A digital tee extrusion production method and equipment

Abstract

The present application provides a digital tee extrusion production method and equipment, which belongs to the technical field of tee extrusion production control. The method includes determining the corresponding extrusion operation parameter group sequence in real time; inputting the extrusion operation parameter group sequence into the tee production simulation model to determine the defect prediction development information. Based on the defect prediction development information and the preset standard operation control parameter information, the defect correction development information is determined; the defect correction development information and the extrusion operation parameter group sequence of the correction period are sent to the management terminal as defect correction information, so as to store the defect correction information and the evaluation label in the preset database based on the feedback evaluation information. When the second extrusion material instruction is received, the defect correction deviation is determined based on the preset database and the extrusion operation parameter group sequence of the second extrusion material, so as to update the preset standard operation control parameter information based on the defect correction deviation and / or send the defect correction deviation to the user terminal, so as to control the production of the tee extrusion device.

Description

Technical Field

[0001] This application relates to the technical field of three-way extrusion production control, and particularly to a digital three-way extrusion production method and equipment. Background Art

[0002] In the prior art, the extrusion of three-way pipes is all driven by a hydraulic extrusion mechanism. The process has high energy consumption, poor accuracy and adjustment variability of the hydraulic mechanism, high energy consumption during the extrusion process, relies on manual assistance, has potential safety hazards, and the efficiency cannot meet the needs of the current digital production line upgrade.

[0003] With the rapid development of intelligent manufacturing, the market's requirements for the digitization, automation, and intelligence of the extrusion process are constantly increasing. There is a need to provide a more intelligent and efficient production method to reduce labor input, ensure the personal safety of employees, and improve the finished product rate and production efficiency. Summary of the Invention

[0004] The embodiments of this application provide a digital three-way extrusion production method and equipment, which are used to solve the technical problems of insufficient digitization, automation, and intelligence in the current three-way pipe extrusion process, high labor costs required for the production line, potential safety hazards, and low production efficiency.

[0005] On the one hand, the embodiments of this application provide a digital three-way extrusion production method. The method is applied to a three-way extrusion device driven by a motor, and the method includes:

[0006] After receiving the first extrusion material instruction, determine the corresponding sequence of extrusion operation parameter groups in real time; wherein, the extrusion operation parameter groups in the sequence of extrusion operation parameter groups at least include the following extrusion operation parameters: motor output torque, extrusion material specification, and real-time extrusion force arm displacement;

[0007] Input the real-time sequence of extrusion operation parameter groups into the three-way production simulation model to determine the defect prediction development information of the corresponding first extrusion material; wherein, the three-way production simulation model is constructed based on historical production records;

[0008] Based on the defect prediction development information and the preset standard operation regulation parameter information, determine the defect correction development information corresponding to the extrusion material;

[0009] Send the defect correction development information and the sequence of extrusion operation parameter groups corresponding to the correction period as defect correction information to the management terminal, and store the defect correction information and the corresponding evaluation label in a preset database based on the feedback evaluation information from the management terminal;

[0010] After receiving the second extrusion material instruction, based on the preset database and the sequence of extrusion operation parameter groups corresponding to the second extrusion material, determine the corresponding defect correction deviation, so as to update the preset standard operation regulation parameter information based on the defect correction deviation and / or send the defect correction deviation to the user terminal, so as to control the operation parameters of the three-way extrusion device and complete the three-way extrusion production.

[0011] In an implementation manner of the present application, input the real-time sequence of extrusion operation parameter groups into the three-way production simulation model to determine the defect prediction development information of the corresponding first extrusion material, specifically including:

[0012] Input the extrusion operation parameter groups corresponding to each extrusion moment in the sequence of extrusion operation parameter groups into the three-way production simulation model in turn, so as to determine the defect prediction information corresponding to each extrusion moment according to the model output result; wherein, the defect prediction information at least includes: defect type, defect location, defect index, development trend; the defect index is used to quantify the severity of the corresponding defect type; the defect type at least includes one or more of the following: buckling, wrinkling, rupture, folding;

[0013] Generate a defect development curve corresponding to each defect prediction information according to the time sequence and the defect type; wherein, the abscissa value of the defect development curve is time, and the ordinate value is the defect index; the defect development curve includes the defect prediction information within a predetermined time length after the extrusion moment;

[0014] According to each defect development curve, the defect threshold interval corresponding to the corresponding defect type, and the preset development trend correction list, determine whether there are correctable defects; wherein, the defect threshold interval is obtained based on historical defect correction records; the historical defect correction records include record information on controlling the operation control parameters to eliminate the corresponding defect occurrence events;

[0015] If so, use the defect development curve corresponding to the correctable defect as the defect prediction development information.

[0016] In an implementation manner of the present application, according to each defect development curve, the defect threshold interval corresponding to the corresponding defect type, and the preset development trend correction list, determine whether there are correctable defects, specifically including:

[0017] Match each defect development curve with the corresponding defect threshold interval respectively, so as to determine whether there is a defect curve segment in the defect development curve according to the first matching result; wherein, each defect index corresponding to the defect curve segment is within the defect threshold interval;

[0018] If so, use the corresponding extrusion moment as the correction start moment, and use the moment corresponding to the start end of the defect curve segment as the correction end moment, so as to determine the standard correction time according to the correction start moment and the correction end moment;

[0019] Compare the development trend with a preset development trend correction list to determine the time required for correction;

[0020] When the standard correction time is greater than or equal to the time required for correction, determine that the defect prediction information corresponds to the correctable defect;

[0021] Otherwise, determine that there is no such correctable defect.

