Method, system and device for determining bar tolerance

Abstract

The embodiment of the invention provides a bar tolerance determination method, system and device, and belongs to the technical field of bar production and machining.The method comprises the steps that a temperature difference influence factor is determined according to the material influence coefficient of a raw material blank corresponding to a bar, the surface temperature difference before and after heating and the heating duration; and determining the bar tolerance according to the theoretical weight of the bar, the actually measured weight of the raw material blank, the error correction coefficient and the temperature difference influence factor. The embodiment of the invention provides an efficient and rapid tolerance real-time calculation method on one hand, and comprehensively considers the influence of the cold and hot conditions of the raw material blank on the deviation of the finished product on the other hand, so that the problem of inconsistent deviation of the finished product caused by the internal and external temperature difference after the raw material blank is heated can be solved, and the tolerance measurement precision is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of bar production and processing, and in particular to a method, system, device, computer-readable storage medium and computer program product for determining bar tolerance. Background Art

[0002] Steel companies often use negative deviation rolling when producing bars. Deviation rolling involves controlling the actual dimensions of the finished steel product within a negative deviation of the nominal size during the rolling process. In simple terms, this means the rolled steel is slightly smaller than the standard size, but still within the specified tolerance range. Using negative deviation rolling can effectively improve yield rates and reduce raw material costs.

[0003] For negative deviation rolling, calculating the finished product tolerance is a key step in ensuring that the rolled bar dimensions meet standard requirements. Existing methods employ two tolerance measurement methods: sampling at the cooling bed inlet and calculating tolerance by weighing the finished product. However, both methods are offline and exhibit a certain degree of lag, hindering accurate control of bar tolerances. Furthermore, once a product is found to be out of tolerance, a significant number of out-of-tolerance products have already been produced, resulting in significant losses. Summary of the Invention

[0004] The purpose of the embodiments of the present invention is to provide a method, system and device for determining the tolerance of a bar, which can solve the above-mentioned defects of the prior art.

[0005] To achieve the above-mentioned object, a first aspect of an embodiment of the present invention provides a method for determining a bar tolerance, the method comprising:

[0006] Determining the temperature difference influence factor based on the influence coefficient of the material of the raw material blank corresponding to the bar, the surface temperature difference before and after heating, and the heating time; and

[0007] The bar tolerance is determined according to the theoretical weight of the bar, the measured weight of the raw material billet, the error correction coefficient, and the temperature difference influencing factor.

[0008] In some embodiments, determining the temperature difference influencing factor based on the influence coefficient of the material of the raw material blank corresponding to the rod, the surface temperature difference before and after heating, and the heating time includes:

[0009] The temperature difference influence factor is calculated according to the following formula:

[0010] X=φlog N (A*τ+(T1-T0))

[0011] in,

[0012] X is the temperature difference influence factor;

[0013] T0 is the surface temperature of the raw material blank before entering the heating furnace;

[0014] T1 is the surface temperature of the raw material blank after being heated in the heating furnace;

[0015] τ is the heating duration of the raw material blank;

[0016] φ is the influence coefficient of the material of the raw material blank;

[0017] A is the heating duration amplification coefficient;

[0018] N is the influence order.

[0019] In some embodiments, determining the temperature difference influence factor according to the influence coefficient of the material of the raw material blank corresponding to the bar, the surface temperature difference before and after heating, and the heating duration includes:

[0020] Calculating the temperature difference influence factor according to the following formula:

[0021] X = φlog N (A*τ+(T1 - T0)+B)

[0022] Wherein,

[0023] X is the temperature difference influence factor;

[0024] T0 is the surface temperature of the raw material blank before entering the heating furnace;

[0025] T1 is the surface temperature of the raw material blank after being heated in the heating furnace;

[0026] τ is the heating duration of the raw material blank;

[0027] φ is the influence coefficient of the material of the raw material blank;

[0028] A is the heating duration amplification coefficient;

[0029] B is the compensation coefficient;

[0030] N is the influence order.

[0031] In some embodiments, when the raw material blank corresponding to the bar is a hot blank, T0 is set to 500; when the raw material blank corresponding to the bar is a cold blank, T0 is set to 100.

