An intelligent parameter adaptive control system and control method for a forging hydraulic press

Abstract

This invention discloses an intelligent parameter adaptive control system and method for a forging hydraulic press. The method includes: acquiring the model of the forging; generating an initial forging parameter variation curve based on the model of the forging; controlling the hydraulic press to forge the test forging using the initial forging parameter variation curve, collecting the actual forging progress of the test forging, and adjusting the forging parameters; updating the initial forging parameter variation curve based on the adjusted forging parameters to determine the forging parameter variation curve; controlling the hydraulic press to forge the forging using the forging parameter variation curve; calculating the parameter difference score based on the real-time operating parameter set of the forging acquisition time frame, and updating the forging parameters corresponding to the forging acquisition time frame using the parameter difference score. This invention automatically adjusts forging parameters by collecting real-time forging data during the forging process, thereby improving forging production efficiency.

Description

Technical Field

[0001] This application relates to the field of forging hydraulic press control technology, and more specifically, to an intelligent parameter adaptive control system and control method for a forging hydraulic press. Background Technology

[0002] Forging hydraulic presses, as important metal forming equipment, play a crucial role in many fields such as aerospace, automotive manufacturing, and machinery manufacturing. Traditional forging hydraulic presses mainly rely on manual operation and preset parameters, making it difficult to adapt to various changes during the forging process in real time, resulting in the following problems:

[0003] Poor parameter adaptability: During the forging process, factors such as material resistance and temperature changes can cause the preset parameters to not match the actual requirements, which can easily lead to equipment failure (such as "stalling") or forging quality defects.

[0004] Low level of intelligence: Existing control systems lack the ability to dynamically close-loop regulate multiple variables (pressure, temperature, displacement, etc.), making it difficult to achieve real-time optimization of process parameters.

[0005] Insufficient efficiency and precision: Manual parameter adjustment is time-consuming and cannot adapt to the process requirements of different materials (such as titanium alloys and high-temperature alloys) or complex forgings.

[0006] Therefore, the existing technology has defects and urgently needs improvement. Summary of the Invention

[0007] In view of the above problems, the purpose of this invention is to provide an intelligent parameter adaptive control system and control method for a forging hydraulic press, which automatically adjusts forging parameters by collecting real-time forging data during the forging process, thereby improving forging production efficiency.

[0008] The first aspect of this invention provides an intelligent parameter adaptive control method for a forging hydraulic press, comprising:

[0009] Obtain the model number of the forging;

[0010] Generate an initial forging parameter variation curve based on the model of the forging;

[0011] The hydraulic press is controlled to forge the test forging by controlling the initial forging parameter variation curve, the actual forging progress of the test forging is collected, and the forging parameters are adjusted accordingly.

[0012] The initial forging parameter variation curve is updated based on the adjusted forging parameters to determine the forging parameter variation curve.

[0013] The hydraulic press is controlled to forge the workpiece by controlling the forging parameter variation curve;

[0014] According to the forging acquisition time frame tj Real-time running parameter set P (tj) Calculate the score Q of the parameter difference. (tj) Q is obtained by analyzing the parameter differences. (tj) Forging acquisition time frame t j The corresponding forging parameters are updated; the real-time operating parameter set P (tj) Including hydraulic press displacement distance P a(tj) and hydraulic pressure P b(tj) .

[0015] In this scheme, the step of controlling the hydraulic press to forge the test forging using the initial forging parameter variation curve, collecting the actual forging progress of the test forging, and adjusting the forging parameters includes:

[0016] Based on the model of the forging, the database is filtered, and the historical forging parameter variation curves of the same model of forging are determined as the initial forging parameter variation curves of the forging.

[0017] The test forging is forged based on the initial forging parameter variation curve;

[0018] Multiple test acquisition time frames t are determined based on the forging start time and the preset forging progress change interval. i ;

[0019] Obtain test acquisition time frame t i The actual forging progress of the test forgings;

[0020] The test acquisition time frame t is calculated based on the actual forging progress and the corresponding simulated forging progress. i The correction factor M 1(i) ;

[0021] According to the correction factor M 1(i) For the test acquisition time frame t i The forging parameters were adjusted.

