Bar and wire rod pass optimization design and rolling pass distribution method and device

Abstract

A method and device for optimizing design of a bar and wire rod pass and distribution of rolling passes, the method comprising: calculating total rolling passes according to input specifications of a blank and a finished product, process parameters and equipment parameters; sequentially performing preliminary design of pass parameters and recursive calculation of rolling piece size for each pass from the first pass to the last pass along the rolling direction according to the total rolling passes to obtain each pass calculation result; calculating corresponding roundness and fullness rate according to the each pass calculation result; performing reverse iteration verification and optimization from the last pass to the first pass along the direction opposite to the rolling direction according to the roundness and the fullness rate; when the roundness or the fullness rate does not meet a predetermined target range, dynamically adjusting an elongation coefficient and / or a pass axis ratio of a relevant pass, and returning to the forward design step to perform recursive calculation again; when the roundness and the fullness rate of all passes meet the target range, outputting final pass parameters of each pass and a rolling process table.

Description

Technical Field

[0001] This application relates to the field of metal pressure processing technology, and more particularly to a method and apparatus for optimizing the design of bar and wire roll pass profiles and allocating rolling passes. Background Technology

[0002] Bars and wire rods constitute a significant portion of steel products, and their dimensional accuracy, surface quality, and microstructure directly impact the processing efficiency and final product quality for downstream users. Pass design and rolling pass allocation, as core technologies in bar and wire rod rolling processes, directly determine the stability of the rolling process, finished product accuracy, roll life, and production costs.

[0003] Currently, the design methods for bar and wire rod pass profiles mainly rely on empirical formulas and manual adjustments. Traditional design processes typically employ fixed elongation factor allocation strategies (e.g., in elliptical-circular pass systems, the pass elongation factor is usually set between 1.2 and 1.4), and use classic spread formulas (such as the Usatovsky formula, Bakhchinov formula, etc.) or empirical regression models based on specific production line data to predict the rolled piece dimensions. While these methods are widely used in practice, they have the following inherent drawbacks: First, the design accuracy is low and the convergence is poor. Empirical formulas fail to fully consider the complexity of metal flow under the coupled effects of multiple factors such as steel grade, temperature, and roll wear, resulting in large prediction deviations for key parameters such as pass filling rate and workpiece roundness. This often leads to insufficient pass filling resulting in dimensional deviations, or overfilling forming surface defects such as "ears" and "folds," requiring repeated manual corrections based on engineers' experience, making the design process difficult to converge and inefficient.

[0004] Second, the pass allocation is rigid and lacks dynamic optimization. Most existing methods use preset, fixed pass extension coefficients, which cannot be adaptively adjusted according to dynamic operating conditions such as material characteristics and rolling temperature drop. This rigid allocation method can easily lead to excessive rolling load in some passes, affecting equipment safety. At the same time, it is difficult to ensure the uniformity and stability of workpiece deformation throughout the entire process, ultimately affecting the consistency of finished product dimensions.

[0005] Third, existing technical solutions have limitations. To address these issues, the industry has proposed several technical solutions, but all have shortcomings. For example, Chinese patent CN109918853A discloses a pass design method combining a relative width expansion formula, which improves applicability through iterative optimization. However, its width expansion coefficient still heavily relies on field experience data, has limited automation, and does not undergo systematic closed-loop optimization with pass allocation. Chinese patent CN117840211A proposes a roll gap setting method based on neural networks and PLC control, achieving local automation in the finishing rolling zone. However, this system is highly complex, places stringent requirements on sensors and basic automation levels, and only addresses roll gap control, without addressing global optimization of pass geometry parameters. Furthermore, special pass designs (such as double-arc elliptical passes) as described in CN102744252A, while improving local deformation, are complex to design and manufacture and are not integrated into the overall process optimization design.

[0006] In summary, the existing technology lacks a systematic method for bar and wire rod die design and pass allocation that can take into account high precision, strong adaptability, and fast convergence. This has become a key bottleneck restricting the realization of high-quality, low-cost, and intelligent development in bar and wire rod production. Summary of the Invention

[0007] The purpose of this application is to provide a method and apparatus for optimizing the design of bar and wire rod pass profiles and allocating rolling passes. This method overcomes the problems of existing technologies, such as reliance on manual experience, low design accuracy, long debugging cycles, and lack of systematic optimization. It utilizes a systematic algorithm that integrates finite element simulation, dual-index (roundness and filling rate) determination, reverse iteration, and priority adjustment to achieve automatic, accurate, and rapid collaborative optimization of pass profile parameters and pass extension coefficients, thereby improving product dimensional accuracy, surface quality, rolling stability, and production efficiency.

[0008] To achieve the above objectives, this application provides a method for optimizing the pass design and allocating rolling passes for bar and wire rods. The method includes: calculating the total number of rolling passes based on input billet and finished product specifications, process parameters, and equipment parameters; performing preliminary design of pass parameters and recursive calculation of workpiece dimensions for each pass sequentially from the first pass to the last pass along the rolling direction based on the total number of rolling passes; calculating the corresponding roundness and fill rate based on the calculation results of each pass; performing reverse iterative verification and optimization of the roundness and fill rate from the last pass to the first pass in the opposite direction to the rolling direction; dynamically adjusting the elongation coefficient and / or pass axial ratio of the relevant passes when the roundness or fill rate does not meet the predetermined target range, and returning to the forward design step to recalculate; and outputting the final pass parameters and rolling process table when the roundness and fill rate of all passes meet the target range.

