A multifunctional extruder for producing plastic protective tubes

Abstract

The present invention relates to the field of plastic molding control technology, and specifically to a multifunctional extruder for producing plastic protective tubes. The present invention obtains the temperature control degree at the prediction moment according to the difference in time series between the adjusted power value data and the temperature value data; obtains the temperature prediction value at the prediction moment according to the temperature value at the current moment, the effective power at the prediction moment, and the temperature control degree; obtains the predicted temperature fluctuation degree at the prediction moment according to the local difference of the temperature prediction value in the temperature value data; adjusts the PID parameters according to the predicted temperature fluctuation degree to obtain the adjusted PID parameters at the prediction moment; and uses the adjusted PID parameters at the prediction moment to perform PID control on the temperature regulating device at the prediction moment. The present invention achieves reasonable temperature control in the production process of plastic protective tubes and ensures the quality stability of plastic protective tubes by making the adjusted PID parameters adapt to the influence of drastic changes at the prediction moment.

Description

Technical Field

[0001] The invention relates to the technical field of plastic molding control, in particular to a multifunctional extruder for producing plastic protection tubes. Background Art

[0002] Plastic protective tube is a tubular article made of plastic material, used to protect the internal objects from the influence and damage of the external environment. Plastic protective tube is widely used in the laying of cables, optical fibers and other electrical or communication lines that need protection. Since the quality of plastic protective tube is directly related to its protective effect and service life, it is necessary to ensure the quality of plastic protective tube. The multifunctional extruder for plastic protective tube production is a device used to produce plastic protective tubes, and its temperature control is a key factor affecting plastic protective tubes.

[0003] PID control (Proportional-Integral-Derivative control) is an automatic control method widely used in industrial control systems. The existing technology uses PID control to adjust the temperature, and PID control has a good control effect on temperature adjustment. In the traditional PID control process, the set PID control parameters are used for temperature adjustment, but the drastic temperature changes will cause the PID control parameters to be difficult to adapt, resulting in the inability to adjust its output in time to respond to the drastic temperature changes, resulting in poor temperature control effect and unstable quality of the plastic protective tube. Summary of the invention

[0004] In order to solve the technical problem that the temperature control effect of the prior art is poor, resulting in unstable quality of plastic protective tubes, the purpose of the present invention is to provide a multifunctional extruder for the production of plastic protective tubes. The technical solution adopted is as follows:

[0005] The present invention proposes a multifunctional extruder for producing plastic protective tubes, the extruder comprising a temperature regulating device for regulating the temperature of production raw materials in each temperature control process, a temperature sensor for collecting the temperature of the production raw materials, a power sensor for collecting the heating power of the temperature regulating device, and a controller for controlling the temperature regulating device, the controller samplingly connects the temperature sensor and the power sensor to obtain the temperature value and the power value at all sampling moments, and controls the temperature regulating device according to the temperature value and the power value at all sampling moments, and the control process comprises:

[0006] According to the relevant conditions of the temperature value data and the power value data corresponding to the preset surrounding time range at the prediction moment, the adjusted power value data and the effective power at the prediction moment are obtained; according to the difference in time series between the adjusted power value data and the temperature value data, the temperature control degree at the prediction moment is obtained; according to the temperature value at the moment before the prediction moment, the effective power at the prediction moment and the temperature control degree, the temperature prediction value at the prediction moment is obtained;

[0007] According to the local differences of the temperature prediction values ​​in the temperature value data, the predicted temperature fluctuation at the prediction moment is obtained; the set PID parameters are adjusted according to the predicted temperature fluctuation to obtain the adjusted PID parameters at the prediction moment; and the temperature control device at the prediction moment is PID controlled using the adjusted PID parameters at the prediction moment.

[0008] Furthermore, the method for obtaining the adjusted power value data and the effective power at the prediction moment includes:

[0009] Obtaining each reference lag time; moving the power value data by the reference lag time, and obtaining the moving power value data corresponding to each reference lag time;

[0010] According to the correlation coefficient between the temperature value data corresponding to the preset surrounding time range of the prediction moment and the mobile power value data corresponding to each reference lag time, the temperature control related index corresponding to each reference lag time is obtained;

[0011] The reference lag time corresponding to the largest temperature control related indicator is used as the temperature control lag time; the moving power value data corresponding to the temperature control lag time is used as the adjusted power value data; the power value corresponding to the predicted moment in the adjusted power value data is used as the effective power at the predicted moment.

[0012] Furthermore, the method for obtaining the temperature control degree includes:

[0013] Get all surrounding moments of the predicted moment;

[0014] According to the difference between the power value at each surrounding moment and the adjacent power values, a power difference index at each surrounding moment is obtained;

[0015] According to the difference between the temperature value at each surrounding moment and the adjacent temperature values, a temperature difference index at each surrounding moment is obtained;

[0016] According to the deviation of the power difference index and the temperature difference index at each ambient moment, the local temperature control index at each ambient moment is obtained;

[0017] The temperature control degree is obtained according to the overall distribution of the local temperature control indexes at all surrounding moments.

[0018] Furthermore, the method for obtaining surrounding moments includes: taking a preset number of sampling moments surrounding the predicted moment as all surrounding moments of the predicted moment.

[0019] Furthermore, the method for obtaining the power difference index includes:

[0020] The difference value of the power value at each surrounding time is calculated to obtain the power difference index at each surrounding time.