[0022] In an implementation manner of the present application, based on the defect prediction development information and the preset standard operation control parameter information, determine the defect correction development information corresponding to the extruded material, specifically including:

[0023] Match the defect prediction development information with a preset defect development sample to determine the control strategy code corresponding to the defect prediction development information according to the corresponding second matching result; wherein, the control strategy code includes the association relationship between the adjustment coefficient set corresponding to the operation control parameters of each operation module of the three-way extrusion device and the control quality; the control quality characterizes the product quality after the adjustment coefficient set adjusts each operation control parameter;

[0024] According to the control strategy code, adjust the operation control parameters of each current operation module to obtain the preset standard operation control parameter information;

[0025] Control each operation module to start from the correction start moment and operate with the preset standard operation control parameter information, and obtain the control change information within a preset time period corresponding to the defect prediction development information in real time, so as to determine the defect correction development information when the control change information meets the correction expectation condition; wherein, the control change information is the defect prediction information obtained within the preset time period after operating with the preset standard operation control parameter information; the correction expectation condition at least includes that the correctable defect in the defect prediction information disappears.

[0026] In an implementation manner of the present application, the method further includes:

[0027] According to the defect prediction information, determine whether there are coexisting defects within the preset time period;

[0028] If so, determine the correction sub-time periods corresponding to each defect curve segment in the coexisting defects, and determine the overlapping time period of each correction sub-time period;

[0029] Determine the adjusted sub-weights corresponding to each of the defect types in the coexistence defects according to each of the defect types corresponding to the coexistence defects, each of the defect indices, and the preset adjustment weight list; wherein, the sum of the adjusted sub-weights corresponding to the coexistence defects is 1;

[0030] Calculate the corresponding weighted adjustment coefficient set according to each of the adjusted sub-weights and the adjustment coefficient sets respectively corresponding to each of the defect types, and use the weighted adjustment coefficient set as the adjustment coefficient set during the overlapping period to adjust each of the operation control parameters corresponding to the overlapping period.

[0031] In an implementation manner of the present application, storing the defect correction information and the corresponding evaluation tags into a preset database based on the feedback evaluation information from the management terminal specifically includes:

[0032] The management terminal determines a first score corresponding to the defect correction information based on expert experience; the first score is used to characterize the first predicted product quality after the defect correction;

[0033] The management terminal simulates the defect correction process based on the defect correction information and the three-way production simulation model, and determines a second score of the first extruded material according to the simulation result; the second score is used to characterize the second predicted product quality obtained based on the three-way production simulation model;

[0034] The management terminal obtains the finished product appearance information from the user terminal to determine a third score of the first extruded material according to the finished product appearance information;

[0035] The management terminal generates the feedback evaluation information according to the first comparison result of comparing the first score, the second score and the third score respectively, and the second comparison result of comparing the third score with a preset score threshold, and when the first comparison result in the feedback evaluation information is that the scores are consistent and the second comparison result is that the third score is greater than or equal to the preset score threshold, use the third score as the evaluation tag, and store the defect correction information and the evaluation tag into the preset database.

[0036] In an implementation manner of the present application, before determining the corresponding defect correction deviation based on the preset database and the extrusion operation parameter group sequence corresponding to the second extruded material, the method further includes:

[0037] Determine the corresponding defect prediction development information according to the extrusion operation parameter group sequence corresponding to the second extruded material and the three-way production simulation model;

[0038] Match the corresponding defect correction information in the preset database according to the defect prediction development information to determine a third matching result; the third matching result includes one or more pieces of the defect correction information and the corresponding evaluation labels.

[0039] Determine corresponding selected defect correction information according to the evaluation labels, and control the three-way extrusion device to extrude the second extruded material according to the preset standard operation control parameter information corresponding to the selected defect correction information, and record the corresponding defect correction events.

[0040] In an implementation manner of the present application, based on the preset database and the extrusion operation parameter group sequence corresponding to the second extruded material, determine the corresponding defect correction deviation, which specifically includes:

[0041] In the case where there is a defect correction event for the second extruded material, compare the extrusion operation parameter group sequence corresponding to the correction period of the second extruded material with the extrusion operation parameter group sequence corresponding to the selected defect correction information to determine the corresponding correction parameter difference value; wherein, the correction parameter difference value is used to characterize the difference degree between the extrusion operation parameter group sequence corresponding to the correction period of the second extruded material and the extrusion operation parameter group sequence corresponding to the selected defect correction information.

[0042] In the case where the correction parameter difference value is greater than a preset threshold, use the correction parameter difference value as the defect correction deviation.

[0043] In an implementation manner of the present application, update the preset standard operation control parameter information based on the defect correction deviation and / or send the defect correction deviation to a user terminal, so as to control the operation control parameters of the three-way extrusion device and complete the three-way extrusion production, which specifically includes:

[0044] Determine a plurality of preset correction deviation control intervals; wherein, each of the correction deviation control intervals corresponds to a different deviation correction strategy.

[0045] Determine the corresponding deviation correction strategy according to the correction deviation control interval corresponding to the defect correction deviation.

[0046] In the case where the deviation correction strategy includes sending the defect correction deviation to the user terminal, generate a defect correction prompt information and send it to the selected user terminal; wherein, the selected user terminal is the user terminal within the area formed by taking the three-way extrusion device as the center and a preset distance as the radius; the relationship between the preset distance and the defect correction deviation is a negative correlation relationship.

[0047] On the other hand, the embodiment of the present application also provides a digital three-way extrusion production device, and the device includes:

[0048] At least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a digital three-way extrusion production method as described above.

[0049] Compared with the prior art, the present application has the following remarkable effects:

[0050] Through the above technical solution, combined with the digital technology application of the three-way production simulation model, the development of defects in the extruded material can be quickly predicted. Based on the defect prediction development information and the preset standard operation control parameter information, this method can automatically generate defect correction development information and send it to the management terminal, realizing intelligent identification and correction of defects in the production process, and reducing the need for manual intervention. At the same time, recording defect correction information and evaluation labels forms a mechanism for continuous learning and improvement. As the production data accumulates, the prediction and correction capabilities of the corresponding system of the present application will continue to improve, improving production efficiency and product quality. The present application can also determine the defect correction deviation for the extruded material that depends on historical production data for defect correction, thereby improving production flexibility and intelligent level. It solves the technical problems of insufficient digitization, automation, and intelligence in the current three-way pipe extrusion process, the need for a large amount of labor cost in the production line, potential safety hazards, and low production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings described herein are used to provide a further understanding of the present application and form a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0052] Figure 1 is a schematic flow chart of a digital three-way extrusion production method in an embodiment of the present application;

[0053] Figure 2 is a schematic structural diagram of a digital three-way extrusion production device in an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments of this application and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts belong to the scope of protection of this application.