[0032] In some embodiments, determining the bar tolerance according to the theoretical weight of the bar, the measured weight of the raw material blank, the error correction coefficient, and the temperature difference influence factor includes:

[0033] Determining the bar tolerance according to the following formula:

[0034]

[0035] Among them,

[0036] W Act is the measured weight of the original blank before processing;

[0037] W l is the theoretical weight of the bar;

[0038] S is the tolerance;

[0039] K is the error correction coefficient;

[0040] X is the temperature difference influence factor.

[0041] In some embodiments, the theoretical weight of the bar is determined according to the total length of the bar and the theoretical weight per meter, wherein the theoretical weight per meter is the weight per unit length corresponding to the standard area;

[0042] The theoretical weight of the bar is determined according to the following formula:

[0043] W l = L Act × W wpm

[0044] Among them,

[0045] L Act is the measured total length of the bar;

[0046] W wpm is the theoretical weight per meter of the bar;

[0047] W l is the theoretical weight of the bar.

[0048] The second aspect of the embodiments of the present invention provides a system for determining the tolerance of a bar, and the system includes:

[0049] A data processing module, which is used to determine the temperature difference influence factor according to the influence coefficient of the material of the raw blank corresponding to the bar, the surface temperature difference before and after heating, and the heating duration; and

[0050] Determine the bar tolerance according to the theoretical weight of the bar, the measured weight of the raw blank, the error correction coefficient, and the temperature difference influence factor.

[0051] In some embodiments, the system includes: a parameter setting module and a data acquisition module;

[0052] The parameter setting module is used to set the influence coefficient of the material of the raw blank corresponding to the bar and the error correction coefficient;

[0053] The data acquisition module is used to obtain the surface temperature difference before and after heating, the heating duration, the theoretical weight of the bar, and the measured weight of the raw blank.

[0054] In some embodiments, determining the temperature difference influence factor based on the influence coefficient of the material of the raw blank corresponding to the bar, the surface temperature difference before and after heating, and the heating duration includes:

[0055] Calculating the temperature difference influence factor according to the following formula:

[0056] X = φlog N (A*τ + (T1 - T0))

[0057] Wherein,

[0058] X is the temperature difference influence factor;

[0059] T0 is the surface temperature of the raw blank before entering the heating furnace;

[0060] T1 is the surface temperature of the raw blank after being heated in the heating furnace;

[0061] τ is the heating duration of the raw blank;

[0062] φ is the influence coefficient of the material of the raw blank;

[0063] A is the heating duration amplification coefficient;

[0064] N is the influence level.

[0065] In some embodiments, determining the temperature difference influence factor based on the influence coefficient of the material of the raw blank corresponding to the bar, the surface temperature difference before and after heating, and the heating duration includes:

[0066] Calculating the temperature difference influence factor according to the following formula:

[0067] X = φlog N (A*τ + (T1 - T0) + B)

[0068] Wherein,

[0069] X is the temperature difference influence factor;

[0070] T0 is the surface temperature of the raw blank before entering the heating furnace;

[0071] T1 is the surface temperature of the raw blank after being heated in the heating furnace;

[0072] τ is the heating duration of the raw blank;

[0073] φ is the influence coefficient of the material of the raw blank;

[0074] A is the heating duration amplification coefficient;

[0075] B is the compensation coefficient;

[0076] N is the influence level.

[0077] In some embodiments, when the raw blank corresponding to the bar is a hot blank, T0 is set to 500; when the raw blank corresponding to the bar is a cold blank, T0 is set to 100.

[0078] In some embodiments, determining the tolerance of the bar according to the theoretical weight of the bar, the measured weight of the raw blank, the error correction coefficient, and the temperature difference influence factor includes:

[0079] Determining the tolerance of the bar according to the following formula:

[0080]

[0081] Wherein,

[0082] W Act is the measured weight of the original blank before processing;

[0083] W l is the theoretical weight of the bar;

[0084] S is the tolerance;

[0085] K is the error correction coefficient;

[0086] X is the temperature difference influence factor.

[0087] In some embodiments, the theoretical weight of the bar is determined according to the total length of the bar and the theoretical weight per meter, wherein the theoretical weight per meter is the weight per unit length corresponding to the standard area;

[0088] The theoretical weight of the bar is determined according to the following formula:

[0089] W l = L Act ×W wpm <d

[0090] Wherein,

[0091] L Act is the measured total length of the bar;

[0092] W wpm is the theoretical weight per meter of the bar;

[0093] W l is the theoretical weight of the bar.

