A temperature control method and system for polyurethane foaming production equipment

Abstract

The present application relates to the technical field of temperature control in the production of foaming machines, and specifically to a temperature control method and system for polyurethane foaming production equipment, the method comprising: determining the fluctuation intensity of each historical temperature data at the current moment; determining the fluctuation difference of each oscillation set at the current moment according to the difference between the peak value ratio, the half-wave peak value ratio and the range ratio in each oscillation set at the current moment; based on all the fluctuation differences, combined with the fluctuation of all historical temperature data at the current moment, determining the temperature fluctuation regularity at the current moment, so as to control the temperature of the polyurethane foaming production equipment. The present application regulates the parameters of the PID controller through the temperature fluctuation regularity, which can improve the accuracy of temperature control in the polyurethane foaming production process.

Description

Technical Field

[0001] The present application relates to the technical field of temperature control in foaming machine production, and in particular to a temperature control method and system for polyurethane foaming production equipment. Background Art

[0002] Polyurethane is a polymer compound generated by isocyanate and polyol under the action of catalyst. It has excellent physical and chemical properties, such as high strength, high toughness, wear resistance, chemical corrosion resistance, etc. Polyurethane can be made into products with moisture-proof, heat-insulating, sound-insulating and other properties through foaming process, and has good market and development prospects.

[0003] During the polyurethane foaming process, too high a temperature will cause the initial injection of foam liquid to react prematurely, while the subsequent injection of foam liquid will not react sufficiently, thus forming cavitation in the product. On the contrary, too low a temperature will cause defects such as internal cracks and cracks in the product, affecting the structural integrity and appearance of the product.

[0004] In traditional technology, PID control algorithm is generally used to control the temperature of polyurethane foam production equipment. However, since the PID control algorithm with fixed parameters is a linear system, overshoot is prone to occur when the temperature of polyurethane foam production equipment is adjusted. Summary of the invention

[0005] In order to solve the above technical problems, the purpose of this application is to provide a temperature control method and system for polyurethane foaming production equipment. The technical solutions adopted are as follows:

[0006] In a first aspect, an embodiment of the present application provides a temperature control method for a polyurethane foaming production device, the method comprising the following steps:

[0007] Collect historical temperature data of all collection moments in the preset time period before the current moment of the polyurethane foam production equipment;

[0008] In each historical temperature data at the current moment and its neighborhood, the fluctuation intensity of each historical temperature data at the current moment is determined according to the fluctuation of all historical temperature data and the difference of all adjacent historical temperature data;

[0009] Get the minimum values ​​in the fluctuation intensity of all historical temperature data at the current moment. The peak value, half-peak value and range of all fluctuation intensity between adjacent minimum values ​​at the current moment constitute the oscillation sequences at the current moment; the ratio of the peak value, half-peak value and range between adjacent oscillation sequences at the current moment constitute the oscillation sets at the current moment;

[0010] According to the differences between the peak value ratio, half-peak value ratio and range ratio of each oscillation set at the current moment, the fluctuation difference degree of each oscillation set at the current moment is determined;

[0011] Based on all the fluctuation differences and in combination with the fluctuation of all historical temperature data at the current moment, the temperature fluctuation regularity at the current moment is determined to control the temperature of the polyurethane foaming production equipment.

[0012] Preferably, the method for determining the fluctuation intensity of each historical temperature data at the current moment is:

[0013] Analyze the range of each historical temperature data at the current moment and all historical temperature data in its neighborhood;

[0014] Analyze the cumulative sum of differences between each historical temperature data at the current moment and all adjacent historical temperature data in its neighborhood, and record it as the first sum value of each historical temperature data at the current moment;

[0015] The fluctuation intensity of each historical temperature data at the current moment is the ratio of the first sum value of each historical temperature data at the current moment to the range.

[0016] Preferably, the fluctuation difference of each oscillation set at the current moment is the result of the fusion of the difference between any two of the ratio of the peak value, the ratio of the half-peak value and the ratio of the range in each oscillation set at the current moment.

[0017] Preferably, the method for determining the temperature fluctuation regularity at the current moment is:

[0018] Analyze the mean of the fluctuation difference of all oscillation sets at the current moment, and record it as the first temperature fluctuation at the current moment;

[0019] Analyze the extreme difference of all historical temperature data at the current moment and record it as the second temperature fluctuation at the current moment;

[0020] The temperature fluctuation regularity at the current moment is determined based on the first temperature fluctuation degree and the second temperature fluctuation degree in combination with the maximum value of all historical temperature data at the current moment.

