Stainless steel plate production management method, device and equipment

Abstract

The invention belongs to the technical field of stainless steel plate production management, and particularly relates to a stainless steel plate production management method, device and equipment, and the method comprises the steps: firstly, starting from the two aspects of obtaining metallographic information and production information, analyzing the metallographic information to obtain initial grain information, and analyzing the production information to obtain mechanical state information and heat treatment state information; then, troubleshooting is carried out on the initial crystal grain information according to the mechanical state information, and troubleshot crystal grain information is obtained; and then determining the first part process performance of the stainless steel plate production device according to the troubleshooting grain information. And then determining a second part of process performance of the stainless steel plate production device according to the heat treatment state information. And finally, comparing the actual processing property with the ideal processing property to obtain the aging condition of each processing property. According to the invention, faults and performance aging of the stainless steel plate production device can be distinguished, and the performance aging degree of the stainless steel plate production device can be evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of stainless steel plate production management, and in particular to a stainless steel plate production management method, device and equipment. Background Art

[0002] Stainless steel plate is a steel plate with good corrosion resistance. It is usually composed of elements such as iron, chromium, and nickel. Due to its corrosion resistance, it is widely used in construction, automobiles, chemicals, food processing and other fields.

[0003] In traditional stainless steel plate production management methods, most of the management methods for stainless steel plate production equipment are to detect the failure of the production equipment, and few management methods are to detect and manage the performance aging of stainless steel plate production equipment. Moreover, the methods for detecting and managing the performance aging of stainless steel plate production equipment all have the problem of excessive errors. Summary of the invention

[0004] The embodiments of the present application provide a stainless steel plate production management method, device and equipment, which can solve the problem of detecting and managing the performance aging of the stainless steel plate production device but with excessive errors, can distinguish between failures and performance aging of the stainless steel plate production device, and can evaluate the degree of performance aging of the stainless steel plate production device.

[0005] In a first aspect, an embodiment of the present application provides a stainless steel plate production management method, which is applied to a stainless steel plate production management device, wherein the stainless steel plate production management device is communicatively connected to a stainless steel plate production device, and the method includes:

[0006] Acquire metallographic information of the stainless steel plate; wherein the metallographic information includes metallographic images of various regions of the stainless steel plate in various processes of processing the stainless steel plate by the stainless steel plate production device;

[0007] Initial grain information is obtained according to the metallographic information; wherein the initial grain information is used to reflect the distribution of grain parameter data of the stainless steel plate in each process of processing the stainless steel plate by the stainless steel plate production device, and the grain parameter data includes grain size and / or grain uniformity;

[0008] Acquire production information; wherein the production information includes jitter information and temperature information of the stainless steel plate production device during the stainless steel plate production process, the jitter information is used to reflect the jitter condition of the stainless steel plate production device, and the temperature information is used to reflect the temperature of the stainless steel plate in the process;

[0009] Obtaining working state information according to the production information; wherein the working state information includes mechanical state information and heat treatment state information, the mechanical state information is used to reflect the working state of the production device using the mechanical processing method in the stainless steel plate production device, and the heat treatment state information is used to reflect the specific temperature of each part of the stainless steel plate being processed by the production device using the heat treatment processing method in the stainless steel plate production device;

[0010] Troubleshooting the initial grain information according to the mechanical state information to obtain troubleshooting grain information; wherein the troubleshooting grain information is used to reflect the distribution of remaining grain parameter data after excluding grain parameter data of an area affected by a fault of a production device using a mechanical processing method in the initial grain information;

[0011] Determine the first part of the process performance of the stainless steel plate production device according to the troubleshooting grain information; wherein the first part of the process performance is used to reflect the performance of the production device using a mechanical processing method in the stainless steel plate production device;

[0012] Determine the second part of the process performance of the stainless steel plate production device according to the heat treatment state information; wherein the second part of the process performance is used to reflect the performance of the production device using the heat treatment processing method in the stainless steel plate production device;

[0013] According to the first part of process performance and the second part of process performance, process performance evaluation information is determined; wherein the process performance evaluation information is used to reflect the aging of process performance of the stainless steel plate production device.

[0014] The above technical solutions in the embodiments of the present application have at least the following technical effects:

[0015] The stainless steel plate production management method provided in the present application, first, starts from the two aspects of obtaining metallographic information and obtaining production information, analyzes the obtained metallographic information to obtain initial grain information, and at the same time, analyzes the production information to obtain mechanical state information and heat treatment state information. Then, according to the mechanical state information, troubleshoot the initial grain information to obtain troubleshooting grain information. When the mechanical state information indicates that the production device has no fault, the troubleshooting grain information is equal to the initial grain information. When there is a fault, the unreliable grain parameter data in the initial grain information is excluded to obtain the troubleshooting grain information. Then, the first part of the process performance of the stainless steel plate production device is determined according to the troubleshooting grain information. The first part of the process performance refers to the performance of the production device using mechanical processing methods. The production device using mechanical processing methods changes the performance of the stainless steel plate by changing the grains of the stainless steel plate. Therefore, the first part of the process performance can be obtained through the troubleshooting grain information. Subsequently, the second part of the process performance of the stainless steel plate production device is determined according to the heat treatment state information. The second part of the process performance refers to the performance of the production device using the heat treatment processing method. The production device using the heat treatment processing method changes the performance of the stainless steel plate by changing the temperature of the stainless steel plate. Therefore, the second part of the process performance can be obtained through the heat treatment state information. Finally, according to the first part of the process performance and the second part of the process performance, the process performance evaluation information is determined. By setting the performance of the standard process and then comparing it with the first part of the process performance and the second part of the process performance, the aging of the first part of the process performance and the second part of the process performance can be obtained, and then the aging of the process performance can be described by the process performance evaluation information. The above method can eliminate the influence of faults, and divide the process of the stainless steel plate production device into two parts, and analyze the grains and temperature respectively to obtain the aging of the process performance of these two parts. Therefore, the process performance evaluation information obtained by the method has reference and management significance.

[0016] In a second aspect, an embodiment of the present application provides a stainless steel plate production management device, which is applied to a stainless steel plate production management device, wherein the stainless steel plate production management device is communicatively connected with the stainless steel plate production device, and the stainless steel plate production management device comprises:

[0017] A metallographic acquisition module, used to obtain metallographic information of the stainless steel plate; wherein the metallographic information includes metallographic images of various regions of the stainless steel plate in various processes of processing the stainless steel plate by the stainless steel plate production device;

[0018] A metallographic analysis module, used for obtaining initial grain information according to the metallographic information; wherein the initial grain information is used for reflecting the distribution of grain parameter data of the stainless steel plate in each process of processing the stainless steel plate by the stainless steel plate production device, and the grain parameter data includes grain size and / or grain uniformity;

[0019] A production acquisition module, used to obtain production information; wherein the production information includes jitter information and temperature information of the stainless steel plate production device during the stainless steel plate production process, the jitter information is used to reflect the jitter condition of the stainless steel plate production device, and the temperature information is used to reflect the temperature of the stainless steel plate in the process;

[0020] A production analysis module, used to obtain working state information according to the production information; wherein the working state information includes mechanical state information and heat treatment state information, the mechanical state information is used to reflect the working state of the production device using the mechanical processing method in the stainless steel plate production device, and the heat treatment state information is used to reflect the specific temperature of each part of the stainless steel plate being processed by the production device using the heat treatment processing method in the stainless steel plate production device;

[0021] a troubleshooting grain module, used for troubleshooting the initial grain information according to the mechanical state information to obtain troubleshooting grain information; wherein the troubleshooting grain information is used to reflect the distribution of remaining grain parameter data after excluding grain parameter data of an area affected by a fault of a production device using a mechanical processing method in the initial grain information;

[0022] A process analysis module, used to determine a first part of the process performance of the stainless steel plate production device according to the troubleshooting grain information; wherein the first part of the process performance is used to reflect the performance of the production device using a mechanical processing method in the stainless steel plate production device;

[0023] The process analysis module is also used to determine the second part of the process performance of the stainless steel plate production device according to the heat treatment state information; wherein the second part of the process performance is used to reflect the performance of the production device using the heat treatment processing method in the stainless steel plate production device;

[0024] The process analysis module is also used to determine process performance evaluation information based on the first part of process performance and the second part of process performance; wherein the process performance evaluation information is used to reflect the aging of the process performance of the stainless steel plate production device.

[0025] In a third aspect, an embodiment of the present application provides a stainless steel plate production management device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any of the methods described in the first aspect when executing the computer program.

[0026] It can be understood that the beneficial effects of the second to third aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] Figure 1 is a schematic flow chart of a stainless steel plate production management method provided in one embodiment of the present application;

[0029] Figure 2 It is a schematic diagram of a rolling performance analysis coordinate system in step 630 of the stainless steel plate production management method provided in an embodiment of the present application;

[0030] Figure 3 It is a schematic diagram of a cooling performance analysis coordinate system in step 720 of the stainless steel plate production management method provided in an embodiment of the present application;

[0031] Figure 4 It is a schematic diagram of a rolling defect type classification in step 810 of the stainless steel plate production management method provided in an embodiment of the present application;

[0032] Figure 5 It is a schematic diagram of a cooling defect type classification in step 830 of the stainless steel plate production management method provided in an embodiment of the present application.

[0033] Figure 6 It is a structural schematic diagram of a stainless steel plate production management device provided in an embodiment of the present application;

[0034] Figure 7 It is a structural schematic diagram of the stainless steel plate production management equipment provided in an embodiment of the present application. DETAILED DESCRIPTION

[0035] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0036] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0037] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0038] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0039] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0040] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0041] In the related art, in existing stainless steel plate production plants, because the production equipment is expensive, some machines often work for a long time, which leads to the aging of machine performance. For example, the actual output of the machining machine is different from the set output. These performance aging are holistic and irreversible, and are easily confused with failures. Failures refer to problems with individual or partial parts, which can be solved by repairing or replacing parts. There is no method in the prior art to detect and evaluate the degree of aging of the overall process performance of the stainless steel plate production device due to the long working time of the stainless steel plate production device.

