CN118906426B - A melt plasticizing extrusion control method and system - Google Patents
A melt plasticizing extrusion control method and system Download PDFInfo
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- CN118906426B CN118906426B CN202411390522.7A CN202411390522A CN118906426B CN 118906426 B CN118906426 B CN 118906426B CN 202411390522 A CN202411390522 A CN 202411390522A CN 118906426 B CN118906426 B CN 118906426B
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- 238000001125 extrusion Methods 0.000 title claims abstract description 97
- 238000000034 method Methods 0.000 title claims abstract description 31
- 239000000155 melt Substances 0.000 title claims description 31
- 238000002844 melting Methods 0.000 claims abstract description 166
- 230000008018 melting Effects 0.000 claims abstract description 166
- 238000012544 monitoring process Methods 0.000 claims abstract description 70
- 230000008859 change Effects 0.000 claims abstract description 64
- 238000012545 processing Methods 0.000 claims abstract description 11
- 238000010438 heat treatment Methods 0.000 claims description 29
- 239000002994 raw material Substances 0.000 claims description 27
- 238000009826 distribution Methods 0.000 claims description 19
- 238000012360 testing method Methods 0.000 claims description 11
- 238000004458 analytical method Methods 0.000 claims description 10
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 claims description 8
- 229910052782 aluminium Inorganic materials 0.000 claims description 8
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000013507 mapping Methods 0.000 claims description 5
- 238000004140 cleaning Methods 0.000 claims description 4
- 238000000605 extraction Methods 0.000 claims description 4
- 230000000694 effects Effects 0.000 abstract description 8
- 230000008569 process Effects 0.000 description 5
- 238000012549 training Methods 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 4
- 238000012986 modification Methods 0.000 description 4
- 230000004048 modification Effects 0.000 description 4
- 238000012937 correction Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000013527 convolutional neural network Methods 0.000 description 1
- 238000002425 crystallisation Methods 0.000 description 1
- 230000008025 crystallization Effects 0.000 description 1
- 238000013075 data extraction Methods 0.000 description 1
- 235000012438 extruded product Nutrition 0.000 description 1
- 238000011049 filling Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000010309 melting process Methods 0.000 description 1
- 238000001304 sample melting Methods 0.000 description 1
- 230000010512 thermal transition Effects 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C48/00—Extrusion moulding, i.e. expressing the moulding material through a die or nozzle which imparts the desired form; Apparatus therefor
- B29C48/25—Component parts, details or accessories; Auxiliary operations
- B29C48/92—Measuring, controlling or regulating
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C2948/00—Indexing scheme relating to extrusion moulding
- B29C2948/92—Measuring, controlling or regulating
- B29C2948/92504—Controlled parameter
- B29C2948/92695—Viscosity; Melt flow index [MFI]; Molecular weight
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C2948/00—Indexing scheme relating to extrusion moulding
- B29C2948/92—Measuring, controlling or regulating
- B29C2948/92504—Controlled parameter
- B29C2948/92704—Temperature
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- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Extrusion Moulding Of Plastics Or The Like (AREA)
Abstract
The invention discloses a method and a system for controlling melt plasticizing extrusion, and relates to the technical field of plastic processing, wherein the method comprises the steps of monitoring plasticizing extrusion quality of a target product of a target extruder in a preset monitoring window, and generating an extrusion quality recording sequence; determining extrusion quality fluctuation factors, obtaining K heat change curves, generating a melting temperature interval of a target product, generating a target melting temperature interval, performing temperature monitoring to obtain a monitoring temperature set, determining a target melting temperature deviation value, performing control parameter configuration according to the target melting temperature deviation value to obtain a target control parameter set, and transmitting the target control parameter set to a control unit of a target extruder for parameter adjustment. The invention solves the technical problem of poor extrusion quality caused by inaccurate determination of the melting temperature interval of the product in the prior art, and achieves the technical effect of improving the accuracy of melting plasticizing extrusion control.
Description
Technical Field
The invention relates to the technical field of plastic processing, in particular to a melting plasticizing extrusion control method and a melting plasticizing extrusion control system.