[0094] The third aspect of the embodiments of the present invention provides a device for calculating the tolerance of a bar, including:

[0095] A memory configured to store instructions; and

[0096] A processor, configured to call the instructions from the memory and capable of implementing the method for determining the tolerance of the bar when executing the instructions.

[0097] A fourth aspect of an embodiment of the present invention provides a computer-readable storage medium, on which instructions are stored, and when the instructions are executed by a processor, the method for determining the tolerance of the bar is implemented.

[0098] A fifth aspect of an embodiment of the present invention provides a computer program product, including a computer program, and when the computer program is executed by a processor, the method for determining the tolerance of the bar is implemented.

[0099] In an embodiment of the present invention, first, a temperature difference influence factor is determined according to the influence coefficient of the material of the raw blank corresponding to the bar, the surface temperature difference before and after heating, and the heating duration. Then, the bar tolerance is determined according to the theoretical weight of the bar, the measured weight of the raw blank, the error correction coefficient, and the temperature difference influence factor. On the one hand, an efficient and fast real-time tolerance calculation method is provided. On the other hand, the influence of the cold and hot conditions of the raw blank on the finished product deviation is comprehensively considered, and the problem of inconsistent finished product deviations caused by the internal and external temperature differences after the raw blank is heated can be solved, thereby improving the tolerance measurement accuracy.

[0100] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent specific implementation part. BRIEF DESCRIPTION OF THE DRAWINGS

[0101] The drawings are used to provide a further understanding of the embodiments of the present invention, and constitute a part of the specification. Together with the following specific implementation, they are used to explain the embodiments of the present invention, but do not constitute a limitation to the embodiments of the present invention. In the drawings:

[0102] Figure 1 is a flowchart of the method for determining the tolerance of the bar provided by an embodiment of the present invention;

[0103] Figure 2 is a schematic diagram of the system for determining the tolerance of the bar provided by an embodiment of the present invention;

[0104] Figure 3 is a program structure diagram of the system for determining the tolerance of the bar provided by an embodiment of the present invention;

[0105] Figure 4 is a schematic diagram of the operation process of the tolerance calculation module in the system for determining the tolerance of the bar provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0106] The following details the specific implementation of the embodiments of the present invention in conjunction with the drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiments of the present invention, and is not used to limit the embodiments of the present invention.

[0107] It should be noted that in the technical solution of this application, the acquisition, transmission, storage, use, processing, etc. of data all comply with the relevant regulations of laws and regulations. In the embodiments of this application, some existing solutions in the industry such as certain software, components, models, etc. may be mentioned, and they should be regarded as exemplary. The purpose is only to illustrate the feasibility in the implementation of the technical solution of this application, but it does not mean that the applicant has already or necessarily used this solution.

[0108] Embodiment 1

[0109] In the research process, the inventors of this application found that the traditional tolerance measurement method is to weigh the raw material billet to obtain the actual weight, measure the actual length of the finished product at the outlet of the rolling line, and convert it into the theoretical weight through the standard meter weight. The two are compared and corrected to obtain the finished product tolerance value. Although the traditional method can quickly measure the bar tolerance when the raw material properties are stable, in the working condition where cold billets and hot billets are mixed, the cold billets are unevenly heated, there is a large temperature difference between the inside and outside, and there is a large difference between the finished product tolerances of cold billets and hot billets.

[0110] Based on this, the inventors of this application propose a method for determining the bar tolerance to solve the problem of inconsistent finished product deviations caused by the temperature difference between the inside and outside after the raw material billet is heated, thereby improving the tolerance measurement accuracy, especially applicable to the bar production line in the working condition of mixed cold and hot billets.

[0111] Specifically, Figure 1 is the flowchart of the method for determining the bar tolerance provided by the embodiments of the present invention. As Figure 1 shown, the embodiments of the present invention provide a method for determining the bar tolerance, and the method includes:

[0112] Step S101, determine the temperature difference influence factor according to the influence coefficient of the material of the raw material billet corresponding to the bar, the surface temperature difference before and after heating, and the heating duration.

[0113] Specifically, tolerance is the allowable range of dimensional variation. The tolerance zone defines the maximum and minimum acceptable values of the part dimensions.