[0042] To solve the above problems, the embodiments of the present application provide a stainless steel plate production management method, device and equipment. In this method, first, starting from the two aspects of obtaining metallographic information and obtaining production information, the obtained metallographic information is analyzed to obtain the initial grain information. At the same time, the production information is analyzed to obtain the mechanical state information and the heat treatment state information. Then, according to the mechanical state information, the initial grain information is troubleshooted to obtain troubleshooting grain information. When the mechanical state information indicates that the production device has no fault, the troubleshooting grain information is equal to the initial grain information. When there is a fault, the unreliable grain parameter data in the initial grain information is excluded to obtain the troubleshooting grain information. Then, the first part of the process performance of the stainless steel plate production device is determined according to the troubleshooting grain information. The first part of the process performance refers to the performance of the production device using the mechanical processing method. The production device using the mechanical processing method changes the performance of the stainless steel plate by changing the grains of the stainless steel plate. Therefore, the first part of the process performance can be obtained through the troubleshooting grain information. Subsequently, the second part of the process performance of the stainless steel plate production device is determined according to the heat treatment state information. The second part of the process performance refers to the performance of the production device using the heat treatment processing method. The production device using the heat treatment processing method changes the performance of the stainless steel plate by changing the temperature of the stainless steel plate. Therefore, the second part of the process performance can be obtained through the heat treatment state information. Finally, according to the first part of the process performance and the second part of the process performance, the process performance evaluation information is determined. By setting the performance of the standard process and then comparing it with the first part of the process performance and the second part of the process performance, the aging of the first part of the process performance and the second part of the process performance can be obtained, and then the aging of the process performance can be described by the process performance evaluation information. The above method can eliminate the influence of faults, and divide the process of the stainless steel plate production device into two parts, and analyze the grains and temperature respectively to obtain the aging of the process performance of these two parts. Therefore, the process performance evaluation information obtained by the method has reference and management significance.

[0043] The stainless steel plate production management method provided in the embodiment of the present application can be applied to stainless steel plate production management equipment. At this time, the stainless steel plate production management equipment is the executor of the stainless steel plate production management method provided in the embodiment of the present application. The embodiment of the present application does not impose any restrictions on the specific type of stainless steel plate production management equipment.

[0044] For example, the stainless steel plate production management equipment may include an information collection device and a control device that is communicatively connected to the information collection device. The information collection device may include a high-temperature laser confocal microscope, an infrared thermometer, a jitter sensor, etc. The control device may include a processor, a memory, and a computer program stored in the memory and run on the processor. The control device may control the high-temperature laser confocal microscope to collect metallographic information, analyze the metallographic information to obtain initial grain information, control the infrared thermometer and the jitter sensor to collect production information, analyze the production information to obtain working status information, and the working status information includes mechanical status information and heat treatment status information. The control device may also analyze the mechanical status information, troubleshoot the initial grain information, and obtain troubleshooting grain information. The control device may also analyze the troubleshooting grain information and the heat treatment status information to obtain process performance evaluation information.

[0045] The stainless steel plate production management device is connected to the stainless steel plate production device in communication, and the stainless steel plate production management device can obtain information from the stainless steel plate production device. For example, the stainless steel plate production management device can obtain the processing stage of each process from the stainless steel plate production device, and can also obtain the process target of each process, and can also obtain the number and model of each production device in the stainless steel plate production device, and can also obtain the running time of the stainless steel plate production device, etc.

[0046] The control device can be a single-chip microcomputer, a microcontroller, a mobile phone, a tablet computer, a wearable device, an in-vehicle device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a desktop computer, a smart screen, a smart TV, a handheld device with wireless communication function, a computing device or other processing device connected to a wireless modem.

[0047] In order to better understand the stainless steel plate production management method provided in the embodiment of the present application, the specific implementation process of the stainless steel plate production management method provided in the embodiment of the present application is exemplarily introduced below.

[0048] Figure 1 A schematic flow chart of a stainless steel plate production management method provided in an embodiment of the present application is shown, and the stainless steel plate production management method includes:

[0049] S100, obtaining metallographic information of a stainless steel plate; wherein the metallographic information includes metallographic images of various regions of the stainless steel plate in various processes of processing the stainless steel plate by a stainless steel plate production device.

[0050] It can be understood that the production process of stainless steel plates includes heating, rolling, straightening, cooling, heat treatment and other processes, and metallographic information is only obtained from the rolling, straightening and other processes that use mechanical processing methods. The stainless steel plates in each process of stainless steel plate production equipment refer to the stainless steel plates after the corresponding process, not specifically the final product. The metallographic image refers to the image obtained by collecting a microscopic image of the grains with a microscope, and the size and specifications of each metallographic image are the same.

[0051] For example, a high-temperature laser confocal microscope can be used to obtain a metallographic image of one area of ​​a stainless steel plate in a high-temperature state after a rolling process, and the metallographic images of other areas of the stainless steel plate can be repeatedly obtained at fixed intervals. The metallographic information can be obtained by repeatedly obtaining the metallographic image in each process using a mechanical processing method for each stainless steel plate.

[0052] With such an arrangement, metallographic information with sufficient accuracy and scale is obtained, and the distribution and statistical significance of the grains of the stainless steel plate can be effectively obtained.

[0053] S200, obtaining initial grain information according to metallographic information; wherein the initial grain information is used to reflect the distribution of grain parameter data of the stainless steel plate in each process of processing the stainless steel plate by the stainless steel plate production device, and the grain parameter data includes grain size and / or grain uniformity.

[0054] It can be understood that the grain size can be measured according to the standard of GB / T 6394-2017, and the grain uniformity can be determined after the grain size is obtained. The grain uniformity refers to the percentage of the number of grains within the range of ±0.5 of the average grain size to the total number of grains. Mathematical tools are used to describe the distribution of grain parameter data of stainless steel plates to obtain initial grain information.

[0055] For example, the grain parameter data of each metallographic image in the metallographic information can be statistically analyzed manually or by computer programs. The grain parameter data include grain size and grain uniformity. The two types of grain parameter data of a metallographic image are divided into two data sets, and then the expectation and variance of the two data sets are calculated respectively. Then, the expectation and variance of the grain parameter data of each metallographic image in the metallographic information are used to describe the initial grain information.

[0056] In this way, grain refinement is a crucial step affecting the quality of stainless steel plates. Grain refinement can improve the performance of stainless steel plates in many aspects without adding trace elements. It is an important process means to improve quality and save costs. The quality of grain refinement is often improved by combining the rolling process with the cooling process. The grain size and grain uniformity can effectively describe the quality of grain refinement, and therefore can also describe the quality of the rolling process and the cooling process, which is conducive to improving the rationality and practicality of the method.

[0057] In a possible implementation, in step S200, initial grain information is obtained according to metallographic information, including:

[0058] S210, performing partition processing on each metallographic image of the metallographic information to obtain a local metallographic image of each area of ​​each metallographic image of the metallographic information.

[0059] It can be understood that the purpose of partition processing is to reduce the amount of calculation and improve the operation efficiency. Therefore, the partition processing needs to simplify the metallographic information of each metallographic diagram. The method can be stratified sampling, random sampling or equidistant sampling.

[0060] For example, a segmentation algorithm (such as threshold segmentation, edge detection, etc.) can be used to divide one of the metallographic images of each metallographic information into regions. Assuming that it is divided into N equal-area regions, the minimum unit range can be randomly extracted from the N equal-area regions. The minimum unit range refers to a preset fixed-size range, and the area of ​​the fixed-size range is smaller than the area of ​​an equal-area region. The metallographic images within the randomly extracted minimum unit range of the N equal-area regions are used to represent the local metallographic images of the region where they are located, so as to obtain the local metallographic images of the N equal-area regions, and then be deduced to each metallographic image in the metallographic information to obtain the local metallographic images of each region of each metallographic image.

[0061] Such a setting can avoid the randomness of randomly selected samples and obtain the advantages of random sampling, which can reduce the amount of calculation while ensuring the reliability of local metallographic images.

[0062] S220, obtaining grain parameter data of each local metallographic image according to the local metallographic images of each region of each metallographic image of the metallographic information.

[0063] It can be understood that the grain parameter data in the local metallographic image can be measured to obtain the grain parameter data of the local metallographic image, and the grain parameter data in a local metallographic image can be measured to obtain the grain parameter data of a region, and then the grain parameter data of each local metallographic image can be obtained by analogy. As shown in Table 1:

[0064] Table 1

[0065]

[0066] Such an arrangement increases the dimension of the grain parameter data of each local metallographic image, which is beneficial to improving the reliability of the subsequent step of obtaining initial grain information from the grain parameter data of each local metallographic image.

[0067] S230, based on the grain parameter data of each local metallographic image, calculating the expectation and variance of the grain parameter data of each local metallographic image to obtain initial grain information.

[0068] It can be understood that the grain parameter data of each local metallographic image can belong to multiple metallographic images, and each metallographic image has grain parameter data of multiple local metallographic images. The grain parameter data of multiple local metallographic images belonging to one metallographic image are collected in one data set, and the expectation and variance of the data set are calculated to represent the distribution of the grain parameter data of the metallographic image. This is analogous to all metallographic images to obtain the initial grain information.

[0069] S300, obtaining production information; wherein the production information includes jitter information and temperature information of a stainless steel plate production device during the stainless steel plate production process, the jitter information is used to reflect the jitter of the stainless steel plate production device, and the temperature information is used to reflect the temperature of the stainless steel plate in the process.

[0070] For example, the jitter information may be an amplitude-time curve or an amplitude-frequency curve.

[0071] It can be understood that a vibration sensor can be set on the stainless steel plate production device to obtain vibration information, and an infrared thermometer or other device can be set at the processing position of the stainless steel plate in the process to obtain temperature information.

[0072] For example, an information input device may be provided, and when an operator inputs limiting conditions into the stainless steel plate production management device, corresponding production information may be obtained. The production information may be temperature information, jitter information, and the like.

[0073] With such a configuration, by using various sensors to obtain the vibration information of the stainless steel plate production device and the temperature information of the stainless steel plate in the process, the time delay can be reduced, the labor cost can be reduced, and the efficiency of all subsequent steps can be improved.

[0074] S400, obtaining working status information according to production information; wherein the working status information includes mechanical status information and heat treatment status information, the mechanical status information is used to reflect the working status of the production device using mechanical processing in the stainless steel plate production device, and the heat treatment status information is used to reflect the specific temperature of each part of the stainless steel plate being processed by the production device using heat treatment processing in the stainless steel plate production device.

[0075] It can be understood that there are two main types of stainless steel plate processing methods, namely mechanical processing and heat treatment processing. The production device of a certain process of the stainless steel plate production device can be both mechanical processing and heat treatment processing, such as controlled rolling and controlled cooling production devices. The production device using mechanical processing can be called a mechanical production device, and the production device using heat treatment processing can be called a heat treatment production device. If the stainless steel plate production device uses both mechanical processing and heat treatment processing, it can be called a mechanical production device or a heat treatment production device, depending on the specific situation. The jitter information of the mechanical production device in the production information can be analyzed to obtain the mechanical state information, and the temperature information of the stainless steel plate processed by the heat treatment production device in the production information can be analyzed to obtain the heat treatment state information.