[0009] In one embodiment, calculating the corresponding roundness and fill rate based on the calculation results of each pass includes: The width is obtained based on the widening model corrected by finite element simulation data; The corresponding roundness and fullness are calculated based on the width and the calculation results of each pass.

[0010] In one embodiment, the widening model includes: A widening model is constructed based on the widening formula and several introduced correction coefficients; The correction factors include at least an independent factor used to distinguish between round and elliptical roll forming processes.

[0011] In one embodiment, constructing the widening model based on the widening formula and a plurality of introduced correction coefficients includes: Obtain historical rolling data of the target production line, and establish a finite element simulation model of the bar and wire rolling process based on the historical rolling data; The simulated width data for each pass is calculated based on the finite element simulation model. The simulated width data is then compared and analyzed with the theoretical width data calculated based on the width formula to obtain the comparison results. Based on the comparison results, multiple correction coefficients are determined through regression analysis, and these correction coefficients are assigned to the widening formula to form a widening model applicable to the target production line.

[0012] In one embodiment, the reverse iterative verification and optimization includes setting roundness control targets with different numerical ranges for different rolling passes in different sections.

[0013] In one embodiment, the roundness control target with different numerical ranges includes: A control target for the roundness of the first and second passes is set for a first numerical range; a control target for the roundness of the last five passes is set for a second numerical range; wherein the absolute value of the difference between the upper and lower limits of the second numerical range is less than the absolute value of the difference between the upper and lower limits of the first numerical range.

[0014] In one embodiment, dynamically adjusting the elongation coefficient and / or bore axial ratio of relevant passes includes: Adjust the extension coefficient of the relevant pass; if the target range is not met, then adjust the hole profile ratio of the relevant pass.

[0015] In one embodiment, the roundness ratio is an indicator characterizing the deviation between the actual width of the rolled piece and the ideal circular width; the filling ratio is an indicator characterizing the degree to which the actual width of the rolled piece fills the die profile.

[0016] In one embodiment, the preliminary design of the aperture parameters includes: for circular apertures and elliptical apertures, using parametric formulas to calculate the geometric parameters of the aperture height, aperture width, roll gap, and arc radius, respectively.

[0017] In one embodiment, the preliminary design of the aperture parameters includes: when assigning an initial elongation coefficient to an elliptical aperture, the value of the initial elongation coefficient is based on the average elongation coefficient, the aperture axial ratio of the corresponding pass, and the expected roundness target, and the initial elongation coefficient increases with the increase of the aperture axial ratio and decreases with the increase of the expected roundness target.

[0018] In one embodiment, during the reverse iterative verification and optimization process, when adjusting the extension coefficient of any intermediate pass, the adjustment direction has the opposite effect on the roundness and fullness of the current pass and the previous pass.

[0019] In one embodiment, the predetermined target range includes: a roundness target range and a filling rate target range; wherein, the upper limit of the filling rate target range for the elliptical hole type is lower than the lower limit of the filling rate target range for the round hole type.

[0020] This application also provides a bar and wire product produced according to the bar and wire profile optimization design and rolling pass allocation method, wherein the product is a round bar and wire with a specification of Φ5.5mm to Φ90mm.

[0021] This application also provides a bar and wire rod pass optimization design apparatus, applicable to the aforementioned bar and wire rod pass optimization design and rolling pass allocation method, the apparatus comprising: The data processing module is used to receive input specifications of billets and finished products, process parameters, and equipment parameters; The optimization calculation module is used to perform the steps of preliminary design of pass parameters and recursive calculation of rolled piece dimensions, index calculation and reverse iterative verification and optimization. The results generation module is used to calculate and output the final pass parameters and rolling process table for each pass when the convergence conditions are met.

[0022] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the bar and wire rod pass optimization design and rolling pass allocation method.

[0023] This application also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the bar / wire profile optimization design and rolling pass allocation method.

[0024] The beneficial technical effects of this application are as follows: By integrating a wide-spread model corrected by finite element simulation, closed-loop judgment of roundness and fullness as dual indicators, and reverse iterative optimization based on priority strategy, automatic and precise collaborative design of roll pass parameters and rolling passes is achieved. This can significantly reduce the debugging time for changing specifications from several hours to about 30 minutes, and significantly improve the dimensional accuracy and surface quality of products. This method has strong versatility and is applicable to the production of bar and wire rods of all specifications from Φ5.5 to Φ90mm. By linking the calculation of rolling speed and stacking coefficient, the stability of the rolling process is ensured. Ultimately, it transforms the traditional experience-based "skill" into a replicable and efficient systems engineering method, laying the core technical foundation for the intelligent upgrading of the industry. Attached Figure Description

[0025] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic flowchart illustrating the bar and wire profile optimization design and rolling pass allocation method provided in an embodiment of this application. Figure 2 This is a schematic diagram of a finite element simulation model of the bar and wire rolling process provided in an embodiment of this application; Figure 3A and Figure 3B This is a schematic diagram of the finite element simulation analysis results of the bar and wire rolling process provided in an embodiment of this application; Figure 4 This is a schematic diagram of the module structure of the bar and wire bore optimization design device provided in an embodiment of this application; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0026] The following will describe in detail the implementation methods of this application with reference to the accompanying drawings and embodiments, so as to fully understand how this application uses technical means to solve technical problems and achieve technical effects, and to implement it accordingly. It should be noted that, as long as there is no conflict, the various embodiments and features in each embodiment of this application can be combined with each other, and the resulting technical solutions are all within the protection scope of this application.