[0022] This plan also includes:

[0023] When forging parameters are adjusted, the test forging is continued to be forged using the adjusted forging parameters;

[0024] When the actual forging progress of the test forging meets the corresponding simulated forging progress, the forging parameters are adjusted to the next acquisition time frame t. i+1 The corresponding forging parameters.

[0025] In this scheme, updating the initial forging parameter variation curve based on the adjusted forging parameters to determine the forging parameter variation curve includes:

[0026] The updated initial forging parameter variation curve corresponding to test forging n is determined as the first forging parameter variation curve;

[0027] The correction score is calculated based on the correction factors before and after the adjustment.

[0028] P i =α×|M 1(i)n -M 1(i)n-1 |;

[0029]

[0030] Among them, P n To test the corrected score of forging n, P i For testing forging n at test acquisition time frame t i Sub-correction score, M 1(i)n For testing forging n at test acquisition time frame t i The correction factor, M 1(i)n-1 For the previous test forging n-1 at test acquisition time frame t i The correction factor, α is the correction coefficient;

[0031] When the corrected score is greater than the preset corrected score threshold, the next test forging is forged using the first forging parameter change curve, the correction factor of the next test forging is calculated, and the first forging parameter change curve is updated.

[0032] When the corrected score is less than or equal to the preset corrected score threshold, the first forging parameter change curve is determined as the forging parameter change curve.

[0033] In this scheme, the step of collecting data based on the forging time frame t... j Real-time running parameter set P (tj) Calculate the score Q of the parameter difference. (tj) Q is obtained by analyzing the parameter differences. (tj) Forging acquisition time frame t j The corresponding forging parameters are updated, including:

[0034] Multiple forging acquisition time frames t are determined based on the forging start time and the preset forging progress change interval. j ;

[0035] Based on forging acquisition time frame t j Collect the real-time operating parameter set P of the hydraulic press (tj) ;

[0036] The real-time operating parameter set P (tj) The real-time operating parameters are compared with the corresponding simulated operating parameters to determine the parameter differences; the parameter differences include the hydraulic press displacement distance difference Q. a(tj)and hydraulic pressure difference Q b(tj) ;

[0037] Calculate the parameter difference score Q based on the parameter difference. (tj) ;

[0038] Q (tj) =k1×Q a(tj) +k2×Q b(tj) ;

[0039] Where k1 and k2 are both correction coefficients;

[0040] When the parameter difference is divided into Q (tj) When the difference exceeds the preset parameter difference threshold, the parameter difference is compared with the maximum and minimum values ​​of the corresponding preset parameter adjustment range to determine the first score of the parameter difference.

[0041] The first scores of all parameter differences are summed to determine the second score;

[0042] No adjustments are made when the second score is 0;

[0043] When the second score is not 0, according to the real-time running parameter set P (tj) Calculate the correction factor M 1(j) And through the correction factor M 1(j) Forging acquisition time frame t j The corresponding forging parameters are updated.

[0044] This plan also includes:

[0045] When the second score is greater than 2, an anomaly is recorded;

[0046] When the number of abnormal records during the forging process of the same forging part exceeds the preset abnormal number threshold, the hydraulic operation is stopped and an early warning is issued.

[0047] In this scheme, the step of comparing the parameter difference with the maximum and minimum values ​​of the corresponding preset parameter adjustment ranges to determine the first score of the parameter difference includes:

[0048] When the parameter difference is less than the minimum value of the corresponding preset parameter adjustment range, the first score of the parameter difference is determined to be 0;

[0049] When the parameter difference is between the maximum and minimum values ​​of the corresponding preset parameter adjustment range, the first score of the parameter difference is determined to be 1;

[0050] When the parameter difference is greater than the maximum value of the corresponding preset parameter adjustment range, the first score of the parameter difference is determined to be 2.

