Intelligent parameter self-adaptive control system and control method for hydraulic forging press

Abstract

The invention discloses an intelligent parameter self-adaptive control system and method for a hydraulic forging press. The method comprises the steps that the type of a forged piece is obtained; generating an initial forging parameter change curve according to the model of the forge piece; the hydraulic machine is controlled to forge the tested forge piece through the initial forging parameter change curve, the actual forging progress of the tested forge piece is collected, and forging parameters are adjusted; the initial forging parameter change curve is updated according to the adjusted forging parameters, and a forging parameter change curve is determined; controlling the hydraulic machine to forge the forge piece through the forging parameter change curve; and calculating a parameter difference score according to the real-time operation parameter set of the forging acquisition time frame, and updating the forging parameters corresponding to the forging acquisition time frame through the parameter difference score. By collecting the real-time forging data in the forging process, the forging parameters are automatically adjusted, and the forging production efficiency is improved.

Description

Technical Field

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

[0002] As an important metal forming equipment, the forging hydraulic press plays a key role in many fields such as aerospace, automobile manufacturing, and machinery manufacturing. Traditional forging hydraulic presses mainly rely on manual operation and preset parameters to work, and it is difficult to adapt to various changes in 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 change cause the preset parameters to not match the actual requirements, easily leading to equipment failures (such as the "jamming" phenomenon) or forging quality defects.

[0004] Low intelligent level: The existing control systems lack the dynamic closed-loop regulation ability for multiple variables (pressure, temperature, displacement, etc.), and it is difficult to realize the real-time optimization of process parameters.

[0005] Insufficient efficiency and accuracy: Manual adjustment of parameters takes a long time and cannot meet the process requirements of different materials (such as titanium alloys, superalloys) or complex forgings.

[0006] Therefore, there are defects in the existing technology and urgent improvements are needed. Summary of the Invention

[0007] In view of the above problems, the purpose of the present 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, and improves forging production efficiency.

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

[0009] Obtain the model of the forging;

[0010] Generate an initial forging parameter change curve according to the model of the forging;

[0011] Control the hydraulic press to forge the test forging through the initial forging parameter change curve, collect the actual forging progress of the test forging, and adjust the forging parameters;

[0012] Update the initial forging parameter change curve according to the adjusted forging parameters, and determine the forging parameter change curve;

[0013] Control the hydraulic press to forge the forging through the forging parameter change curve;

[0014] According to the forging acquisition time frame tj The set P of real-time operation parameters (tj) Calculate the parameter difference score Q (tj) , and through the parameter difference score Q (tj) Forge the acquisition time frame t j Update the corresponding forging parameters; the set P of real-time operation parameters (tj) Includes the hydraulic press displacement distance P a(tj) And the hydraulic pressure P b(tj) .

[0015] In this solution, the hydraulic press is controlled by the initial forging parameter change curve to forge the test forging, collect the actual forging progress of the test forging, and adjust the forging parameters, including:

[0016] Screen in the database according to the model of the forging, and determine the historical forging parameter change curve of the forgings of the same model as the initial forging parameter change curve of the forging;

[0017] Forging the test forging based on the initial forging parameter change curve;

[0018] Determine multiple test acquisition time frames t based on the forging start time and the preset forging progress change interval i ;

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

[0020] Calculate the correction factor M of the test acquisition time frame t according to the actual forging progress and the corresponding simulated forging progress i ; 1(i) ;

[0021] Adjust the forging parameters of the test acquisition time frame t according to the correction factor M 1(i) ; i ;

[0022] In this solution, it also includes:

[0023] When adjusting the forging parameters, continue to forge the test forging with the adjusted forging parameters;

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

[0025] In this solution, updating the initial forging parameter change curve according to the adjusted forging parameters to determine the forging parameter change curve includes:

[0026] Determine the updated initial forging parameter change curve corresponding to the test forging n as the first forging parameter change curve;

[0027] Calculate the correction score according to the correction factors before and after adjustment;

[0028] P i = α × |M 1(i)n - M 1(i)n-1 |;

[0029]