[0027] Furthermore, the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0028] This application provides a method for optimizing the roll pass design and allocating rolling passes for bar and wire rods. The method includes: The total number of rolling passes is calculated based on the input billet and finished product specifications, process parameters and equipment parameters. Based on the total number of rolling passes, the preliminary design of the pass shape parameters and the recursive calculation of the workpiece size are performed sequentially from the first pass to the last pass along the rolling direction to obtain the calculation results of each pass. Calculate the corresponding roundness and filling rate based on the calculation results of each pass, and perform reverse iterative verification and optimization from the last pass to the first pass based on the roundness and filling rate in the direction opposite to the rolling direction. When the roundness or the filling rate does not meet the predetermined target range, the extension coefficient and / or the bore axial ratio of the relevant passes are dynamically adjusted, and the forward design step is returned to recalculate. When the roundness and filling rate of all passes meet the target range, the final pass profile parameters and rolling process table for each pass are output.

[0029] Please refer to the details. Figure 1 As shown, the bar and wire rod pass optimization design and rolling pass allocation method provided in this application can be applied using the following process: S101 parameter input and initialization: Input the cold and hot specifications of the billet and finished product, including the cold diameter of the billet (D_billet_cold), the hot diameter of the billet (D_billet_hot), and the cold diameter of the finished product. Finished product hot diameter Input the following parameters: _hot, hot billet length L_billet_hot, cold billet length L_billet_cold, and billet weight W_billet. Also input the production process parameters, including heating temperature, roughing temperature T_rm, and finishing temperature T_fm; input equipment parameters, including the maximum diameter of each mill roll, maximum rolling force, maximum torque, and maximum power; input the material's thermophysical properties, including the coefficient of thermal expansion α (taken as 0.0000125). Set the final pass rolling speed V_hot, the allowable pass deviation ΔH_allow, the allowable range of the stretching coefficient, and the average elongation coefficient μ_ave.

[0030] S102 Overall Process Parameter Calculation:

[0031] Thermal expansion correction is performed based on the input parameters: Diameter of hot finished product: _hot = × (1 + α × T_fm); Cross-sectional area of ​​the hot finished product: A_hot = π × ( _hot)² / 4; Diameter of hot billet: D_billet_hot = D_billet_cold × (1 + α × T_rm); Length of hot billet: L_billet_hot = L_billet_cold × (1 + α × T_rm); Billet volume: V_hot = A_hot × L_billet_hot; Calculate the total elongation coefficient μ_z = (D_billet_hot²) / ( _hot²); Calculate the total number of rolling passes N = log(μ_z) / log(μ_ave) and round down.

[0032] Preliminary design of S103 pass parameters and recursive calculation of rolled piece dimensions: Based on the total number of rolling passes N, the preliminary design of the pass profile parameters for each pass is carried out sequentially from the first pass to the last pass along the rolling direction.

[0033] Calculation of round hole parameters: Design rolling height H_e = Design rolling width B_e = sqrt(4×A_post[i] / π); The design hole height H_k = k_h × H_e, where k_h is the circular hole height coefficient (taken as 1.0). The design hole width is B_k = k_b × B_e, where k_b is the hole width coefficient (taken as 1.0). Design the base circle radius of the hole type R_base=H_k / 2; The outer radius of the hole is designed as R_out = k_out × R_base, where k_out is the outer radius coefficient (taken as 0.16). The design of the roll gap is S_k = sr × H_k, where sr is the roll gap coefficient (taken as 0.2). Design aperture expansion angle θ_k=arccos(1 - (ΔH_allow / R_base)).

[0034] Calculation of elliptical die parameters: Design workpiece height H_e = H_k + ΔH_allow; The design width of the rolled piece is B_e = 4 × A_post[i] / (π × H_e); The design aperture chord height coefficient a_xg=(B_e / H_e) / 2; Design the arc height of the hole shape: H_arc = H_e - S_k; Design aperture height H_k = H_arc + S_k; Design the hole width B_k=B_e; The design radius of the hole arc is R_k = (B_k² + 4×H_arc²) / (8×H_arc); Design the outer radius of the hole type R_out = k_out × R_k; Design the roll gap S_k=sr×H_k; Design the central angle of the roll gap. _k = 2 × arcsin(B_k / (2 × R_k)); Initial extension coefficient calculation: Elliptical hole type: μ[i] = (u_ave + 0.096×a_k) / η²; Circular hole type: μ[i] = (u_ave - 0.096×a_k) / η².

[0035] It is worth noting that the bar and wire rod pass optimization design and rolling pass allocation method provided in this application can be extended to the production of various materials such as copper, stainless steel, and titanium alloys, while keeping the core algorithm unchanged and only adjusting the material-related physical parameters and deformation resistance model. For example, for copper, the coefficient of thermal expansion α is adjusted to 0.0000165, and the deformation resistance model adopts the corresponding constitutive equation; for stainless steel, the high-temperature mechanical property parameters are adjusted according to the specific grade. This extension ensures the versatility of the method and makes it applicable to the production of bar and wire rods from multiple materials.