[0051] This plan also includes:

[0052] Based on the previous forging acquisition time frame t j-1 and forging acquisition time frame t j Simulated forging was performed using the forging progress variation values ​​to determine the forging acquisition time frame t. j Predicted acquisition time frame t corresponding to forging progress q ;

[0053] Calculate the predicted acquisition time frame t q and forging acquisition time frame t j Time difference;

[0054] When the time difference is less than a preset time difference threshold, the predicted acquisition time frame t is used. q Forging acquisition time frame t j Update.

[0055] This invention discloses an intelligent parameter adaptive control system and method for a forging hydraulic press. The method includes: acquiring the model of the forging; generating an initial forging parameter variation curve based on the model of the forging; controlling the hydraulic press to forge the test forging using the initial forging parameter variation curve, collecting the actual forging progress of the test forging, and adjusting the forging parameters; updating the initial forging parameter variation curve based on the adjusted forging parameters to determine the forging parameter variation curve; controlling the hydraulic press to forge the forging using the forging parameter variation curve; calculating the parameter difference score based on the real-time operating parameter set of the forging acquisition time frame, and updating the forging parameters corresponding to the forging acquisition time frame using the parameter difference score. This invention automatically adjusts forging parameters by collecting real-time forging data during the forging process, thereby improving forging production efficiency. Attached Figure Description

[0056] Figure 1 A flowchart of an intelligent parameter adaptive control method for a forging hydraulic press provided by the present invention is shown;

[0057] Figure 2 A flowchart of the method for adjusting forging parameters by testing forgings provided by the present invention is shown;

[0058] Figure 3 A flowchart of the method for determining the forging parameter variation curve provided by the present invention is shown. Detailed Implementation

[0059] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0060] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0061] Figure 1 A flowchart of an intelligent parameter adaptive control method for a forging hydraulic press provided by the present invention is shown.

[0062] like Figure 1 As shown, this invention discloses an intelligent parameter adaptive control method for a forging hydraulic press, comprising:

[0063] S102, obtain the model number of the forging;

[0064] S104, Generates the initial forging parameter variation curve based on the forging model;

[0065] S106, the hydraulic press is controlled to forge the test forging by the initial forging parameter change curve, the actual forging progress of the test forging is collected, and the forging parameters are adjusted accordingly;

[0066] S108, Update the initial forging parameter variation curve based on the adjusted forging parameters, and determine the forging parameter variation curve;

[0067] S110, the hydraulic press is controlled to forge the workpiece by controlling the forging parameter variation curve;

[0068] S112, based on the forging acquisition time frame t j Real-time running parameter set P (tj) Calculate the score Q of the parameter difference. (tj) Q is obtained by analyzing the parameter differences. (tj) Forging acquisition time frame t j Update the corresponding forging parameters; real-time running parameter set P (tj) Including hydraulic press displacement distance P a(tj) and hydraulic pressure P b(tj) .

[0069] According to an embodiment of the present invention, the system extracts and identifies the model of the forging from the forging request data input by the user. Based on the model of the forging, it filters the historical forging parameter change curves of forgings of the same model from the database to determine the initial forging parameter change curve of the current forging. Multiple test acquisition time frames t are determined based on the forging start time and a preset forging progress change interval. i According to the test acquisition time frame t i The actual forging progress is compared with the corresponding simulated forging progress, and the correction factor M is calculated. 1(i) For the test acquisition time frame ti The forging parameters are adjusted, and the initial forging parameter variation curve is updated based on the adjusted parameters. The updated initial forging parameter variation curve is then determined as the first forging parameter variation curve, and a correction score is calculated. When the correction score exceeds a preset correction score threshold, the first forging parameter variation curve is determined as the final forging parameter variation curve. The speed of the hydraulic motor is adjusted according to the forging parameter variation curve to perform batch forging of the forgings. During the forging process, the data is collected based on the forging acquisition time frame t. j Collect the real-time operating parameter set P of the hydraulic press (tj) According to the real-time operating parameter set P (tj) Adjust the curve of forging parameter variation.

