Digital tee joint extrusion production method and equipment

Abstract

The invention provides a digital tee joint extrusion production method and equipment, and belongs to the technical field of tee joint extrusion production control. The method comprises the following steps: determining a corresponding extrusion operation parameter group sequence in real time; and inputting the extrusion operation parameter group sequence into the three-way production simulation model to determine defect prediction development information. Determining defect correction development information based on the defect prediction development information and preset standard operation regulation and control parameter information; and sending the defect correction development information and the extrusion operation parameter group sequence of the correction time period to a management terminal as defect correction information, so as to store the defect correction information and the evaluation label to a preset database based on the feedback evaluation information. And when a second extrusion material instruction is received, determining a defect correction deviation based on a preset database and the extrusion operation parameter group sequence of the second extrusion material, and updating preset standard operation regulation and control parameter information and / or sending the defect correction deviation to the user terminal based on the defect correction deviation so as to control the three-way extrusion device to produce.

Description

Technical Field

[0001] The present application relates to the technical field of tee extrusion production control, and in particular to a digital tee extrusion production method and equipment. Background Art

[0002] In the existing technology, three-way pipe extrusion is all driven by a hydraulic extrusion mechanism, the process has high energy consumption, the accuracy and adjustment of the hydraulic mechanism are poor, the extrusion process has high energy consumption, relies on manual assistance, has safety hazards, and the efficiency cannot meet the current needs of digital production line upgrades.

[0003] With the rapid development of intelligent manufacturing, the market's requirements for the digitization, automation and intelligence of extrusion processes are constantly increasing. It is necessary to provide a more intelligent and efficient production method to reduce manpower input, ensure the personal safety of employees, and improve the yield and production efficiency. Summary of the invention

[0004] The embodiments of the present application provide a digital three-way extrusion production method and equipment, which are used to solve the technical problems that the current three-way pipe extrusion process is insufficiently digitalized, automated and intelligent, the production line requires a large amount of manpower costs, and there are safety hazards and low production efficiency.

[0005] On the one hand, an embodiment of the present application provides a digital three-way extrusion production method, which is applied to a three-way extrusion device driven by a motor, and the method includes:

[0006] 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;

[0007] 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;

[0008] Determining defect correction development information corresponding to the extruded material based on the defect prediction development information and preset standard operation control parameter information;

[0009] 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;

[0010] After receiving the second extrusion material instruction, the corresponding defect correction deviation is determined based on the preset database and the extrusion operating parameter group sequence corresponding to the second extrusion material, so as to update the preset standard operating 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 operating parameters of the three-way extrusion device and complete the three-way extrusion production.

[0011] In one implementation of the present application, the real-time extrusion operation parameter group sequence is input into the tee production simulation model to determine the defect prediction development information of the corresponding first extruded material, specifically including:

[0012] 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;

[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 defect prediction information within a predetermined time after the extrusion moment;

[0014] 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; 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 operation control parameters to eliminate the corresponding defect occurrence event;

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

[0016] In one implementation of the present application, determining whether there is a correctable defect based on each of the defect development curves, the defect threshold interval of the corresponding defect type, and the preset development trend correction list specifically includes:

[0017] 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;

[0018] 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;

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

[0020] 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;

[0021] Otherwise, it is determined that the correctable defect does not exist.

[0022] In one implementation of the present application, 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:

[0023] 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;

[0024] 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;

[0025] 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.

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

[0027] Determining whether there are coexisting defects within the predetermined time period according to the defect prediction information;

[0028] 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;

[0029] 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;

[0030] 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.

[0031] In one implementation 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:

[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 a first predicted product quality after the defect is corrected;

[0033] 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;

[0034] 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;

[0035] 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.

[0036] In an implementation 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 extrusion material, the method further includes:

[0037] 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;

[0038] 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;

[0039] 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.

[0040] In one implementation of the present application, 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:

[0041] 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;

[0042] When the correction parameter difference value is greater than a preset threshold, the correction parameter difference value is used as the defect correction deviation.

[0043] In one implementation of the present application, the preset standard operation control parameter information is updated based on the defect correction deviation and / or the defect correction deviation is sent 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, specifically including:

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

[0045] Determining the corresponding deviation correction strategy according to the correction deviation control interval corresponding to the defect correction deviation;

[0046] 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.

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

[0048] At least one processor; and a memory in communication with 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 above.