[0021] Furthermore, the method for obtaining the temperature prediction value includes:

[0022] According to the difference between the applied power at the prediction moment and the power value at the previous moment, the power change parameter at the prediction moment is obtained;

[0023] According to the power change parameter and the temperature control degree at the prediction time, the temperature change parameter at the prediction time is obtained;

[0024] The temperature change parameters and the temperature value at the moment before the prediction moment are combined to obtain the temperature prediction value at the prediction moment.

[0025] Furthermore, the method for obtaining the predicted temperature fluctuation at the predicted time includes:

[0026] Obtain the reference fluctuation time of the prediction time; obtain the surrounding fluctuation index of the prediction time according to the fluctuation of the temperature values ​​corresponding to all reference fluctuation times;

[0027] Obtaining a predicted fluctuation index at the predicted moment according to the difference between the predicted temperature value at the predicted moment and the overall distribution of temperature values ​​at all reference fluctuation moments;

[0028] The predicted temperature fluctuation degree at the prediction moment is obtained according to the deviation between the predicted fluctuation index at the prediction moment and the surrounding fluctuation index; the predicted fluctuation index is positively correlated with the predicted temperature fluctuation degree; the surrounding fluctuation index is negatively correlated with the predicted temperature fluctuation degree.

[0029] Furthermore, the method for obtaining the predicted volatility index includes:

[0030] The average of the temperature values ​​of all reference fluctuation moments at the prediction moment is calculated to obtain the overall ambient temperature value at the prediction moment; the absolute value of the difference between the temperature prediction value at the prediction moment and the overall ambient temperature value is calculated to obtain the prediction fluctuation index.

[0031] Furthermore, the method for obtaining the adjusted PID parameters at the prediction time includes:

[0032] The PID parameters to be set include: a preset proportional coefficient, a preset integral coefficient, and a preset differential coefficient;

[0033] Calculate the sum of 1 and the predicted temperature fluctuation, calculate the product of the sum and the preset proportional coefficient, and obtain the adjusted proportional coefficient;

[0034] Calculate the difference between 1 and the predicted temperature fluctuation, calculate the product of the difference and the preset integral coefficient, and obtain the adjusted integral coefficient;

[0035] Calculate the sum of 1 and the predicted temperature fluctuation, calculate the product of the sum and the preset differential coefficient, and obtain the adjusted differential coefficient;

[0036] The adjusted proportional coefficient, the adjusted integral coefficient and the adjusted differential coefficient are used as the adjusted PID parameters at the prediction time.

[0037] Furthermore, the last sampling moment is the current moment, and the next moment of the current moment is used as the predicted moment.

[0038] The present invention has the following beneficial effects:

[0039] The main purpose of the present invention is to reasonably control the temperature of the temperature control equipment in the temperature control process, and to achieve reasonable temperature control of the plastic protection tube production process by predicting the temperature value at the prediction time and adjusting the PID control parameters at the prediction time according to the volatility of the prediction result. In order to predict the temperature value at the prediction time, since the power of the temperature regulating device is the main factor affecting the temperature change, it is necessary to analyze the influence of the power value of the temperature regulating device on the temperature. Considering that the temperature change of the plastic caused by the power of the temperature regulating device has a certain hysteresis, the adjusted power value data is obtained, so that the adjusted power value data and the temperature value data are aligned in time, so as to more accurately reflect the immediate influence of the power on the temperature change. The power at the prediction time reflects the power value corresponding to the temperature change at the prediction time. The temperature control degree at the prediction time is obtained, and the temperature control degree reflects the influence of the power change of the temperature regulating device at the prediction time on the temperature change; thereby obtaining the temperature prediction value at the prediction time, and the temperature prediction value can more accurately reflect the temperature value at the prediction time. Considering that the PID parameters are difficult to adapt to the influence of the drastic temperature change, the PID control has a poor effect on the temperature adjustment. The predicted temperature fluctuation reflects the drastic degree of the predicted temperature value change. The larger the predicted temperature fluctuation, the more likely it is to have a drastic change. Thereby, the PID parameters are adjusted to obtain the adjusted PID parameters at the prediction moment; the adjusted PID parameters can better adapt to the impact of drastic changes at the prediction moment, thereby reasonably controlling the temperature at the prediction moment, achieving reasonable control of the temperature of the plastic protective tube production process, and ensuring the quality stability of the plastic protective tube. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 A schematic diagram of the structure of a barrel of a multifunctional extruder for producing a plastic protective tube provided by one embodiment of the present invention;

[0042] Figure 2 A schematic diagram of the overall structure of a multifunctional extruder for producing plastic protective tubes provided by one embodiment of the present invention;

[0043] Figure 3 A flow chart of a temperature control method for producing a plastic protective tube provided by one embodiment of the present invention;

[0044] Figure 4 A flow chart of a method for obtaining adjusted power value data and effective power provided by an embodiment of the present invention;

[0045] Reference numerals:

[0046] 1. Barrel; 2. Feed hopper; 3. Conical screw; 4. Discharge port; 5. Motor; 6. First heating component; 7. Second heating component; 8. Filter; 9. Cooling fan; 10. First temperature sensor; 11. Second temperature sensor; 12. Controller. DETAILED DESCRIPTION

[0047] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation, structure, features and effects of a multifunctional extruder for producing plastic protective tubes proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0048] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0049] The specific scheme of a multifunctional extruder for producing plastic protective tubes provided by the present invention is described in detail below with reference to the accompanying drawings.