[0030] Where P n is the correction score of the test forging n, P i is the sub-correction score of the test forging n at the test acquisition time frame t i M 1(i)n is the correction factor of the test forging n at the test acquisition time frame t i M 1(i)n-1 is the correction factor of the previous test forging n - 1 at the test acquisition time frame t i α is the correction coefficient;

[0031] When the correction score is greater than the preset correction score threshold, forge the next test forging through the first forging parameter change curve, calculate the correction factor of the next test forging, and update the first forging parameter change curve;

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

[0033] In this solution, calculating the parameter difference score Q j based on the real-time operation parameter set P (tj) at the forging acquisition time frame t (tj) , and updating the forging parameters corresponding to the forging acquisition time frame t (tj) through the parameter difference score Q j includes:

[0034] Determine multiple forging acquisition time frames t j based on the forging start time and the preset forging progress change interval;

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

[0036] Compare the real-time operation parameters in the real-time operation parameter set P (tj) with the corresponding simulated operation parameters respectively to determine the parameter difference; the parameter difference includes the hydraulic press displacement distance difference Q a(tj)and the hydraulic pressure difference Q b(tj) ;

[0037] Calculate the parameter difference score Q according to the parameter difference (tj) ;

[0038] Q (tj) = k 1 × Q a(tj) + k 2 × Q b(tj) ;

[0039] wherein, k 1 and k 2 are both correction factors;

[0040] When the parameter difference score Q (tj) is greater than the preset parameter difference threshold, compare the parameter difference with the maximum and minimum values of the corresponding preset parameter adjustment interval respectively to determine the first score of the parameter difference;

[0041] Accumulate the first scores of all parameter differences to determine the second score;

[0042] When the second score is 0, make no adjustment;

[0043] When the second score is not 0, calculate the correction factor M according to the real-time operating parameter set P (tj) and update the forging parameters corresponding to the forging acquisition time frame t 1(j) through the correction factor M 1(j) j j corresponding to the forging parameters.

[0044] In this solution, it also includes:

[0045] When the second score is greater than 2, record the abnormality;

[0046] When the number of abnormality records during the forging process of the same forging is greater than the preset abnormality number threshold, stop the hydraulic work and give a warning reminder.

[0047] In this solution, the step of comparing the parameter difference with the maximum and minimum values of the corresponding preset parameter adjustment interval respectively 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 interval, determine the first score of the parameter difference as 0;

[0049] When the parameter difference is between the maximum and minimum values of the corresponding preset parameter adjustment interval, determine the first score of the parameter difference as 1;

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

[0051] This solution also includes:

[0052] Based on the previous forging acquisition time frame t j-1 and the forging acquisition time frame t j perform simulated forging on the forging progress change value, and determine the predicted acquisition time frame t j corresponding to the forging progress of the forging acquisition time frame t q ;

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

[0054] When the time difference is less than the preset time difference threshold, update the forging acquisition time frame t q through the predicted acquisition time frame t j ;

[0055] The present invention discloses an intelligent parameter adaptive control system and control method for a forging hydraulic press. The method includes: obtaining the model of the forging; generating an initial forging parameter change curve according to the model of the forging; controlling the hydraulic press to forge the test forging through the initial forging parameter change curve, collecting the actual forging progress of the test forging, and adjusting the forging parameters; updating the initial forging parameter change curve according to the adjusted forging parameters to determine the forging parameter change curve; controlling the hydraulic press to forge the forging through the forging parameter change curve; calculating the parameter difference score according to the real-time operation parameter set of the forging acquisition time frame, and updating the forging parameters corresponding to the forging acquisition time frame through the parameter difference score. The present invention automatically adjusts the forging parameters by collecting the real-time forging data during the forging process, improving the forging production efficiency. Brief Description of the Drawings

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

[0057] Figure 2 Shows a flowchart of a method for adjusting forging parameters by a test forging provided by the present invention;

[0058] Figure 3 Shows a flowchart of a method for determining a forging parameter change curve provided by the present invention. Detailed Embodiments

[0059] In order to more clearly understand the above-mentioned objects, features, and advantages of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0060] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

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

[0062] As Figure 1 shown, the present invention discloses an intelligent parameter adaptive control method for a forging hydraulic press, including:

[0063] S102, obtaining the model of the forging;