[0076] With this arrangement, when a mechanical power device fails, it will cause sudden and violent shaking, and will also directly cause a change in mass distribution, thereby causing the natural frequency of the machine to change. Different failures will cause different changes in natural frequency. The working condition of the mechanical production device is analyzed through the shaking information in the production information to determine whether there is a fault and obtain the fault information. Failures of heat treatment production devices are not common, so the situation where the heat treatment production device fails is not considered. By analyzing the temperature information of the stainless steel plate in the process in the production information, the working condition of the heat treatment production device can be reflected. The production information is refined into working status information, which improves the information effectiveness of the working status information.

[0077] In a possible implementation, in step S400, obtaining working status information according to production information includes:

[0078] S410, obtaining jitter information of each production device using a mechanical processing method in the stainless steel plate production device from the production information.

[0079] It can be understood that a specific identifier can be set for each production device using a mechanical processing method in the stainless steel plate production device, and the specific identifier can be retrieved in the production information to obtain the jitter information of each production device using a mechanical processing method corresponding to the specific identifier.

[0080] Such an arrangement can quickly find the jitter information of each production device using a mechanical processing method, which is beneficial to improving the efficiency of obtaining working status information.

[0081] S420, performing time domain comparison on the jitter information of each production device using the mechanical processing method and the corresponding preset reference information, to obtain the time domain comparison information of each production device using the mechanical processing method; wherein the production device using the mechanical processing method corresponds one-to-one to the preset reference information, and the time domain comparison information is used to reflect whether the amplitude of the jitter information exceeds a threshold.

[0082] For example, the preset reference information may be information about the maximum normal jitter amplitude of the machining device in the time domain, and the preset reference information may also be information about the minimum normal jitter amplitude of the machining device in the time domain.

[0083] It can be understood that the jitter information of each production device using a mechanical processing method can be aligned with the corresponding preset reference information on the time axis so that the two have corresponding values ​​at the same time point. The value reflected by the jitter information at the same time point is compared with the value reflected by the preset reference information to obtain time domain comparison information. For example, at the timestamp of 7:00, the jitter information reflects that the value of the jitter amplitude of the mechanical processing device in the time domain is 3 times / second, and the preset reference information reflects that the value of the maximum normal jitter amplitude of the mechanical processing device in the time domain is 2 times / second, then the current mechanical processing device in the time domain The jitter amplitude exceeds the threshold; conversely, the jitter information reflects that the value of the jitter amplitude of the mechanical processing device in the time domain is 1 time / second, then the current mechanical processing device in the time domain does not exceed the threshold; the preset reference information can also set the minimum normal jitter amplitude, and the example is not repeated here.

[0084] With such an arrangement, abnormal jitter information can be found in the time domain, thereby improving the credibility of the abnormal jitter information obtained, and facilitating the subsequent step of obtaining the mechanical state information.

[0085] S430, performing frequency domain comparison on the jitter information of each production device using the mechanical processing method and the specific characteristic information, to obtain the frequency domain comparison information of each production device using the mechanical processing method; wherein the specific characteristic information refers to the frequency domain characteristic information of the jitter when a production device using the mechanical processing method fails, and the frequency domain comparison information is used to reflect whether the frequency domain characteristics of the jitter information are the same as the frequency domain characteristics of the specific characteristic information.

[0086] For example, the specific characteristic information can be the frequency domain characteristics of the jitter signal caused by any fault. A specific characteristic information database can be established, which includes the frequency domain characteristics of various machines when various faults occur. This database can be provided by the manufacturer's test or by the user's own test. The test method can be: placing jitter sensors at multiple parts of the machine, manually selecting different parts to have different fault types (such as broken teeth on the first gear, poor meshing of the first gear, etc.), recording the jitter signals of each part, and saving them in pairs with the corresponding machine type and fault type to obtain a database of specific characteristic information.

[0087] It can be understood that the frequency domain features of the jitter information and the frequency domain features of the specific feature information can be compared in the frequency domain. The frequency domain features can be the center frequency and the frequency standard deviation. These two frequency domain features can reflect the dispersion of the power spectrum energy distribution of the machine. The frequency domain features of the two information are compared to obtain frequency domain comparison information. For example, the center frequency of the jitter information of a specific model of machine is f1, and the frequency standard deviation is f2. In the database of specific feature information, there is a specific feature information in the database of the specific model, and the difference between its center frequency f3 and f1 is less than the first preset threshold, and the difference between its frequency standard deviation f4 and f2 is less than the second preset threshold. Then it is determined that the jitter information and the specific feature information have the same frequency domain features to obtain frequency domain comparison information.

[0088] Furthermore, there may be a situation where a machine includes multiple faults. In this case, the frequency domain characteristics of the jitter information are caused by multiple faults together, and there are many types of compound faults caused by multiple faults. Therefore, it is not realistic to add the frequency domain characteristics of compound faults to the specific feature information database. Therefore, this problem can be solved by increasing the dimension of the frequency domain characteristics. For example, the specific energy distribution of each frequency level of the jitter information can be extracted through wavelet packet energy analysis. Because the energy of different types of faults is often distributed within a specific frequency level, the compound fault can be decomposed to obtain the specific fault type.

[0089] With such a configuration, jitter information with the same frequency domain characteristics as the fault can be found in the frequency domain, and it can be determined that the machine to which the jitter information belongs has a fault of the corresponding fault type.

[0090] S440, obtaining mechanical state information of each production device using the mechanical processing method according to the time domain comparison information and frequency domain comparison information of each production device using the mechanical processing method.

[0091] For example, the mechanical state information may be information for determining whether a mechanical production device has a fault, or may be information including the fault type of the mechanical production device.

[0092] It can be understood that the mechanical status information includes whether the production device has a fault and the type of fault. The time domain comparison information can be used to determine whether the first sub-mechanical production device has a fault. For example, if the time domain comparison information indicates that the jitter information exceeds the preset reference information, there is a fault, otherwise there is no fault. If there is a fault, the fault type can be determined by the frequency domain comparison information. For example, if the frequency domain comparison information indicates that the frequency domain characteristics of the jitter information are the same as the specific frequency domain characteristics of a certain fault type, then the fault type of the mechanical production device to which the jitter information belongs is the corresponding fault type. The mechanical status information of one of the mechanical production devices is obtained according to the above steps, and is analogized to each production device that uses a mechanical processing method to obtain the mechanical status information of each production device that uses a mechanical processing method.

[0093] Furthermore, there may be a situation where the time domain comparison information indicates a fault, but the frequency domain comparison information indicates no fault type; there may also be a situation where the time domain comparison information indicates no fault, but the frequency domain comparison information indicates a fault type; there may also be a situation where the time domain comparison information indicates a fault, but the fault type indicated by the frequency domain comparison information is not the fault type of the fault. The specific determination method is shown in the following example.

[0094] For example, if the time domain comparison information indicates that the first jitter information (time domain signal) exceeds the preset reference signal, and the frequency domain comparison information does not indicate a corresponding fault signal, the corresponding mechanical state information of the mechanical production device is obtained as follows: there is a fault, and the fault type is unknown.

[0095] For example, the time domain comparison information has no indication information, and the frequency domain comparison information, regardless of whether there is indication information or not, obtains the corresponding mechanical state information of the mechanical production device as: no fault.

[0096] For example, the time domain comparison information indicates that the first jitter information (time domain signal) exceeds the preset reference signal, and the frequency domain comparison information indicates that the second jitter information (frequency domain signal) has the same frequency domain characteristics as a certain specific characteristic information, then the first jitter information is subjected to a fast Fourier transform, and the transformed signal obtained is compared with the second jitter information, or the second jitter information is subjected to an inverse fast Fourier transform, and the inverse transformed signal obtained is compared with the first jitter information, to determine whether they are the same signal. If they are the same signal, the mechanical status information of the first sub-mechanical production device is obtained as follows: there is a fault, and the fault type is the fault type corresponding to the frequency domain characteristics of the second jitter information; if they are not the same signal, the mechanical status information is: there is a fault, and the fault type is unknown.

[0097] With this arrangement, various possible situations for obtaining mechanical state information are listed, which is beneficial for the subsequent steps of troubleshooting the initial grain information.

[0098] S450, obtaining temperature information of each production device using a heat treatment processing method in the stainless steel plate production device from the production information.

[0099] For example, there is a heat treatment production device that is processing a stainless steel plate in a process. The temperature information can be a thermal image of the stainless steel plate in the process, or a temperature array containing the temperatures of various parts of the stainless steel plate in the entire process, etc., but is not limited to this.

[0100] It can be understood that a specific identifier can be set for each production device using a heat treatment process, and the specific identifier can be retrieved in the production information to obtain the temperature information of the stainless steel plate in the process of each production device using a heat treatment process corresponding to the specific identifier.

[0101] Such an arrangement can quickly find the temperature information of the first sub-heat treatment production device, which is beneficial to improving the efficiency of obtaining the working status information.

[0102] S460, obtaining heat treatment state information of each production device using the heat treatment processing method according to the temperature information of each production device using the heat treatment processing method.

[0103] For example, the heat treatment state information may be N pieces of temperature-time curve information, or may be video information consisting of thermal imaging images.

[0104] It can be understood that temperature information is a two-dimensional information reflecting the temperature-position of the stainless steel plate in the process, while the heat treatment status information is a three-dimensional information reflecting the temperature-position-time of the working state of the heat treatment production equipment. Therefore, the temperature information is expanded on the time axis to obtain the heat treatment status information.

[0105] For example, the temperature information is a thermal image of a stainless steel plate in the process. After the thermal image is partitioned into N equal-area areas, a pixel point in one of the equal-area areas is randomly selected to represent the equal-area area, and a thermal image with reduced clarity is obtained. By analogy to the thermal images at other time points, the heat treatment status information is the thermal imaging video information composed of thermal images with reduced clarity.

[0106] For example, the temperature information is a temperature array. After partitioning the temperature array into N equal-sized arrays, an array element is randomly selected from one of the equal-sized arrays to represent the equal-sized array, thereby obtaining a temperature array with reduced data volume. By analogy to the temperature arrays at other time points, the heat treatment state information is N temperature-time curve information.

[0107] With such a setting, through partition processing plus random processing, the size of the heat treatment state information can be reduced while ensuring the reliability of the heat treatment state information, which is beneficial to improving the efficiency of the subsequent heat treatment state information analysis step.

[0108] S500, troubleshooting the initial grain information according to the mechanical state information to obtain troubleshooting grain information; wherein the troubleshooting grain information is used to reflect the distribution of remaining grain parameter data after excluding the grain parameter data of the area affected by the fault of the production device using the mechanical processing method in the initial grain information.

[0109] It can be understood that the initial grain information includes all grain parameter data (including unreliable grain parameter data affected by the fault), so the initial grain information needs to be troubleshooted (i.e., unreliable grain parameter data affected by the fault is deleted) to obtain troubleshooting grain information. The mechanical state information can be analyzed to obtain the fault impact according to the fault type (faults of the same type have related fault impacts), and then troubleshooting is performed to obtain troubleshooting grain information.