[0049] Compared with the prior art, the present invention has the following significant effects:

[0050] Through the above technical scheme, combined with the application of digital technology of the tee production simulation model, the defect development of the extruded material can be quickly predicted. Based on the defect prediction development information and the preset standard operation control parameter information, the 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, reducing the need for manual intervention. At the same time, the defect correction information and evaluation labels are recorded to form a mechanism for continuous learning and improvement. With the accumulation of production data, the prediction and correction capabilities of the corresponding system of this application will continue to improve, thereby improving production efficiency and product quality. The present application can also determine the defect correction deviation for extruded materials that rely on historical production data for defect correction, thereby improving production flexibility and intelligence. It solves the current technical problems of insufficient digitization, automation and intelligence of the tee pipe extrusion process, the need to invest a lot of manpower costs in the production line, 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 constitute 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 on the present application. In the drawings:

[0052] Figure 1 A schematic diagram of a process of a digital tee extrusion production method in an embodiment of the present application;

[0053] Figure 2 This is a structural schematic diagram of a digital tee extrusion production equipment in an embodiment of the present application. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0055] The embodiments of the present application provide a digital tee extrusion production method and equipment to solve the technical problems that the current tee pipe extrusion process is insufficiently digitalized, automated and intelligent, the production line requires a large amount of manpower costs, there are safety hazards and low production efficiency.

[0056] The following describes in detail various embodiments of the present application in conjunction with the accompanying drawings.

[0057] The embodiment of the present application provides a digital tee extrusion production method, which is applied to a motor-driven tee extrusion device, which is driven by a motor to perform tee pipe extrusion production work, and no longer relies on hydraulic equipment to perform tee pipe extrusion. Figure 1 As shown, the method may include steps S101-S105:

[0058] S101, after receiving the first extrusion material instruction, the microcontroller determines the corresponding extrusion operation parameter group sequence in real time.

[0059] 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.

[0060] It should be noted that the microcontroller, as the executor of the digital three-way extrusion production method, is only an example. The executor is not limited to the microcontroller, and this application does not make specific restrictions on this. The microcontroller described in this application is arranged inside the above-mentioned three-way extrusion device to drive the operation of various modules, such as the drive motor, the cooling module, the laser displacement sensor for measuring the displacement of the extrusion force arm, and the camera for collecting the rules of the extruded material. If the executor is a server, the server is connected to the three-way extrusion device by wire or wirelessly to drive the operation of various modules.

[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. The instruction can be generated after the first extrusion material enters the extrusion area and completes the extrusion preparation work through a sensor such as a camera, or it can be an instruction sent by an operator. This application does not make specific limitations on this.

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

[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 may include several extrusion operation parameter groups and marked defect information labels manually recorded when the tee extrusion device produced the tee pipe in the past. The defect information labels include defect type, defect location, defect index and development trend. The development trend is the development relationship of defect severity deduced according to several historical extrusion operation parameter group sequences and corresponding defect indexes in the historical production process. The tee production simulation model is constructed based on the above-mentioned large number of historical production records by training machine learning or deep learning algorithms. 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 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 to which the corresponding defect affects the quality of the final product. The product of the defect score and the defect weight is the defect index; by setting the defect weight, all defect types can maintain 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 extrusion material specifically includes:

[0067] 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 to determine the defect prediction information corresponding to each extrusion moment according to the model output result. Among them, the defect prediction information includes at least: 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. According to the time sequence and defect type, a defect development curve corresponding to each defect prediction information is generated. Among them, the horizontal coordinate value of the defect development curve is time, and the vertical coordinate value is the defect index. The defect development curve includes defect prediction information within a predetermined time after the extrusion moment. According to each defect development curve, 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. Among them, the defect threshold interval is obtained based on the historical defect correction record. The historical defect correction record includes the record information of the control operation control parameters to eliminate the corresponding defect occurrence event. And when it is determined that there is a correctable defect, the defect development curve corresponding to the correctable defect 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 to perform 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 a time. Multiple extrusion moments can be set by the user so that the same model prediction can be performed at a certain frequency to avoid errors in single data. For example, one extrusion moment is 1 second, and multiple extrusion moments are 5 seconds, 10 seconds or 15 seconds, etc. This application does not make specific limitations on this.