[0064] S104, generating an initial forging parameter change curve according to the model of the forging;

[0065] S106, controlling the hydraulic press to forge the test forging through the initial forging parameter change curve, collecting the actual forging progress of the test forging, and adjusting the forging parameters;

[0066] S108, updating the initial forging parameter change curve according to the adjusted forging parameters to determine the forging parameter change curve;

[0067] S110, controlling the hydraulic press to forge the forging through the forging parameter change curve;

[0068] S112, calculating the parameter difference score Q according to the real-time operation parameter set P of the forging acquisition time frame t j and updating the forging parameters corresponding to the forging acquisition time frame t (tj) through the parameter difference score Q; the real-time operation parameter set P (tj) includes the hydraulic press displacement distance P (tj) and the hydraulic pressure P j . (tj) a(tj) 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, and based on the model of the forging, screens the historical forging parameter change curves of forgings of the same model from the database and determines them as the initial forging parameter change curves of the current forging. Based on the forging start time and the preset forging progress change interval preset by the system, a plurality of test acquisition time frames t are determined. i According to the test acquisition time frame t i The actual forging progress obtained and the corresponding simulated forging progress are compared to calculate the correction factor M. 1(i) The forging parameters of the test acquisition time frame t i are adjusted. According to the adjusted forging parameters, the initial forging parameter change curve is updated, and the updated initial forging parameter change curve is determined as the first forging parameter change curve, and the correction score is calculated. When the correction score is greater than the preset correction score threshold preset by the system, the first forging parameter change curve is determined as the forging parameter change curve. According to the forging parameter change curve, the rotation speed of the hydraulic motor is adjusted, and the forgings are forged in batches. During the forging process, according to the forging acquisition time frame t j The real-time operation parameter set P of the hydraulic press is collected. (tj) According to the real-time operation parameter set P (tj) The forging parameter change curve is adjusted.

[0070] The real-time operation parameters in the real-time operation parameter set P (tj) are respectively compared with the corresponding simulated operation parameters to determine the parameter difference, and the parameter difference score is calculated. When the parameter difference score is greater than the preset parameter difference threshold preset by the system, the second score is calculated through the parameter difference. When the second score is not 0, the correction factor M is calculated through the real-time operation parameter set P (tj) And the forging parameters corresponding to the forging acquisition time frame t 1(j) are updated through the correction factor M. 1(j) The forging parameter corresponding to the forging acquisition time frame t j is updated.

[0071] Figure 2 FIG. shows a flowchart of a method for adjusting forging parameters by testing forgings provided by the present invention.

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

[0073] S202, screening in the database according to the model of the forging, and determining the historical forging parameter change curve of the forging of the same model as the initial forging parameter change curve of the forging;

[0074] S204, forge the test forging based on the initial forging parameter change curve;

[0075] S206, determine multiple test acquisition time frames t based on the forging start time and the preset forging progress change interval i ;

[0076] S208, obtain the actual forging progress of the test forging at the test acquisition time frame t i ;

[0077] S210, calculate the correction factor M of the test acquisition time frame t according to the actual forging progress and the corresponding simulated forging progress i ; 1(i) ;

[0078] S212, adjust the forging parameters of the test acquisition time frame t according to the correction factor M 1(i) ; i ;

[0079] It should be noted that by collecting various forging data generated during the forging process of the forging by the hydraulic press, the mutual relationship between parameters such as forging progress, forging pressure, and hydraulic motor speed is determined based on the forging start time and the duration, and the historical forging parameter change curve between the forging progress and the hydraulic motor speed is drawn and stored in the database. When forging the forging by the hydraulic press, the system identifies the input forging model, combines with the detection device to obtain the appearance image of the forging, and screens the historical forging parameter change curve of the forging with the same model from the database as the initial forging parameter change curve of the current forging. Among them, when there are multiple historical forging parameter change curves of forgings with the same model, the historical forging parameter change curve closest to the current time is selected as the initial forging parameter change curve of the current forging. When there is no historical forging parameter change curve of the forging with the same model, the system selects the historical forging parameter change curve of the forging with the same or similar material and similar specifications in the database for analysis, conducts simulated forging, and generates the initial forging parameter change curve of 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 respectively.