[0021] Preferably, the determining of the temperature fluctuation regularity at the current moment based on the first temperature fluctuation degree and the second temperature fluctuation degree in combination with the maximum value of all historical temperature data at the current moment further includes:

[0022] Analyze the ratio of the second temperature fluctuation at the current moment to the maximum value of all historical temperature data at the current moment, and record it as the first ratio at the current moment;

[0023] The oscillation regularity at the current moment is the product of the first temperature fluctuation degree at the current moment and the first ratio.

[0024] Preferably, the temperature of the polyurethane foaming production equipment is controlled, comprising:

[0025] Move the current moment forward by a preset time length, and record it as the forward moment of the current moment;

[0026] Based on the temperature fluctuation regularity at the current moment and the proportional coefficient, integral coefficient and differential coefficient of the PID controller at the previous moment, determine the proportional coefficient, integral coefficient and differential coefficient of the PID controller at the current moment;

[0027] The temperature data of the polyurethane foaming production equipment at the current moment is obtained, and the temperature data at the current moment and the preset target temperature are used as the input of the PID controller. Combined with the proportional coefficient, integral coefficient and differential coefficient of the PID controller at the current moment, the temperature control signal at the current moment is obtained to regulate the temperature data at the current moment.

[0028] Preferably, the expression of the proportional coefficient of the PID controller at the current moment is: K p =K p ′×exp(-hf); where K p Indicates the proportional coefficient of the PID controller at the current moment; K p ′ represents the proportional coefficient of the forward-moving PID controller at the current moment; hf represents the regularity of temperature fluctuation at the current moment; exp() represents an exponential function with a natural constant as the base.

[0029] Preferably, the expression of the integral coefficient of the PID controller at the current moment is: In the formula, K I Indicates the integral coefficient of the PID controller at the current moment; K I ′ represents the integral coefficient of the forward-moving PID controller at the current moment; E represents the ratio of the temperature fluctuation regularity at the current moment to the sum of all temperature fluctuation regularities in the polyurethane foaming production process; x represents the number of iterations of the PID algorithm in the polyurethane foaming production up to the current moment.

[0030] Preferably, the differential coefficient of the PID controller at the current moment is expressed as: K d =K d ′×sig(hf); where K d Indicates the differential coefficient of the PID controller at the current moment; K d ′ represents the differential coefficient of the forward PID controller at the current moment; hf represents the temperature fluctuation regularity at the current moment; sig() represents the sigmoid function.

[0031] In the second aspect, an embodiment of the present application also provides a temperature control system for polyurethane foam production equipment, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of a temperature control method for polyurethane foam production equipment described in any one of the above items are implemented.

[0032] This application has at least the following beneficial effects:

[0033] The present application determines the fluctuation intensity of each historical temperature data at the current moment according to the fluctuation of all historical temperature data and the difference of all adjacent historical temperature data in each historical temperature data and its neighborhood at the current moment, so as to predict and prevent possible temperature fluctuation problems; determines the fluctuation difference of each oscillation set at the current moment according to the difference of the ratio of the peak value, the ratio of the half-wave peak value and the ratio of the extreme difference in each oscillation set at the current moment, so as to monitor the law of temperature change and identify the overshoot phenomenon in the control system; determines the temperature fluctuation regularity at the current moment based on all the said fluctuation differences and the fluctuation of all historical temperature data at the current moment, so as to adjust the parameters of the PID controller and reduce temperature overshoot and vibration.

[0034] The present application obtains the temperature fluctuation regularity by analyzing the oscillation state of the temperature data of the polyurethane foaming production equipment, and adjusts the parameters of the PID controller according to the temperature fluctuation regularity, thereby achieving precise control of the temperature in the polyurethane foaming production process and avoiding the occurrence of overshoot. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application 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 application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0036] Figure 1 A flow chart of the steps of a temperature control method for polyurethane foaming production equipment provided in one embodiment of the present application;

[0037] Figure 2 Schematic diagram of the temperature fluctuation regularity extraction process provided by this application;

[0038] Figure 3 Schematic diagram of the temperature control process of the polyurethane foaming production equipment provided in this application. DETAILED DESCRIPTION

[0039] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the temperature control method and system of a polyurethane foaming production equipment proposed in the present application, its specific implementation, structure, characteristics and effects, 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.

[0040] 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 application belongs.

[0041] The following is a detailed description of a temperature control method and system for polyurethane foaming production equipment provided by the present application in conjunction with the accompanying drawings.

[0042] See also Figure 1 , which shows a flow chart of the steps of a temperature control method for polyurethane foaming production equipment provided by an embodiment of the present application, the method comprising the following steps:

[0043] Step S1: collecting historical temperature data of the polyurethane foaming production equipment during the production process through a temperature sensor, and preprocessing the historical temperature data.