[0055] The embodiments of this application provide a digital three-way extrusion production method and device, which are used to solve the technical problems of insufficient digitalization, automation, and intelligence in the current three-way pipe extrusion process, the need for a large amount of labor cost in the production line, potential safety hazards, and low production efficiency.

[0056] The following will detail each embodiment of this application in conjunction with the drawings.

[0057] The embodiments of this application provide a digital three-way extrusion production method, which is applied to a three-way extrusion device driven by a motor. The three-way extrusion device is driven by the motor to carry out the three-way pipe extrusion production work, and no longer relies on hydraulic equipment for three-way pipe extrusion. As Figure 1 shown, this method may include steps S101 - S105:

[0058] S101, after the microcontroller receives the first extrusion material instruction, it determines the corresponding sequence of extrusion operation parameter groups in real time.

[0059] Among them, the extrusion operation parameter groups in the sequence of extrusion operation parameter groups at least include the following extrusion operation parameters: motor output torque, extrusion material specification, and real-time extrusion force arm displacement.

[0060] It should be noted that the microcontroller, as the execution entity of the digital three-way extrusion production method, is only an example. The execution entity is not limited to the microcontroller, and this application does not make specific limitations in this regard. The microcontroller described in this application is arranged inside the above three-way extrusion device to drive the operation of each module, such as driving the motor, cooling module, laser displacement sensor for measuring the extrusion force arm displacement, camera for collecting extrusion material rules, etc. If the execution entity is a server, the server is connected to the three-way extrusion device in a wired or wireless manner to drive the operation of each module.

[0061] The first extrusion material instruction can be understood as the first extrusion material entering the three-way extrusion device and preparing for extrusion production. This instruction can be generated after the first extrusion material enters the extrusion area and the extrusion preparation work is completed through sensors such as cameras, or it can be an instruction sent by an operator. This application does not make specific limitations in this regard.

[0062] The microcontroller is communicatively connected to each module. When extruding and producing the first extruded material, the microcontroller can store the extrusion operation parameters from each module as extrusion operation parameter groups according to the acquisition time, and establish an extrusion operation parameter group sequence for the extrusion operation parameter groups obtained over a period of time in chronological order.

[0063] S102, the microcontroller inputs the real-time extrusion operation parameter group sequence into the tee production simulation model to determine the defect prediction development information of the corresponding first extruded material.

[0064] Among them, the tee production simulation model is constructed based on historical production records. The historical production records can include several extrusion operation parameter groups manually recorded and the labeled defect information tags when the tee extrusion device historically produced tee pipes. The defect information tags include defect type, defect location, defect index, and development trend. The development trend is the relationship of the defect severity development deduced from several historical extrusion operation parameter group sequences and the corresponding defect indices during the historical production process. The tee production simulation model is constructed by training machine learning or deep learning algorithms based on the above large number of historical production records. The tee production simulation model can accurately predict the defect prediction information of the extruded material under a given extrusion operation parameter group. At the same time, the tee production simulation model can graphically display the state of the extruded material, including information such as the display of the defect location and the shape of the defect on the surface of the extruded material.

[0065] The above defect index is used to quantify the severity of the corresponding defect type. The specific calculation method is as follows: there is a defect score for the actual situation corresponding to the defect type, and a defect weight is assigned to the degree of the corresponding defect affecting the quality of the final product. The product value of the defect score and the defect weight is the defect index; by setting the defect weight, all defect types can be evaluated with a unified dimension to evaluate the severity of the defect type.

[0066] In the embodiment of the present application, the above-mentioned input of the real-time extrusion operation parameter group sequence into the tee production simulation model to determine the defect prediction development information of the corresponding first extruded material specifically includes:

[0067] Sequentially input the extrusion operation parameter groups corresponding to each extrusion moment in the extrusion operation parameter group sequence into the tee production simulation model to determine the defect prediction information corresponding to each extrusion moment according to the model output results. Among them, the defect prediction information at least includes: defect type, defect location, defect index, and development trend. The defect index is used to quantify the severity of the corresponding defect type. The defect type at least includes one or more of the following: buckling, wrinkling, rupture, and folding. Generate defect development curves corresponding to each defect prediction information according to the time sequence and defect type. Among them, the abscissa value of the defect development curve is time, and the ordinate value is the defect index. The defect development curve includes defect prediction information within a predetermined time period after the extrusion moment. Determine whether there are correctable defects according to each defect development curve, the defect threshold interval of the corresponding defect type, and the preset development trend correction list. Among them, the defect threshold interval is obtained based on historical defect correction records. The historical defect correction records include the record information of controlling the operation control parameters to eliminate the corresponding defect occurrence events. And when it is determined that there are correctable defects, the defect development curve corresponding to the correctable defects is used as the defect prediction development information.

[0068] In other words, the present application can sequentially input the extrusion operation parameter groups corresponding to the extrusion moments into the tee production simulation model for defect prediction. The tee production simulation model will output the defect prediction information corresponding to each extrusion moment as the model output result. In addition, the tee production simulation model can also process the extrusion operation parameter groups corresponding to multiple consecutive extrusion moments at one time. The multiple extrusion moments can be set by the user to perform the same model prediction at a certain frequency to avoid errors in individual data. For example, one extrusion moment is 1 second, and multiple extrusion moments are 5 seconds, 10 seconds, or 15 seconds, etc. The present application does not make specific limitations on this.