Background
In the production of plastic products, plasticization extrusion is a critical process. However, if the melting temperature interval of the product is not accurately determined at the time of plasticizing extrusion, poor extrusion quality may result. In addition, the unstable melting temperature also causes inconsistent extrusion speed, further affecting the dimensional accuracy and appearance quality of the product. Therefore, precise control of the melting temperature interval of the plastic is an important element in ensuring the quality of the extruded product. At present, when the melting plasticization extrusion control is performed, the melting temperature interval of a product is not accurately determined, and the extruder cannot be adaptively adjusted and controlled, so that the extrusion quality is poor.
Disclosure of Invention
The application provides a melting plasticizing extrusion control method and a melting plasticizing extrusion control system, which are used for solving the technical problem of poor extrusion quality caused by inaccurate determination of a product melting temperature interval in the prior art.
In view of the above, the present application provides a melt plasticizing extrusion control method and system.
In a first aspect of the present application, there is provided a melt plasticization extrusion control method, the method comprising:
Performing plasticizing extrusion quality monitoring of a target product of a target extruder in a preset monitoring window to generate an extrusion quality recording sequence;
Analyzing the extrusion quality record sequence based on a preset melting quality index, and determining an extrusion quality fluctuation factor according to an analysis result;
Carrying out melting temperature test on K product raw material samples by using a differential scanning calorimeter to obtain K heat change curves, and carrying out scattered point edge identification on the K heat change curves to generate a melting temperature interval of the target product;
correcting the melting temperature interval based on the extrusion quality fluctuation factor to generate a target melting temperature interval;
Continuously monitoring the temperature of a melting zone of the target extruder in a preset continuous monitoring window to obtain a monitoring temperature set;
Determining a target melting temperature deviation value based on the monitored temperature set and the target melting temperature interval, and performing control parameter configuration according to the target melting temperature deviation value to obtain a target control parameter set, wherein the target control parameter comprises heating temperature, heating time and melting pressure;
And transmitting the target control parameter set to a control unit of a target extruder for parameter adjustment.
In a second aspect of the present application, there is provided a melt plasticizing extrusion control system, the system comprising:
the extrusion quality record sequence generation module is used for executing plasticization extrusion quality monitoring of a target product of the target extruder in a preset monitoring window to generate an extrusion quality record sequence;
The extrusion quality fluctuation factor determining module is used for analyzing the extrusion quality record sequence based on a preset melting quality index and determining an extrusion quality fluctuation factor according to an analysis result;
The melting temperature interval generation module is used for carrying out melting temperature test on K product raw material samples by utilizing a differential scanning calorimeter to obtain K heat change curves, carrying out scattered point edge identification on the K heat change curves, and generating a melting temperature interval of the target product;
the target melting temperature interval generation module is used for correcting the melting temperature interval based on the extrusion quality fluctuation factor to generate a target melting temperature interval;
The monitoring temperature set obtaining module is used for continuously monitoring the temperature of the melting zone of the target extruder in a preset continuous monitoring window to obtain a monitoring temperature set;
The target control parameter set obtaining module is used for determining a target melting temperature deviation value based on the monitored temperature set and the target melting temperature interval, and carrying out control parameter configuration according to the target melting temperature deviation value to obtain a target control parameter set, wherein the target control parameter set comprises heating temperature, heating time and melting pressure;
and the parameter adjustment module is used for transmitting the target control parameter set to a control unit of the target extruder for parameter adjustment.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
according to the application, plasticizing extrusion quality monitoring of a target product of a target extruder is performed in a preset monitoring window to generate an extrusion quality recording sequence, then the extrusion quality recording sequence is analyzed based on a preset melting quality index, extrusion quality fluctuation factors are determined according to analysis results, and then K raw material samples of the product are subjected to melting temperature testing by utilizing a differential scanning calorimeter to obtain K heat change curves, scattered point edge identification is performed on the K heat change curves to generate a melting temperature interval of the target product, the melting temperature interval is corrected based on the extrusion quality fluctuation factors to generate a target melting temperature interval, then the melting area of the target extruder is continuously subjected to temperature monitoring in the preset continuous monitoring window to obtain a monitoring temperature set, a target melting temperature deviation value is determined based on the monitoring temperature set and the target melting temperature interval, and a target control parameter set is obtained according to control parameter configuration of the target melting temperature deviation value, wherein the target control parameters comprise heating temperature, heating time and melting pressure, and then the target control parameter set is transmitted to a control unit of the target extruder for parameter adjustment. The technical effects of improving the control reliability of parameters and improving the quality of melt plasticization extrusion are achieved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a melt plasticizing extrusion control method according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a melt plasticizing extrusion control system according to an embodiment of the present application.