[0114] In machining, a negative deviation means that the dimension of the machined part is smaller than the designed dimension. A negative deviation is a specific case in the tolerance zone, indicating that the actual dimension is close to the lower limit of the tolerance zone. Through specific numerical examples, illustrate the position of the negative deviation in the tolerance zone and its impact on the part quality. For example, if the designed dimension is 10mm and the tolerance is ±0.1mm, in the case of negative deviation, the actual dimension may be 9.9mm. A negative deviation is a possible situation in the tolerance zone, which reflects the deviation direction of the actual dimension relative to the designed dimension. In quality control, the negative deviation needs to be controlled within the tolerance range to ensure the function and interchangeability of the part.

[0115] Specifically, based on the influence coefficients of the materials of the raw billets corresponding to the bars, the surface temperature difference before and after heating, and the relationship between the heating duration and the finished product tolerance of the bars, a functional relationship is established:

[0116] X = f(ΔT, τ, φ) (1)

[0117] Wherein, X is the temperature difference influence factor;

[0118] ΔT is the surface temperature difference of the raw billet before and after heating;

[0119] τ is the heating duration of the raw billet;

[0120] It should be noted that by analyzing a large amount of operation data in bar production and processing, it is found that during continuous and stable rolling, when hot and cold billets are mixed, the heating duration has a greater impact on the finished product tolerance.

[0121] φ: The influence coefficient of the steel type of the raw billet.

[0122] In some embodiments, the influence of the temperature difference and the heating duration on the finished product tolerance is in a logarithmic relationship.

[0123] Specifically, determining the temperature difference influence factor according to the influence coefficient of the material of the raw billet corresponding to the bar, the surface temperature difference before and after heating, and the heating duration includes:

[0124] Calculating the temperature difference influence factor according to the following formula:

[0125] X = φlog N (A*τ + (T1 - T0) + B) (2)

[0126] Wherein,

[0127] X is the temperature difference influence factor;

[0128] T0 is the surface temperature of the raw billet before entering the heating furnace, in °C;

[0129] T1 is the surface temperature of the raw billet after being heated in the heating furnace, in °C;

[0130] τ is the heating duration of the raw billet, in minutes;

[0131] φ is the influence coefficient of the material of the raw billet;

[0132] A is the heating duration amplification coefficient;

[0133] B is the compensation coefficient;

[0134] N is the influence level.

[0135] In some embodiments, determining the temperature difference influence factor based on the influence coefficient of the material of the raw billet corresponding to the bar, the surface temperature difference before and after heating, and the heating duration includes:

[0136] Calculating the temperature difference influence factor according to the following formula:

[0137] X = φlog N (A * τ + (T1 - T0)) (3)

[0138] Wherein,

[0139] X is the temperature difference influence factor;

[0140] T0 is the surface temperature of the raw billet before entering the heating furnace;

[0141] T1 is the surface temperature of the raw billet after being heated in the heating furnace;

[0142] τ is the heating duration of the raw billet;

[0143] φ is the influence coefficient of the material of the raw billet;

[0144] A is the heating duration amplification coefficient;

[0145] N is the influence level.

[0146] In some embodiments, when the raw billet corresponding to the bar is a hot billet, T0 is set to 500; when the raw billet corresponding to the bar is a cold billet, T0 is set to 100.

[0147] In some embodiments, when the raw billet corresponding to the bar is a hot billet, T0 is set to any value between 400 and 800; when the raw billet corresponding to the bar is a cold billet, T0 is set to any value between 25 and 400.

[0148] Step S102, determining the bar tolerance according to the theoretical weight of the bar, the measured weight of the raw billet, the error correction coefficient, and the temperature difference influence factor.

[0149] In some embodiments, determining the bar tolerance according to the theoretical weight of the bar, the measured weight of the raw billet, the error correction coefficient, and the temperature difference influence factor includes:

[0150] Determining the bar tolerance according to the following formula:

[0151]

[0152] Wherein,

[0153] W ActW is the measured weight of the original blank before processing, with the unit of Kg. Specifically, the measured weight of the original blank before processing can be obtained by weighing the original blank at the entrance of the rolling mill.

[0154] W l is the theoretical weight of the bar, with the unit of Kg.

[0155] S is the tolerance. Specifically, S represents the predicted value of negative deviation, with the unit of %.

[0156] K is the error correction coefficient.

[0157] X is the temperature difference influence factor.

[0158] In some embodiments, the theoretical weight of the bar is determined according to the total length of the bar and the theoretical weight per meter, where the theoretical weight per meter is the weight per unit length corresponding to the standard area.

[0159] The theoretical weight of the bar is determined according to the following formula:

[0160] W l = L Act ×W wpm (5)

[0161] Where,

[0162] L Act is the measured total length of the finished bar, with the unit of m.