[0070] The real-time running parameter set P (tj) The real-time operating parameters are compared with the corresponding simulated operating parameters to determine the parameter difference and calculate the parameter difference score. When the parameter difference score is greater than the system's preset parameter difference threshold, a second score is calculated based on the parameter difference. When the second score is not 0, the real-time operating parameter set P is used. (tj) Calculate the correction factor M 1(j) And by adjusting factor M 1(j) Forging acquisition time frame t j The corresponding forging parameters are updated.

[0071] Figure 2 A flowchart of the method for adjusting forging parameters by testing forgings provided by the present invention is shown.

[0072] like Figure 2 As shown, according to an embodiment of the present invention, the hydraulic press is controlled to forge the test forging by controlling the initial forging parameter variation curve, the actual forging progress of the test forging is collected, and the forging parameters are adjusted, including:

[0073] S202, based on the model of the forging, filter in the database and determine the historical forging parameter change curves of the same model of forging as the initial forging parameter change curve of the forging;

[0074] S204, the test forging is forged based on the initial forging parameter variation curve;

[0075] S206, Multiple test acquisition time frames t are determined based on the forging start time and the preset forging progress change interval. i ;

[0076] S208, Obtain the test acquisition time frame t i The actual forging progress of the test forgings;

[0077] S210, calculate the test acquisition time frame t based on the actual forging progress and the corresponding simulated forging progress. i The correction factor M 1(i) ;

[0078] S212, according to the correction factor M 1(i) For the test acquisition time frame t i The forging parameters were adjusted.

[0079] It should be noted that by collecting various forging data generated during the forging process of the hydraulic press, the system determines the interrelationships between parameters such as forging progress, forging pressure, and hydraulic motor speed based on the forging start time and duration. Historical forging parameter variation curves between forging progress and hydraulic motor speed are plotted and stored in the database. When forging a workpiece using a hydraulic press, the system identifies the input forging model, obtains an image of the forging's appearance using a detection device, and filters historical forging parameter variation curves of the same model from the database to determine the initial forging parameter variation curve for the current forging. If multiple historical forging parameter variation curves of the same model exist, the curve closest to the current time is selected as the initial forging parameter variation curve. If no historical forging parameter variation curves of the same model exist, the system analyzes historical forging parameter variation curves of forgings with the same or similar materials and specifications from the database, performs simulated forging, and generates the initial forging parameter variation curve for the current forging.

[0080] The preset forging progress change interval is set by those skilled in the art according to actual needs, and the simulated forging progress at each preset forging progress change interval corresponds to a test acquisition time frame.

[0081] Due to factors such as hydraulic press leakage, hydraulic oil type, viscosity range, and operating temperature, there is a certain energy loss, which affects the test acquisition time frame t. i The actual forging progress differs from the corresponding simulated forging progress. A correction factor M is calculated to address this discrepancy. 1(i) For the test acquisition time frame t i The forging parameters are adjusted. The actual forging progress can be determined by monitoring the hydraulic press's movement distance and analyzing changes in the forging within the detected images, with a correction factor M. 1(i) The ratio of the simulated forging progress to the actual forging progress is given by the correction factor M. 1(i) With test acquisition time frame t i The original forging parameters are multiplied to determine the adjusted forging parameters. The forging progress can be represented by the displacement distance of the hydraulic press.

[0082] According to an embodiment of the present invention, it further includes:

[0083] When forging parameters are adjusted, the test forging is continued to be forged using the adjusted forging parameters;

[0084] When the actual forging progress of the test forging meets the corresponding simulated forging progress, the forging parameters will be adjusted to the next acquisition time frame t. i+1 The corresponding forging parameters.

[0085] It should be noted that when the forging is in the current acquisition time frame t i When the actual forging progress does not meet the corresponding simulated forging progress, if the forging parameters are directly adjusted to the next acquisition time frame t... i+1 Incorrect forging parameters may lead to abnormalities in the forging process, such as the actual forging progress in each subsequent acquisition time frame not matching the corresponding simulated forging progress. The test forging is then continued using the adjusted forging parameters. When the actual forging progress of the test forging meets the corresponding simulated forging progress, the forging parameters are adjusted to the next acquisition time frame t. i+1 The corresponding forging parameters. Simultaneously, based on the time frame when the actual forging progress of the test forging meets the corresponding simulated forging progress and the preset forging progress change interval, the next acquisition time frame t is determined. i+1 Update.