Reference numerals indicate that the extrusion quality record sequence generating module 11, the extrusion quality fluctuation factor determining module 12, the melting temperature interval generating module 13, the target melting temperature interval generating module 14, the monitoring temperature set obtaining module 15, the target control parameter set obtaining module 16 and the parameter adjusting module 17.
Detailed Description
The application provides a melting plasticizing extrusion control method and a melting plasticizing extrusion control system, which are used for solving the technical problem of poor extrusion quality caused by inaccurate determination of a product melting temperature interval in the prior art.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that the terms "comprises" and "comprising" are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
Example 1
As shown in fig. 1, the present application provides a melt plasticizing extrusion control method, wherein the method includes:
Step 100, performing plasticizing extrusion quality monitoring of a target product of a target extruder in a preset monitoring window to generate an extrusion quality recording sequence;
In one possible embodiment, in order to analyze the fluctuation degree of the quality of the product processed by the production of the target extruder, the processed product is subjected to plasticizing extrusion quality monitoring within a preset monitoring window, and key parameters and quality indexes are recorded in the monitoring process, so as to generate the extrusion quality recording sequence. The preset monitoring window is a monitoring time period set by a person skilled in the art, for example, a monitoring window is set from 10 th minute to 60 th minute after the extruder is started, and the extruder reaches a stable working state and continuously produces target products.
The monitoring equipment such as a temperature sensor, a pressure sensor and the like is arranged at key parts (such as an extruder head, a die and the like) of the extruder and is used for recording key parameters such as temperature, pressure and the like in the extrusion process in real time. And simultaneously, recording data such as melt index of the produced product, and arranging the recorded data according to time sequence to obtain the extrusion quality recording sequence. The technical effect of correcting the melting temperature interval for the actual production condition of the subsequent combined extruder and providing basic analysis data is achieved.
Step 200, analyzing the extrusion quality record sequence based on a preset melting quality index, and determining an extrusion quality fluctuation factor according to an analysis result;
Further, the preset melt quality index includes a melt index, a thermal stability, and a melt viscosity.
In one embodiment, the extrusion quality recording sequence is subjected to data extraction by taking the preset melt quality index as an index to obtain a melt index set, a thermal stability set and a melt viscosity set. And respectively carrying out variance calculation on the melt index set, the thermal stability set and the melt viscosity set, and taking calculation results as a melt index fluctuation factor, a thermal stability fluctuation factor and a melt viscosity fluctuation factor. The larger the variance, the greater the volatility of the corresponding index, the poorer the extruder production stability.
The melt index refers to the mass of the melt flowing out of the molten plastic in unit time of passing through the die head at a preset temperature and a preset load. The thermal stability is the ability of a plastic to retain its properties at high temperatures. The melt viscosity is the viscosity of the plastic in a molten state.
And carrying out weighted calculation on the melt index fluctuation factor, the thermal stability fluctuation factor and the melt viscosity fluctuation factor according to a weight ratio preset by a person skilled in the art, and taking a weighted calculation result as the extrusion quality fluctuation factor. The technical effect of quantifying the working stability of the extruder is achieved.
S300, carrying out melting temperature test on K product raw material samples by using a differential scanning calorimeter to obtain K heat change curves, and carrying out scattered point edge identification on the K heat change curves to generate a melting temperature interval of the target product;
Further, the melting temperature test is performed on K product raw material samples by using a differential scanning calorimeter to obtain K heat change curves, and step S300 of the embodiment of the present application further includes:
placing the K product raw material samples in an aluminum crucible, and placing the aluminum crucible in a sample frame of a differential scanning calorimeter for completing baseline calibration;
heating K raw material samples of the product according to a preset heating rate until reaching a preset heating temperature, and leading out a record curve of a differential scanning calorimeter to generate K initial heat change curves;
And traversing the K initial heat change curves to perform data cleaning, and determining the K heat change curves.