[0081] Affected by the leakage of the hydraulic press, the type of hydraulic oil, the viscosity range, and the working temperature, there are certain energy consumption losses, resulting in a difference between the actual forging progress of the test acquisition time frame t i and the corresponding simulated forging progress. By calculating the correction factor M 1(i) to adjust the test acquisition time frame t iAdjust the forging parameters. Among them, the actual forging progress can be analyzed and determined by monitoring the moving distance of the hydraulic press and combining the changes of the forgings in the detected images, and the correction factor M 1(i) is the ratio of the corresponding simulated forging progress to the actual forging progress of the actual forging progress. Multiply the correction factor M 1(i) by the test acquisition time frame t i to multiply the original forging parameters to determine the adjusted forging parameters. Among them, the forging progress can be represented by the displacement distance of the hydraulic press.

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

[0083] When adjusting the forging parameters, continue to forge the test forgings with the adjusted forging parameters;

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

[0085] It should be noted that when the actual forging progress of the forgings in the current acquisition time frame t i does not meet the corresponding simulated forging progress, at this time, if the forging parameters are directly adjusted to the forging parameters corresponding to the next acquisition time frame t i+1 it may cause abnormalities in the forging process, such as the actual forging progress of each subsequent acquisition time frame does not match the corresponding simulated forging progress. Continue to forge the test forgings with the adjusted forging parameters. When the actual forging progress of the test forgings meets the corresponding simulated forging progress, adjust the forging parameters to the forging parameters corresponding to the next acquisition time frame t i+1 corresponding. At the same time, update the next acquisition time frame t i+1 according to the time frame when the actual forging progress of the test forgings meets the corresponding simulated forging progress and the preset forging progress change interval.

[0086] Figure 3 Shows the flowchart of the forging parameter change curve determination method provided by the present invention.

[0087] As Figure 3 shown, according to the embodiments of the present invention, update the initial forging parameter change curve according to the adjusted forging parameters to determine the forging parameter change curve, including:

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

[0089] S304, calculate the correction score according to the correction factors before and after adjustment;

[0090] P i = α × |M 1(i)n - M 1(i)n-1 |;

[0091]

[0092] Wherein, P n is the corrected score of the test forging n, P i is the sub-corrected score of the test forging n in the test acquisition time frame t i M 1(i)n is the correction factor of the test forging n in the test acquisition time frame t i M 1(i)n-1 is the correction factor of the previous test forging n - 1 in the test acquisition time frame t i α is the correction coefficient;

[0093] S306. When the corrected score is greater than the preset corrected score threshold, forge the next test forging through the first forging parameter change curve, calculate the correction factor of the next test forging, and update the first forging parameter change curve;

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

[0095] It should be noted that after the forging work of the test forging n is completed, calculate the sub-corrected scores of the test forging n in each test acquisition time frame in turn, accumulate the sub-corrected scores of all test acquisition time frames, and determine the corrected score P n of the test forging n. Through the corrected score P n the fluctuation situation of the initial forging parameter change curves corresponding to the test forging n and the test forging n - 1 can be determined. Compare the corrected score with the 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 change curve corresponding to the test forging n is small to meet the preset requirements of the system, and it is determined as the final forging parameter change curve; otherwise, continue to forge the test forging n + 1 based on the initial forging parameter change curve corresponding to the test forging n until the corrected score of the test forging is less than or equal to the preset corrected score threshold. Among them, the preset corrected score threshold is set by those skilled in the art according to actual needs. At the same time, those skilled in the art can limit the number of test forgings. If the corrected score is still greater than the preset corrected score threshold after all test forgings are forged, a pop-up window reminder is given to remind relevant personnel to repair the hydraulic press.