[0050] See also Figure 1The structure diagram of the barrel of a multifunctional extruder for producing a plastic protective tube provided by an embodiment of the present invention is shown. Figure 2 A schematic diagram of the overall structure of a multifunctional extruder for producing plastic protective tubes provided by an embodiment of the present invention is shown.

[0051] Combination Figure 1 and Figure 2 The process of producing a plastic protective tube by a multifunctional extruder for producing a plastic protective tube provided by an embodiment of the present invention is as follows:

[0052] (1) Raw material preparation process: Various plastic fixed particles are added to the feed hopper 2 for stirring treatment, which is used to mix different types of plastic particles to ensure the uniformity and consistency of the raw materials. (2) Heating process: After the raw material particles enter the barrel 1, the raw material particles are heated to a molten state by the heating component, which is composed of a first heating component 6 and a second heating component 7. The heating component can convert solid plastic particles into molten plastic for subsequent processing. (3) Transmission and stirring process: The molten plastic is transmitted forward through the conical screw 3 inside the barrel 1. Among them, the motor 5 controls the speed at which the conical screw 3 transmits the plastic. (4) Filtration process: The molten plastic is filtered through the filter 8 inside the barrel 1. The filter 8 is used to prevent the incompletely melted plastic particles from entering the subsequent extrusion forming process, thereby affecting the quality of the final product. After the molten plastic passes through the filter 8, the temperature is detected by the first temperature sensor 10. The temperature of the first temperature sensor 10 reflects the temperature of the plastic after the heating process. (5) Heat dissipation process: Further temperature control is performed through the heat dissipation fan 9. This prevents the plastic from being overheated during the subsequent extrusion process, causing the chemical components inside the plastic to decompose and denature, affecting the physical properties and chemical stability of the product. The temperature is detected by the second temperature sensor 11, and the temperature of the second temperature sensor 11 reflects the temperature of the plastic after the heat dissipation process. (6) Extrusion molding: The molten plastic after temperature control is extruded through the discharge port 4 to obtain a plastic protective tube. In addition, the extruder is also provided with a power sensor (not shown in the figure), which can read the power of the heating component and the cooling fan 9. The controller 12 is sampled and connected to the first temperature sensor 10, the second temperature sensor 11 and the power sensor. During the heating process and the heat dissipation process, the controller 12 can read the temperature of the first temperature sensor 10, the temperature of the second temperature sensor 11, and the power of the heating component and the cooling fan 9, and control the motor 5, the first heating component 6, the second heating component 7 and the cooling fan 9. The process of the controller 12 controlling the first heating component 6, the second heating component 7 and the cooling fan 9 will be described in detail below.

[0053] See also Figure 3, which shows a flow chart of a temperature control method for a multifunctional extruder for producing a plastic protective tube provided by an embodiment of the present invention, the method comprising the following steps:

[0054] Step S1: Acquire a process data set of a temperature control process; the process data set includes: set PID parameters of a temperature control device, temperature values ​​corresponding to a temperature sensor at each sampling time, and a power value of the temperature control device.

[0055] Specifically, in order to perform temperature control later, it is considered that the multifunctional extruder for producing the plastic protective tube has two temperature control processes, namely, a heating process and a heat dissipation process.

[0056] For the heating process, the temperature of the plastic is controlled by the heating component so that the plastic is heated to a molten state, wherein the temperature detected by the first temperature sensor can monitor the corresponding temperature value of the plastic after heating. The heating component is used as a temperature regulating device, and the first temperature sensor is used as a temperature sensor; according to the preset sampling frequency, synchronous data acquisition is performed on the production process of the plastic protective tube, and the power value of the heating component at each sampling moment is obtained from the power sensor, and the temperature value corresponding to the first temperature sensor at each sampling moment is obtained. The set PID parameters of the heating component are obtained. The PID parameters include a preset proportional coefficient, a preset differential coefficient, and a preset integral coefficient. It should be noted that the preset proportional coefficient, the preset differential coefficient, and the preset integral coefficient can be obtained by the Ziegler-Nichols method, which is a well-known technology and will not be repeated here. The process data set of the heating process is: the set PID parameters of the heating component, the temperature value corresponding to the first temperature sensor at each sampling moment, and the power value of the heating component.

[0057] During the heat dissipation process, further temperature control is performed through the heat dissipation fan to prevent the plastic from being overheated during the subsequent extrusion process, so that the plastic can be stabilized in the preset temperature range after cooling, and the second temperature sensor detects the temperature and can monitor the corresponding temperature value of the plastic after cooling. The heat dissipation fan is used as a temperature regulating device, and the second temperature sensor is used as a temperature sensor; according to the preset sampling frequency, synchronous data collection is performed on the production process of the plastic protective tube, and the power value of the heat dissipation fan at each sampling moment is obtained from the power sensor, and the temperature value corresponding to the second temperature sensor at each sampling moment is obtained. The set PID parameters of the heat dissipation fan are obtained. The process data set of the heat dissipation process is: the set PID parameters of the heat dissipation fan, the temperature value corresponding to the second temperature sensor at each sampling moment, and the power value of the heat dissipation fan.