In one possible embodiment, in order to determine the melting temperature interval of the raw material of the target product in the extruder, K samples of the raw material of the product are first tested to determine the melting temperature interval that corresponds to the condition of the raw material itself. The differential scanning calorimeter is an instrument for measuring the temperature and heat flow relation related to the internal thermal transition of a material. The K product raw material samples are tested through the differential scanning calorimeter, so that accidental errors can be effectively avoided, and the analysis accuracy is improved. The K heat change curves reflect the melting crystallization conditions of K raw material samples of the product. And further, the scattered point edge recognition is carried out on the K heat change curves, so that the melting temperature interval of the raw materials meeting the batch of target products can be effectively determined.
In one embodiment, the K product raw material samples are placed in aluminum crucibles and the aluminum crucibles are placed in a sample holder of a differential scanning calorimeter that completes the baseline calibration, respectively. Alternatively, baseline calibration may be achieved by conducting a blank test on a differential scanning calorimeter using two empty crucibles under the same temperature conditions.
The preset temperature rise rate is the amplitude of the temperature rise per unit time set by a person skilled in the art. The preset heating temperature is a temperature value set by a person skilled in the art to be heated. Optionally, the K product raw material samples are heated at a preset heating rate, for example, 10 ℃ per minute or 20 ℃ per minute, until a preset heating temperature is reached, for example, from room temperature to 300 ℃. At this time, the recording curves of the differential scanning calorimeter are respectively derived, and K initial heat change curves are obtained. Optionally, filling missing values and break points in the K initial heat change curves, and removing the abnormal values by using a box diagram method, so that the K heat change curves after cleaning is obtained.
Further, step S300 of the embodiment of the present application further includes:
Carrying out alignment treatment on the K heat change curves based on the same time, numbering the K heat change curves according to the sequence of curve starting nodes, and generating K heat change curve numbers, wherein the K heat change curve numbers are in one-to-one correspondence with the K heat change curves;
Extracting a first curve starting point and a first curve ending point of the K heat change curves respectively, mapping the extraction results according to the K heat change curve numbers, and determining a first curve starting point sequence and a first curve ending point sequence, wherein the first curve starting point is a peak starting point of a melting peak of the heat change curve, and the first curve ending point is a peak ending point of the melting peak of the heat change curve;
and carrying out scattered point edge identification based on the first curve starting point sequence and the first curve ending point sequence, and generating the melting temperature interval.
Further, step S300 of the embodiment of the present application further includes:
Extracting intermediate values of K first curve starting points of the first curve starting point sequence to obtain first curve starting point intermediate values;
taking the intermediate value of the starting point of the first curve as the starting point, and determining a first identification temperature interval according to a preset edge identification step length;
Moving the first identification temperature interval to the left side of the left side end point and the right side of the right side end point according to a preset edge identification step length to obtain a second identification temperature interval;
judging whether the distribution density difference value of the first identification temperature interval and the second identification temperature interval meets a preset difference value threshold value, if so, carrying out average value processing on a plurality of first curve starting points in the first identification temperature interval to obtain an interval left end point;
extracting intermediate values of K first curve end points of the first curve end point sequence, and carrying out scattered point edge identification on the first curve end point sequence by taking the intermediate values of the first curve end points as starting points to obtain a right end point of a section;
And generating the melting temperature interval according to the left end point of the interval and the right end point of the interval.
Further, step S300 of the embodiment of the present application further includes:
if not, moving the second identification temperature interval to the left side of the left side end point and the right side of the right side end point according to a preset edge identification step length to obtain a third identification temperature interval;
Judging whether the distribution density difference value of the second identification temperature interval and the third identification temperature interval meets a preset difference value threshold value, if so, carrying out average value processing on a plurality of first curve starting points in the second identification temperature interval to obtain an interval left end point;
if not, carrying out scattered point edge recognition based on the third recognition temperature interval, and determining the left end point of the interval.
In one possible embodiment, the same time is a time when the test starts, and based on the same, the K thermal variation curves are aligned, and the K thermal variation curves are numbered according to the sequence of the curve start nodes, so as to generate K thermal variation curve numbers, where the K thermal variation curve numbers are in one-to-one correspondence with the K thermal variation curves.
The K heat change curves have peaks and valleys. The peak is a melting peak corresponding to the melting process of the plastic. And taking a peak starting point of a melting peak in the thermal variation curve as the first curve starting point and a peak ending point of the melting peak of the thermal variation curve as the first curve ending point.