[0096] According to an embodiment of the present invention, according to the real-time operation parameter set P j of the forging acquisition time frame t (tj)Calculate the parameter difference score Q (tj) , and update the forging parameters corresponding to the forging acquisition time frame t (tj) through the parameter difference score Q j , including:

[0097] Determine multiple forging acquisition time frames t based on the forging start time and the preset forging progress change interval j ;

[0098] Collect the real-time operation parameter set P of the hydraulic press based on the forging acquisition time frame t j ; (tj)

[0099] Compare the real-time operation parameters in the real-time operation parameter set P (tj) with the corresponding simulated operation parameters respectively to determine the parameter difference; the parameter difference includes the hydraulic press displacement distance difference Q a(tj) and the hydraulic pressure difference Q b(tj) ;

[0100] Calculate the parameter difference score Q according to the parameter difference (tj) ;

[0101] Q (tj) = k 1 × Q a(tj) + k 2 × Q b(tj) ;

[0102] where k 1 and k 2 are both correction factors;

[0103] When the parameter difference score Q (tj) is greater than the preset parameter difference threshold, compare the parameter difference with the maximum and minimum values of the corresponding preset parameter adjustment interval respectively to determine the first score of the parameter difference;

[0104] Accumulate the first scores of all parameter differences to determine the second score;

[0105] When the second score is 0, make no adjustment;

[0106] When the second score is not 0, calculate the correction factor M (tj) based on the real-time operation parameter set P of the hydraulic press 1(j) , and update the forging parameters corresponding to the forging acquisition time frame t 1(j) through the correction factor M j ;

[0107] It should be noted that the real-time operation parameters in the real-time operation parameter set P of the hydraulic press (tj) include the forging acquisition time frame t​j The displacement distance P of the hydraulic press a(tj) and the hydraulic pressure P b(tj) , calculate the displacement distance P of the hydraulic press a(tj) and the hydraulic pressure P b(tj) respectively, and determine the parameter difference between the displacement distance P of the hydraulic press and the corresponding simulated operating parameters (simulated displacement distance of the hydraulic press and simulated hydraulic pressure), and determine the displacement distance difference Q of the hydraulic press a(tj) and the hydraulic pressure difference Q b(tj) .

[0108] Among them, the values of the correction factors k 1 and k 2 are set by the system.

[0109] By calculating the parameter difference score Q (tj) judge whether it is necessary to adjust the forging parameter of the forging acquisition time frame t j . When the parameter difference score Q (tj) is greater than the preset parameter difference threshold, calculate the second score through the displacement distance difference Q of the hydraulic press a(tj) and the hydraulic pressure difference Q b(tj) . When the second score is 0, it means that the parameter differences of the real-time operating parameters in the real-time operating parameter set P (tj) are all within the error range allowed by the system, and there is no need to adjust the forging parameters; when the second score is not 0, it means that at least the parameter differences of the real-time operating parameters in the real-time operating parameter set P (tj) exceed the error range allowed by the system. Determine the correction factor M by calculating the ratio of the simulated displacement distance of the hydraulic press to the displacement distance of the hydraulic press of the forging acquisition time frame t j . Among them, the preset parameter difference threshold is set by those skilled in the art according to actual needs. 1(j) .

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

[0111] When the second score is greater than 2, an abnormal record is made;

[0112] When the number of abnormal records during the forging process of the same forging exceeds the preset abnormal number threshold, stop the hydraulic work and give a warning reminder.

[0113] It should be noted that when the second score is greater than 2, it means that the displacement distance difference Q of the hydraulic press a(tj) and the hydraulic pressure difference Q b(tj) are both greater than the maximum value of the corresponding preset parameter adjustment interval, and the forging acquisition time frame t jThe difference value between the set of real-time operation parameters and the corresponding simulated operation parameters is relatively large. To avoid data fluctuations during the forging process, the number of abnormal records during the forging process of the same forgings is statistically counted and compared with a preset abnormal number threshold to determine whether to give a warning reminder. Among them, the preset abnormal number threshold is set by those skilled in the art according to actual needs.

[0114] According to an embodiment of the present invention, comparing the parameter difference with the maximum and minimum values of the corresponding preset parameter adjustment intervals respectively to determine the first score of the parameter difference, including:

[0115] When the parameter difference is less than the minimum value of the corresponding preset parameter adjustment interval, 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 interval, 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 interval, the first score of the parameter difference is determined to be 2.

[0118] It should be noted that different preset parameter adjustment intervals are respectively set for the parameter differences of each real-time operation parameter according to the parameter type of the real-time operation parameter, and the parameter differences are divided into three levels by the maximum and minimum values of the preset parameter adjustment interval, and the corresponding first scores are assigned according to the divided levels.