[0058] That is, a process data set of the heating process and the heat dissipation process is obtained; the process data set includes: PID parameters of the temperature control device, the temperature value corresponding to the temperature sensor at each sampling time, and the power value of the temperature control device. Since the temperature control process of the heating process and the heat dissipation process is similar in the present invention, the heating process is used as the temperature control process for explanation.

[0059] It should be noted that, in one embodiment of the present invention, synchronous sampling is performed according to a preset frequency, each sampling is taken as a sampling moment, and the preset frequency is 1 time / second. It should be noted that, in order to facilitate calculations, all indicator data involved in the calculations in the embodiments of the present invention are subjected to data preprocessing to eliminate the dimension effect. The specific means of removing the dimension effect are technical means well known to those skilled in the art and are not limited here. It should be noted that, in one embodiment of the present invention, the last sampling moment is the current moment.

[0060] Step S2: According to the temperature values ​​and power values ​​at all sampling moments, obtain temperature value data and power value data; according to the relevant conditions of the temperature value data and power value data corresponding to the preset surrounding time range of the prediction moment, obtain the adjusted power value data and the effective power at the prediction moment; according to the difference in time series between the adjusted power value data and the temperature value data, obtain the temperature control degree at the prediction moment; according to the temperature value at the current moment, the effective power at the prediction moment and the temperature control degree, obtain the temperature prediction value at the prediction moment.

[0061] The main purpose of the present invention is to reasonably control the temperature of the temperature control equipment in the temperature control process, and to achieve reasonable temperature control of the plastic protective tube production process by predicting the temperature value at the prediction time and adjusting the PID control parameters at the prediction time according to the volatility of the prediction result. In order to predict the temperature value at the prediction time, since the power of the temperature regulating device is the main factor affecting the temperature change, it is necessary to analyze the influence of the power value of the temperature regulating device on the temperature. Considering that the temperature change of the plastic caused by the power of the temperature regulating device has a certain lag, the adjusted power value data is obtained, so that the adjusted power value data and the temperature value data are aligned in time, so as to more accurately reflect the immediate influence of power on temperature change. The effective power at the prediction time reflects the corresponding power value that causes the temperature change at the prediction time. The temperature control degree at the prediction time is obtained, and the temperature control degree reflects the influence of the power change of the temperature regulating device at the prediction time on the temperature change; thereby obtaining the temperature prediction value at the prediction time, and the temperature prediction value can more accurately reflect the temperature value at the prediction time.

[0062] In order to facilitate the subsequent analysis of the hysteresis of the temperature value data compared to the power value data, the temperature value data and the power value data are first constructed. Preferably, in one embodiment of the present invention, the method for obtaining the temperature value data and the power value data includes:

[0063] Based on a temperature two-dimensional coordinate system, the horizontal axis of the temperature two-dimensional coordinate system is time, and the vertical axis of the temperature two-dimensional coordinate system is temperature value; the coordinate point of the temperature value at the sampling time determined in the temperature two-dimensional coordinate system is taken as a temperature data point, and all temperature data points are counted to obtain temperature value data;

[0064] Based on the power two-dimensional coordinate system, the horizontal axis of the power two-dimensional coordinate system is time, and the vertical axis of the power two-dimensional coordinate system is power value; the coordinate point of the power value at the sampling time determined in the power two-dimensional coordinate system is taken as a power data point, and all power data points are counted to obtain power value data.

[0065] Since the last sampling moment is the current moment, in order to predict the next moment after the current moment, in one embodiment of the present invention, the next moment after the current moment is used as the predicted moment.

[0066] Considering that the motor controls the conical screw to transfer the plastic, the conical screw will be adjusted to a certain extent according to the temperature, fluidity and other properties of the molten plastic. For example, when the extruder starts to run, the temperature inside the cavity is relatively low, and the solid mixed plastic melts relatively slowly. Therefore, in the time neighborhood corresponding to the start moment, the screw speed is relatively slow, and the lag time is relatively long at this time. Considering that the speed of the motor-controlled conical screw has a certain continuity and inertia. By analyzing the preset surrounding time range of the predicted moment, the lag time corresponding to the predicted moment can be better analyzed. In one embodiment of the present invention, the method for obtaining the preset surrounding time range includes: using the time range corresponding to the sampling moments before the preset number of the predicted moment as the preset surrounding time range of the predicted moment. In one embodiment of the present invention, the preset number is 50.

[0067] Considering that the temperature change of the plastic caused by the power of the temperature regulating device has a certain lag, the adjusted power value data is obtained so that the adjusted power value data and the temperature value data are aligned in time, so as to more accurately reflect the immediate impact of power on temperature change. The effective power at the prediction moment reflects the power value corresponding to the temperature change at the prediction moment.

[0068] See also Figure 4 , which shows a flow chart of a method for obtaining adjusted power value data and effective power in one embodiment of the present invention. Preferably, in one embodiment of the present invention, the method for obtaining adjusted power value data and effective power at a predicted time includes:

[0069] Step S201: Acquire each reference lag time; move the power value data by the reference lag time to acquire the moving power value data corresponding to each reference lag time.

[0070] In one embodiment of the present invention, the reference lag time includes: 0, 1, 2, 3, ... 8, 9, 10. Based on the two-dimensional coordinate system, the power value data is moved rightward by the reference lag time to obtain the moving power value data corresponding to each reference lag time.