[0069] The present application will generate defect development curves of each predicted defect prediction information according to the time sequence and defect type. Different defect types have different defect development curves. The defect development curve is generated from the defect prediction information within a predetermined time period predicted by the tee production simulation model after the last extrusion moment is input into the tee production simulation model. The predetermined time period can be set by the user according to the actual usage scenario, such as 10 seconds, 15 seconds, etc. The present application does not make specific limitations on this.

[0070] Further, the present application presets a defect threshold range for different defect types. The defect threshold range can be understood as that when the curve value of the defect development curve of the corresponding defect type reaches within this defect threshold range, it indicates that the occurrence of this defect has reached the level that needs to be corrected. The present application also sets a preset development trend correction list to further determine whether the defect meets the correctable conditions, and determines that there is a correctable defect when the correctable conditions are met. At this time, the microcontroller takes the defect development curve of this correctable defect as the defect prediction development information. The defect threshold range can be set by the user according to the actual usage scenario, and the present application does not make specific limitations on this.

[0071] Among them, in the embodiment of the present application, determining whether there is a correctable defect according to each defect development curve, the defect threshold range of the corresponding defect type, and the preset development trend correction list specifically includes:

[0072] Respectively match each defect development curve with the corresponding defect threshold range to determine whether there is a defect curve segment in the defect development curve according to the first matching result. Among them, each defect index corresponding to the defect curve segment is within the defect threshold range. When it is determined that there is a defect curve segment in the defect development curve, take the corresponding extrusion moment as the correction start moment, and take the moment corresponding to the starting end of the defect curve segment as the correction end moment, so as to determine the standard correction time according to the correction start moment and the correction end moment. Compare the development trend with the preset development trend correction list to determine the time required for correction. When the standard correction time is greater than or equal to the time required for correction, it is determined that the defect prediction information corresponds to a correctable defect.

[0073] That is to say, the present application takes the partial curve segment within the defect threshold range in the defect development curve as the defect curve segment. When the microcontroller determines that there is a defect curve segment in the defect development curve, it will extract the moment corresponding to the starting end of the defect curve segment as the correction end moment, and take the last extrusion moment input into the three-way production simulation model as the correction start moment, and take the time between the correction start moment and the correction end moment as the standard correction time. For example, if the extrusion moment input into the three-way production simulation model is 8:00:00, then the correction start moment is 8:00:00, the preset duration is 10 seconds, and the correction end moment is 8:00:10; another example is that the extrusion moment input into the three-way production simulation model is 9:00:00 - 9:00:10, the correction start moment is 9:00:10, and the correction end moment is 9:00:20.

[0074] The microcontroller will also analyze the defective curve segment to obtain the development trend of the defective curve segment, and compare the development trend with the information in the preset development trend correction list, so as to obtain the time required for correcting the defect corresponding to the defective development curve. The preset development trend correction list contains the corresponding relationship between the development trends of different defect types and the time required for correction. When the microcontroller determines that the above correction standard time is greater than or equal to the obtained time required for correction, the curve corresponding to the defect prediction information is regarded as a correctable defect. That is, the defect correction can be completed within the correction standard time.

[0075] In the case where it is determined that the defective development curve does not have a defective curve segment or the defective development curve has a defective curve segment but the correction standard time is less than the time required for correction, it is determined that there is no correctable defect.

[0076] Specifically, when it is determined that the defective development curve does not have a defective curve segment, it means that there is no defect, and at this time, no defect correction is required. When it is determined that the defective development curve has a defective curve segment and the obtained correction standard time is less than the time required for correction, the microcontroller cannot control each module to complete the defect correction within the correction standard time at this time, and an alarm message can be generated and sent to the user terminal for manual intervention in defect correction. The alarm message can be a sound message, a text message, etc., for example: Serious defects of materials may occur during a certain period. The above situations where no defect correction is required and the defect correction cannot be completed within the correction standard time both mean that there is no correctable defect.

[0077] Through the above solution, it is possible to rely on the microcontroller to automatically perform partial defect correction, without relying too much on manual participation, liberating manpower, and at the same time improving the yield and production efficiency.

[0078] S103. The microcontroller determines the defect correction development information corresponding to the extruded material based on the defect prediction development information and the preset standard operation control parameter information.

[0079] In the embodiment of the present application, the above determining the defect correction development information corresponding to the extruded material based on the defect prediction development information and the preset standard operation control parameter information specifically includes:

[0080] Match the defect prediction development information with the preset defect development samples to determine the control strategy code corresponding to the defect prediction development information according to the corresponding second matching result. Among them, the control strategy code includes the association relationship between the adjustment coefficient set corresponding to the operation control parameters of each operation module of the adjustable three-way extrusion device and the control quality. The control quality characterizes the product quality after the adjustment coefficient set adjusts each operation control parameter. According to the control strategy code, adjust the operation control parameters of each current operation module to obtain the preset standard operation control parameter information. Control the self-correction start time of each operation module to operate with the preset standard operation control parameter information, and obtain the control change information within the preset time length corresponding to the defect prediction development information in real time, so as to determine the defect correction development information when the control change information meets the correction expectation conditions. Among them, the control change information is the defect prediction information obtained within the preset time length after operating with the preset standard operation control parameter information. The correction expectation conditions at least include the disappearance of the correctable defects in the defect prediction information.

[0081] In other words, the microcontroller can store preset defect development samples, and the preset defect development samples include the corresponding relationships with different control strategy codes. The microcontroller matches the defect prediction development information with the preset defect development samples to obtain the control strategy code corresponding to the defect prediction development information. The control strategy code corresponds to an adjustment coefficient set and its control quality. The microcontroller controls each operation module according to the obtained control strategy code, adjusts the corresponding operation control parameters, and thus obtains the preset standard operation control parameter information. Adjusting the operation control parameters includes increasing or decreasing the current parameters. During the correction period, control each operation module to operate with the standard operation control parameters corresponding to the above preset standard operation control parameter information starting from the correction start time. At the same time, the microcontroller will also obtain the control change information within the corresponding preset time length in real time, and judge whether it meets the correction expectation conditions through the control change information, that is, compare the original defect prediction information with the defect prediction information after correcting the operation control parameters, and determine whether the correctable defects in the original defect prediction information become a state where defect correction is not required. If so, the microcontroller uses the control change information and the original defect prediction development information as the defect correction development information.