[0086] Figure 3 A flowchart of the method for determining the forging parameter variation curve provided by the present invention is shown.

[0087] like Figure 3 As shown, according to an embodiment of the present invention, the initial forging parameter variation curve is updated based on the adjusted forging parameters to determine the forging parameter variation curve, including:

[0088] S302, the updated initial forging parameter change curve corresponding to the test forging n is determined as the first forging parameter change curve;

[0089] S304, calculate the correction score based on the correction factors before and after adjustment;

[0090] P i =α×|M 1(i)n -M 1(i)n-1 |;

[0091]

[0092] Among them, P n To test the corrected score of forging n, P i For testing forging n at test acquisition time frame t i Sub-correction score, M 1(i)nFor testing forging n at test acquisition time frame t i The correction factor, M 1(i)n-1 For the previous test forging n-1 at test acquisition time frame t i The correction factor, α is the correction coefficient;

[0093] S306, when the correction score is greater than the preset correction score threshold, the next test forging is forged according to the first forging parameter change curve, the correction factor of the next test forging is calculated, and the first forging parameter change curve is updated.

[0094] S308, when the corrected score is less than or equal to the preset corrected score threshold, the first forging parameter change curve is determined as the forging parameter change curve.

[0095] It should be noted that after the forging of test forging n is completed, the sub-correction score of test forging n is calculated sequentially for each test acquisition time frame. The sub-correction scores of all test acquisition time frames are then summed to determine the correction score P of test forging n. n By adjusting the score P n The fluctuation of the initial forging parameter variation curves corresponding to test forging n and test forging n-1 can be determined. The corrected score is compared with a preset corrected score threshold. When the corrected score is less than or equal to the preset corrected score threshold, the adjustment range of the initial forging parameter variation curve corresponding to test forging n is small to meet the system's preset requirements, and this is determined as the final forging parameter variation curve. Otherwise, based on the initial forging parameter variation curve corresponding to test forging n, test forging n+1 continues to be forged until the corrected score of the test forging is less than or equal to the preset corrected score threshold. The preset corrected score threshold is set by those skilled in the art according to actual needs. Furthermore, those skilled in the art can limit the number of test forgings. If, after all test forgings are completed, the corrected score is still greater than the preset corrected score threshold, a pop-up reminder is issued, prompting relevant personnel to maintain the hydraulic press.

[0096] According to an embodiment of the present invention, based on the forging acquisition time frame t j Real-time running parameter set P (tj) Calculate the score Q of the parameter difference. (tj) Q is obtained by analyzing the parameter differences. (tj) Forging acquisition time frame t j The corresponding forging parameters are updated, including:

[0097] Multiple forging acquisition time frames t are determined based on the forging start time and the preset forging progress change interval. j ;

[0098] Based on forging acquisition time frame t jCollect the real-time operating parameter set P of the hydraulic press (tj) ;

[0099] The real-time running parameter set P (tj) The real-time operating parameters are compared with the corresponding simulated operating parameters to determine the parameter differences; the parameter differences include the hydraulic press displacement distance difference Q. a(tj) and hydraulic pressure difference Q b(tj) ;

[0100] Calculate the parameter difference score Q based on the parameter difference. (tj) ;

[0101] Q (tj) =k1×Q a(tj) +k2×Q b(tj) ;

[0102] Where k1 and k2 are both correction coefficients;

[0103] When the parameter difference is divided into Q (tj) When the difference exceeds the preset parameter difference threshold, the parameter difference is compared with the maximum and minimum values ​​of the corresponding preset parameter adjustment range to determine the first score of the parameter difference.

[0104] The first scores of all parameter differences are summed to determine the second score;

[0105] No adjustments are made when the second score is 0;

[0106] When the second score is not 0, according to the real-time running parameter set P (tj) Calculate the correction factor M 1(j) And by adjusting factor M 1(j) Forging acquisition time frame t j The corresponding forging parameters are updated.