[0110] For example, it is possible to determine whether the mechanical production device has a repairable fault through the mechanical state information. If there is a fault, the fault information provided in the mechanical state information is used to determine the range of influence of the stainless steel plate grains in the process caused by the fault, and then troubleshoot the initial grain information according to the grain influence caused by the fault (remove the affected grain information from the initial grain information) to obtain troubleshooting grain information. For specific implementation, please refer to the subordinate steps of S500.

[0111] In this way, this step troubleshoots the initial grain information according to the mechanical state information, because the purpose of this method is to obtain the performance aging of the stainless steel plate production process, which does not include faults, and the impact of faults is more serious than the impact of performance aging. If there is a fault, the result of the process performance will be completely unreliable, so troubleshooting is a necessary preprocessing means. Excluding the influence of repairable faults to obtain troubleshooting grain information improves the accuracy of the obtained process performance evaluation information.

[0112] In a possible implementation, in step S500, troubleshooting the initial grain information according to the mechanical state information to obtain troubleshooting grain information includes:

[0113] S510, judging whether each production device using the mechanical processing method has a fault according to the mechanical state information of each production device using the mechanical processing method.

[0114] It can be understood that a specific corresponding specific identifier can be set for each production device using mechanical processing methods, and the corresponding specific identifier can be retrieved from all mechanical status information to quickly find the target mechanical status information, which includes information on whether the target mechanical production device is faulty.

[0115] Such an arrangement can quickly find the target mechanical state information of the target mechanical production device, which is beneficial to improving the efficiency of obtaining troubleshooting grain information.

[0116] S520, if the production device using the mechanical processing method has a fault, then the grain information troubleshooting range is obtained according to the mechanical state information of the corresponding production device using the mechanical processing method; wherein the grain information troubleshooting range is used to reflect the range in which the grains of the stainless steel plate processed by the corresponding production device using the mechanical processing method are affected by the fault of the corresponding production device using the mechanical processing method.

[0117] It can be understood that the grain information troubleshooting range is related to the power and fault type of the mechanical production device, and from the central limit theorem, under the same power and the same fault type of the mechanical production device, the grain information troubleshooting range obtained from multiple tests satisfies the normal distribution, and the grain information troubleshooting range of the μ+3σ coordinate point of the normal distribution diagram is set as the maximum impact range (99.7% probability point). The maximum impact range can be used to represent the grain information troubleshooting range; the specific impact range of the fault can also be divided into the proportion of the maximum impact range within the maximum impact range according to the amplitude of the abnormal jitter caused by the fault, to represent the grain information troubleshooting range. It can be seen that the maximum impact range is determined by the power size and the fault type, as shown in Table 2:

[0118] Table 2

[0119] Power 1 Power 2 Power 3 Fault 1 Maximum range of influence 1 Maximum range of influence 2 Maximum range of influence 3 Fault 2 Maximum range of influence 4 Maximum range of influence: 5 Maximum range of influence 6

[0120] Such a setting can improve the accuracy of the calculated grain information troubleshooting range. Setting the maximum impact range to represent the grain information troubleshooting range can improve the completeness of the troubleshooting process and ensure that no grains in the troubleshooting grain information are affected by the fault, which is conducive to the subsequent quantitative process performance evaluation information.

[0121] In a possible implementation, in step S520, obtaining a grain information troubleshooting range according to the corresponding mechanical state information of a production device using a mechanical processing method includes:

[0122] S521, according to the mechanical state information of the corresponding production device using the mechanical processing method, obtain the mechanical fault type of the corresponding production device using the mechanical processing method, and obtain abnormal jitter information from the time domain comparison information of the corresponding production device using the mechanical processing method; wherein the abnormal jitter information is jitter information with an amplitude exceeding a threshold.

[0123] For example, the mechanical fault type may be information of a known fault type, or information of an unknown fault type; the abnormal jitter information may be jitter information of a known fault type, or jitter information of an unknown fault type.

[0124] It can be understood that the mechanical status information includes information about whether a production device is faulty and the type of fault, and the fault type includes known types and unknown types. When a production device has a known type of fault, the mechanical fault type can be directly obtained, and an information output device can be set up. When the operator enters the production device number and the fault type, the information output device can query the time domain comparison signal corresponding to the fault and output the corresponding abnormal jitter information of the fault. When the production device has a fault, but the fault is of an unknown type, the mechanical fault type and abnormal jitter information can be set to unknown.

[0125] Furthermore, there is a situation where a production device has multiple faults at the same time, which requires detailed analysis, as shown in the following example.

[0126] For example, there is a mechanical production device with multiple known types of faults. Through the above-mentioned information output device, the mixed abnormal jitter information of each known type of fault is obtained. Because the fault type of each fault is known, the frequency domain distribution of the corresponding abnormal jitter information of each fault can be found in the frequency domain. The abnormal jitter information of each fault can be obtained by dividing the frequency domain signal and then Fourier inverse transforming.

[0127] For example, there is a mechanical production device with one or more known type faults and one or more unknown type faults. In the jitter information of a mechanical production device, the abnormal jitter information of all faults is mixed together. Because the frequency domain distribution of the unknown type faults cannot be known, the frequency domain cannot be divided. Therefore, in the time domain and frequency domain, the abnormal jitter information of each fault is mixed together. Therefore, it is impossible to obtain the abnormal jitter information of each fault. Therefore, the abnormal jitter information of known type faults and unknown type faults is set to unknown.

[0128] For example, there are multiple unknown faults in a mechanical production device. As can be seen from the above example, it is impossible to know the abnormal jitter information of the unknown fault type, so the abnormal jitter information of one or more unknown fault types is set to unknown.

[0129] Such an arrangement refines the detailed processing methods for various situations, which is beneficial to improving the accuracy of the obtained grain information troubleshooting range.

[0130] S522, determining a first range according to the type of mechanical failure; wherein the first range is used to reflect the focal range of the range in which the grains of the stainless steel plate processed by the production device using the mechanical processing method are affected by the failure of the corresponding production device using the mechanical processing method.

[0131] It can be understood that the focal range can be understood as the center of a circle or the focus of an ellipse. The difference is that the focal range is not a point but a range, and the focal range is only related to the fault type. The skeleton of the maximum influence range of each power under the same fault type can be extracted by the skeleton extraction algorithm, and then the first range of the corresponding fault type can be obtained by least squares fitting, or the first range can be obtained by experiment.

[0132] For example, the skeleton extraction algorithm can be used to extract the skeleton of the maximum influence range of each power under the same fault type. The central idea of ​​the skeleton extraction algorithm is to extract the central axis of the figure. For example, a chopstick is extracted into a straight line and a circle is extracted into a point. Therefore, the skeleton of the maximum influence range of each power can be obtained through the skeleton extraction algorithm, and then multiple skeletons are fitted into a universal skeleton through the least squares method, that is, the first range.

[0133] Such an arrangement can separate the focal range of the fault-affected die from other influencing factors, thereby improving the accuracy of determining the fault-affected range and facilitating improving the accuracy of the die information troubleshooting range.

[0134] S523, determining a first area according to the abnormal jitter information; wherein the first area is used to reflect the area of ​​the range in which the grains of the stainless steel plate processed by the production device using the mechanical processing method are affected by the failure of the corresponding production device using the mechanical processing method.

[0135] For example, the first area may be 0, the first area may be the area of ​​the corresponding maximum impact range, or the first area may be any area value between 0 and the area of ​​the maximum impact range.

[0136] It can be understood that the first area is an area value proportional to the maximum jitter amplitude of the abnormal jitter information. The larger the maximum jitter amplitude of the abnormal jitter information, the closer the first area is to the corresponding maximum impact range, and the smaller the maximum jitter amplitude of the abnormal jitter information, the closer the first area is to 0. The first area is only related to the maximum jitter amplitude of the abnormal jitter information. When the maximum jitter amplitude of the abnormal jitter information reaches the maximum jitter amplitude allowed by the mechanical production device, the first area is equal to the area of ​​the corresponding maximum impact range, and when the maximum jitter amplitude of the abnormal jitter information is close to 0, the first area is also close to 0.

[0137] For example, the maximum jitter amplitude of the abnormal jitter information can be obtained from the abnormal jitter information. The specification of a mechanical production device stipulates that the maximum jitter amplitude under normal working conditions is S1. When the jitter amplitude of the mechanical production device is ≥ S2, it will automatically shut down. Therefore, the first area relationship can be obtained, then

[0138] This arrangement can separate the area size of the fault-affected grain range from other influencing factors, thereby improving the accuracy of determining the degree of fault impact and helping to improve the accuracy of the grain information troubleshooting range.

[0139] S524, obtaining a grain information troubleshooting range according to the first range and the first area.

[0140] It can be understood that the first range can be discretized into multiple focuses, and the first area can be set as the area enclosed by the multi-focus curve to construct a multi-focus curve. The range enclosed by the multi-focus curve is the grain information troubleshooting range. The first range can also be expanded through an expansion algorithm, and the area of ​​the expanded figure can be detected at all times. When the area of ​​the expanded figure is equal to the first area, the expansion is stopped, and the range after the expansion processing is the grain information troubleshooting range, and so on, but not limited to this.

[0141] Such an arrangement is helpful to improve the accuracy of the obtained grain information troubleshooting range.

[0142] S530, determining troubleshooting die information based on the initial die information and troubleshooting ranges of each die information.

[0143] For example, the troubleshooting grain information may be the initial grain information, or the information recalculated after removing a part of the grain parameter data from the initial grain information, or the NULL information after removing all the grain parameter data from the initial grain information.

[0144] It can be understood that operations can be performed on the original data of the initial grain information. For example, if the grain information troubleshooting range indicates that the grain parameter data of the second range of the stainless steel plate in a certain process is unreliable data affected by a fault, the grain parameter data of the corresponding range in the grain parameter data of the initial grain information is deleted, and then all the grain parameter data of the remaining range are processed according to the method of step S240 to obtain the troubleshooting grain information. If all the grain parameter data of the stainless steel plate in a certain process are deleted during the troubleshooting of the grain information, that is, the distribution of the grain parameter data of the stainless steel plate in the process is NULL information, the stainless steel plate in the process is abandoned.

[0145] With such a setting, when there is no fault, the initial grain information is directly equal to the troubleshooting grain information. When there is a fault, only the expectation and variance need to be recalculated once, which is conducive to improving the speed of obtaining the troubleshooting grain information.

[0146] S600, determining a first part of process performance of a stainless steel plate production device according to troubleshooting grain information; wherein the first part of process performance is used to reflect the performance of a production device using a mechanical processing method in the stainless steel plate production device.