[0071] Step S202: obtaining temperature control related indicators corresponding to each reference lag time according to the correlation coefficient between the temperature value data corresponding to the preset surrounding time range of the prediction moment and the mobile power value data corresponding to each reference lag time.

[0072] Considering that during the heating process, as the power of the first heating component increases, the plastic temperature will also increase, thereby increasing the temperature detected by the first temperature sensor. Under the effect of eliminating the lag time, the power will have a strong correlation with the temperature. The temperature control related indicators reflect the correlation between the temperature value data and the mobile power value data corresponding to each reference lag time. The larger the value, the greater the correlation.

[0073] In one embodiment of the present invention, the absolute value of the Pearson correlation coefficient of the temperature value data corresponding to the preset surrounding time range at the prediction time and the mobile power value data corresponding to each reference lag time is calculated to obtain the temperature control related index corresponding to each reference lag time. It should be noted that the Pearson correlation coefficient is a prior art well known to those skilled in the art and will not be described in detail here.

[0074] Step S203: Use the reference lag time corresponding to the maximum temperature control related indicator as the temperature control lag time; use the moving power value data corresponding to the temperature control lag time as the adjusted power value data; use the power value corresponding to the predicted moment in the adjusted power value data as the effective power at the predicted moment.

[0075] Considering that power and temperature have a strong correlation when the effect of lag time is excluded, the temperature control lag time reflects the lag time between the power of the temperature control device and the temperature change of the plastic. The adjusted power value data is obtained so that the adjusted power value data and temperature value data exclude the influence of time lag, and the effective power at the prediction time reflects the effect of the corresponding power value that causes the temperature change of the plastic at the prediction time.

[0076] For example, the temperature value data is T(t), the power value data is P(t), where t represents the sampling time, and the temperature control lag time is , introduce Express the mobile power value data corresponding to the temperature control hysteresis time, =P(t- ), T(t) and It can eliminate the influence of time lag and more accurately reflect the immediate impact of power on temperature changes.

[0077] In order to analyze the influence of the power change of the temperature regulating device on the temperature change at the prediction time, preferably, in one embodiment of the present invention, the method for obtaining the temperature control degree includes:

[0078] Get all surrounding moments of the predicted moment;

[0079] According to the difference between the power value at each surrounding moment and the adjacent power values, a power difference index at each surrounding moment is obtained;

[0080] According to the difference between the temperature value at each surrounding moment and the adjacent temperature values, a temperature difference index at each surrounding moment is obtained;

[0081] According to the deviation of the power difference index and the temperature difference index at each ambient moment, the local temperature control index at each ambient moment is obtained;

[0082] The temperature control degree is obtained according to the overall distribution of the local temperature control index at all surrounding moments.

[0083] Specifically for the above steps, the sampling moments of the preset number of surroundings before the predicted moment are taken as all the surrounding moments of the predicted moment, wherein the surrounding moments do not include the predicted moment. Calculate the difference value of the power value at each surrounding moment to obtain the power difference index at each surrounding moment; calculate the difference value of the temperature value at each surrounding moment to obtain the temperature difference index at each surrounding moment; calculate the sum of the power difference index and the denominator adjustment factor, calculate the ratio of the temperature difference index to the sum, and obtain the local temperature control index at the surrounding moment. In one embodiment of the present invention, the denominator adjustment factor is used to ensure that the denominator is not 0. The denominator adjustment factor is a number greater than 0. This embodiment sets it to 0.1, and the implementer can set it according to the implementation scenario. Calculate the mean of the local temperature control index at all surrounding moments to obtain the temperature control degree. It should be noted that the present invention adopts backward difference to calculate the difference value, that is, the next data minus the current data. In one embodiment of the present invention, the preset number of surroundings is 100, and the implementer can set it according to the implementation scenario.

[0084] In order to analyze the impact of power changes of temperature control equipment on temperature changes at the prediction moment, considering that different power changes have different impacts on temperature changes, and considering that the power effect of temperature control equipment has a certain continuity, the sampling moments of the preset number of surroundings before the prediction moment are taken as all surrounding moments of the prediction moment. By analyzing all surrounding moments of the prediction moment, the impact of power changes on temperature changes at the prediction moment can be better analyzed. The larger the power difference index of the surrounding moments, the greater the power becomes at the surrounding moments compared with the previous moment; the larger the temperature difference index of the surrounding moments, the greater the temperature becomes at the surrounding moments compared with the previous moment. The local temperature control index reflects the degree of temperature change caused by the power change corresponding to the surrounding moments; the temperature control degree reflects the impact of the power change of the temperature control equipment at the prediction moment on the temperature change.

[0085] In one embodiment of the present invention, the formula for obtaining the temperature control degree includes:

[0086]

[0087] In the formula, is the total number of all surrounding moments of the predicted moment; For the Temperature difference index at each surrounding moment; For the Power difference index at each surrounding moment; is the denominator adjustment factor.

[0088] In order to obtain the temperature value at the predicted time, preferably, in one embodiment of the present invention, the method for obtaining the temperature prediction value includes:

[0089] According to the difference between the applied power at the prediction moment and the power value at the previous moment, the power change parameter at the prediction moment is obtained;

[0090] According to the power change parameter and the temperature control degree at the prediction time, the temperature change parameter at the prediction time is obtained;

[0091] The temperature change parameters and the temperature value at the current moment are combined to obtain the temperature prediction value at the prediction moment.