[0163] W wpm is the theoretical weight per meter of the bar, with the unit of Kg / m.

[0164] W l is the theoretical weight of the bar, with the unit of Kg.

[0165] In some embodiments, after substituting Formula (5) and Formula (2) into Formula (4), the formula (6) for calculating the tolerance of the bar is further obtained:

[0166]

[0167] Where, L Act 、W Act 、W wpm 、τ, T0 and T1 can be obtained by measurement or from the standard specifications, and K, φ, N, A, B can be obtained by regression analysis based on experience or historical tolerance data.

[0168] On some production lines, since there is no high-temperature gauge in front of the furnace and the T0 value cannot be obtained, at this time, the raw material blank can be identified as a hot blank or a cold blank by a hot metal detector, so as to set a fixed T0 value, and its value can be set according to the on-site situation. For example:

[0169]

[0170] An embodiment of the present invention also provides a device for calculating the tolerance of bars, including: a memory configured to store instructions; and a processor configured to call the instructions from the memory and capable of implementing the method for determining the tolerance of bars when executing the instructions.

[0171] An embodiment of the present invention also provides a computer-readable storage medium, on which instructions are stored, and when the instructions are executed by a processor, the method for determining the tolerance of bars is implemented.

[0172] An embodiment of the present invention also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the method for determining the tolerance of bars is implemented.

[0173] In an embodiment of the present invention, first, a temperature difference influence factor is determined according to the influence coefficient of the material of the raw billet corresponding to the bar, the surface temperature difference before and after heating, and the heating duration. Then, the bar tolerance is determined according to the theoretical weight of the bar, the measured weight of the raw billet, the error correction coefficient, and the temperature difference influence factor. The influence of the hot and cold conditions of the raw billet on the finished product deviation is comprehensively considered, and the problem of inconsistent finished product deviations caused by the internal and external temperature differences after the raw billet is heated can be solved, thereby improving the tolerance measurement accuracy.

[0174] Embodiment Two

[0175] Figure 2 is a schematic diagram of the system for determining the tolerance of bars provided by an embodiment of the present invention. Referring to Figure 2 , an embodiment of the present invention provides a system for determining the tolerance of bars, including at least the following parts:

[0176] A measurement host, which can be an industrial control computer or a server, is installed in the workshop computer room or the main control room, responsible for receiving signals and data collected by other systems, calculating the tolerance of bars, storing tolerance data, and providing data analysis services.

[0177] A billet weighing system, arranged in front of the heating furnace or before the entrance of the rolling mill, to obtain the measured weight value of the raw billet.

[0178] A finished product weighing system, arranged downstream of the cooling bed, to obtain the measured data of the bundled weight of the finished product weighing.

[0179] A rolled piece tracking system, arranged on the rolling line, to obtain the movement and operation conditions of the raw billet on the entire rolling line, corresponding to the raw material data and the production plan, and ensure the consistency of the logistics and the information flow.

[0180] A heating furnace system, arranged in the heating furnace area of the rolling line, to obtain the heating data of the raw billet in the heating furnace, including the furnace entry time, the furnace exit time, the heating system, etc.

[0181] The programmable logic controller in front of the furnace (furnace front PLC) is arranged in front of the heating furnace, obtains the operation information of the raw billet on the front furnace roller table, receives and processes the detection signals of the hot metal detector and the high-temperature thermometer in front of the furnace, and obtains the surface temperature of the raw billet in front of the furnace.

[0182] The programmable logic controller of the main rolling mill (main rolling mill PLC) is arranged on the main rolling line behind the heating furnace, obtains the operation information of the raw billet on the rear furnace roller table and the main rolling line, receives and processes the detection signals of the hot metal detector and the high-temperature thermometer behind the furnace, and obtains the surface temperature of the raw billet behind the furnace.

[0183] The programmable logic controller of the flying shear for multiple lengths (multiple-length flying shear PLC) is arranged at the outlet of the main rolling line, and obtains the total length of the rolled piece at the outlet of the main rolling line;

[0184] The hot metal detectors are arranged in front of and behind the heating furnace, and are used to detect whether the raw billet is a hot billet or a cold billet, as well as the running and positioning conditions of the raw billet.

[0185] The high-temperature thermometers are arranged in front of and behind the heating furnace, or in front of the rough rolling mill, and are used to detect the surface temperature of the raw billet in front of and behind the furnace.