[0082] Through the above solution, the adjustable correction of correctable defects can be carried out without manual intervention.

[0083] In addition, when performing defect prediction, there may not be only one type of defect in the prediction result, and multiple defects may exist in the form of a defect combination. To avoid the problem that only one defect is corrected during defect correction, resulting in other defects becoming more serious or remaining, ultimately affecting the quality of the finished product, the present application provides the following technical solutions, which specifically include:

[0084] The microcontroller determines whether there are coexisting defects within a predetermined time duration based on the defect prediction information. In the case where it is determined that there are coexisting defects within the predetermined time duration, it determines the correction sub-time intervals corresponding to the respective defect curve segments in the coexisting defects, and determines the overlapping time interval of the respective correction sub-time intervals. According to the respective defect types and defect indices corresponding to the coexisting defects and a preset adjustment weight list, it determines the adjustment sub-weights corresponding to the respective defect types in the coexisting defects. Among them, the sum of the adjustment sub-weights corresponding to the coexisting defects is 1. According to the respective adjustment sub-weights and the adjustment coefficient sets corresponding to the respective defect types, it calculates the corresponding weighted adjustment coefficient sets, and uses the weighted adjustment coefficient sets as the adjustment coefficient sets within the overlapping time interval to adjust the respective operation control parameters corresponding to the overlapping time interval.

[0085] That is to say, the microcontroller can identify coexisting defects through the defect prediction information. If multiple defect types occur within the predetermined time duration, it indicates that there are coexisting defects. At this time, the microcontroller will respectively determine the correction sub-time intervals of the defect curve segments corresponding to the respective defects, and identify the overlapping time interval between the respective correction sub-time intervals. The correction sub-time interval can be understood as the time interval for correcting the defect occurrence time interval with coexisting defects (i.e., the time interval with multiple defect curve segments), and this correction sub-time interval is before the defect occurrence time interval. The microcontroller also stores a preset adjustment weight list of the association relationships between different defect types, different defect indices and preset weights. The defect indices and the preset adjustment weight list can be used to calculate the adjustment sub-weights corresponding to different coexisting defects, which are specifically obtained based on the following calculation method.

[0086] For example, there are n defect types in the coexisting defects, the defect index of each defect type i is D, the preset adjustment weight list is W, and the adjustment sub-weight w in the list i :

[0087]

[0088] Among them, the value range of j is from 1 to n. W i represents the weight corresponding to the defect type i.

[0089] The above adjustment coefficient sets correspond to the defect types, one defect type corresponds to one adjustment coefficient set, and the adjustment coefficient set contains m adjustment coefficients. For example, the adjustment coefficient set C i ={c i1 , c i2 , …, c im}, and the respective adjustment coefficients are used to adjust different operation control parameters. The weighted adjustment coefficient c c weighted,k in the weighted adjustment coefficient set represents the kth weighted adjustment coefficient, and the value range of k is from 1 to m.

[0090] The microcontroller uses the weighted adjustment coefficient set as the adjustment coefficient set corresponding to the coincidence period to adjust each operation control parameter within the coincidence period.

[0091] In addition, when it is determined that there are no coexistence defects within the predetermined duration, only one defect is subjected to the above step S103.

[0092] Through the above solution, multiple coexistence defects can be corrected efficiently, thereby improving the intelligent level of the three-way extrusion production system and the finished product rate.

[0093] S104, the microcontroller sends the defect correction development information and the sequence of extrusion operation parameter groups corresponding to the corresponding correction period as defect correction information to the management terminal, so as to store the defect correction information and the corresponding evaluation label in a preset database based on the feedback evaluation information from the management terminal.

[0094] After the product production is completed, the microcontroller packages the above defect correction development information and the sequence of extrusion operation parameter groups collected during the corresponding correction period as defect correction information and sends it to the management terminal. The management terminal can be understood as the computer of the management personnel or the terminal device of the expert system, and the present application does not make specific limitations thereto.

[0095] In the embodiment of the present application, storing the defect correction information and the corresponding evaluation label in a preset database based on the feedback evaluation information from the management terminal specifically includes:

[0096] The management terminal determines the first score corresponding to the defect correction information based on expert experience. The first score is used to characterize the first predicted product quality after defect correction. The management terminal simulates the defect correction process based on the defect correction information and the three-way production simulation model, and determines the second score of the first extrusion material according to the simulation result. The second score is used to characterize the second predicted product quality obtained based on the three-way production simulation model. The management terminal obtains the finished product appearance information from the user terminal to determine the third score of the first extrusion material according to the finished product appearance information. The management terminal generates feedback evaluation information according to the first comparison result of comparing the first score, the second score and the third score respectively, and the second comparison result of comparing the third score with the preset score threshold, so as to use the third score as the evaluation label and store the defect correction information and the evaluation label in a preset database when the first comparison result in the feedback evaluation information is that the scores are consistent and the second comparison result is that the third score is greater than or equal to the preset score threshold.

[0097] That is to say, the management terminal can analyze the defect correction information relying on expert experience. The management terminal can be connected to the expert system via a network, so as to score the defect correction information with the help of expert experience and obtain a first score given by the expert. At the same time, the management terminal can simulate the defect correction process with the help of the defect correction information and the three-way production simulation model. The simulation result can be the change of the first extruded material in the visualized defect correction process. The operator of the management terminal can score the simulation result to obtain a second score. After obtaining the finished product of the first extruded material, the user terminal can produce the finished product appearance information by taking a picture of the finished product or manual input and send it to the management terminal. The user terminal can be devices such as the mobile phone or computer of the on-site operator, and the present application does not make specific limitations thereon. The operator of the management terminal can perform a third scoring operation based on the finished product appearance information. Subsequently, the management terminal compares whether the above three scores are consistent to obtain a first comparison result, and compares the third score with a preset score threshold to obtain a second comparison result. Combining the first comparison result and the second comparison result, an evaluation label is obtained, and the corresponding defect correction information and evaluation label are screened and stored in a preset database for use as reference data during subsequent production. The above preset score threshold can be set by the user during actual use, and the present application does not make specific limitations thereon. The preset database and the microcontroller can be connected by wire or wirelessly, and the present application does not make specific limitations thereon.