[0092] Specifically, the difference between the effective power at the prediction moment and the power value at the moment before the prediction moment is calculated to obtain the power change parameter at the prediction moment; the product of the power change index at the prediction moment and the temperature control degree is calculated to obtain the temperature change parameter at the prediction moment; the sum of the temperature change parameter and the temperature value at the current moment is calculated to obtain the temperature prediction value at the prediction moment.

[0093] For the above steps, the power change parameter at the prediction moment reflects the increase in the power value at the prediction moment compared with the previous moment; considering that the temperature control degree reflects the influence of the power change of the temperature regulating device at the prediction moment on the temperature change, the temperature change parameter at the prediction moment is obtained according to the power change parameter and temperature control degree at the prediction moment; the temperature change parameter can reflect the degree of temperature increase caused by power at the prediction moment. The temperature prediction value at the prediction moment is obtained by combining the temperature change parameter with the temperature value at the current moment. The temperature prediction value can more accurately reflect the corresponding temperature value at the prediction moment.

[0094] At this point, the temperature prediction value is obtained.

[0095] Step S3: According to the local differences of the temperature prediction values ​​in the temperature value data, the predicted temperature fluctuation at the prediction time is obtained; the PID parameters are adjusted according to the predicted temperature fluctuation to obtain the adjusted PID parameters at the prediction time; and the temperature regulating equipment at the prediction time is PID controlled using the adjusted PID parameters at the prediction time.

[0096] Considering that PID parameters are difficult to adapt to the impact of drastic temperature changes, the PID control has a poor effect on temperature regulation. The predicted temperature fluctuation reflects the drastic degree of change in the predicted temperature value. The larger the predicted temperature fluctuation, the more likely it is to change drastically. Therefore, the PID parameters are adjusted to obtain the adjusted PID parameters at the prediction time; the adjusted PID parameters can better adapt to the impact of drastic changes at the prediction time, thereby reasonably controlling the temperature at the prediction time, realizing reasonable temperature control of the plastic protective tube production process, and ensuring the quality stability of the plastic protective tube.

[0097] In order to analyze the severity of the change in the predicted temperature value, preferably, in one embodiment of the present invention, the method for obtaining the predicted temperature fluctuation at the prediction time includes:

[0098] Obtain the reference fluctuation time of the prediction time; obtain the surrounding fluctuation index of the prediction time according to the fluctuation of the temperature values ​​corresponding to all reference fluctuation times;

[0099] Obtain the predicted fluctuation index at the predicted moment according to the difference between the predicted temperature value at the predicted moment and the overall distribution of the temperature values ​​at all reference fluctuation moments;

[0100] According to the deviation between the predicted fluctuation index at the prediction moment and the surrounding fluctuation index, the predicted temperature fluctuation degree at the prediction moment is obtained; the predicted fluctuation index is positively correlated with the predicted temperature fluctuation degree; the surrounding fluctuation index is negatively correlated with the predicted temperature fluctuation degree.

[0101] Specifically, the sampling moment of the preset fluctuation number before the prediction moment is used as the reference fluctuation moment of the prediction moment; in one embodiment of the present invention. The preset fluctuation number is 100, and the implementer can set it according to the implementation scenario. Calculate the standard deviation of the temperature values ​​corresponding to all reference fluctuation moments to obtain the surrounding fluctuation index at the prediction moment. Calculate the mean of the temperature values ​​of all reference fluctuation moments at the prediction moment to obtain the surrounding overall temperature value at the prediction moment; calculate the absolute value of the difference between the temperature prediction value at the prediction moment and the surrounding overall temperature value to obtain the predicted fluctuation index; calculate the sum of the surrounding overall temperature value and the denominator adjustment parameter, calculate the ratio of the predicted fluctuation index at the prediction moment to the sum and normalize the ratio to obtain the predicted temperature fluctuation degree at the prediction moment. In one embodiment of the present invention, the normalization method is: use The normalization function performs normalization to limit the value range to between 0 and 1.

[0102] In one embodiment of the present invention, the formula for predicting temperature fluctuation at the prediction time is:

[0103]

[0104] In the formula, is the predicted temperature fluctuation at the prediction time; is the predicted temperature value at the predicted time; is the mean of the temperature values ​​of all reference fluctuation moments at the prediction moment, that is, the overall ambient temperature value at the prediction moment; To predict volatility indicators; is the standard deviation of the temperature values ​​at all reference fluctuation moments at the prediction moment, that is, the surrounding fluctuation index at the prediction moment; is the normalization function; It is a denominator adjustment parameter. In one embodiment of the present invention, the denominator adjustment parameter is set to 0.01 to prevent the denominator from being 0. The implementer can set it according to the implementation scenario.

[0105] In the formula for predicting temperature fluctuation at the prediction time, Reflects the degree of temperature fluctuation at the prediction time. The larger the value, the greater the temperature fluctuation at the prediction time. Reflects the degree of temperature fluctuation in the period before the prediction moment; the predicted temperature fluctuation reflects the degree of fluctuation at the prediction moment compared with the degree of temperature fluctuation in the period before. The larger the value, the more drastic the change in the predicted temperature value.