And respectively extracting a first curve starting point and a first curve ending point from the K heat change curves, mapping the extraction results according to the numbers of the K heat change curves, and determining a first curve starting point sequence and a first curve ending point sequence. The first curve starting point sequence reflects the time series of the onset of melting of the K product raw material samples. The first curve end point sequence reflects the time series of the end of melting of K product raw material samples.
And extracting intermediate values of K first curve starting points of the first curve starting point sequence to obtain a first curve starting point intermediate value, and then determining a first identification temperature interval according to a preset edge identification step length by taking the first curve starting point intermediate value as a starting point. The preset edge identification step length is a temperature amplitude which is set by a person skilled in the art and is moved on one side during interval identification. And respectively moving preset edge recognition step sizes to two sides of the starting point by taking the middle value of the starting point of the first curve as the starting point according to the preset edge recognition step sizes to obtain two end points of the first recognition temperature interval. And obtaining a first distribution density of the first identification temperature interval by counting the number of the first curve starting points contained in the first identification temperature interval and comparing the counted result with the length of the first identification temperature interval. Wherein the first distribution density reflects a degree of intensity of a first curve start point of the distribution within the first identification temperature interval.
And further, moving the first identification temperature interval to the left side of the left side end point and the right side of the right side end point according to a preset edge identification step length to obtain a second identification temperature interval. A second distribution density of the second identified temperature interval is obtained based on the same principle as the first distribution density.
Judging whether the distribution density difference value (the difference value between the first distribution density and the second distribution density) between the first identification temperature interval and the second identification temperature interval meets a preset difference value threshold, if so, indicating that the first identification temperature interval can represent the temperature distribution condition of a first curve starting point sequence, and carrying out average value processing on a plurality of first curve starting points in the first identification temperature interval to obtain an interval left end point.
If not, moving the second identification temperature interval to the left side of the left side end point and the right side of the right side end point according to a preset edge identification step length to obtain a third identification temperature interval;
and determining a third distribution density of a third identification temperature interval based on the same acquisition principle as the first distribution density, further judging whether the distribution density difference between the second identification temperature interval and the third identification temperature interval meets a preset difference threshold, and if so, carrying out mean value processing on a plurality of first curve starting points in the second identification temperature interval to obtain an interval left end point. If not, carrying out scattered point edge recognition based on the third recognition temperature interval until the distribution density difference value of two adjacent recognition temperature intervals meets a preset difference value threshold, and determining the left end point of the interval.
And extracting intermediate values of K first curve end points of the first curve end point sequence based on the same acquisition principle as that of the left end point of the interval, and carrying out scattered point edge identification on the first curve end point sequence by taking the intermediate values of the first curve end points as starting points to acquire the right end point of the interval. And generating the melting temperature interval according to the left end point of the interval and the right end point of the interval.
Step 400, correcting the melting temperature interval based on the extrusion quality fluctuation factor to generate a target melting temperature interval;
in one possible embodiment, a target extrusion quality fluctuation factor (an extrusion product quality fluctuation condition of an extruder in a standard operation state) of the target product raw material is extracted, and a ratio of the extrusion quality fluctuation factor to the target extrusion quality fluctuation factor is used as a correction factor. And multiplying the correction factor by the melting temperature interval to obtain the target melting temperature interval. The aim of correcting the melting temperature interval according to the actual working fluctuation condition of the extruder is fulfilled.
Step 500, continuously monitoring the temperature of a melting zone of the target extruder in a preset continuous monitoring window to obtain a monitoring temperature set;
In one possible embodiment, the preset monitoring window is a monitoring period preset by a person skilled in the art. And monitoring the temperature of the melting area of the target extruder by using devices such as a thermocouple, a thermometer and the like, and reading monitoring data to obtain the monitoring temperature set. Wherein, the monitoring temperature set reflects the temperature change condition of the melting zone when the extruder actually works.
Step 600, determining a target melting temperature deviation value based on the monitored temperature set and the target melting temperature interval, and configuring control parameters according to the target melting temperature deviation value to obtain a target control parameter set, wherein the target control parameters comprise heating temperature, heating time and melting pressure;
And step S700, transmitting the target control parameter set to a control unit of a target extruder for parameter adjustment.