[0098] Through the above solution, a sample library containing high-quality correction cases can be constructed to facilitate subsequent automatic, flexible, and efficient defect correction for other extruded materials without manual intervention.

[0099] S105. After receiving the second extruded material instruction, the microcontroller determines the corresponding defect correction deviation based on the preset database and the extrusion operation parameter group sequence corresponding to the second extruded material, so as to update the preset standard operation control parameter information based on the defect correction deviation and / or send the defect correction deviation to the user terminal, so as to control the operation control parameters of the three-way extrusion device and complete the three-way extrusion production.

[0100] In the embodiment of the present application, the first extruded material and the second extruded material are materials of the same extruded material specification, and the second extruded material can be the next batch of materials after the three-way extrusion device completes the production of the first extruded material.

[0101] In the embodiment of the present application, before determining the corresponding defect correction deviation based on the preset database and the extrusion operation parameter group sequence corresponding to the second extruded material, the method further includes:

[0102] Determine the corresponding defect prediction development information according to the extrusion operation parameter group sequence corresponding to the second extrusion material and the tee production simulation model. According to the defect prediction development information, match the corresponding defect correction information in the preset database to determine the third matching result. The third matching result includes one or more defect correction information and corresponding evaluation labels. According to the evaluation labels, determine the corresponding selected defect correction information, and control the tee extrusion device to extrude the second extrusion material according to the preset standard operation control parameter information corresponding to the selected defect correction information, and record the corresponding defect correction event.

[0103] That is to say, when the microcontroller receives the second extrusion material instruction to extrude the second extrusion material, the microcontroller will execute the above steps S101 - S102 for the second extrusion material. Based on the execution of the above steps S101 - S102, the microcontroller will determine the defect prediction development information corresponding to the second extrusion material, and then determine the defect correction information corresponding to the current defect prediction development information of the second extrusion material in the preset database through a matching operation. If there is matching defect correction information, the selected defect correction information will be obtained according to the matching defect correction information and the value of the evaluation label, for example, selecting the defect correction information corresponding to the evaluation label with the largest value for defect correction. If there is no matching defect correction information, steps S103 - S104 will be executed.

[0104] In the embodiment of the present application, the above determination of the corresponding defect correction deviation based on the preset database and the extrusion operation parameter group sequence corresponding to the second extrusion material specifically includes:

[0105] In the case where there is a defect correction event for the second extrusion material, compare the extrusion operation parameter group sequence corresponding to the corresponding correction period of the second extrusion material with the extrusion operation parameter group sequence corresponding to the selected defect correction information to determine the corresponding correction parameter difference value. The correction parameter difference value is used to characterize the difference degree between the extrusion operation parameter group sequence corresponding to the corresponding correction period of the second extrusion material and the extrusion operation parameter group sequence corresponding to the selected defect correction information. When the correction parameter difference value is greater than the preset threshold, the correction parameter difference value is used as the defect correction deviation.

[0106] In other words, the microcontroller will record in real time the preset standard operation control parameter information corresponding to the second extruded material according to the selected defect correction information that matches, and perform the extrusion operation parameter group sequence when controlling the three-way extrusion device. Then, it will compare the extrusion operation parameter group sequence corresponding to the second extruded material with the extrusion operation parameter group sequence of the selected defect correction information. Thus, according to the comparison result, such as calculating the difference between the corresponding extrusion operation parameters at the same moment, the correction parameter difference value at each corresponding moment in the correction period can be obtained. Next, the correction parameter difference value is compared with the preset threshold. If the correction parameter difference value is greater than the preset threshold, it indicates that a correction deviation has occurred, and this correction parameter difference value is used as the defect correction deviation. The preset threshold can be set by the user according to the actual usage scenario. For example, when the finished product precision requirement is relatively high, the preset threshold is set to 0.95; when the finished product precision requirement is general and the production cycle is short, the preset threshold is set to 0.8, etc. The present application does not make specific limitations on this.

[0107] Through the above technical solutions, on the one hand, the historical correction records can be used for defect correction during subsequent extrusion production, and on the other hand, it can be judged whether there is a defect correction deviation according to the actual production environment, thus avoiding the problem that the defect correction is abnormal due to unknown reasons and affecting the quality of the final finished product.

[0108] In the embodiment of the present application, updating the preset standard operation control parameter information based on the defect correction deviation and / or sending the defect correction deviation to the user terminal specifically includes:

[0109] The microcontroller determines a plurality of preset correction deviation control intervals. Among them, each correction deviation control interval corresponds to a different deviation correction strategy. According to the correction deviation control interval corresponding to the defect correction deviation, the corresponding deviation correction strategy is determined. When the deviation correction strategy includes sending the defect correction deviation to the user terminal, a defect correction prompt message is generated and sent to the selected user terminal. The selected user terminal is the user terminal within the area formed by taking the three-way extrusion device as the center and the preset distance as the radius. The relationship between the preset distance and the defect correction deviation is a negative correlation.

[0110] In other words, after obtaining the above-mentioned defect correction deviation, the microcontroller can match it with the correction deviation control intervals corresponding to different deviation correction strategies, so as to obtain the deviation correction strategy of the defect correction deviation. The deviation correction strategy is, for example, to perform parameter compensation on each operation control parameter, so as to update the preset standard operation control parameter information. The specific compensation value can correspond to different deviation correction strategies and can be specifically set according to the actual production data. The present application does not make specific limitations on this.