[0036] S104 Width Model Calculation and Index Determination: The width was obtained based on the widening model corrected by finite element simulation data: Model Construction: Obtain historical rolling data of the target production line and establish a finite element simulation model of the bar and wire rolling process (e.g., Figure 2 (As shown in Table 1). The simulated width data for each pass was calculated using a finite element simulation model. The simulated width data was then compared and analyzed with the theoretical width data calculated based on the width formula. Please refer to [reference needed]. Figure 3A and Figure 3B As shown, correction coefficients C1-C5 were determined through regression analysis, where C1 is the cross-sectional shape correction coefficient, C2 is the work roll diameter correction coefficient, C3 is the reduction rate correction coefficient, C4 is the elliptical roll pass correction coefficient, and C5 is the round roll pass correction coefficient.

[0037] Detailed steps for width calculation: Calculate the average height after rolling: h_ave_post[i] = A_post[i] / B_post[i]; Calculate the average width after rolling: b_ave_post[i] = A_post[i] / H_post[i]; Calculate the post-rolling length: L_post = V_hot / A_post[i]; Calculate the working diameter of the roll: D_work[i] = D_max[i] + s_gap[i] - h_ave_post[i]; Calculate the cross-sectional shape factor: δ = B_pre[i] / H_ave_pre[i]; Calculate the roll diameter coefficient: ε = H_ave_pre[i] / D_work[i]; Calculate the relative breadth index: w = 10^(-1.269×δ×C1×ε^(C2×0.556)); Calculate the reciprocal of the compression coefficient: η = h_ave_post[i] / H_ave_pre[i]; Calculate the spread factor: β = η^(-C3×w); Calculate the width of the hole: for elliptical holes, b_e[i] = C4×B_pre[i]×β, and for circular holes, b_c[i] = C5×B_pre[i]×β.

[0038] Calculation of roundness and fullness: Roundness η = b / B_post[i] (b is b_e[i] or b_c[i]); Fullness χ = b / B_k[i]; S105 Reverse Iterative Verification and Optimization: Based on the roundness and fullness ratio in the opposite direction to the rolling direction, reverse iterative verification and optimization are performed from the last pass to the first pass: Hierarchical convergence strategy: First priority: Prioritize adjusting the axial ratio a_k and elongation coefficient μ_i of the first and second passes to ensure that the roundness η satisfies [100%, 100.3%]; Second priority: Control the roundness of the last 5 passes to [100%, 100.1%], and the roundness of other passes to [100%, 100.5%]; control the filling rate of elliptical holes to [92%, 96%], and the filling rate of round holes to [96%, 100%]; Third priority: The roundness η and fullness χ of all passes meet the target interval, and the stacking coefficient f_i∈[0.98, 1.02]; Parameter adjustment rules: First adjust the elongation coefficient μ_i, then adjust the hole profile axial ratio a_k; Parameter influence relationship: Increase the shaft ratio a_k → decrease the roundness, fullness η, and χ of this pass; increase the elongation μ_i → increase the roundness, fullness η, and χ of this pass, and decrease the previous pass; check the roundness and fullness of each pass step by step from the last pass to the front; prioritize the correction of the shaft ratio and elongation coefficient of the first and second passes in the first two passes.

[0039] Shaft ratio optimization strategy: The axial ratio of the elliptical die in the first 1 to 6 passes gradually increases; after reaching a certain value, it remains basically constant; the axial ratio of the elliptical die in the last 1 to 6 passes gradually decreases. When the roundness or the filling rate does not meet the predetermined target range, the extension coefficient and / or the bore shaft ratio of the relevant pass are dynamically adjusted, and the process returns to S103 to recalculate.

[0040] S106 Result Output: When the circularity and fill rate of all passes meet the target range, calculate: Rolling speed: v_i = π×D_work[i]×n_i / 60; Continuous rolling constant: C_i = A_post[i]×v_i; Inter-rack stacking factor: f_i = C_i / C_(i-1); Output the final pass parameters and rolling process table for each pass.

[0041] In one embodiment, calculating the corresponding roundness and fullness based on the calculation results of each pass includes: obtaining the spread width based on the spread model corrected by finite element simulation data; and calculating the corresponding roundness and fullness based on the spread width and the calculation results of each pass.

[0042] Furthermore, the width expansion model includes: constructing a width expansion model based on the width expansion formula and multiple introduced correction coefficients; the correction coefficients include at least independent coefficients used to distinguish between round and elliptical roll forming processes.

[0043] The process of constructing a width expansion model based on the width expansion formula and multiple introduced correction coefficients includes: acquiring historical rolling data of the target production line; establishing a finite element simulation model of the bar and wire rolling process based on the historical rolling data; calculating the simulated width expansion data corresponding to each pass based on the finite element simulation model; comparing and analyzing the simulated width expansion data with the theoretical width expansion data calculated based on the width expansion formula to obtain comparison results; determining multiple introduced correction coefficients through regression analysis based on the comparison results; and assigning the correction coefficients to the width expansion formula to form a width expansion model applicable to the target production line.

[0044] Specifically, in practical work, historical rolling data of the target production line can be obtained first, including the pass parameters, rolling process parameters, and corresponding post-rolled workpiece dimensions for each pass. Based on this historical rolling data, a finite element simulation model of the bar and wire rod rolling process can be established, such as... Figure 2The finite element model of bar and wire rod rolling is shown. Simulated width spread data for each pass were calculated using the finite element simulation model. Specific data are shown in Table 1, which illustrates the dimensional changes in the bar and wire rod rolling process based on ABAQUS finite element simulation. The simulated width spread data was compared with the theoretical width spread data calculated based on the width spread formula to obtain the comparison results.