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

[0070] Furthermore, the present application pre-sets defect threshold intervals for different defect types. The defect threshold interval can be understood as when the curve value of the defect development curve of the corresponding defect type reaches the defect threshold interval, it means that the defect has reached a 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 judges that there is a correctable defect when the correctable conditions are met. At this time, the microcontroller uses the defect development curve of the correctable defect as defect prediction development information. The defect threshold interval can be set by the user according to the actual usage scenario, and the present application does not make specific restrictions on this.

[0071] Among them, in the embodiment of the present application, the above-mentioned determination of whether there is a correctable defect based on each defect development curve, the defect threshold interval of the corresponding defect type and the preset development trend correction list specifically includes:

[0072] 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. Among them, each defect index corresponding to the defect curve segment is within the defect threshold interval. In the case of determining that there is a defect curve segment in the defect development curve, the corresponding extrusion moment is used as the correction start moment, and the moment corresponding to the starting end of the defect curve segment is used as the correction end moment, so as to determine the correction standard 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. In the case where the correction standard time is greater than or equal to the correction time, it is determined that the defect prediction information corresponds to a correctable defect.

[0073] That is to say, the present application regards the partial curve segments in the defect development curve that are in the defect threshold interval as defect curve segments. If the microcontroller determines that there is a defect curve segment in the defect development curve, the corresponding moment of the starting end of the defect curve segment is extracted as the correction end moment, and the last extrusion moment input into the tee production simulation model is used as the correction start moment, and the time between the correction start moment and the correction end moment is used as the correction standard time consumption. For example, if the extrusion moment input into the tee production simulation model is 8:00:00, then the correction start moment is 8:00:00, and the predetermined duration is 10 seconds, then the correction end moment is 8:00:10; for another example, if the extrusion moment input into the tee 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 defect curve segment to obtain the development trend of the defect curve segment, and compare the development trend with the information in the preset development trend correction list to obtain the time required to correct the defect corresponding to the defect development curve. The preset development trend correction list contains the corresponding relationship between the development trend 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 above correction time required, 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] When it is determined that there is no defect curve segment in the defect development curve or there is a defect curve segment in the defect development curve 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 there is no defect curve segment in the defect development curve, it means that there is no defect, and there is no need to correct the defect at this time. When it is determined that there is a defect curve segment in the defect development curve, 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, then an alarm message can be generated and sent to the user terminal for manual intervention to correct the defect. The alarm message can be a sound message, a text message, etc., for example: a certain period of time may cause serious defects in the material. The above-mentioned absence of defect correction and the inability to complete defect correction within the correction standard time both mean that there is no correctable defect.

[0077] Through the above solution, the microcontroller can be relied upon to automatically correct some defects without over-reliance on manual participation, thus freeing up manpower and improving yield and production efficiency.

[0078] S103, the microcontroller determines 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 defect correction development information corresponding to the extruded material is determined based on the defect prediction development information and the preset standard operation control parameter information, specifically including:

[0080] The defect prediction development information is matched 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. 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 characterizes the product quality after the adjustment coefficient set adjusts each operation control parameter. According to the control strategy code, the operation control parameters of each current operation module are adjusted to obtain the preset standard operation control parameter information. Each operation module is controlled to operate with the preset standard operation control parameter information from the start time of self-correction, and the control change information within the predetermined time period corresponding to the defect prediction development information is obtained in real time, so as to determine the defect correction development information when the control change information meets the expected correction conditions. The control change information is the defect prediction information obtained within the predetermined time period after the operation based on the preset standard operation control parameter information. The expected correction 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, which contain corresponding relationships with different control strategy codes. The microcontroller matches the defect prediction development information with the preset defect development samples, thereby obtaining the control strategy code corresponding to the defect prediction development information. The control strategy code corresponds to a set of adjustment coefficients and its control quality. The microcontroller controls each operation module according to the control strategy code obtained by matching, 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, each operation module is controlled to operate with the standard operation control parameters corresponding to the above-mentioned preset standard operation control parameter information from the start time of correction. At the same time, the microcontroller will also obtain the control change information within the corresponding predetermined time in real time, and judge whether the expected correction conditions are met 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 have 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 defect correction development information.

[0082] Through the above scheme, correctable defects can be regulated and corrected without human intervention.