Further, determining a target melting temperature deviation value based on the monitored temperature set and the target melting temperature interval, and performing control parameter configuration according to the target melting temperature deviation value to obtain a target control parameter set, where step S600 further includes:
Traversing the monitoring temperature set to perform average value calculation, and determining a monitoring temperature average value;
Calculating a difference value between the monitored temperature average value and the central melting temperature of the target melting temperature interval, and determining the target melting temperature deviation value;
Constructing a control parameter configuration network layer;
and identifying the target melting temperature deviation value and the target extruder parameter range by utilizing the control parameter configuration network layer, and determining a target control parameter set.
In one possible embodiment, a target melting temperature deviation value is determined based on the monitored temperature set and the target melting temperature interval, and then a control parameter configuration is performed based on the target melting temperature deviation value to obtain a target control parameter set, wherein the target control parameter includes a heating temperature, a heating time and a melting pressure. And transmitting the target control parameter set to a control unit of a target extruder for parameter adjustment. The technical effects of performing control parameter configuration according to the actual conditions of the extruder and the actual melting temperature interval of the raw materials of the target product and improving the control accuracy are achieved.
In one embodiment, the monitored temperature set is traversed to perform a mean calculation to determine a monitored temperature mean. And further, calculating a difference value between the monitored temperature average value and the central melting temperature of the target melting temperature interval, and determining the target melting temperature deviation value. Wherein the target melting temperature deviation value is a temperature deviation value to be corrected. The control parameter configuration network layer is used for intelligently configuring extruder parameters according to the actual conditions of the extruder and the target melting temperature deviation value to be corrected.
Optionally, acquiring a plurality of sample melting temperature deviation values and a plurality of sample extruder parameter ranges, and a plurality of sample control parameter sets as training data, performing supervised training on a network layer constructed based on a convolutional neural network by using the training data, and learning a two-to-one mapping relation between the melting temperature deviation values and the extruder parameter ranges and the control parameter sets in training until model output reaches convergence, so as to obtain the control parameter configuration network layer after training is completed. And inputting the target melting temperature deviation value and the target extruder parameter range into a control parameter configuration network layer for identification, and determining a target control parameter set.
In summary, the embodiment of the application has at least the following technical effects:
According to the application, plasticizing extrusion quality monitoring of a target product of a target extruder is performed in a preset monitoring window to generate an extrusion quality record sequence, then an extrusion quality fluctuation factor is determined according to an analysis result to obtain K heat change curves, scattered point edge recognition is performed on the K heat change curves to generate a melting temperature interval of the target product, the melting temperature interval is corrected based on the extrusion quality fluctuation factor to generate a target melting temperature interval, a target for correcting the melting temperature interval according to the actual working state of the extruder is realized, then the melting area of the target extruder is continuously monitored in the preset continuous monitoring window to obtain a monitoring temperature set, a target melting temperature deviation value is determined based on the monitoring temperature set and the target melting temperature interval, control parameter configuration is performed according to the target melting temperature deviation value to obtain a target control parameter set, wherein the target control parameter set comprises heating temperature, heating time and melting pressure, and then the target control parameter set is transmitted to a control unit of the target extruder for parameter adjustment. The technical effects of improving the control accuracy of the extruder and improving the melt plasticizing extrusion quality are achieved.
Example two
Based on the same inventive concept as one of the melt plasticizing extrusion control methods in the foregoing embodiments, as shown in fig. 2, the present application provides a melt plasticizing extrusion control system, and the system and method embodiments in the embodiments of the present application are based on the same inventive concept. Wherein the system comprises:
the extrusion quality record sequence generation module 11 is used for performing plasticization extrusion quality monitoring of a target product of the target extruder in a preset monitoring window to generate an extrusion quality record sequence;
An extrusion quality fluctuation factor determination module 12, configured to analyze the extrusion quality record sequence based on a preset melt quality index, and determine an extrusion quality fluctuation factor according to an analysis result;
The melting temperature interval generating module 13 is configured to perform melting temperature test on K product raw material samples by using a differential scanning calorimeter to obtain K heat change curves, and perform scattered point edge recognition on the K heat change curves to generate a melting temperature interval of the target product;
A target melting temperature interval generation module 14 for correcting the melting temperature interval based on the extrusion quality fluctuation factor to generate a target melting temperature interval;
the monitoring temperature set obtaining module 15 is configured to continuously monitor the temperature of the melting zone of the target extruder in a preset continuous monitoring window, so as to obtain a monitoring temperature set;
a target control parameter set obtaining module 16, configured to determine a target melting temperature deviation value based on the monitored temperature set and the target melting temperature interval, and perform control parameter configuration according to the target melting temperature deviation value, so as to obtain a target control parameter set, where the target control parameter includes a heating temperature, a heating time, and a melting pressure;
And the parameter adjustment module 17 is used for transmitting the target control parameter set to a control unit of the target extruder for parameter adjustment.