[0147] It can be understood that in the processing technology, it can be divided into two major categories of processes according to the different ways of changing the stainless steel plate in the process. The two ways are changing the grain of the stainless steel plate in the process and changing the temperature of the stainless steel plate in the process. Among them, the process of changing the grain of the stainless steel plate in the process is divided into the first part of the process, for example, the rolling process is the first part of the process. The change in the troubleshooting grain information before and after the first part of the process can be analyzed, and the characteristic amount of the change in the grain information can be used to represent the performance of the first part of the process (such as grain size and grain uniformity) to obtain the performance of the first part of the process, and by comparing the troubleshooting grain information before and after any processing step, the performance of any first part of the process can be accurately determined.

[0148] For example, a stainless steel plate in a process can be set up. The stainless steel plate in the process is low-carbon steel under high temperature. The temperature is in the austenite non-recrystallization zone, the grain size is level 2, and the grain uniformity is 100%. The grains in the austenite non-recrystallization zone basically will not change automatically. The stainless steel plate in the first part of the process machine to be tested is processed in the process. The stainless steel plate has been in the austenite non-recrystallization zone during the processing. The first part of the process machine to be tested sets the first parameter to process the stainless steel plate in the process (the process target of the first parameter is: the grain size of the stainless steel plate in the process after processing is level 7 and the grain uniformity is 100%). After the processing is completed, the initial grain information is recorded, and then the grain information to be tested is troubleshooted to obtain the troubleshooting grain information. For example, the troubleshooting grain information is grain size level 6 and grain uniformity 99%, then the first part of the process performance can be obtained. The performance of the grain size characteristics can be expressed as The performance of the grain uniformity characteristic is expressed as A2=99%, and other expressions may also be used, but are not limited thereto.

[0149] Such an arrangement improves the accuracy of judging the process performance of the first part.

[0150] In a possible implementation, referring to S600, determining the first part of process performance according to the troubleshooting die information includes:

[0151] S610, obtaining preset grain change information of the stainless steel plates processed by each production device using a mechanical processing method in the stainless steel plate production device; wherein the preset grain change information is used to reflect the preset change amount of the grain parameter data of the stainless steel plates processed by the production device of the corresponding process before and after processing.

[0152] For example, an information input device can be provided, and when an operator inputs limiting conditions into the stainless steel plate production management device, corresponding process target information can be detected. Process target information refers to information including process targets, which can be grain information, temperature information, etc., and each process has a process target.

[0153] It can be understood that the preset grain change information of a process = the process target of the grain parameter data after processing of the process - the process target of the grain parameter data before processing of the process. The process target of the grain parameter data after processing of each process and the process target of the grain parameter data before processing of each process can be obtained through the above-mentioned information input device, and finally the preset grain change information of the stainless steel plates processed by each production device using mechanical processing method is obtained by performing difference operation.

[0154] Such an arrangement allows the scope to be precisely limited to a specific first part process production device, thereby improving the accuracy of the obtained process performance, and is conducive to the subsequent quantification of the aging of the process performance of the stainless steel plate production device.

[0155] S620, based on the troubleshooting grain information, obtain the actual grain change information of the stainless steel plates processed by each production device using the mechanical processing method; wherein the actual grain change information is used to reflect the actual change in the grain parameter data of the stainless steel plates processed by the production device of the corresponding process before and after processing.

[0156] It can be understood that, corresponding to step S610, the distribution of grain parameter data after processing in each process and the distribution of grain parameter data before processing in each process are obtained, and finally a difference operation is performed to obtain the actual grain change information of the stainless steel plates processed by each production device using a mechanical processing method.

[0157] Such an arrangement allows the scope to be precisely limited to a specific first part process production device, thereby improving the accuracy of the obtained process performance, and is conducive to the subsequent quantification of the aging of the process performance of the stainless steel plate production device.

[0158] S630, comparing the actual grain change information with the preset grain change information to obtain the first part of the process performance.

[0159] It can be understood that the first part of the process includes the rolling process, etc. The first part of the process performance is a quantity reflecting the gap between the performance of the first part of the process and the ideal process. The comparison process can be to extract the characteristics of the grain information for comparison to obtain the first part of the process performance.

[0160] For example, the characteristic quantity of the grain change can be extracted as the x and y axes of the analysis coordinate system, and the first part of the process performance can be obtained by analyzing the image. Taking the rolling process as an example, the method can be:

[0161] 1. According to the actual grain change information, N rolling process data sets are obtained; wherein the rolling process data set refers to the grain information change of the same area of ​​the stainless steel plate in the process before and after the rolling process, and the jth rolling process data set includes the jth rolling grain size change and the jth rolling grain uniformity change.

[0162] It can be understood that the rolling process data set is the difference in grain parameter data before and after the rolling process in a region. Assuming that there are N rolling process data sets in total, the rolling process data set includes the grain size change and the grain uniformity change. The grain size change is the difference between the two grain sizes, and the maximum grain size change is 11 levels (maximum grain size 12 levels - minimum grain size 1 level); the grain uniformity change refers to the difference between the two grain uniformities. The quantification method of grain uniformity in this application is to statistically calculate the percentage ratio of the number of grains with an average grain size of ±0.5 levels, so the maximum grain uniformity change is 100%; the two characteristic quantities have different units, so they are normalized. The specific operation is grain size change / 11, and the grain uniformity change remains unchanged.

[0163] 2. The rolling grain size change and the rolling grain uniformity change are used as the characteristic quantities of the rolling process, and then N rolling process data sets are clustered to obtain the cluster center C1 and the maximum cluster radius D1, and the rolling process target is placed in the rolling performance analysis coordinate system to obtain the rolling process target point E1; wherein, the rolling process target is the grain size change and grain uniformity change of the stainless steel plate in the post-processing process of the rolling process under ideal conditions based on the preset grain change information, and the y-axis of the rolling performance analysis coordinate system is from high to low in grain uniformity starting from the origin, and the x-axis is from low to high in grain size starting from the origin.

[0164] It is understandable that Figure 2 As shown in the figure, the rolling grain size change is used as the x-axis in the rolling performance analysis coordinate system, and the rolling grain uniformity change is used as the y-axis in the rolling performance analysis coordinate system (the grain uniformity change is from high to low). Then, the N rolling process data sets are substituted into the rolling performance analysis coordinate system to obtain the cluster center C1 and the maximum cluster radius D1. Then, according to the rolling process target, the rolling process target point E1 is obtained, for example Figure 2 The rolling process target E1 shown is that the change in grain uniformity is 0 and the change in grain size is 0.77×11.

[0165] 3. Rolling process performance vector express, as follows:

[0166]

[0167] Among them, d1 refers to the Euclidean distance between the cluster center C1 and the rolling process target point E1, L1 refers to the Euclidean distance between the rolling process target point E1 and the origin, α1 refers to the angle between the straight line C1E1 and the straight line OE1, and O refers to the origin.

[0168] It can be understood that the relevant line segments and sites are as follows Figure 2As shown, the rolling process performance vector The expression is in polar coordinate form. The vector modulus reflects the degree to which the cluster center C1 plus the maximum cluster radius D1 deviates from the rolling process target. The vector angle reflects the ratio of the grain size change to the grain uniformity change in the offset. Therefore, the rolling process performance vector At least it can express the deviation degree of rolling process performance and the proportion of grain size variation deviation and grain uniformity variation deviation in the deviation degree.

[0169] Such an arrangement improves the accuracy and dimensionality of the first part of the process performance obtained, which is beneficial to the subsequent quantification of the aging of the process performance.

[0170] S700, determining a second part of process performance of the stainless steel plate production device according to the heat treatment state information; wherein the second part of process performance is used to reflect the performance of the production device using a heat treatment processing method in the stainless steel plate production device.

[0171] It can be understood that the second part of the process includes cooling process, heating process, etc., and the second part of the process performance is a quantity that reflects the gap between the performance of the second part of the process and the ideal process. The N temperature-time curves (heat treatment state information) of the stainless steel plate in the process can be analyzed, and the performance of the second part of the process (such as cooling rate and final cooling temperature, etc.) can be expressed by the characteristic quantities of the N temperature-time curves to obtain the second part of the process performance.

[0172] With such arrangement, the performance of the second part of the process is obtained by analyzing the temperature information of the stainless steel plate in the process step of the second part of the process, thereby improving the accuracy of judging the performance of the second part of the process.

[0173] In a possible implementation, referring to S700, determining the second part of the process performance of the stainless steel plate production device according to the heat treatment state information includes:

[0174] S710, obtaining preset temperature information of the stainless steel plates processed by each production device using a heat treatment processing method in the stainless steel plate production device; wherein the preset temperature information is used to reflect the preset temperature information of the stainless steel plates processed by the production device of the corresponding process.

[0175] It can be understood that the preset temperature information of a process can be obtained through the information input device in step S610.

[0176] Such an arrangement allows the scope to be precisely limited to a specific second part process production device, thereby improving the accuracy of the obtained process performance, and is conducive to the subsequent quantification of the aging of the process performance of the stainless steel plate production device.

[0177] S720, comparing the preset temperature information with the heat treatment state information to obtain the second part of the process performance.

[0178] It can be understood that the second part of the process includes a heating process, a cooling process, etc. The second part of the process performance is a quantity reflecting the gap between the performance of the second part of the process and the ideal process. The comparison process can be to extract the characteristics of the heat treatment state information for comparison to obtain the second part of the process performance.

[0179] For example, the second part of the process performance includes the heating process and the cooling process (the cooling process will produce fog, making it difficult to observe the stainless steel plate grains in the process, so the cooling process is analyzed through the heat treatment state information). Taking the cooling process as an example, the method can be:

[0180] 1. According to the heat treatment state information, N cooling process data sets are obtained; wherein the cooling process data set refers to the curve-related information of the temperature-time curve of one of the N regions in the cooling process of the stainless steel plate in the process, and in the jth cooling process data set, the jth cooling cooling rate and the jth cooling final cooling temperature are included; wherein the cooling cooling rate refers to the average cooling rate in the cooling process, and the cooling final cooling temperature refers to the temperature at the end of the cooling process.

[0181] It can be understood that the cooling process data set is the temperature-time curve information of one of the N regions of the stainless steel plate in the process, including the average cooling rate of the curve (average negative slope) and the temperature at the end of the cooling process (the y value at the end of the curve).

[0182] 2. The cooling rate and the final cooling temperature are used as the characteristic quantities of the cooling process, and then N cooling process data sets are clustered to obtain the cluster center C2 and the maximum cluster radius D2, and the cooling process target in the preset temperature information is placed in the cooling performance analysis coordinate system to obtain the cooling process target point E2; wherein, the cooling process target refers to the cooling rate and the final cooling temperature of the stainless steel plate in the cooling process processing under ideal conditions, and the y-axis of the cooling performance analysis coordinate system is the final cooling temperature from low to high starting from the origin, and the x-axis is the cooling rate from low to high starting from the origin.