[0111] The deviation correction strategy can include both updating the preset standard operation control parameter information and sending the defect correction deviation to the user terminal.

[0112] The deviation correction strategy may also only include sending the defect correction deviation to the user terminal to enable manual intervention for defect correction. At this time, the microcontroller can obtain a predetermined area based on the defect correction deviation and send the defect correction prompt information to the user terminals within the predetermined area, so as to enable manual participation in the defect governance process in a timely manner according to the degree of the defect correction deviation.

[0113] Through the above technical solution, combined with the digital technology application of the three-way production simulation model, the development of defects in the extruded material can be quickly predicted. Based on the defect prediction development information and the preset standard operation control parameter information, this method can automatically generate defect correction development information and send it to the management terminal, realizing the intelligent identification and correction of defects in the production process, and reducing the need for manual intervention. At the same time, defect correction information and evaluation labels are recorded to form a mechanism for continuous learning and improvement. As the production data accumulates, the prediction and correction capabilities of the corresponding system of this application will be continuously improved, improving production efficiency and product quality. This application can also determine the defect correction deviation for the extruded material that relies on historical production data for defect correction, thereby improving production flexibility and intelligent level. It solves the technical problems of insufficient digitalization, automation, and intelligence in the current three-way pipe extrusion process, the need for a large amount of labor costs in the production line, potential safety hazards, and low production efficiency.

[0114] Figure 2 The structural schematic diagram of a digital three-way extrusion production device provided by an embodiment of this application is as Figure 2 shown. The device includes:

[0115] At least one processor. And, a memory communicatively connected to the at least one processor. Wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to:

[0116] After receiving the first extrusion material instruction, the corresponding sequence of extrusion operation parameter groups is determined in real time. Among them, the extrusion operation parameter groups in the sequence of extrusion operation parameter groups at least include the following extrusion operation parameters: motor output torque, extrusion material specification, and real-time extrusion force arm displacement. The real-time sequence of extrusion operation parameter groups is input into the tee production simulation model to determine the defect prediction and development information of the corresponding first extrusion material. Among them, the tee production simulation model is constructed based on historical production records. Based on the defect prediction and development information and the preset standard operation control parameter information, the defect correction and development information corresponding to the extrusion material is determined. The defect correction and development information and the sequence of extrusion operation parameter groups corresponding to the corresponding correction period are sent to the management terminal as defect correction information, so as to store the defect correction information and the corresponding evaluation label in the preset database based on the feedback evaluation information from the management terminal. After receiving the second extrusion material instruction, based on the preset database and the sequence of extrusion operation parameter groups corresponding to the second extrusion material, the corresponding defect correction deviation is determined, so as to update the preset standard operation control parameter information based on the defect correction deviation and / or send the defect correction deviation to the user terminal, so as to control the operation control parameters of the tee extrusion device and complete the tee extrusion production.

[0117] Each embodiment in this application is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0118] The devices provided in the embodiments of this application correspond one by one to the methods. Therefore, the devices also have beneficial technical effects similar to the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices will not be elaborated here.

[0119] It should also be noted that the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, commodity or device. Without further limitation, the element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, commodity or device including the element.

[0120] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A digital tee extrusion production method, characterized in that: The method is applied to a three-way extrusion device driven by a motor, and the method comprises: After receiving the first extrusion material instruction, the corresponding extrusion operation parameter group sequence is determined in real time; wherein the extrusion operation parameter group in the extrusion operation parameter group sequence includes at least the following extrusion operation parameters: motor output torque, extrusion material specifications and real-time extrusion force arm displacement; Inputting the real-time extrusion operation parameter group sequence into a tee production simulation model to determine defect prediction development information of the corresponding first extruded material; wherein the tee production simulation model is constructed based on historical production records; Determining defect correction development information corresponding to the extruded material based on the defect prediction development information and preset standard operation control parameter information; Sending the defect correction development information and the extrusion operation parameter group sequence corresponding to the corresponding correction period to a management terminal as defect correction information, so as to store the defect correction information and the corresponding evaluation label in a preset database based on the feedback evaluation information from the management terminal; After receiving the second extrusion material instruction, the corresponding defect correction deviation is determined based on the preset database and the extrusion operation parameter group sequence corresponding to the second extrusion material, so as to update the preset standard operation control parameter information based on the defect correction deviation and / or send the defect correction deviation to the user terminal, so as to control the operation control parameters of the three-way extrusion device and complete the three-way extrusion production.

2. A digital tee extrusion production method according to claim 1, characterized in that: Inputting the real-time extrusion operation parameter group sequence into the tee production simulation model to determine the defect prediction development information of the corresponding first extrusion material, specifically including: The extrusion operation parameter groups corresponding to each extrusion moment in the extrusion operation parameter group sequence are sequentially input into the tee production simulation model, so as to determine the defect prediction information corresponding to each extrusion moment according to the model output result; wherein the defect prediction information at least includes: defect type, defect location, defect index, and development trend; the defect index is used to quantify the severity of the corresponding defect type; the defect type includes at least one or more of the following: buckling, wrinkling, rupture, and folding; Generate a defect development curve corresponding to each defect prediction information according to the time sequence and the defect type; wherein the abscissa value of the defect development curve is time and the ordinate value is the defect index; the defect development curve includes defect prediction information within a predetermined time after the extrusion moment; Determine whether there is a correctable defect according to each of the defect development curves, the defect threshold interval corresponding to the defect type and the preset development trend correction list; wherein the defect threshold interval is obtained based on the historical defect correction record; the historical defect correction record includes the record information of controlling the operating parameters to eliminate the corresponding defect occurrence event; If so, the defect development curve corresponding to the correctable defect is used as the defect prediction development information.