[0107] It should be noted that the real-time operating parameter set P of the hydraulic press (tj) The real-time operating parameters include the forging acquisition time frame t. j hydraulic press displacement distance P a(tj) and hydraulic pressure P b(tj) Calculate the displacement distance P of the hydraulic press respectively. a(tj) and hydraulic pressure P b(tj) Determine the hydraulic press displacement distance difference Q by comparing the parameter differences with the corresponding simulated operating parameters (simulated hydraulic press displacement distance and simulated hydraulic pressure). a(tj) and hydraulic pressure difference Q b(tj) .

[0108] The values ​​of the correction coefficients k1 and k2 are set by the system.

[0109] The score Q is calculated by measuring the parameter difference. (tj) It is necessary to determine the time frame t of the forging process. j Adjust the forging parameters, when the parameter difference is Q (tj) When the difference exceeds the preset parameter threshold, the displacement distance difference Q of the hydraulic press is used. a(tj) and hydraulic pressure difference Q b(tj) Calculate the second score. A second score of 0 indicates that the real-time running parameter set P is 0. (tj) The parameter differences of the real-time operating parameters within the system are all within the allowable error range, and no adjustment of the forging parameters is required; when the second score is not 0, it indicates that the real-time operating parameter set P... (tj) If at least one of the intended real-time operating parameters exceeds the system's allowable error range, the error can be calculated by measuring the forging acquisition time frame t. j The correction factor M is determined by the ratio of the simulated hydraulic press displacement distance to the hydraulic press displacement distance. 1(j) The preset parameter difference threshold is set by those skilled in the art according to actual needs.

[0110] According to an embodiment of the present invention, it further includes:

[0111] When the second score is greater than 2, an anomaly is recorded;

[0112] When the number of abnormal records during the forging process of the same forging part exceeds the preset abnormal number threshold, the hydraulic operation is stopped and an early warning is issued.

[0113] It should be noted that when the second score is greater than 2, it indicates that the displacement distance difference Q of the hydraulic press is significant. a(tj) and hydraulic pressure difference Q b(tj) All are greater than the maximum value of the corresponding preset parameter adjustment range, forging acquisition time frame t j The real-time operating parameter set and the corresponding simulated operating parameters differ significantly. To avoid data fluctuations during the forging process, the number of abnormal records during the forging process of the same forging is counted and compared with a preset abnormal number threshold to determine whether an early warning should be issued. The preset abnormal number threshold is set by those skilled in the art based on actual needs.

[0114] According to an embodiment of the present invention, the parameter difference is compared with the maximum and minimum values ​​of the corresponding preset parameter adjustment ranges to determine a first score for the parameter difference, including:

[0115] When the parameter difference is less than the minimum value of the corresponding preset parameter adjustment range, the first score of the parameter difference is determined to be 0;

[0116] When the parameter difference is between the maximum and minimum values ​​of the corresponding preset parameter adjustment range, the first score of the parameter difference is determined to be 1;

[0117] When the parameter difference is greater than the maximum value of the corresponding preset parameter adjustment range, the first score of the parameter difference is determined to be 2.

[0118] It should be noted that, based on the parameter type of the real-time operating parameters, different preset parameter adjustment ranges are set for the parameter difference of each real-time operating parameter. The parameter difference is divided into three levels by the maximum and minimum values ​​of the preset parameter adjustment ranges, and a corresponding first score is assigned according to the level.

[0119] According to an embodiment of the present invention, it further includes:

[0120] Based on the previous forging acquisition time frame t j-1 and forging acquisition time frame t j Simulated forging was performed using the forging progress variation values ​​to determine the forging acquisition time frame t. j Predicted acquisition time frame t corresponding to forging progress q ;

[0121] Calculate the predicted acquisition time frame t q and forging acquisition time frame t j Time difference;

[0122] When the time difference is less than the preset time difference threshold, the acquisition time frame t is predicted. q Forging acquisition time frame t j Update.