[0083] In addition, when predicting defects, the prediction result may not only contain one defect, but multiple defects may exist in the form of defect combinations. In order to avoid the problem that only one defect is corrected during defect correction, which causes other defects to become more serious or continue to exist, and ultimately affects the quality of the finished product, the present application provides the following technical solutions, including:

[0084] The microcontroller determines whether there are coexisting defects within a predetermined time period based on the defect prediction information. When it is determined that there are coexisting defects within the predetermined time period, the correction sub-periods corresponding to each defect curve segment in the coexisting defects are determined, and the overlap period of each correction sub-period is determined. According to each defect type and each defect index corresponding to the coexisting defect and the preset adjustment weight list, the adjustment sub-weight corresponding to each defect type in the coexisting defect is determined. Among them, the sum of each adjustment sub-weight corresponding to the coexisting defect is 1. According to each adjustment sub-weight and the adjustment coefficient set corresponding to each defect type, the corresponding weighted adjustment coefficient set is calculated, and the weighted adjustment coefficient set is used as the adjustment coefficient set in the overlap period to adjust each operation control parameter corresponding to the overlap period.

[0085] That is to say, the microcontroller can identify coexisting defects through defect prediction information. If multiple defect types appear within a predetermined time period, it means that there are coexisting defects. At this time, the microcontroller will respectively determine the correction sub-periods of the defect curve segments corresponding to each defect, and identify the overlapping time periods between each correction sub-period. The correction sub-period can be understood as a time period for correcting the defect occurrence period (i.e., the time period when there are multiple defect curve segments) in which the coexisting defect exists, and the correction sub-period is before the defect occurrence period. The microcontroller also stores a preset adjustment weight list of the association between different defect types, different defect indices and preset weights. The defect index and the preset adjustment weight list can 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 coexisting defects, the defect index of each defect type i is D, the preset adjustment weight list is W, and the adjustment sub-weight in the list is w i :

[0087]

[0088] Wherein, j ranges from 1 to n. i Represents the weight corresponding to defect type i.

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

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

[0091] In addition, when it is determined that there are no coexisting defects within the predetermined time period, the above step S103 is performed only for one defect.

[0092] Through the above scheme, multiple coexisting defects can be corrected efficiently, thereby improving the intelligence level of the tee extrusion production system and increasing the yield rate.

[0093] S104, the microcontroller sends the defect correction development information and the extrusion operation parameter group sequence corresponding to the corresponding correction period to the 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.

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

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

[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 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 the 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 obtains the finished product appearance information from the user terminal to determine the third score of the first extruded material according to the finished product appearance information. The management terminal generates feedback evaluation information based on the first comparison result of comparing the first score, the second score and the third score, and the second comparison result of comparing the third score with the preset score threshold, so that when the first comparison result in the feedback evaluation information is consistent in the score 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.

[0097] That is to say, the management terminal can analyze the defect correction information based on expert experience, and the management terminal can be connected to the expert system through a network, so as to score the defect correction information with the help of expert experience, and obtain the first score scored 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, and the simulation result can be the change of the first extruded material in the visual defect correction process. The operator of the management terminal can score the simulation result to obtain the second score. After obtaining the finished product of the first extruded material, the user terminal can take the finished product image or manually input the finished product appearance information and send it to the management terminal. The user terminal can be a mobile phone, computer or other device of the on-site operator, and this application does not make specific restrictions on this. 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 the first comparison result, and compares the third score with the preset score threshold to obtain the second comparison result. Based on the first comparison result and the second comparison result, an evaluation label is obtained, and the corresponding defect correction information and evaluation labels are screened and stored in the preset database for use as reference data in subsequent production. The preset scoring threshold can be set by the user in actual use, and this application does not make any specific restrictions on this. The preset database and the microcontroller can be connected via wired or wireless means, and this application does not make any specific restrictions on this.

[0098] Through the above solution, a sample library containing high-quality correction cases can be built to facilitate automatic, flexible and efficient defect correction of other extruded materials in the future without human intervention.

[0099] S105, after receiving the second extrusion 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 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.

[0100] In the embodiment of the present application, the first extrusion material and the second extrusion material are materials of the same extrusion material specification, and the second extrusion material may be the next batch of materials after the three-way extrusion device completes the production of the first extrusion 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 extrusion material, the method further includes:

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

[0103] That is to say, when the microcontroller receives the second extrusion material instruction for extruding 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 defect correction information corresponding to the evaluation tag with the largest value, for example, will be selected according to the matched defect correction information and the numerical value of the evaluation tag, so as to obtain the selected defect correction information for defect correction. If there is no matching defect correction information, execute steps S103-S104.