[0106] In one embodiment of the present invention, a method for obtaining adjusted PID parameters at a prediction time includes:

[0107] PID parameters include: preset proportional coefficient, preset integral coefficient and preset differential coefficient;

[0108] According to the preset proportional coefficient and the predicted temperature fluctuation, an adjusted proportional coefficient is obtained; the preset proportional coefficient and the predicted temperature fluctuation are both positively correlated with the adjusted proportional coefficient;

[0109] According to the preset integral coefficient and the predicted temperature fluctuation, an adjusted integral coefficient is obtained; the preset integral coefficient and the adjusted integral coefficient are positively correlated, and the predicted temperature fluctuation and the adjusted integral coefficient are negatively correlated;

[0110] According to the preset differential coefficient and the predicted temperature fluctuation, an adjusted differential coefficient is obtained; the preset differential coefficient and the predicted temperature fluctuation are both positively correlated with the adjusted differential coefficient;

[0111] The adjusted proportional coefficient, the adjusted integral coefficient, and the adjusted differential coefficient are used as adjusted PID parameters at the prediction time.

[0112] For the above steps, specifically, the sum of 1 and the predicted temperature fluctuation is calculated, and the product of the sum and the preset proportional coefficient is calculated to obtain the adjusted proportional coefficient; the difference between 1 and the predicted temperature fluctuation is calculated, and the product of the difference and the preset integral coefficient is calculated to obtain the adjusted integral coefficient. The sum of 1 and the predicted temperature fluctuation is calculated, and the product of the sum and the preset differential coefficient is calculated to obtain the adjusted differential coefficient; the adjusted proportional coefficient, the adjusted differential coefficient and the adjusted integral coefficient are used as the adjusted PID parameters at the prediction time.

[0113] In one embodiment of the present invention, considering that the role of the proportional coefficient is to speed up the response speed of the system, responding immediately to the current error helps to reduce the error. The greater the predicted temperature fluctuation, the greater the degree of change in the temperature value at the predicted moment, and the more it is necessary to increase the preset proportional coefficient so that the system can respond faster and reduce the error. The formula for obtaining the adjusted proportional coefficient includes:

[0114]

[0115] In the formula, is the adjusted proportional coefficient at the prediction moment; is the predicted temperature fluctuation at the prediction time; is the preset scale factor.

[0116] In one embodiment of the present invention, since the role of the integral coefficient is to eliminate steady-state errors, the control amount is gradually adjusted by accumulating past errors. Although the integral effect helps to eliminate steady-state errors, when the temperature changes drastically, an excessively large integral coefficient may cause the system to overshoot or oscillate. Considering that the greater the predicted temperature fluctuation, the greater the degree of change in the temperature value at the predicted moment, the more it is necessary to reduce the preset integral coefficient to avoid the integral term accumulating errors too quickly and affecting the stability of the system. The formula for obtaining the adjusted integral coefficient includes:

[0117]

[0118] In the formula, is the adjusted integral coefficient at the prediction moment; is the predicted temperature fluctuation at the prediction time; is the preset integral coefficient.

[0119] In one embodiment of the present invention, since the role of the differential coefficient is to improve the dynamic performance of the system, adjusting the control amount in advance by predicting the change trend of the error helps to reduce overshoot and oscillation. Considering that the larger the predicted temperature fluctuation, the more drastic the change in the temperature value at the predicted moment, increasing the preset differential coefficient can help the system better predict the change in the error, thereby more smoothly transitioning to a new steady state and reducing overshoot and oscillation. The formula for obtaining the adjusted differential coefficient includes:

[0120]

[0121] In the formula, is the adjusted differential coefficient at the prediction time; is the predicted temperature fluctuation at the prediction time; is the preset differential coefficient.

[0122] The adjusted proportional coefficient, adjusted differential coefficient and adjusted integral coefficient are used as the adjusted PID parameters at the prediction time. The adjusted PID parameters can better adapt to the impact of drastic changes at the prediction time, thereby reasonably controlling the temperature at the prediction time, realizing reasonable temperature control of the plastic protective tube production process, and ensuring the quality stability of the plastic protective tube.

[0123] Then, the adjusted PID parameters at the prediction time are used to perform PID control on the temperature regulating device at the prediction time. It should be noted that PID control is a commonly used feedback control method, which is a prior art well known to those skilled in the art and will not be described in detail here.

[0124] In summary, the embodiment of the present invention provides a multifunctional extruder for the production of plastic protective tubes. First, the temperature control degree at the prediction moment is obtained according to the difference in time series between the adjusted power value data and the temperature value data; the temperature prediction value at the prediction moment is obtained according to the temperature value at the current moment, the effective power at the prediction moment, and the temperature control degree; the predicted temperature fluctuation degree at the prediction moment is obtained according to the local difference of the temperature prediction value in the temperature value data; the PID parameters are adjusted according to the predicted temperature fluctuation degree to obtain the adjusted PID parameters at the prediction moment; the temperature regulating device at the prediction moment is PID controlled using the adjusted PID parameters at the prediction moment. The embodiment of the present invention achieves reasonable temperature control of the plastic protective tube production process and ensures the quality stability of the plastic protective tube by making the adjusted PID parameters adapt to the influence of drastic changes at the prediction moment.