[0123] It should be noted that when the second score is not 0, the system uses the previous forging acquisition time frame t. j-1 and forging acquisition time frame t j Simulated forging was performed using the forging progress variation values ​​to determine the forging acquisition time frame t. j Predicted acquisition time frame t corresponding to forging progress q And calculate its relationship with the forging acquisition time frame t. j The absolute value of the difference is used to determine the time difference. When the time difference is less than a preset time difference threshold, the acquisition time frame t is predicted. q Forging acquisition time frame t j Update by adjusting the previous forging acquisition time frame t. j-1 and forging acquisition time frame t j The length of the time interval between them must satisfy the forging acquisition time frame t. j The actual forging progress meets the expected requirements; when the time difference is greater than or equal to the preset time difference threshold, the forging acquisition time frame t will be changed. j Restore initial values ​​based on the real-time running parameter set P (tj) Calculate the correction factor M 1(j)And by adjusting factor M 1(j) Forging acquisition time frame t j The corresponding forging parameters are updated. The preset time difference threshold is set by those skilled in the art based on actual needs.

[0124] When forging acquisition time frame t j When making adjustments, the adjusted forging acquisition time frame t is used. j The preset forging progress change interval is used to update the subsequent forging acquisition time frames.

[0125] All information (including but not limited to user equipment information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals (including but not limited to signals transmitted between user terminals and other devices) involved in this application have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, the "forging type" and "historical forging parameter variation curve" involved in this disclosure were obtained with full authorization.

[0126] This invention discloses an intelligent parameter adaptive control system and method for a forging hydraulic press. The method includes: acquiring the model of the forging; generating an initial forging parameter variation curve based on the model of the forging; controlling the hydraulic press to forge the test forging using the initial forging parameter variation curve, collecting the actual forging progress of the test forging, and adjusting the forging parameters; updating the initial forging parameter variation curve based on the adjusted forging parameters to determine the forging parameter variation curve; controlling the hydraulic press to forge the forging using the forging parameter variation curve; calculating the parameter difference score based on the real-time operating parameter set of the forging acquisition time frame, and updating the forging parameters corresponding to the forging acquisition time frame using the parameter difference score. This invention automatically adjusts forging parameters by collecting real-time forging data during the forging process, thereby improving forging production efficiency.

[0127] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0128] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0129] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0130] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0131] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. A method for intelligent adaptive parameter control of a forging hydraulic press, characterized in that, include: Obtain the model number of the forging; Generate an initial forging parameter variation curve based on the model of the forging; The hydraulic press is controlled to forge the test forging by controlling the initial forging parameter variation curve, the actual forging progress of the test forging is collected, and the forging parameters are adjusted accordingly. The initial forging parameter variation curve is updated based on the adjusted forging parameters to determine the forging parameter variation curve. The hydraulic press is controlled to forge the workpiece by controlling the forging parameter variation curve; According to the forging acquisition time frame t j Real-time running parameter set P (tj) Calculate the score Q of the parameter difference. (tj) Q is obtained by analyzing the parameter differences. (tj) Forging acquisition time frame t j The corresponding forging parameters are updated; the real-time operating parameter set P (tj) Including hydraulic press displacement distance P a(tj) and hydraulic pressure P b(tj) ; The data is collected based on the forging time frame t. j Real-time running parameter set P (tj) Calculate the score Q of the parameter difference. (tj) Q is obtained by analyzing the parameter differences. (tj) Forging acquisition time frame t j The corresponding forging parameters are updated, including: Multiple forging acquisition time frames t are determined based on the forging start time and the preset forging progress change interval. j ; Based on forging acquisition time frame t j Collect the real-time operating parameter set P of the hydraulic press (tj) ; The real-time operating parameter set P (tj) The real-time operating parameters are compared with the corresponding simulated operating parameters to determine the parameter differences; the parameter differences include the hydraulic press displacement distance difference Q. a(tj) and hydraulic pressure difference Q b(tj) ; Calculate the parameter difference score Q based on the parameter difference. (tj) ; ； Where k1 and k2 are both correction coefficients; When the parameter difference is divided into Q (tj) When the difference exceeds the preset parameter difference threshold, the parameter difference is compared with the maximum and minimum values ​​of the corresponding preset parameter adjustment range to determine the first score of the parameter difference. The first scores of all parameter differences are summed to determine the second score; No adjustments are made when the second score is 0; When the second score is not 0, according to the real-time running parameter set P (tj) Calculate the correction factor M 1(j) And through the correction factor M 1(j) Forging acquisition time frame t j The corresponding forging parameters are updated.