[0183] It is understandable that Figure 3 As shown in the figure, the cooling rate is used as the x-axis in the cooling performance analysis coordinate system, and the final cooling temperature is used as the y-axis in the cooling performance analysis coordinate system. Then, the N cooling process data sets are substituted into the cooling performance analysis coordinate system to obtain the cluster center C2 and the maximum cluster radius D2. Then, according to the cooling process target, the cooling process target point E2 is obtained, for example Figure 3 The cooling process targets shown are a cooling rate of 20°C / s and a final cooling temperature of 745°C.

[0184] 3. Cooling process performance vector express, as follows:

[0185]

[0186] Among them, d2 refers to the Euclidean distance between the cluster center C2 and the cooling process target point E2, L2 refers to the Euclidean distance between the cooling process target point E2 and the y-axis, α2 refers to the angle between the straight line C2E2 and the straight line YE2, and Y refers to the foot of the perpendicular of E2 on the y-axis.

[0187] It can be understood that the relevant line segments and sites are as follows Figure 3 As shown, the cooling process performance vector The expression is in polar coordinate form. The vector modulus reflects the degree to which the cluster center C2 plus the maximum cluster radius D2 deviates from the cooling process target. The vector angle reflects the proportion of the final cooling temperature deviation and the cooling rate deviation in the deviation. Therefore, the cooling process performance vector At least it can express the deviation degree of cooling process performance and the proportion of final cooling temperature deviation and cooling rate deviation in the deviation degree.

[0188] For example, the performance of the heating process includes the fixed temperature performance and the uniform temperature performance. The fixed temperature performance is used to reflect the ability of the heating process to make the actual temperature of the stainless steel plate in the process close to the target temperature, and the uniform temperature performance is used to reflect the ability of the heating process to make the temperature of each area of ​​the stainless steel plate in the process uniform. The fixed temperature performance and the uniform temperature performance can be discussed separately. The temperature of the stainless steel plate in the whole process is determined according to the average temperature of the fixed temperature information. Then, the temperature of the stainless steel plate in the whole process is compared with the heating process target on the curve chart. The temperature deviation curve of the stainless steel plate in the whole process can be obtained to represent the fixed temperature performance; the variance can also be calculated according to the fixed temperature information of different areas, and the uniform temperature performance is represented by the size of the variance. The method for obtaining the heating process performance can be:

[0189] 1. According to the heat treatment state information, N heating process data sets are obtained; wherein the heating process data set refers to a temperature-time curve of one of the N regions of the stainless steel plate in the process during the heating process.

[0190] It can be understood that the heating process data set is a temperature-time curve when one of the N regions of the stainless steel plate in the process is heated by the heating process.

[0191] 2. The N heating process data sets are processed by the average curve method to obtain the average curve f1, and the average curve f1 and the heating process target curve f2 in the preset temperature information are subtracted to obtain the temperature offset curve f3; wherein the heating process target curve f2 refers to the temperature-time curve of the stainless steel plate in the process of the heating process under ideal conditions.

[0192] It can be understood that the average curve method is used to process multiple curves with the same independent variable, and the average value of N heating process data sets at the same time point is calculated to obtain the average curve f1, and then the difference operation is performed with the heating process target curve f2 to obtain the temperature offset curve f3 interspersed on the x-axis. The temperature offset curve f3 can represent the relationship between the average temperature of the stainless steel plate in the process of the heating process and the heating process target temperature.

[0193] 3. The constant temperature performance of the heating process is represented by the array HP1. 如下：

[0194]

[0195] Among them, T refers to the total duration of the heating process, and HP1 includes two elements, namely the area enclosed by the positive part of f3 and the x-axis, and the area enclosed by the negative part of f3 and the x-axis.

[0196] It can be understood that the constant temperature performance of the heating process is expressed as an array containing two elements, namely the area enclosed by the positive part of the f3 curve and the x-axis, and the area enclosed by the negative part of the f3 curve and the x-axis. The physical meaning can be described as the accumulation of Δ temperature (i.e., temperature difference) over time, that is, the larger the area, the longer the impact of Δ temperature. Therefore, the constant temperature performance of the heating process is expressed in two parts, one is the impact of the constant temperature being higher than the target temperature, and the other is the impact of the constant temperature being lower than the target range. Therefore, HP1 can at least express the degree of impact of too high a constant temperature in the heating process and the degree of impact of too low a constant temperature in the heating process.

[0197] 4. Uniformly sample M points over the total duration T of the heating process, obtain the temperatures of M time points in N heating process data sets, and obtain an array of N rows and M columns; where M ≥ 2.

[0198] It can be understood that, on the heating process data set of each area, M time points are uniformly sampled, the temperature is obtained at the sampling point, and then N heating process data sets are traversed to obtain N×M temperature data.

[0199] 5. The temperature uniformity performance of the heating process is expressed by the parameter HP2, which is as follows:

[0200]

[0201] Among them,2 It means finding the variance of each column of data in an array of N rows and M columns, and obtaining the i-th variance among the M variances. The larger the HP2, the worse the temperature uniformity performance.

[0202] It can be understood that N×M temperatures are divided according to M time points and N spatial points. Now we need to express the uniform temperature performance of the heating process, and then we take the N spatial points at the same time point as a group and calculate the variance, and get a total of M groups of variances. The physical meaning of these M groups of variances can be described as the uniform temperature performance at M time points. Then the uniform temperature performance of the overall heating process can be expressed as the average value of the uniform temperature performance at M time points, that is, HP2. Therefore, HP2 can at least express the overall uniform temperature performance of the process in the heating process.

[0203] 6. Then the heating process performance array HP = (HP1, HP2).

[0204] It can be understood that the heating process performance is represented by an array HP, and HP includes two elements, namely, the constant temperature performance HP1 and the uniform temperature performance HP2 of the heating process.

[0205] Such an arrangement improves the accuracy and dimensionality of the obtained second part of the process performance, which is beneficial to the subsequent quantification of the aging of the process performance.

[0206] S800, determining process performance evaluation information according to the first part of process performance and the second part of process performance; wherein the process performance evaluation information is used to reflect the aging of process performance of the stainless steel plate production device.

[0207] For example, the process performance evaluation information may be the process performance evaluation information of the first part or the process performance evaluation information of the second part, may be the defect type of the process performance of the first part or the defect type of the process performance of the second part, may be the defect error quantification value of the process performance of the first part or the defect error quantification value of the process performance of the second part.

[0208] It can be understood that the process performance of the first part and the process performance of the second part are analyzed separately to obtain the performance evaluation value of each process. The proportion of each characteristic quantity of the process performance of the first part can be analyzed and divided into different types of performance defects. For example, the rolling process can be divided into four types of performance defects according to the characteristics of grain size change and grain uniformity change. The rolling process performance evaluation value can be represented by a combination of four defect types and defect error quantization values. The process performance of the second part is similar, and the grain characteristic quantity can be replaced by the temperature characteristic quantity.

[0209] With such a setting, process performance evaluation information can be obtained based on comprehensive analysis of multiple process performances, which improves the credibility and information dimension of the process performance evaluation information and improves the accuracy of the method.

[0210] In a possible implementation, referring to S800, the process performance evaluation information is determined according to the first part of the process performance and the second part of the process performance, including:

[0211] S810, obtaining a first part of process defect information according to the first part of process performance; wherein the first part of process defect information is used to reflect defect information of the grains analyzed in the first part of process performance.

[0212] It can be understood that the first part of the process performance can represent the gap between the performance of the first part of the process and the target process, and the first part of the process defect information further analyzes the gap between the first part of the process performance and the target process performance, and divides the gap into the form of (defect type + defect severity). Because the first part of the process performance is obtained by analyzing the grains, multiple feature quantities are extracted from the grain information, and the defect type and defect severity are determined by the feature quantities to obtain the first part of the process defect information.

[0213] For example, the first part of the process includes a rolling process, and the rolling process performance is represented by the vector It means that, taking the rolling process as an example, the method for obtaining the first part of the process defect information can be:

[0214] 1. The variation of rolling grain uniformity is divided into qualified and unqualified, and the variation of rolling grain size is divided into large and small. Four situations can be obtained, as shown in Table 3 below:

[0215] Table 3 Four types of rolling defects

[0216]

[0217] 2. When α1∈[0,π / 2-β), it is applicable to the second rolling defect type; where β is used to indicate the qualified threshold of grain uniformity, which can be customized by the user, and β∈(0,π / 2).

[0218] It is understandable that Figure 4 As shown, when α1∈[0,π / 2-β), the rolling grain size variation is small and the rolling grain uniformity variation is qualified, which is applicable to the second rolling defect type.

[0219] 3. When α1∈[π / 2-β,π / 2), it is applicable to the fourth rolling defect type.

[0220] It is understandable that Figure 4 As shown, when α1∈[π / 2-β,π / 2), the rolling grain size change is small and the rolling grain uniformity change is unqualified, which is applicable to the fourth rolling defect type.

[0221] 4. When α1∈[π / 2,(π / 2)+β), it is applicable to the third rolling defect type.

[0222] It is understandable that Figure 4 As shown, when α1∈[π / 2,(π / 2)+β), the rolling grain size variation is too large and the rolling grain uniformity variation is unqualified, which is applicable to the third rolling defect type.

[0223] 5. When α1∈[(π / 2)+β,π], it is applicable to the first rolling defect type.

[0224] It is understandable that Figure 4 As shown, when α1∈[(π / 2)+β,π], the rolling grain size variation is large and the rolling grain uniformity variation is qualified, which is applicable to the first rolling defect type.

[0225] 6. And by the rolling process performance vector The modulus length indicates the severity of each rolling defect type.

[0226] Such a setting can filter out the influence of inconspicuous factors, improve the accuracy of the first part of process defect information obtained, and facilitate the subsequent determination of the first part of process performance evaluation information.

[0227] S820, determining the first part of process performance evaluation information according to the first part of process defect information; wherein the first part of process performance evaluation information is used to reflect the type and error quantization value of defects in the first part of the process.

[0228] It can be understood that the defect types of the first part of the process defect information and the first part of the process performance evaluation information can match, but the defect severity and the defect error quantification value still need some calculations to match. A parameter X1 can be set to represent the qualified range of rolling process performance. For example, the defect severity ( The module length) is 0.5, then the defect error quantization value can be regarded as 0.5-X1 (regarded as 0 when the result is negative) to obtain the rolling process performance evaluation information.

[0229] With such a setting, the aging condition of the process performance of the first part can be clearly obtained.

[0230] S830, obtaining a second part of process defect information according to the second part of process performance; wherein the second part of process defect information is used to reflect defect information of the temperature analyzed in the second part of process performance.