[0125] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0126] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A multifunctional extruder for producing plastic protective tubes, characterized in that: The extruder includes a temperature regulating device for regulating the temperature of the production raw materials in each temperature control process, a temperature sensor for collecting the temperature of the production raw materials, a power sensor for collecting the heating power of the temperature regulating device, and a controller for controlling the temperature regulating device. The controller samples and connects the temperature sensor and the power sensor to obtain the temperature value and the power value at all sampling moments, and controls the temperature regulating device according to the temperature value and the power value at all sampling moments. The control process includes: According to the relevant conditions of the temperature value data and the power value data corresponding to the preset surrounding time range at the prediction moment, the adjusted power value data and the effective power at the prediction moment are obtained; according to the difference in time series between the adjusted power value data and the temperature value data, the temperature control degree at the prediction moment is obtained; according to the temperature value at the moment before the prediction moment, the effective power at the prediction moment and the temperature control degree, the temperature prediction value at the prediction moment is obtained; According to the local difference of the temperature prediction value in the temperature value data, the predicted temperature fluctuation at the prediction time is obtained; according to the predicted temperature fluctuation, the set PID parameters are adjusted to obtain the adjusted PID parameters at the prediction time; and the adjusted PID parameters at the prediction time are used to perform PID control on the temperature regulating device at the prediction time; The method for obtaining the adjusted power value data and the effective power at the prediction time includes: Obtaining each reference lag time; moving the power value data by the reference lag time, and obtaining the moving power value data corresponding to each reference lag time; According to the correlation coefficient between the temperature value data corresponding to the preset surrounding time range of the prediction moment and the mobile power value data corresponding to each reference lag time, the temperature control related index corresponding to each reference lag time is obtained; The reference lag time corresponding to the maximum temperature control related index is used as the temperature control lag time; the mobile power value data corresponding to the temperature control lag time is used as the adjusted power value data; the power value corresponding to the predicted time in the adjusted power value data is used as the effective power at the predicted time; The method for obtaining the temperature control degree includes: Get all surrounding moments of the predicted moment; According to the difference between the power value at each surrounding moment and the adjacent power values, a power difference index at each surrounding moment is obtained; According to the difference between the temperature value at each surrounding moment and the adjacent temperature values, the temperature difference index at each surrounding moment is obtained; According to the deviation of the power difference index and the temperature difference index at each ambient moment, the local temperature control index at each ambient moment is obtained; Obtaining the temperature control degree according to the overall distribution of local temperature control indicators at all surrounding moments; The method for obtaining the temperature prediction value comprises: According to the difference between the applied power at the prediction moment and the power value at the previous moment, the power change parameter at the prediction moment is obtained; According to the power change parameter and the temperature control degree at the prediction time, the temperature change parameter at the prediction time is obtained; The temperature change parameter and the temperature value at the moment before the prediction moment are combined to obtain the temperature prediction value at the prediction moment; The method for obtaining the predicted temperature fluctuation at the predicted time includes: Obtain the reference fluctuation time of the prediction time; obtain the surrounding fluctuation index of the prediction time according to the fluctuation of the temperature values ​​corresponding to all reference fluctuation times; Obtaining a predicted fluctuation index at the predicted moment according to the difference between the predicted temperature value at the predicted moment and the overall distribution of temperature values ​​at all reference fluctuation moments; According to the deviation between the predicted fluctuation index at the predicted time and the surrounding fluctuation index, the predicted temperature fluctuation degree at the predicted time is obtained; the predicted fluctuation index is positively correlated with the predicted temperature fluctuation degree; the surrounding fluctuation index is negatively correlated with the predicted temperature fluctuation degree; The method for obtaining the adjusted PID parameters at the prediction time includes: The PID parameters to be set include: a preset proportional coefficient, a preset integral coefficient, and a preset differential coefficient; Calculate the sum of 1 and the predicted temperature fluctuation, calculate the product of the sum and the preset proportional coefficient, and obtain the adjusted proportional coefficient; Calculate the difference between 1 and the predicted temperature fluctuation, calculate the product of the difference and the preset integral coefficient, and obtain the adjusted integral coefficient; Calculate the sum of 1 and the predicted temperature fluctuation, calculate the product of the sum and the preset differential coefficient, and obtain the adjusted differential coefficient; The adjusted proportional coefficient, the adjusted integral coefficient and the adjusted differential coefficient are used as the adjusted PID parameters at the prediction time.

2. A multifunctional extruder for producing plastic protective tubes according to claim 1, characterized in that: The method for acquiring surrounding moments includes: taking a preset number of sampling moments surrounding the predicted moment as all surrounding moments of the predicted moment.

3. The multifunctional extruder for producing plastic protective tubes according to claim 1, characterized in that: The method for obtaining the power difference index includes: The difference value of the power value at each surrounding time is calculated to obtain the power difference index at each surrounding time.

4. The multifunctional extruder for producing plastic protective tubes according to claim 1, characterized in that: Methods for obtaining the forecast volatility index include: The average of the temperature values ​​of all reference fluctuation moments at the prediction moment is calculated to obtain the overall ambient temperature value at the prediction moment; the absolute value of the difference between the temperature prediction value at the prediction moment and the overall ambient temperature value is calculated to obtain the prediction fluctuation index.

5. The multifunctional extruder for producing plastic protective tubes according to claim 1, characterized in that: The last sampling moment is the current moment, and the next moment after the current moment is taken as the predicted moment.

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