[0186] The hot metal detectors and the high-temperature thermometers are connected to the programmable logic controller through an industrial bus network, and transmit the signals to the programmable logic controller.

[0187] Usually, a measurement terminal is arranged in the operation room, which allows the operator to monitor the measurement results, adjust the measurement parameters, and analyze the historical data. In order to display the measurement results to the workers on the production line, a field large screen connected to the measurement terminal can be set up. In addition, a handheld mobile terminal can be set up, which is connected to the measurement host through a wireless network and serves as a terminal for data entry and display.

[0188] Each component of the system is connected through a network, such as Ethernet, and can use a wired network or a wireless network.

[0189] In the whole system, the measurement host is the core of the system, undertakes the main measurement and calculation tasks, and the corresponding software program structure of the system is as Figure 3 shown.

[0190] Refer to Figure 3 , the data acquisition module is responsible for acquiring the status data of the raw billet and the finished product on the entire production line, including data such as the weight of the raw billet, the temperature in front of the furnace, the temperature behind the furnace, the furnace entry time, the furnace exit time, the total length of the rolled piece, the sample length and weight, the weight and number of pieces of the finished product bundle, etc. After acquiring these data, it is transmitted to the tolerance calculation module for tolerance calculation.

[0191] Figure 4It is a schematic diagram of the operation process of the tolerance calculation module in the bar tolerance determination system provided by the embodiments of the present invention. Refer to Figure 4 , the tolerance calculation module loads calculation parameters, calculates the bar tolerance after receiving the measured data of the rolled piece, obtains the final tolerance value through the heating compensation model, and saves the calculation result to the historical database.

[0192] Among them, the heating compensation model first determines the temperature difference influence factor according to the influence coefficient of the material of the raw billet corresponding to the bar, the surface temperature difference before and after heating, and the heating duration; then determines the bar tolerance according to the theoretical weight of the bar, the measured weight of the raw billet, the error correction coefficient, and the temperature difference influence factor.

[0193] Specifically, the determination of the temperature difference influence factor according to the influence coefficient of the material of the raw billet corresponding to the bar, the surface temperature difference before and after heating, and the heating duration includes:

[0194] Calculate the temperature difference influence factor according to the following formula:

[0195] X = φlog N (A*τ + (T1 - T0) + B) (2)

[0196] Among them,

[0197] X is the temperature difference influence factor;

[0198] T0 is the surface temperature of the raw billet before entering the heating furnace;

[0199] T1 is the surface temperature of the raw billet after being heated in the heating furnace;

[0200] τ is the heating duration of the raw billet;

[0201] φ is the influence coefficient of the material of the raw billet;

[0202] A is the heating duration amplification coefficient;

[0203] B is the compensation coefficient;

[0204] N is the influence order.

[0205] Furthermore, the determination of the bar tolerance according to the theoretical weight of the bar, the measured weight of the raw billet, the error correction coefficient, and the temperature difference influence factor includes:

[0206] Determine the bar tolerance according to the following formula:

[0207]

[0208] Among them,

[0209] W Act is the measured weight of the original billet before processing;

[0210] W l is the theoretical weight of the bar;

[0211] S is the tolerance;

[0212] K is the error correction coefficient;

[0213] X is the temperature difference influence factor.

[0214] In some embodiments, the theoretical weight of the bar is determined according to the total length and the theoretical weight per meter of the bar, wherein the theoretical weight per meter is the weight per unit length corresponding to the standard area;

[0215] The theoretical weight of the bar is determined according to the following formula:

[0216] W l = L Act ×W wpm (5)

[0217] wherein,

[0218] L Act is the measured total length of the finished bar, with the unit of m;

[0219] W wpm is the theoretical weight per meter of the bar, with the unit of Kg / m;

[0220] W l is the theoretical weight of the bar, with the unit of Kg.

[0221] The embodiment of the present invention realizes an online measurement method for the tolerance of bars under the condition of mixed loading of hot and cold billets. The tolerance calculation module calculates the tolerance according to the original properties and heating conditions of the raw billets, and a more accurate tolerance measurement value can be obtained. Among them, the original properties of the raw billets refer to the influence coefficient of the steel type of the raw billets, and the heating conditions refer to the surface temperature difference before and after heating of the raw billets and the heating duration of the raw billets.

[0222] The tolerance measurement database, which can be a relational database, is used to store the tolerance measurement results and various data of the entire system, providing support for data analysis.