Further, the preset melt quality index includes a melt index, a thermal stability, and a melt viscosity.
Further, the melting temperature interval generation module 13 is configured to perform the following steps:
placing the K product raw material samples in an aluminum crucible, and placing the aluminum crucible in a sample frame of a differential scanning calorimeter for completing baseline calibration;
heating K raw material samples of the product according to a preset heating rate until reaching a preset heating temperature, and leading out a record curve of a differential scanning calorimeter to generate K initial heat change curves;
And traversing the K initial heat change curves to perform data cleaning, and determining the K heat change curves.
Further, the melting temperature interval generation module 13 is configured to perform the following steps:
Carrying out alignment treatment on the K heat change curves based on the same time, numbering the K heat change curves according to the sequence of curve starting nodes, and generating K heat change curve numbers, wherein the K heat change curve numbers are in one-to-one correspondence with the K heat change curves;
Extracting a first curve starting point and a first curve ending point of the K heat change curves respectively, mapping the extraction results according to the K heat change curve numbers, and determining a first curve starting point sequence and a first curve ending point sequence, wherein the first curve starting point is a peak starting point of a melting peak of the heat change curve, and the first curve ending point is a peak ending point of the melting peak of the heat change curve;
and carrying out scattered point edge identification based on the first curve starting point sequence and the first curve ending point sequence, and generating the melting temperature interval.
Further, the melting temperature interval generation module 13 is configured to perform the following steps:
Extracting intermediate values of K first curve starting points of the first curve starting point sequence to obtain first curve starting point intermediate values;
taking the intermediate value of the starting point of the first curve as the starting point, and determining a first identification temperature interval according to a preset edge identification step length;
Moving the first identification temperature interval to the left side of the left side end point and the right side of the right side end point according to a preset edge identification step length to obtain a second identification temperature interval;
judging whether the distribution density difference value of the first identification temperature interval and the second identification temperature interval meets a preset difference value threshold value, if so, carrying out average value processing on a plurality of first curve starting points in the first identification temperature interval to obtain an interval left end point;
extracting intermediate values of K first curve end points of the first curve end point sequence, and carrying out scattered point edge identification on the first curve end point sequence by taking the intermediate values of the first curve end points as starting points to obtain a right end point of a section;
And generating the melting temperature interval according to the left end point of the interval and the right end point of the interval.
Further, the melting temperature interval generation module 13 is configured to perform the following steps:
if not, moving the second identification temperature interval to the left side of the left side end point and the right side of the right side end point according to a preset edge identification step length to obtain a third identification temperature interval;
Judging whether the distribution density difference value of the second identification temperature interval and the third identification temperature interval meets a preset difference value threshold value, if so, carrying out average value processing on a plurality of first curve starting points in the second identification temperature interval to obtain an interval left end point;
if not, carrying out scattered point edge recognition based on the third recognition temperature interval, and determining the left end point of the interval.
Further, the target control parameter set obtaining module 16 is configured to perform the following steps:
Traversing the monitoring temperature set to perform average value calculation, and determining a monitoring temperature average value;
Calculating a difference value between the monitored temperature average value and the central melting temperature of the target melting temperature interval, and determining the target melting temperature deviation value;
Constructing a control parameter configuration network layer;
and identifying the target melting temperature deviation value and the target extruder parameter range by utilizing the control parameter configuration network layer, and determining a target control parameter set.
It should be noted that the sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the foregoing description has been directed to specific embodiments of this specification. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the application are intended to be included within the scope of the application.
The specification and figures are merely exemplary illustrations of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents that fall within the scope of the application. It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the scope of the application. Thus, the present application is intended to include such modifications and alterations insofar as they come within the scope of the application or the equivalents thereof.
Claims (7)
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