[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 the forging acquisition time frame t j of the forging progress change value for simulated forging to determine the predicted acquisition time frame t j corresponding to the forging progress of the forging acquisition time frame t q ;

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

[0122] When the time difference is less than the preset time difference threshold, update the forging acquisition time frame t q through the predicted acquisition time frame t j ;

[0123] It should be noted that when the second score is not 0, the system passes the previous forging acquisition time frame t j-1 and the forging acquisition time frame t jSimulate forging with the forging progress change value to determine the forging acquisition time frame t that is satisfied j The predicted acquisition time frame t corresponding to the forging progress q , and calculate the absolute value of its difference from the forging acquisition time frame t j to determine the time difference. When the time difference is less than the preset time difference threshold, update the forging acquisition time frame t q through the predicted acquisition time frame t j by adjusting the time interval length between the previous forging acquisition time frame t j-1 and the forging acquisition time frame t j so that the actual forging progress meets the expected requirements when the forging acquisition time frame t j is satisfied; when the time difference is greater than or equal to the preset time difference threshold, reset the forging acquisition time frame t j to its initial value, calculate the correction factor M (tj) according to the real-time operation parameter set P 1(j) , and update the forging parameters corresponding to the forging acquisition time frame t 1(j) through the correction factor M j . Among them, the preset time difference threshold is set by those skilled in the art according to actual needs.

[0124] When the forging acquisition time frame t j is adjusted, update the subsequent forging acquisition time frames according to the adjusted forging acquisition time frame t j and the preset forging progress change interval.

[0125] The information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data 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 are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions. For example, the "model of forgings", "historical forging parameter change curves", etc. involved in this disclosure are all obtained under full authorization.

[0126] The present invention discloses an intelligent parameter adaptive control system and control method for a forging hydraulic press. The method includes: obtaining the model of the forging; generating an initial forging parameter change curve according to the model of the forging; controlling the hydraulic press to forge a test forging through the initial forging parameter change curve, collecting the actual forging progress of the test forging, and adjusting the forging parameters; updating the initial forging parameter change curve according to the adjusted forging parameters to determine the forging parameter change curve; controlling the hydraulic press to forge the forging through the forging parameter change curve; calculating a parameter difference score according to the real-time operation parameter set of the forging acquisition time frame, and updating the forging parameters corresponding to the forging acquisition time frame through the parameter difference score. By collecting real-time forging data during the forging process, the present invention automatically adjusts the forging parameters to improve the forging production efficiency.

[0127] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined, or can be 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. The indirect coupling or communication connection of devices or units can be electrical, mechanical, or other forms.

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

[0129] In addition, in each embodiment of the present invention, the various functional units can all be integrated in one processing unit, or each unit can be separately used as a unit, or two or more units can be integrated in one unit; the above integrated units can be implemented in the form of hardware, or in the form of a combination of hardware and software functional units.

[0130] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed 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 including those of the above method embodiments. The aforementioned storage medium includes various media that can store program codes, such as removable storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0131] Alternatively, if the above integrated units of the present invention are implemented in the form of software function modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present invention, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media that can store program codes, such as removable storage devices, ROM, RAM, magnetic disks, or optical discs.

Claims

1. A method for intelligent parameter adaptive control of a forging hydraulic press, characterized in that: include: Get the model of the forging; generating an initial forging parameter variation curve according to the model of the forging; Controlling the hydraulic press to forge the test forging by 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 according to the adjusted forging parameters to determine the forging parameter variation curve; Controlling the hydraulic press to forge the forging by the forging parameter variation curve; According to the forging acquisition time frame t j The real-time operating parameter set P (tj) Calculate parameter difference score Q (tj) , by parameter difference score Q (tj) Forging collection 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) .

2. The intelligent parameter adaptive control method for forging hydraulic press according to claim 1 is characterized in that: The controlling the hydraulic press to forge the test forging by the initial forging parameter variation curve, collecting the actual forging progress of the test forging, and adjusting the forging parameters include: Screening in a database according to the model of the forgings, and determining the historical forging parameter change curve of the forgings of the same model as the initial forging parameter change curve of the forgings; Forging a test forging based on the initial forging parameter variation curve; Determine multiple test acquisition time frames t based on the forging start time and the preset forging progress change interval i ; Get the test acquisition time frame t i The actual forging progress of the test forgings; The test acquisition time frame t is calculated according to 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 Adjust the forging parameters.