[0223] The data analysis module, on the one hand, classifies and statistically analyzes the tolerance measurement results, and statistically analyzes the average value, maximum value, minimum value, standard deviation, qualified rate, and controlled rate of the tolerance according to the steel type, specification, fixed-length, number of bundled pieces, etc., improving the production management efficiency; on the other hand, through regression analysis of historical tolerance measurement values and actual values, the basic parameters of tolerance measurement are corrected, thereby improving the measurement accuracy.

[0224] The parameter setting module is responsible for managing various parameters of tolerance measurement, including the influence coefficient φ of steel grade, the heating duration amplification coefficient A, the compensation coefficient B, the influence level N, the error correction coefficient K, and the target tolerance range, etc.

[0225] The user interface module is responsible for providing a friendly operation interface for users, mainly including the main monitoring interface, the product specification maintenance interface, the parameter setting interface, the data analysis interface, the sampling data entry interface, the roll gap adjustment interface, etc. The user interface provides a computer version and a mobile APP version, which can run on computers and mobile devices to meet the application requirements of different scenarios.

[0226] Figure 3 It is the program structure diagram of the bar tolerance determination system provided by the embodiment of the present invention. Refer to Figure 3 Yes, the operation process of the bar tolerance determination system provided by the embodiment of the present invention will be specifically described.

[0227] First, the program starts and loads the tolerance calculation parameters from the parameter setting data.

[0228] Then start the data acquisition program to collect data such as the weight of the raw material billet, the temperature before the furnace, the temperature after the furnace, the furnace entry time, the furnace exit time, the total length of the rolled piece, and the finished product weighing value. The rolled piece tracking program binds this data to the rolled piece model.

[0229] After receiving the total length of the rolled piece, the final rolled piece tolerance is obtained through calculation by the heating compensation model. Specifically, the heating compensation model first determines the temperature difference influence factor according to the influence coefficient of the material of the raw material billet corresponding to the rolled piece, the surface temperature difference before and after heating, and the heating duration; then determines the final rolled piece tolerance according to the theoretical weight of the rolled piece, the measured weight of the raw material billet, the error correction coefficient, and the temperature difference influence factor.

[0230] Then save the rolled piece tolerance result to the historical database.

[0231] After receiving the actual weighing value of the finished product, calculate the actual tolerance, retrieve the measurement data of the relevant rolled piece from the historical database, adjust the tolerance calculation parameters through regression analysis, and update the tolerance calculation parameters for the next tolerance calculation.

[0232] Specifically, adjust the error correction coefficient K, the influence coefficient φ of the material of the raw material billet, the influence level N, the heating duration amplification coefficient A, and the compensation coefficient B in the tolerance calculation parameters through regression analysis.

[0233] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0234] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the specified functions in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0235] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the specified functions in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0236] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the specified functions in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0237] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0238] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0239] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0240] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0241] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for determining the tolerance of bars, characterized in that, The method includes: Determining a temperature difference influence factor according to an influence coefficient of the material of the raw blank corresponding to the bar, the surface temperature difference before and after heating, and the heating duration; and Determining the bar tolerance according to the theoretical weight of the bar, the measured weight of the raw blank, an error correction coefficient, and the temperature difference influence factor.

2. The method according to claim 1, characterized in that, The determining the temperature difference influence factor according to the influence coefficient of the material of the raw blank corresponding to the bar, the surface temperature difference before and after heating, and the heating duration includes: Calculating the temperature difference influence factor according to the following formula: X = φ log N (A * τ+(T1 - T0)) Wherein, X is the temperature difference influence factor; T0 is the surface temperature of the raw blank before entering the heating furnace; T1 is the surface temperature of the raw blank after being heated in the heating furnace; τ is the heating duration of the raw blank; φ is the influence coefficient of the material of the raw blank; A is the heating duration amplification coefficient; N is the influence order.

3. The method according to claim 1, wherein The determining the temperature difference influence factor according to the influence coefficient of the material of the raw blank corresponding to the bar, the surface temperature difference before and after heating, and the heating duration includes: Calculating the temperature difference influence factor according to the following formula: X = φlog N (A*τ+(T1 - T0)+B) Wherein, X is the temperature difference influence factor; T0 is the surface temperature of the raw blank before entering the heating furnace; T1 is the surface temperature of the raw blank after being heated in the heating furnace; τ is the heating duration of the raw blank; φ is the influence coefficient of the material of the raw blank; A is the heating duration amplification coefficient; B is the compensation coefficient; N is the influence order.