[0045] Table 1

[0046] Based on the comparison results, several correction coefficients were determined through regression analysis, including C1 cross-sectional shape correction coefficient, C2 work roll diameter correction coefficient, C3 reduction rate correction coefficient, C4 elliptical roll pass process correction coefficient, and C5 round roll pass process correction coefficient. These correction coefficients were assigned to the width expansion formula to form a modified width expansion model suitable for the target production line.

[0047] The specific calculation process of this expansion model includes: The relative expansion index w = 10^(-1.269×δ×C1×ε^(C2×0.556)) is calculated, and the expansion coefficient β =η^(-C3×w) is calculated. Finally, the expansion width b_e[i] = C4×B_pre[i]×β and the expansion width b_c[i] = C5×B_pre[i]×β of the elliptical hole type are obtained.

[0048] It is worth noting that in practical work, the spread model can be based on either the Smirnov spread formula or the Bakhchinov spread formula, and both can be corrected using finite element simulation data. The Smirnov spread formula is: Δb = 1.15×(Δh / 2H)×(√(R×Δh) - Δh / f), where Δb is the absolute spread, Δh is the reduction, H is the pre-roll height, R is the roll radius, and f is the coefficient of friction. The Bakhchinov spread formula is: Δb = 1.15×(Δh / 2H)×(√(R×Δh) - Δh / (2f)). Both formulas can be corrected using finite element simulation data to improve the prediction accuracy for specific production lines. Empirical spread formulas based on actual production data can also be used. By collecting a large amount of production data from a specific production line, a dedicated spread model can be established using regression analysis. When production processes, roll design, or equipment parameters change, data collection and model regression should be performed again to ensure that the model always matches the current production conditions.

[0049] In one embodiment, the reverse iterative verification and optimization includes setting roundness control targets with different numerical ranges for rolling passes in different sections. Furthermore, during the reverse iterative verification and optimization process, when adjusting the elongation coefficient of any intermediate pass, the adjustment direction has the opposite effect on the roundness and fill rate of the current pass and its preceding pass.

[0050] In another embodiment, setting roundness control targets with different numerical ranges includes: setting a control target for the roundness of the first and second passes within a first numerical range; and setting a control target for the roundness of the last five passes within a second numerical range; wherein the absolute value of the difference between the upper and lower limits of the second numerical range is less than the absolute value of the difference between the upper and lower limits of the first numerical range. For dynamically adjusting the elongation coefficient and / or bore axial ratio of relevant passes, this may include: adjusting the elongation coefficient of the relevant passes; and if the target range is not met, then further adjusting the bore axial ratio of the relevant passes.

[0051] In practical work, a graded adjustment strategy can be adopted for the reverse iterative verification and optimization process provided in this application. For rolling passes of different sections, roundness control targets with different numerical ranges are set.

[0052] Specifically, a first numerical range of control targets is set for the roundness of the first and second passes. This range is relatively wide, for example, [100%, 100.3%], to accommodate larger initial deformation fluctuations. A second numerical range of control targets is set for the roundness of the last five passes. This range is more stringent, with the absolute value of the difference between its upper and lower limits being less than the absolute value of the difference between the upper and lower limits of the first numerical range, for example, controlled within the range of [100%, 100.1%], to ensure the dimensional accuracy of the finished product.

[0053] When dynamically adjusting the elongation coefficient and / or die axial ratio of relevant passes, a specific adjustment sequence is adopted: first, adjust the elongation coefficient of the relevant passes; if the target range is still not met, then adjust the die axial ratio of the relevant passes. This adjustment sequence is based on the principle that the elongation coefficient has a more direct and significant impact on roundness and fill rate.

[0054] In the process of reverse iterative verification and optimization, when adjusting the extension coefficient of any intermediate pass, the direction of adjustment has opposite effects on the roundness and fill rate of the current pass and the previous pass. This means that increasing the extension coefficient of the current pass will lead to an increase in the roundness and fill rate of this pass, but will decrease the roundness and fill rate of the previous pass. This relationship is an important theoretical basis for the convergence of reverse iterative processes.

[0055] In practical applications, fuzzy PID controllers can be used instead of iterative algorithms. By using the errors between the actual and target values ​​of roundness ratio η and filling rate χ as inputs to the fuzzy PID controller, the controller outputs the adjustment amount for the bore diameter axial ratio a_k in real time, achieving automatic and smooth parameter adjustment. The design of the fuzzy PID controller includes defining the membership functions of the input and output, formulating fuzzy rules, and developing defuzzification methods. For example, roundness error and filling rate error can be used as input variables, and axial ratio adjustment can be used as the output variable, achieving precise control through a fuzzy inference system. The extension coefficient and axial ratio adjustment can be further improved by using adaptive and genetic algorithms to enhance convergence efficiency. The genetic algorithm treats μ_i and a_k of each pass as individuals, using the overall deviation of η and χ from the target value across all passes as the fitness function, and searches for the optimal parameter combination through selection, crossover, and mutation operations. The adaptive algorithm dynamically adjusts the search step size based on the convergence status to avoid local optima. Machine learning algorithms can also be introduced during the reverse iteration process, training a prediction model using historical optimization data to quickly estimate the optimal parameter range and significantly reduce the number of iterations. Algorithms such as neural networks and support vector machines can be used to establish a nonlinear mapping relationship between parameters and optimization objectives, thereby achieving intelligent optimization. This application does not impose further limitations, and those skilled in the art can choose the appropriate settings according to actual needs.