3. The intelligent parameter adaptive control method for forging hydraulic press according to claim 2 is characterized in that: Also includes: When the 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 press according to claim 1 is characterized in that: The updating of the initial forging parameter variation curve according to the adjusted forging parameters to determine the forging parameter variation curve includes: Determining the updated initial forging parameter variation curve corresponding to the test forging n as the first forging parameter variation curve; Calculate the modified score based on the pre-adjustment and post-adjustment modification factors; P i =α×|M 1(i)n -M 1(i)n-1 |; Among them, P n is the corrected score of the test forging n, P i For the test forging n in the test acquisition time frame t i Sub-corrected score, M 1(i)n For the test forging n in the test acquisition time frame t i The correction factor, M 1(i)n-1 For the last test forging n-1 at the test acquisition time frame t i The correction factor is α, and α is the correction coefficient; When the correction score is greater than a preset correction score threshold, forging the next test forging by using the first forging parameter variation curve, calculating the correction factor of the next test forging, and updating the first forging parameter variation curve; When the correction score is less than or equal to the preset correction score threshold, the first forging parameter variation curve is determined as the forging parameter variation curve.

5. The intelligent parameter adaptive control method for a forging hydraulic press according to claim 1, characterized in that: The forging acquisition time frame t j The real-time operating parameter set P (tj) Calculate parameter difference score Q (tj) , by parameter difference score Q (tj) Forging collection time frame t j The corresponding forging parameters are updated, including: Determine multiple forging acquisition time frames t based on the forging start time and the preset forging progress change interval j ; Based on the 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 in the simulation are compared with the corresponding simulation operating parameters to determine the parameter difference; the parameter difference includes the hydraulic press displacement distance difference Q a(tj) and hydraulic pressure difference Q b(tj) ; Calculate the parameter difference score Q according to the parameter difference (tj) ; Q (tj) =k1×Q a(tj) +k2×Q b(tj) ; Among them, k1 and k2 are correction coefficients; When the parameter difference score Q (tj) When the parameter difference is greater than a preset parameter difference threshold, the parameter difference is compared with the maximum value and the minimum value of the corresponding preset parameter adjustment interval to determine a first score of the parameter difference; The first scores of all parameter differences are accumulated to determine a second score; When the second score is 0, no adjustment is made; When the second score is not 0, according to the real-time operation parameter set P (tj) Calculate the correction factor M 1(j) , and through the correction factor M 1(j) Forging collection time frame t j The corresponding forging parameters are updated.

6. The intelligent parameter adaptive control method for forging hydraulic press according to claim 5 is characterized in that: Also includes: When the second score is greater than 2, an abnormal record is made; When the number of abnormal records during the forging process of the same forging is greater than the preset abnormal number threshold, the hydraulic work is stopped and an early warning reminder is issued.

7. The intelligent parameter adaptive control method for a forging hydraulic press according to claim 5, characterized in that: The step of comparing the parameter difference with the maximum value and the minimum value of the corresponding preset parameter adjustment interval to determine a first score of the parameter difference includes: When the parameter difference is less than the minimum value of the corresponding preset parameter adjustment interval, the first score of the parameter difference is determined to be 0; When the parameter difference is between the maximum value and the minimum value of the corresponding preset parameter adjustment interval, 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 interval, the first score of the parameter difference is determined to be 2.

8. The intelligent parameter adaptive control method for a forging hydraulic press according to claim 5, characterized in that: Also includes: Based on the last forging acquisition time frame t j-1 and forging acquisition time frame t j The forging progress change value is used to simulate forging and determine the forging acquisition time frame t j Corresponding to the predicted collection time frame t of the forging progress q ; Calculate the predicted acquisition time frame t q and forging acquisition time frame t j The time difference of When the time difference is less than the preset time difference threshold, the predicted acquisition time frame t q Forging collection time frame t j to update.

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