[0104] In the embodiment of the present application, the above-mentioned 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 in the second extruded material, the extrusion operation parameter group sequence corresponding to the corresponding correction period of the second extruded material is compared 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 degree of difference between the extrusion operation parameter group sequence corresponding to the corresponding correction period of the second extruded material and the extrusion operation parameter group sequence corresponding to the selected defect correction information. In the case where the correction parameter difference value is greater than a 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 selected defect correction information of the second extruded material, and control the extrusion operation parameter group sequence when the three-way extrusion device is controlled, and the extrusion operation parameter group sequence corresponding to the second extruded material is compared with the extrusion operation parameter group sequence of the selected defect correction information, so as to obtain the correction parameter difference value corresponding to each moment in the correction period according to the comparison result, such as calculating the difference between the corresponding extrusion operation parameters at the same time. Then, the correction parameter difference value is compared with the preset threshold value. If the correction parameter difference value is greater than the preset threshold value, it means that a correction deviation has occurred, and the correction parameter difference value is used as the defect correction deviation. The preset threshold value can be set by the user according to the actual use scenario. For example, if the finished product precision requirement is high, the preset threshold value is set to 0.95; if the finished product precision requirement is general and the production cycle is short, the preset threshold value is set to 0.8, etc. This application does not make specific restrictions on this.

[0107] Through the above technical solution, on the one hand, historical correction records can be used to correct defects in subsequent extrusion production, and on the other hand, it can be judged whether there is a defect correction deviation based on the actual production environment, thereby avoiding abnormalities in defect correction due to unknown reasons, which affects the quality of the final product.

[0108] In the embodiment of the present application, the above-mentioned updating of 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 pre-set correction deviation control intervals. 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, a corresponding deviation correction strategy is determined. 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. The selected user terminal is a user terminal in an area with a preset distance as a radius centered on the three-way extrusion device. The preset distance is negatively correlated with the defect correction deviation.

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

[0111] The deviation correction strategy may 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 so that manual intervention can be performed for defect correction. In this case, the microcontroller can obtain a predetermined area through the defect correction deviation and send defect correction prompt information to the user terminal in the predetermined area, so that manual intervention can be performed for defect management in a timely manner according to the degree of defect correction deviation.

[0113] Through the above technical scheme, combined with the application of digital technology of the tee production simulation model, the defect development of the extruded material can be quickly predicted. Based on the defect prediction development information and the preset standard operation control parameter information, the 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, reducing the need for manual intervention. At the same time, the defect correction information and evaluation labels are recorded to form a mechanism for continuous learning and improvement. With the accumulation of production data, the prediction and correction capabilities of the corresponding system of this application will continue to improve, thereby improving production efficiency and product quality. The present application can also determine the defect correction deviation for extruded materials that rely on historical production data for defect correction, thereby improving production flexibility and intelligence. It solves the current technical problems of insufficient digitization, automation and intelligence of the tee pipe extrusion process, the need to invest a lot of manpower costs in the production line, safety hazards and low production efficiency.

[0114] Figure 2 A structural schematic diagram of a digital three-way extrusion production equipment provided in an embodiment of the present application, such as Figure 2 As shown, the device includes:

[0115] At least one processor. And a memory in communication with the at least one processor. 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 extrusion operation parameter group sequence is determined in real time. Among them, 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. The real-time extrusion operation parameter group sequence is input into the tee production simulation model to determine the defect prediction 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 development information and the preset standard operation control parameter information, the defect correction development information corresponding to the extrusion material is determined. The defect correction development information and the extrusion operation parameter group sequence corresponding to the corresponding correction period are sent to the management terminal as defect correction information, so that the defect correction information and the corresponding evaluation label are stored 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 extrusion operation parameter group sequence corresponding to the second extrusion material, the corresponding defect correction deviation is determined, so that the preset standard operation control parameter information is updated based on the defect correction deviation and / or the defect correction deviation is sent 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, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0118] The device and method provided in the embodiments of the present application correspond one to one, and therefore, the device also has similar beneficial technical effects as its corresponding method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the device will not be repeated here.

[0119] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0120] The above is only the embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in 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 control strategy code, the operation control parameters of each of the current operation modules are adjusted to obtain the preset standard operation control 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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