[0056] In one embodiment, the roundness ratio is an index characterizing the deviation between the actual width of the rolled piece and the ideal circular width; the filling ratio is an index characterizing the degree to which the actual width of the rolled piece fills the pass profile. The preliminary design of the pass parameters includes: for circular and elliptical passes, calculating their pass height, pass width, roll gap, and arc radius geometric parameters using parametric formulas. Further, the preliminary design of the pass parameters includes: when assigning an initial elongation coefficient to an elliptical pass, the value of the initial elongation coefficient is based on the average elongation coefficient, the pass axial ratio of the corresponding pass, and the expected roundness target; the initial elongation coefficient increases with the increase of the pass axial ratio and decreases with the increase of the expected roundness target.

[0057] In practical applications, this application uses parametric formulas to calculate the geometric parameters of the hole height, hole width, roll gap, and arc radius for both circular and elliptical hole types.

[0058] For a circular pass, the designed workpiece height H_e and the designed workpiece width B_e are equal, both being sqrt(4×A_post[i] / π). The designed pass height H_k = k_h × H_e, where k_h is the circular pass height coefficient, typically taken as 1.0. The designed pass width B_k = k_b × B_e, where k_b is the circular pass width coefficient, typically taken as 1.0. The designed pass base circle radius R_base = H_k / 2. The designed pass outer circle radius R_out = k_out × R_base, where k_out is the outer circle radius coefficient, typically taken as 0.16. The designed pass roll gap S_k = sr × H_k, where sr is the roll gap coefficient, typically taken as 0.2. The designed pass expansion angle θ_k = arccos(1 - (ΔH_allow / R_base)).

[0059] For an elliptical pass, the design workpiece height H_e = H_k + ΔH_allow. The design workpiece width B_e = 4×A_post[i] / (π×H_e). The design pass chord height coefficient a_xg = (B_e / H_e) / 2. The design pass arc height H_arc = H_e - S_k. The design pass height H_k = H_arc + S_k. The design pass width B_k = B_e. The design pass arc radius R_k = (B_k² + 4×H_arc²) / (8×H_arc). The design pass outer radius R_out = k_out × R_k. The design pass roll gap S_k = sr × H_k. The design pass central angle. _k = 2×arcsin(B_k / (2×R_k)).

[0060] When assigning an initial elongation factor to an elliptical pass, the value of the initial elongation factor is based on the average elongation factor, the pass axial ratio of the corresponding pass, and the expected roundness target. The initial elongation factor increases with the increase of the pass axial ratio and decreases with the increase of the expected roundness target. This relationship is specifically reflected by the formula μ[i] = (u_ave + 0.096×a_k) / η².

[0061] In practical applications, the aforementioned die type can be extended to a three-roll die system, maintaining consistency in parameter recursion and decision-making logic. The parameterized design formula for the three-roll die needs corresponding adjustments, but the core processes of width calculation, dual-index decision-making, and reverse iterative optimization remain unchanged. For example, the geometric parameter calculation for the three-roll die needs to consider the arrangement angles and radii of the three rolls, but the initial extension coefficient allocation and optimization strategy are similar to those of the elliptical-circular die system. Alternatively, the elliptical die can be replaced with a square die or a flat elliptical die, maintaining the roundness η and filling rate χ error control methods. The geometric parameter calculation formulas for different die types need corresponding adjustments, but the closed-loop control logic based on dual indices remains unchanged. For example, the design of a square die needs to consider side straightness and corner radius, while the flat elliptical die needs to adjust the axial ratio and contour curve, but the calculation and decision-making methods for roundness and filling rate remain consistent.

[0062] In one embodiment, the predetermined target range includes: a roundness target range and a filling rate target range; wherein, the upper limit of the filling rate target range for the elliptical hole type is lower than the lower limit of the filling rate target range for the round hole type.

[0063] In practice, the target range includes the roundness target range and the filling rate target range. The upper limit of the filling rate target range for elliptical holes is lower than the lower limit of the filling rate target range for round holes.

[0064] Specifically, the target range for the filling rate of the elliptical orifice is set at [92%, 96%], while the target range for the filling rate of the circular orifice is set at [96%, 100%]. This differentiated setting is determined based on the different effects of different orifice shapes on metal flow characteristics. In the elliptical orifice, an excessively high filling rate can easily lead to metal overflow and the formation of lugs, so its upper limit needs to be controlled; while in the circular orifice, incomplete filling will lead to dimensional deviations, so a higher lower limit for the filling rate needs to be ensured.

[0065] The roundness target range is set using a tiered strategy: the roundness target for the first and second passes is set in the first numerical range, [100%, 100.3%]; the roundness target for the last five passes is set in the second numerical range, [100%, 100.1%]; and the roundness for other intermediate passes is controlled within the range of [100%, 100.5%]. This tiered setting ensures different precision requirements at the beginning and end of the rolling process, with the earlier passes primarily ensuring deformation stability and the later passes primarily ensuring finished product precision.

[0066] This application also provides a bar and wire product produced according to the bar and wire profile optimization design and rolling pass allocation method, wherein the product is a round bar and wire with a specification of Φ5.5mm to Φ90mm.