[0231] It can be understood that the performance of the second part of the process can represent the gap between the performance of the second part of the process and the target process. The gap between the performance of the second part of the process and the target process is further analyzed, and the gap is divided into the form of (defect type + defect severity). Because the performance of the second part of the process is obtained by analyzing the temperature, multiple feature quantities are extracted from the temperature information, and the defect type and defect severity are determined by the feature quantities to obtain the defect information of the second part of the process.

[0232] For example, the second part of the process includes heating process and cooling process, etc. The heating process performance is represented by array HP, and the cooling process performance is represented by vector It means that, taking the heating process as an example, the method for obtaining the second part of the process defect information can be:

[0233] 1. The fixed temperature performance is divided into three cases: the fixed temperature is too high, the fixed temperature is too low and the fixed temperature is unstable. The uniform temperature performance is divided into two cases: qualified and unqualified. It should be noted that the fixed temperature performance and the uniform temperature performance are independent, so they are not discussed jointly. The fixed temperature is too high means that the fixed temperature is too high in the heating process as a whole, the fixed temperature is too low means that the fixed temperature is too low in the heating process as a whole, and the unstable fixed temperature means that the fixed temperature is high and low in the heating process as a whole.

[0234] It can be understood that the two elements in the constant temperature performance array HP1 can determine the influence of high constant temperature and low constant temperature. According to the influence ratio of high constant temperature and low constant temperature, the three situations of too high constant temperature, too low constant temperature and unstable constant temperature are distinguished. Then a threshold is set to divide the uniform temperature performance into qualified and unqualified situations. There is no intrinsic connection between constant temperature and uniform temperature (high temperature and low temperature will have uneven heating, and the influencing factor is mainly heating time), so they are not discussed jointly. Three types of constant temperature defects and one type of uniform temperature defect are listed.

[0235] With this setup, the constant temperature performance and uniform temperature performance of the heating process are discussed separately, and all possibilities are listed.

[0236] 2. When the first element of the HP1 array ≥ G × the second element, it is applicable to the case where the fixed temperature is too high, and the severity of the defect of the first fixed temperature defect type is determined by the size of the first element; among them, G is used to judge three situations of fixed temperature performance and can be customized by the user.

[0237] It can be understood that a constant G is set to distinguish the proportion of high and low fixed temperature effects, and to distinguish three cases of fixed temperature performance. When the first element of the HP1 array ≥ G × the second element, the high fixed temperature effect is dominant, which is suitable for the case where the fixed temperature is too high. The defect severity of the first fixed temperature defect type is determined by the size of the first element of the HP1 array representing the high fixed temperature effect.

[0238] 3. When the second element of the HP1 array ≥ G × the first element, it applies to the case where the fixed temperature is too low, and the defect severity of the second fixed temperature defect type is determined by the size of the second element.

[0239] It can be understood that when the second element of the HP1 array ≥ G×the first element, the low fixed temperature effect is dominant, which is applicable to the case where the fixed temperature is too low, and the defect severity of the second fixed temperature defect type is determined by the size of the second element of the HP1 array representing the low fixed temperature effect.

[0240] 4. When the first element of the HP1 array is less than G×the second element, and the second element is less than G×the first element, the case of variable constant temperature is applicable, and the defect severity of the third constant temperature defect type is determined by the size of the first element+the second element.

[0241] It can be understood that when the first element of the HP1 array is less than G×the second element, it means that the high influence of the constant temperature is not dominant, and when the second element of the HP1 array is less than G×the first element, it means that the low influence of the constant temperature is not dominant either. Therefore, this situation is applicable to the case of uncertain low temperature, and the defect severity of the third constant temperature defect type is determined by the size of the first element + the second element.

[0242] 5. When HP2∈[0,ε), it is applicable to the case where the temperature uniformity performance is qualified and there is no temperature uniformity defect; among them, ε is used to judge whether the temperature uniformity performance is qualified.

[0243] It can be understood that HP2 represents the uniform temperature performance of the heating process. The larger the HP2, the worse the uniform temperature performance. A constant ε is set to judge whether the uniform temperature performance is qualified. ε can be customized by the user. When HP2∈[0,ε), it is applicable to the case where the uniform temperature performance is qualified and there is no defect type related to the uniform temperature defect.

[0244] 6. When HP2∈[ε,+∞), it is applicable to the case where the uniform temperature performance is unqualified, and the severity of the uniform temperature performance defect is determined according to the size of HP2.

[0245] Taking the cooling process as an example, the method for obtaining the second part of the process defect information can also be:

[0246] 1. The cooling rate is divided into too large and too small, and the cooling final temperature is divided into too large and too small, thus four situations can be obtained, as shown in Table 4 below:

[0247] Table 4 Four types of cooling defects

[0248] The final cooling temperature is too high Final cooling temperature is too low Cooling Cooling rate is too high First cooling defect type Second Cooling Defect Type Cooling Cooling rate is too low The third cooling defect type The fourth cooling defect type

[0249] 2. When α2∈[0,π / 2), the third cooling defect type is applicable.

[0250] It is understandable that Figure 5 As shown, when α2∈[0,π / 2), the cooling final temperature is too high and the cooling rate is too low, which is applicable to the third cooling defect type.

[0251] 3. When α2∈[π / 2,π), it is applicable to the first cooling defect type.

[0252] It is understandable that Figure 5 As shown, when α2∈[π / 2,π), the cooling final temperature is too high and the cooling rate is too high, which is applicable to the first cooling defect type.

[0253] 4. When α2∈[π,3π / 2), the second cooling defect type is applicable.

[0254] It is understandable that Figure 5 As shown, when α2∈[π,3π / 2), the cooling final temperature is too small and the cooling rate is too large, which is suitable for the second cooling defect type.

[0255] 5. When α2∈[3π / 2,2π), the fourth cooling defect type is applicable.

[0256] It is understandable that Figure 5 As shown, when α2∈[3π / 2,2π), the cooling final temperature is too small and the cooling rate is too small, which is applicable to the fourth cooling defect type.

[0257] 6. And by the cooling process performance vector The module length determines the defect severity of each cooling defect type.

[0258] Such a setting can filter out the influence of inconspicuous factors, improve the accuracy of the second part of process defect information obtained, and facilitate the subsequent determination of the second part of process performance evaluation information.

[0259] S840, determining the second part of process performance evaluation information according to the second part of process defect information; wherein the second part of process performance evaluation information is used to reflect the type of defects and error quantization values ​​in the second part of the process.

[0260] It can be understood that the defect types of the second part of the process defect information and the second part of the process performance evaluation information can match, but the defect severity and the defect error quantification value still need some calculations to match. Taking the cooling process as an example, a parameter X2 can be set to represent the qualified range of cooling process performance. For example, the defect severity ( The modulus length of the defect error is 0.5, and the defect error quantization value can be regarded as 0.5-X2 (when the result is negative, it is regarded as level 0) to obtain the cooling process performance evaluation information. The heating process is similar.

[0261] With such setting, the aging condition of the process performance of the second part can be clearly obtained.

[0262] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0263] Corresponding to the stainless steel plate production management method described in the above embodiment, the embodiment of the present application further provides a stainless steel plate production management device, and each module of the device can implement each step of the stainless steel plate production management method. Figure 6 A structural block diagram of a stainless steel plate production management device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0264] Reference Figure 6 , the device comprises:

[0265] A metallographic acquisition module, used to obtain metallographic information of the stainless steel plate; wherein the metallographic information includes metallographic images of various regions of the stainless steel plate in various processes of processing the stainless steel plate by the stainless steel plate production device;

[0266] A metallographic analysis module, used for obtaining initial grain information according to the metallographic information; wherein the initial grain information is used for reflecting the distribution of grain parameter data of the stainless steel plate in each process of processing the stainless steel plate by the stainless steel plate production device, and the grain parameter data includes grain size and / or grain uniformity;

[0267] A production acquisition module, used to obtain production information; wherein the production information includes jitter information and temperature information of the stainless steel plate production device during the stainless steel plate production process, the jitter information is used to reflect the jitter condition of the stainless steel plate production device, and the temperature information is used to reflect the temperature of the stainless steel plate in the process;

[0268] A production analysis module, used to obtain working state information according to the production information; wherein the working state information includes mechanical state information and heat treatment state information, the mechanical state information is used to reflect the working state of the production device using the mechanical processing method in the stainless steel plate production device, and the heat treatment state information is used to reflect the specific temperature of each part of the stainless steel plate being processed by the production device using the heat treatment processing method in the stainless steel plate production device;

[0269] a troubleshooting grain module, used for troubleshooting the initial grain information according to the mechanical state information to obtain troubleshooting grain information; wherein the troubleshooting grain information is used to reflect the distribution of remaining grain parameter data after excluding grain parameter data of an area affected by a fault of a production device using a mechanical processing method in the initial grain information;

[0270] A process analysis module, used to determine a first part of the process performance of the stainless steel plate production device according to the troubleshooting grain information; wherein the first part of the process performance is used to reflect the performance of the production device using a mechanical processing method in the stainless steel plate production device;

[0271] The process analysis module is also used to determine the second part of the process performance of the stainless steel plate production device according to the heat treatment state information; wherein the second part of the process performance is used to reflect the performance of the production device using the heat treatment processing method in the stainless steel plate production device;

[0272] The process analysis module is also used to determine process performance evaluation information based on the first part of process performance and the second part of process performance; wherein the process performance evaluation information is used to reflect the aging of the process performance of the stainless steel plate production device.

[0273] It should be noted that the information interaction, execution process and other contents between the above-mentioned modules are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0274] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the modules in the above-mentioned device can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0275] The present application also provides a stainless steel plate production management device, Figure 7 This is a schematic diagram of the structure of a stainless steel plate production management device provided in one embodiment of the present application. Figure 7As shown, the stainless steel plate production management device of this embodiment includes: at least one processor 30 ( Figure 7 Only one is shown), at least one memory 31 ( Figure 7 Only one is shown in the figure) and a computer program 32 stored in the at least one memory 31 and executable on the at least one processor 30. When the processor 30 executes the computer program 32, the stainless steel plate production management device implements the steps in any of the above-mentioned stainless steel plate production management method embodiments, or the stainless steel plate production management device 3 implements the functions of each module in the above-mentioned device embodiments.

[0276] Exemplarily, the computer program 32 may be divided into one or more modules / units, which are stored in the memory 31 and executed by the processor 30 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, which are used to describe the execution process of the computer program 32 in the electronic device 3.

[0277] The stainless steel plate production management device 3 can be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The stainless steel plate production management device can include, but is not limited to, a processor 30 and a memory 31. Those skilled in the art can understand that Figure 7 It is only an example of the stainless steel plate production management device 3 and does not constitute a limitation on the stainless steel plate production management device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, buses, etc.