4. The method according to claim 1, wherein The determining the bar tolerance according to the theoretical weight of the bar, the measured weight of the raw blank, an error correction coefficient, and the temperature difference influence factor includes: Determining the bar tolerance according to the following formula: Wherein, W Act is the measured weight of the original blank before processing; W l is the theoretical weight of the bar; S is the tolerance; K is the error correction coefficient; X is the temperature difference influence factor.

5. The method according to claim 1, wherein The theoretical weight of the bar is determined according to the total length of the bar and the theoretical weight per meter, wherein the theoretical weight per meter is the weight per unit length corresponding to the standard area; The theoretical weight of the bar is determined according to the following formula: W l = L Act × W wpm Wherein, L Act is the measured total length of the bar; W wpm is the theoretical weight per meter of the bar; W l is the theoretical weight of the bar.

6. A system for determining the tolerance of bars, characterized in that, The system includes: A data processing module, which is used to determine a temperature difference influence factor according to an influence coefficient of the material of the raw blank corresponding to the bar, the surface temperature difference before and after heating, and the heating duration; and Determining the bar tolerance according to the theoretical weight of the bar, the measured weight of the raw blank, an error correction coefficient, and the temperature difference influence factor.

7. The system according to claim 6, wherein The system includes: a parameter setting module and a data acquisition module; The parameter setting module is used to set an influence coefficient of the material of the raw blank corresponding to the bar and an error correction coefficient; The data acquisition module is used to obtain the surface temperature difference before and after heating, the heating duration, the theoretical weight of the bar, and the measured weight of the raw blank.

8. The system according to claim 6, characterized in that, The determining the temperature difference influence factor according to the influence coefficient of the material of the raw blank corresponding to the bar, the surface temperature difference before and after heating, and the heating duration includes: Calculating the temperature difference influence factor according to the following formula: X = φlog N (A*τ+(T1 - T0)) Wherein, X is the temperature difference influence factor; T0 is the surface temperature of the raw blank before entering the heating furnace; T1 is the surface temperature of the raw blank after being heated in the heating furnace; τ is the heating duration of the raw blank; φ is the influence coefficient of the material of the raw blank; A is the heating duration amplification coefficient; N is the influence order.

9. The system according to claim 6, wherein Determining the temperature difference influence factor based on the influence coefficient of the material of the raw blank corresponding to the bar, the surface temperature difference before and after heating, and the heating duration includes: Calculating the temperature difference influence factor according to the following formula: X = φ log N (A * τ+(T1 - T0)+B) Wherein, X is the temperature difference influence factor; T0 is the surface temperature of the raw blank before entering the heating furnace; T1 is the surface temperature of the raw blank after being heated in the heating furnace; τ is the heating duration of the raw blank; φ is the influence coefficient of the material of the raw blank; A is the heating duration amplification coefficient; B is the compensation coefficient; N is the influence order.

10. The system according to claim 6, wherein Determining the bar tolerance based on the theoretical weight of the bar, the measured weight of the raw blank, the error correction coefficient, and the temperature difference influence factor includes: Determining the bar tolerance according to the following formula: Wherein, W Act is the measured weight of the original blank before processing; W l is the theoretical weight of the bar; S is the tolerance; K is the error correction coefficient; X is the temperature difference influence factor.

11. The system according to claim 6, wherein The theoretical weight of the bar is determined according to the total length of the bar and the theoretical weight per meter, wherein the theoretical weight per meter is the weight per unit length corresponding to the standard area; The theoretical weight of the bar is determined according to the following formula: W l = L Act × W wpm Wherein, L Act is the measured total length of the bar; W wpm is the theoretical weight per meter of the bar; W l is the theoretical weight of the bar.

12. A device for calculating the tolerance of bars, characterized in that, Including: A memory configured to store instructions; And A processor configured to call the instructions from the memory and capable of implementing the method for determining the bar tolerance according to any one of claims 1 to 5 when executing the instructions.

13. A computer-readable storage medium having instructions stored thereon, characterized in that, When the instructions are executed by the processor, the method for determining the bar tolerance according to any one of claims 1 to 5 is implemented.

14. A computer program product, characterized in that, Including a computer program which, when executed by the processor, implements the method for determining the bar tolerance according to any one of claims 1 to 5.

Images