[0067] This bar and wire product is rolled using the aforementioned high-precision, automated pass design and pass allocation method, resulting in excellent dimensional accuracy and surface quality. The roundness deviation is controlled within 0.1%, dimensional tolerances meet Class C accuracy requirements, and the surface is free of defects such as burrs and folds, exhibiting a uniform and dense metallographic structure. Overall, the production process parameters are determined according to the aforementioned optimization method, including pass dimensions, rolling speed, and temperature regime for each pass, ensuring the stability of the entire rolling process and the consistency of the product. Products manufactured using this method can be used for deep processing in fields such as construction, machinery manufacturing, and automotive parts.

[0068] This application also provides a bar and wire rod pass optimization design apparatus, applicable to the aforementioned bar and wire rod pass optimization design and rolling pass allocation method, the apparatus comprising: The data processing module is used to receive input specifications of billets and finished products, process parameters, and equipment parameters; The optimization calculation module is used to perform the steps of preliminary design of pass parameters and recursive calculation of rolled piece dimensions, index calculation and reverse iterative verification and optimization. The results generation module is used to calculate and output the final pass parameters and rolling process table for each pass when the convergence conditions are met.

[0069] For details, please refer to [link / reference]. Figure 4 As shown, the data processing module receives input billet and finished product specifications, process parameters, and equipment parameters. This module includes a data interface unit, a data verification unit, and a data storage unit to ensure the integrity and accuracy of the input data. The optimization calculation module performs the steps of preliminary design of pass parameters, recursive calculation of rolled piece dimensions, index calculation, and reverse iterative verification and optimization. This module includes a parameter initialization unit, a forward calculation unit, a width expansion model calculation unit, an index determination unit, and a reverse iterative optimization unit. Each unit executes its corresponding calculation task according to the process flow of the method described above. The result generation module calculates and outputs the final pass parameters and rolling process table for each pass when the convergence condition is met. This module includes a convergence determination unit, a process parameter calculation unit, and a report generation unit. The output results include a pass size table, a rolling speed table, and a continuous rolling constant table.

[0070] The beneficial technical effects of this application are as follows: By integrating a wide-spread model corrected by finite element simulation, closed-loop judgment of roundness and fullness as dual indicators, and reverse iterative optimization based on priority strategy, automatic and precise collaborative design of roll pass parameters and rolling passes is achieved. This can significantly reduce the debugging time for changing specifications from several hours to about 30 minutes, and significantly improve the dimensional accuracy and surface quality of products. This method has strong versatility and is applicable to the production of bar and wire rods of all specifications from Φ5.5 to Φ90mm. By linking the calculation of rolling speed and stacking coefficient, the stability of the rolling process is ensured. Ultimately, it transforms the traditional experience-based "skill" into a replicable and efficient systems engineering method, laying the core technical foundation for the intelligent upgrading of the industry.

[0071] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method.

[0072] This application also provides a computer-readable storage medium storing a computer program that performs the above-described methods.

[0073] This application also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described method.

[0074] like Figure 5 As shown, the electronic device 600 may also include: a communication module 110, an input unit 120, an audio processor 130, a display 160, and a power supply 170. It is worth noting that the electronic device 600 does not necessarily need to include these components. Figure 5 All components shown; in addition, the electronic device 600 may also include Figure 5 For components not shown, please refer to existing technology.

[0075] like Figure 5 As shown, the central processing unit 100, sometimes also referred to as a controller or operating control, may include a microprocessor or other processor device and / or logic device. The central processing unit 100 receives inputs and controls the operation of various components of the electronic device 600.

[0076] The memory 140 may be, for example, one or more of a cache, flash memory, hard drive, removable media, volatile memory, non-volatile memory, or other suitable devices. It may store the aforementioned failure-related information, and also store a program for executing that information. The central processing unit 100 may execute the program stored in the memory 140 to perform information storage or processing, etc.

[0077] Input unit 120 provides input to central processing unit 100. Input unit 120 may be, for example, a keypad or touch input device. Power supply 170 provides power to electronic device 600. Display 160 displays images and text. Display may be, for example, an LCD display, but is not limited thereto.

[0078] The memory 140 can be a solid-state memory, such as a read-only memory (ROM), random access memory (RAM), a SIM card, etc. It can also be a memory that retains information even when power is off, can be selectively erased, and contains more data; examples of this type of memory are sometimes referred to as EPROMs. The memory 140 can also be some other type of device. The memory 140 includes a buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application / function storage unit 142 for storing application programs and function programs or processes for executing the operation of the electronic device 600 via the central processing unit 100.

[0079] The memory 140 may also include a data storage unit (data 143) for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit (driver 144) of the memory 140 may include various drivers for the electronic device's communication functions and / or for performing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0080] The communication module 110 is a transmitter / receiver that transmits and receives signals via the antenna 111. The communication module (transmitter / receiver) 110 is coupled to the central processing unit 100 to provide input signals and receive output signals, which can be the same as in a conventional mobile communication terminal.

[0081] Based on different communication technologies, multiple communication modules 110 can be configured in the same electronic device, such as cellular network modules, Bluetooth modules, and / or wireless LAN modules. The communication module (transmitter / receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide audio output via the speaker 131 and receive audio input from the microphone 132, thereby enabling typical telecommunications functions. The audio processor 130 may include any suitable buffer, decoder, amplifier, etc. Additionally, the audio processor 130 is coupled to a central processing unit 100, enabling on-device recording via the microphone 132 and on-device playback of stored audio via the speaker 131.