2. The intelligent parameter adaptive control method for forging hydraulic presses according to claim 1, characterized in that, The process of controlling the hydraulic press to forge the test forging using the initial forging parameter variation curve, collecting the actual forging progress of the test forging, and adjusting the forging parameters includes: Based on the model of the forging, the database is filtered, and the historical forging parameter variation curves of the same model of forging are determined as the initial forging parameter variation curves of the forging. The test forging is forged based on the initial forging parameter variation curve; Multiple test acquisition time frames t are determined based on the forging start time and the preset forging progress change interval. i ; Obtain test acquisition time frame t i The actual forging progress of the test forgings; The test acquisition time frame t is calculated based on the actual forging progress and the corresponding simulated forging progress. i The correction factor M 1(i) ; According to the correction factor M 1(i) For the test acquisition time frame t i The forging parameters were adjusted.

3. The intelligent parameter adaptive control method for forging hydraulic presses according to claim 2, characterized in that, Also includes: When forging parameters are adjusted, the test forging is continued to be forged using the adjusted forging parameters; When the actual forging progress of the test forging meets the corresponding simulated forging progress, the forging parameters are adjusted to the next acquisition time frame t. i+1 The corresponding forging parameters.

4. The intelligent parameter adaptive control method for forging hydraulic presses according to claim 1, characterized in that, The step of updating the initial forging parameter variation curve based on the adjusted forging parameters to determine the forging parameter variation curve includes: The updated initial forging parameter variation curve corresponding to test forging n is determined as the first forging parameter variation curve; The correction score is calculated based on the correction factors before and after the adjustment. ； ； Among them, P n To test the corrected score of forging n, P i For testing forging n at test acquisition time frame t i Sub-correction score, M 1(i)n For testing forging n at test acquisition time frame t i The correction factor, M 1(i)n-1 For the previous test forging n-1 at test acquisition time frame t i The correction factor, α is the correction coefficient; When the corrected score is greater than the preset corrected score threshold, the next test forging is forged using the first forging parameter change curve, the correction factor of the next test forging is calculated, and the first forging parameter change curve is updated. When the corrected score is less than or equal to the preset corrected score threshold, the first forging parameter change curve is determined as the forging parameter change curve.

5. The intelligent parameter adaptive control method for forging hydraulic presses according to claim 1, characterized in that, Also includes: When the second score is greater than 2, an anomaly is recorded; When the number of abnormal records during the forging process of the same forging part exceeds the preset abnormal number threshold, the hydraulic operation is stopped and an early warning is issued.

6. The intelligent parameter adaptive control method for forging hydraulic presses according to claim 1, characterized in that, The step of comparing the parameter difference with the maximum and minimum values ​​of the corresponding preset parameter adjustment ranges to determine the first score of the parameter difference includes: When the parameter difference is less than the minimum value of the corresponding preset parameter adjustment range, the first score of the parameter difference is determined to be 0; When the parameter difference is between the maximum and minimum values ​​of the corresponding preset parameter adjustment range, the first score of the parameter difference is determined to be 1; When the parameter difference is greater than the maximum value of the corresponding preset parameter adjustment range, the first score of the parameter difference is determined to be 2.

7. The intelligent parameter adaptive control method for forging hydraulic presses according to claim 1, characterized in that, Also includes: Based on the previous forging acquisition time frame t j-1 and forging acquisition time frame t j Simulated forging was performed using the forging progress variation values ​​to determine the forging acquisition time frame t. j Predicted acquisition time frame t corresponding to forging progress q ; Calculate the predicted acquisition time frame t q and forging acquisition time frame t j Time difference; When the time difference is less than a preset time difference threshold, the predicted acquisition time frame t is used. q Forging acquisition time frame t j Update.

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