3. A digital tee extrusion production method according to claim 2, characterized in that: According to each of the defect development curves, the defect threshold interval of the corresponding defect type and the preset development trend correction list, it is determined whether there is a correctable defect, specifically including: Matching each of the defect development curves with the corresponding defect threshold interval respectively, so as to determine whether the defect development curve has a defect curve segment according to a first matching result; wherein each of the defect indexes corresponding to the defect curve segment is within the defect threshold interval; If yes, the corresponding extrusion moment is used as the correction start moment, and the corresponding moment of the starting end of the defect curve segment is used as the correction end moment, so as to determine the correction standard time consumption according to the correction start moment and the correction end moment; Comparing the development trend with a preset development trend correction list to determine the time required for correction; In a case where the correction standard time is greater than or equal to the correction required time, determining that the defect prediction information corresponds to the correctable defect; Otherwise, it is determined that the correctable defect does not exist.

4. A digital tee extrusion production method according to claim 3, characterized in that: Based on the defect prediction development information and the preset standard operation control parameter information, the defect correction development information corresponding to the extruded material is determined, specifically including: Match the defect prediction development information with the preset defect development sample to determine the control strategy code corresponding to the defect prediction development information according to the corresponding second matching result; wherein the control strategy code includes the correlation relationship and control quality of the adjustment coefficient set corresponding to the operation control parameters of each operation module of the three-way extrusion device; the control quality represents the product quality after the adjustment coefficient set adjusts each of the operation control parameters; According to the regulation strategy code, the operation control parameters of each of the current operation modules are adjusted to obtain the preset standard operation regulation parameter information; Control each of the operating modules to operate according to the preset standard operating control parameter information from the start moment of self-correction, and obtain in real time the control change information within a preset time period corresponding to the defect prediction development information, so as to determine the defect correction development information when the control change information meets the expected correction conditions; wherein, the control change information is the defect prediction information obtained within the preset time period after operating based on the preset standard operating control parameter information; and the expected correction conditions include at least the disappearance of the correctable defect in the defect prediction information.

5. A digital tee extrusion production method according to claim 4, characterized in that: The method further comprises: Determining whether there are coexisting defects within the predetermined time period according to the defect prediction information; If yes, determine the correction sub-periods corresponding to the defect curve segments in the coexisting defects, and determine the overlap period of the correction sub-periods; Determine, according to each defect type and each defect index corresponding to the coexisting defect and a preset adjustment weight list, an adjustment sub-weight corresponding to each defect type in the coexisting defect; wherein the sum of each adjustment sub-weight corresponding to the coexisting defect is 1; According to the adjustment coefficient sets corresponding to the weights of the adjustment sub-weights and the defect types, the corresponding weighted adjustment coefficient sets are calculated, and the weighted adjustment coefficient sets are used as the adjustment coefficient sets within the overlap period to adjust the operation control parameters corresponding to the overlap period.

6. A digital tee extrusion production method according to claim 1, characterized in that: Based on the feedback evaluation information from the management terminal, the defect correction information and the corresponding evaluation label are stored in a preset database, specifically including: The management terminal determines a first score corresponding to the defect correction information based on expert experience; the first score is used to characterize a first predicted product quality after the defect is corrected; The management terminal simulates the defect correction process based on the defect correction information and the tee production simulation model, and determines a second score of the first extruded material according to the simulation result; the second score is used to characterize the second predicted product quality obtained based on the tee production simulation model; The management terminal acquires the finished product appearance information from the user terminal to determine a third score of the first extruded material according to the finished product appearance information; The management terminal generates the feedback evaluation information based on a first comparison result of comparing the first score, the second score and the third score respectively, and a second comparison result of comparing the third score with a preset score threshold, so that when the first comparison result in the feedback evaluation information is that the scores are consistent and the second comparison result is that the third score is greater than or equal to the preset score threshold, the third score is used as the evaluation label, and the defect correction information and the evaluation label are stored in the preset database.

7. A digital tee extrusion production method according to claim 1, characterized in that: Before determining the corresponding defect correction deviation based on the preset database and the extrusion operation parameter group sequence corresponding to the second extrusion material, the method further includes: Determining the corresponding defect prediction development information according to the extrusion operation parameter group sequence corresponding to the second extrusion material and the tee production simulation model; According to the defect prediction development information, matching the corresponding defect correction information in the preset database to determine a third matching result; the third matching result includes one or more defect correction information and the corresponding evaluation label; According to the evaluation label, the corresponding selected defect correction information is determined, so as to control the three-way extrusion device to extrude the second extrusion material according to the preset standard operation adjustment parameter information corresponding to the selected defect correction information, and record the corresponding defect correction event.

8. A digital tee extrusion production method according to claim 7, characterized in that: Based on the preset database and the extrusion operation parameter group sequence corresponding to the second extrusion material, determining the corresponding defect correction deviation specifically includes: In the case where the defect correction event exists in the second extruded material, the extrusion operating parameter group sequence corresponding to the correction period of the second extruded material is compared with the extrusion operating parameter group sequence corresponding to the selected defect correction information to determine a corresponding correction parameter difference value; wherein the correction parameter difference value is used to represent the degree of difference between the extrusion operating parameter group sequence corresponding to the correction period of the second extruded material and the extrusion operating parameter group sequence corresponding to the selected defect correction information; When the correction parameter difference value is greater than a preset threshold, the correction parameter difference value is used as the defect correction deviation.

9. A digital tee extrusion production method according to claim 1, characterized in that: Updating the preset standard operation control parameter information based on the defect correction deviation and / or sending the defect correction deviation to the user terminal specifically includes: Determining a plurality of preset deviation correction control intervals; wherein each of the deviation correction control intervals corresponds to a different deviation correction strategy; Determining the corresponding deviation correction strategy according to the correction deviation control interval corresponding to the defect correction deviation; When the deviation correction strategy includes sending the defect correction deviation to the user terminal, defect correction prompt information is generated and sent to the selected user terminal; wherein the selected user terminal is the user terminal in an area with a preset distance as the radius centered on the three-way extrusion device; the relationship between the preset distance and the defect correction deviation is a negative correlation.

10. A digital three-way extrusion production equipment, characterized in that: The device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a digital tee extrusion production method as described in any one of claims 1 to 9.

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