[0278] The processor 30 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0279] In some embodiments, the memory 31 may be an internal storage unit of the stainless steel plate production management device 3, such as a hard disk or memory of the stainless steel plate production management device 3. In other embodiments, the memory 31 may also be an external storage device of the stainless steel plate production management device 3, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the stainless steel plate production management device 3. Further, the memory 31 may also include both an internal storage unit and an external storage device of the stainless steel plate production management device 3. The memory 31 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program, etc. The memory 31 may also be used to temporarily store data that has been output or is to be output.

[0280] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0281] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0282] In the embodiments provided in the present application, it should be understood that the disclosed stainless steel plate production management device, equipment and method can be implemented in other ways. For example, the device / stainless steel plate production management equipment embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0283] 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.

[0284] The embodiments described above 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, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such 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, and should all be included in the protection scope of the present application.

Claims

1. A stainless steel plate production management method, characterized in that: Applied to a stainless steel plate production management device, the stainless steel plate production management device is communicatively connected with a stainless steel plate production device, the method comprises: Acquire metallographic information of the stainless steel plate; wherein the metallographic information includes metallographic images of various regions of the stainless steel plate in various processes of processing the stainless steel plate by the stainless steel plate production device; Initial grain information is obtained according to the metallographic information; wherein the initial grain information is used to reflect the distribution of grain parameter data of the stainless steel plate in each process of processing the stainless steel plate by the stainless steel plate production device, and the grain parameter data includes grain size and / or grain uniformity; Acquire production information; wherein the production information includes jitter information and temperature information of the stainless steel plate production device during the stainless steel plate production process, the jitter information is used to reflect the jitter condition of the stainless steel plate production device, and the temperature information is used to reflect the temperature of the stainless steel plate in the process; Obtaining working state information according to the production information; wherein the working state information includes mechanical state information and heat treatment state information, the mechanical state information is used to reflect the working state of the production device using the mechanical processing method in the stainless steel plate production device, and the heat treatment state information is used to reflect the specific temperature of each part of the stainless steel plate being processed by the production device using the heat treatment processing method in the stainless steel plate production device; Troubleshooting the initial grain information according to the mechanical state information to obtain troubleshooting grain information; wherein the troubleshooting grain information is used to reflect the distribution of remaining grain parameter data after excluding grain parameter data of an area affected by a fault of a production device using a mechanical processing method in the initial grain information; Determine the first part of the process performance of the stainless steel plate production device according to the troubleshooting grain information; wherein the first part of the process performance is used to reflect the performance of the production device using a mechanical processing method in the stainless steel plate production device; Determine the second part of the process performance of the stainless steel plate production device according to the heat treatment state information; wherein the second part of the process performance is used to reflect the performance of the production device using the heat treatment processing method in the stainless steel plate production device; According to the first part of process performance and the second part of process performance, process performance evaluation information is determined; wherein the process performance evaluation information is used to reflect the aging of process performance of the stainless steel plate production device.

2. The stainless steel plate production management method according to claim 1, characterized in that: Initial grain information is obtained according to the metallographic information, including: Partitioning each metallographic image of the metallographic information to obtain a local metallographic image of each area of ​​each metallographic image of the metallographic information; According to the local metallographic images of each region of each metallographic image of the metallographic information, grain parameter data of each local metallographic image is obtained; Based on the grain parameter data of each local metallographic image, the expectation and variance of the grain parameter data of each local metallographic image are calculated to obtain the initial grain information.

3. The stainless steel plate production management method according to claim 2, characterized in that: Obtaining working status information according to the production information includes: Obtaining jitter information of each production device using a mechanical processing method in the stainless steel plate production device from the production information; Performing time domain comparison on the jitter information of each production device using the mechanical processing method and the corresponding preset reference information, respectively, to obtain time domain comparison information of each production device using the mechanical processing method; wherein the production device using the mechanical processing method corresponds to the preset reference information one by one, and the time domain comparison information is used to reflect whether the amplitude of the jitter information exceeds a threshold value; Performing frequency domain comparison on the jitter information of each production device using the mechanical processing method and the specific characteristic information, respectively, to obtain frequency domain comparison information of each production device using the mechanical processing method; wherein the specific characteristic information refers to the frequency domain characteristic information of the jitter when the production device using the mechanical processing method fails, and the frequency domain comparison information is used to reflect whether the frequency domain characteristics of the jitter information are the same as the frequency domain characteristics of the specific characteristic information; Obtaining mechanical state information of each production device using the mechanical processing method according to the time domain comparison information and the frequency domain comparison information of each production device using the mechanical processing method; Obtaining temperature information of each production device using a heat treatment processing method in the stainless steel plate production device from the production information; According to the temperature information of each production device using the heat treatment processing method, the heat treatment state information of each production device using the heat treatment processing method is obtained.

4. The stainless steel plate production management method according to claim 3, characterized in that: Troubleshooting the initial grain information according to the mechanical state information to obtain troubleshooting grain information includes: According to the mechanical status information of each production device using the mechanical processing method, it is judged whether each production device using the mechanical processing method has a fault; If the production device using the mechanical processing method has a fault, a grain information troubleshooting range is obtained according to the mechanical state information of the corresponding production device using the mechanical processing method; wherein the grain information troubleshooting range is used to reflect the range in which the grains of the stainless steel plate processed by the corresponding production device using the mechanical processing method are affected by the fault of the corresponding production device using the mechanical processing method; The troubleshooting die information is determined based on the initial die information and each of the die information troubleshooting ranges.

5. The stainless steel plate production management method as claimed in claim 4, characterized in that: Obtaining the grain information troubleshooting range according to the mechanical state information of the corresponding production device using the mechanical processing method includes: According to the mechanical state information of the corresponding production device using the mechanical processing method, the mechanical fault type of the corresponding production device using the mechanical processing method is obtained, and the abnormal jitter information is obtained from the time domain comparison information of the corresponding production device using the mechanical processing method; wherein the abnormal jitter information is jitter information with an amplitude exceeding a threshold value; Determine a first range according to the type of mechanical failure; wherein the first range is used to reflect the focal range of the range in which the grains of the stainless steel plate processed by the production device using the mechanical processing method are affected by the failure of the corresponding production device using the mechanical processing method; Determine a first area according to the abnormal jitter information; wherein the first area is used to reflect the area of ​​the range in which the grains of the stainless steel plate processed by the production device using the mechanical processing method are affected by the failure of the corresponding production device using the mechanical processing method; The grain information troubleshooting range is obtained according to the first range and the first area.

6. The stainless steel plate production management method as claimed in claim 5, characterized in that: The determining of the first part of the process performance of the stainless steel plate production device according to the troubleshooting grain information includes: Obtaining preset grain change information of the stainless steel plates processed by each production device using a mechanical processing method in the stainless steel plate production device; wherein the preset grain change information is used to reflect the preset change amount of the grain parameter data of the stainless steel plates processed by the production device of the corresponding process before and after processing; According to the troubleshooting grain information, the actual grain change information of the stainless steel plates processed by each production device using the mechanical processing method is obtained; wherein the actual grain change information is used to reflect the actual change amount of the grain parameter data of the stainless steel plates processed by the production device of the corresponding process before and after processing; The actual grain change information is compared with the preset grain change information to obtain the first part of process performance.

7. The stainless steel plate production management method as claimed in claim 6, characterized in that: The determining of the second part of the process performance of the stainless steel plate production device according to the heat treatment state information comprises: Acquire preset temperature information of the stainless steel plates processed by each production device using a heat treatment processing method in the stainless steel plate production device; wherein the preset temperature information is used to reflect the preset temperature information of the stainless steel plates processed by the production device of the corresponding process; The preset temperature information is compared with the heat treatment state information to obtain a second part of process performance.

8. The stainless steel plate production management method as claimed in claim 7, characterized in that: Determining process performance evaluation information according to the first part of process performance and the second part of process performance includes: According to the first part of process performance, a first part of process defect information is obtained; wherein the first part of process defect information is used to reflect defect information of the grains analyzed in the first part of process performance; Determine the first part of process performance evaluation information according to the first part of process defect information; wherein the first part of process performance evaluation information is used to reflect the type and error quantization value of the defect in the first part of the process; According to the second part of the process performance, a second part of the process defect information is obtained; wherein the second part of the process defect information is used to reflect the defect information of the temperature analyzed in the second part of the process performance; According to the second part of process defect information, the second part of process performance evaluation information is determined; wherein the second part of process performance evaluation information is used to reflect the type and error quantization value of the defect in the second part of the process.

9. A stainless steel plate production management device, characterized in that: Applied to stainless steel plate production management equipment, the stainless steel plate production management equipment is communicatively connected with the stainless steel plate production device, and the stainless steel plate production management device includes: A metallographic acquisition module, used to obtain metallographic information of the stainless steel plate; wherein the metallographic information includes metallographic images of various regions of the stainless steel plate in various processes of processing the stainless steel plate by the stainless steel plate production device; A metallographic analysis module, used for obtaining initial grain information according to the metallographic information; wherein the initial grain information is used for reflecting the distribution of grain parameter data of the stainless steel plate in each process of processing the stainless steel plate by the stainless steel plate production device, and the grain parameter data includes grain size and / or grain uniformity; A production acquisition module, used to obtain production information; wherein the production information includes jitter information and temperature information of the stainless steel plate production device during the stainless steel plate production process, the jitter information is used to reflect the jitter condition of the stainless steel plate production device, and the temperature information is used to reflect the temperature of the stainless steel plate in the process; A production analysis module, used to obtain working state information according to the production information; wherein the working state information includes mechanical state information and heat treatment state information, the mechanical state information is used to reflect the working state of the production device using the mechanical processing method in the stainless steel plate production device, and the heat treatment state information is used to reflect the specific temperature of each part of the stainless steel plate being processed by the production device using the heat treatment processing method in the stainless steel plate production device; a troubleshooting grain module, used for troubleshooting the initial grain information according to the mechanical state information to obtain troubleshooting grain information; wherein the troubleshooting grain information is used to reflect the distribution of remaining grain parameter data after excluding grain parameter data of an area affected by a fault of a production device using a mechanical processing method in the initial grain information; A process analysis module, used to determine a first part of the process performance of the stainless steel plate production device according to the troubleshooting grain information; wherein the first part of the process performance is used to reflect the performance of the production device using a mechanical processing method in the stainless steel plate production device; The process analysis module is also used to determine the second part of the process performance of the stainless steel plate production device according to the heat treatment state information; wherein the second part of the process performance is used to reflect the performance of the production device using the heat treatment processing method in the stainless steel plate production device; The process analysis module is also used to determine process performance evaluation information based on the first part of process performance and the second part of process performance; wherein the process performance evaluation information is used to reflect the aging of the process performance of the stainless steel plate production device.

10. A stainless steel plate production management device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

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