[0082] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0083] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0084] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0085] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0086] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above descriptions are merely specific embodiments of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for optimizing the roll pass design and allocating rolling passes for bar and wire rods, characterized in that, The method includes: The total number of rolling passes is calculated based on the input billet and finished product specifications, process parameters and equipment parameters. Based on the total number of rolling passes, the preliminary design of the pass shape parameters and the recursive calculation of the workpiece size are performed sequentially from the first pass to the last pass along the rolling direction to obtain the calculation results of each pass. Calculate the corresponding roundness and filling rate based on the calculation results of each pass, and perform reverse iterative verification and optimization from the last pass to the first pass based on the roundness and filling rate in the direction opposite to the rolling direction. When the roundness or the filling rate does not meet the predetermined target range, the extension coefficient and / or the bore axial ratio of the relevant passes are dynamically adjusted, and the forward design step is returned to recalculate. When the roundness and filling rate of all passes meet the target range, the final pass profile parameters and rolling process table for each pass are output.

2. The method for optimizing the roll pass design and allocating rolling passes for bar and wire rods according to claim 1, characterized in that, The roundness and fill rate are calculated based on the results of each pass, including: The width is obtained based on the widening model corrected by finite element simulation data; The corresponding roundness and fullness are calculated based on the width and the calculation results of each pass.

3. The method for optimizing the pass design and allocating rolling passes for bar and wire rods according to claim 2, characterized in that, The widening model includes: A widening model is constructed based on the widening formula and several introduced correction coefficients; The correction factors include at least an independent factor used to distinguish between round and elliptical roll forming processes.

4. The method for optimizing the pass design and allocating rolling passes for bar and wire rods according to claim 3, characterized in that, The widening model is constructed based on the widening formula and several introduced correction coefficients, including: Obtain historical rolling data of the target production line, and establish a finite element simulation model of the bar and wire rolling process based on the historical rolling data; The simulated width data for each pass is calculated based on the finite element simulation model. The simulated width data is then compared and analyzed with the theoretical width data calculated based on the width formula to obtain the comparison results. Based on the comparison results, multiple correction coefficients are determined through regression analysis, and these correction coefficients are assigned to the widening formula to form a widening model applicable to the target production line.

5. The method for optimizing the pass design and rolling pass allocation of bar and wire rods according to claim 1, characterized in that, The reverse iterative verification and optimization include setting roundness control targets with different numerical ranges for different rolling passes in different sections.

6. The method for optimizing the pass design and rolling pass allocation of bar and wire rods according to claim 5, characterized in that, Roundness control targets with different numerical ranges include: A control target for the roundness of the first and second passes is set for a first numerical range; a control target for the roundness of the last five passes is set for a second numerical range; wherein the absolute value of the difference between the upper and lower limits of the second numerical range is less than the absolute value of the difference between the upper and lower limits of the first numerical range.

7. The method for optimizing the pass design and rolling pass allocation of bar and wire rods according to claim 1, characterized in that, Dynamically adjusting the elongation coefficient and / or bore axial ratio of relevant passes includes: Adjust the extension coefficient of the relevant pass; if the target range is not met, then adjust the hole profile ratio of the relevant pass.

8. The method for optimizing the roll pass design and allocating rolling passes for bar and wire rods according to claim 1, characterized in that, The roundness ratio is an index characterizing the deviation between the actual width of the rolled piece and the ideal circular width; the filling ratio is an index characterizing the degree to which the actual width of the rolled piece fills the die profile.

9. The method for optimizing the roll pass design and allocating rolling passes for bar and wire rods according to claim 1, characterized in that, The preliminary design of the die parameters includes: for circular and elliptical die types, the geometric parameters of the die height, die width, roll gap, and arc radius are calculated using parametric formulas.

10. The method for optimizing the pass design and rolling pass allocation of bar and wire rods according to claim 1 or 9, characterized in that, The preliminary design of the aperture parameters includes: when assigning an initial extension coefficient to an elliptical aperture, the value of the initial extension coefficient is based on the average extension coefficient, the aperture axis ratio of the corresponding pass, and the expected roundness target. The initial extension coefficient increases with the increase of the aperture axis ratio and decreases with the increase of the expected roundness target.

11. The method for optimizing the pass design and rolling pass allocation of bar and wire rods according to claim 1, characterized in that, During the reverse iterative verification and optimization process, when adjusting the extension coefficient of any intermediate pass, the direction of adjustment has the opposite effect on the roundness and filling rate of the current pass and the previous pass.

12. The method for optimizing the pass design and rolling pass allocation of bar and wire rods according to claim 1, characterized in that, The predetermined target ranges include: the roundness target range and the filling rate target range; wherein, the upper limit of the filling rate target range for the elliptical hole type is lower than the lower limit of the filling rate target range for the round hole type.

13. A bar and wire rod product produced by the bar and wire rod pass optimization design and rolling pass allocation method according to any one of claims 1 to 12, characterized in that, The product is a round bar wire with a diameter of Φ5.5mm to Φ90mm.

14. A device for optimizing the pass design of bar and wire rods, applicable to the bar and wire rod pass optimization design and rolling pass allocation method according to any one of claims 1 to 12, characterized in that, The device includes: The data processing module is used to receive input specifications of billets and finished products, process parameters, and equipment parameters; The optimization calculation module is used to perform the steps of preliminary design of pass parameters and recursive calculation of rolled piece dimensions, index calculation and reverse iterative verification and optimization. The results generation module is used to calculate and output the final pass parameters and rolling process table for each pass when the convergence conditions are met.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 12.

16. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 12.

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