the accuracy of the furnace roller as described in any one of claims 1 to 7.

Images