[0044] A temperature sensor is installed in the polyurethane foam production equipment to collect temperature data during the production process of polyurethane foam products. The collection frequency is f, and the collected temperature data is stored in the temperature control system of the polyurethane foam production equipment. For the current moment, the historical temperature data of the temperature control system for a preset time before the current moment is collected.

[0045] It should be noted that the values ​​of the acquisition frequency f and the preset time length are both manually set. In this embodiment, the acquisition frequency f is 10 Hz and the preset time length is set to 30s. The implementer can also set it according to the specific situation. This embodiment does not impose any special restrictions.

[0046] Since the temperature sensor may fail, resulting in missing data collected by the temperature sensor, this embodiment uses a data cleaning method to complete the missing values.

[0047] It should be understood that there are many commonly used methods for filling missing values. In this embodiment, the mean difference method is used to fill the missing temperature data. Under the premise of ensuring the purpose of filling missing values, the implementer can also use other missing value filling methods such as regression interpolation method and EM algorithm. This embodiment does not impose any special restrictions.

[0048] Among them, the mean interpolation method is a well-known technology, and its specific filling process will not be repeated.

[0049] Step S2: In each historical temperature data at the current moment and its neighborhood, the fluctuation intensity of each historical temperature data at the current moment is determined according to the fluctuation of all historical temperature data and the difference of all adjacent historical temperature data.

[0050] In the process of controlling the temperature of polyurethane foam production equipment, the production temperature of the foaming equipment oscillates within a certain range due to factors such as heating equipment and environment. The higher the oscillation of temperature data, the more sensitive the control system of the foaming equipment is to the control input. In the temperature control of the foaming equipment, the proportional coefficient of PID control should be reduced to reduce the amplitude of the control signal and reduce the oscillation of the system.

[0051] Therefore, in order to evaluate the sensitivity of the control system to environmental changes, based on the fluctuation of all historical temperature data and the difference of all adjacent historical temperature data, the fluctuation intensity of each historical temperature data at the current moment is determined to predict and prevent possible temperature fluctuation problems, thereby adjusting the parameters of the PID controller, reducing the oscillation of the system, and improving the quality of polyurethane foam products. Specifically:

[0052] The neighborhood W is divided with the historical temperature data at the current moment as the center, wherein the value of the neighborhood W is set manually. In this embodiment, the value of the neighborhood W is 4, and the implementer can also set it according to the specific situation. This embodiment does not impose any special restrictions.

[0053] Analyze the range of each historical temperature data at the current moment and all historical temperature data in its neighborhood;

[0054] Analyze the cumulative sum of differences between each historical temperature data at the current moment and all adjacent historical temperature data in its neighborhood, and record it as the first sum value of each historical temperature data at the current moment;

[0055] It should be noted that there are many ways to measure differences. In this embodiment, the absolute value of the difference between the adjacent historical temperature data is taken to measure the difference therebetween. The implementer may also use other methods of measuring differences such as ratios according to specific circumstances, and this embodiment does not impose any special restrictions.

[0056] The fluctuation intensity of each historical temperature data at the current moment is the ratio of the first sum value of each historical temperature data at the current moment to the range.

[0057] The temperature oscillation of the polyurethane foam production equipment is constantly changing within a range, rather than having only a single trend of growth or decline. When the difference between the adjacent historical temperature data is greater, that is, the first sum value is larger, it means that the temperature oscillation is higher, and when the range value is smaller, it means that the range of temperature oscillation is narrowed but the frequency of temperature oscillation is increased, that is, the higher the temperature oscillation, the greater the fluctuation intensity at the current moment; conversely, when the difference between the adjacent historical temperature data is smaller, that is, the first sum value is smaller, it means that the temperature oscillation is lower, and when the range value is larger, it means that the range of temperature oscillation is expanded but the frequency of temperature oscillation is reduced, that is, the lower the temperature oscillation, the smaller the fluctuation intensity at the current moment.

[0058] Step S3: Determine the fluctuation difference of each oscillation set at the current moment according to the difference between the peak value ratio, the half-peak value ratio and the range ratio in each oscillation set at the current moment.

[0059] When the temperature change in the production process of polyurethane foam production equipment has a certain convergence characteristic, that is, the temperature of the foam production equipment oscillates around the preset production temperature, and the amplitude of the oscillation is getting smaller and smaller. The temperature fluctuation in the production process of polyurethane foam production equipment is a regular fluctuation. This fluctuation can be used to control the temperature of polyurethane foam production equipment by adjusting the proportional integral of the PID control algorithm, so that the temperature of the polyurethane foam production equipment can reach the preset target temperature faster.

[0060] First, the fluctuation intensity of all historical temperature data at the current moment is used as the input of the extreme point detection algorithm to obtain each minimum value, obtain the peak value of all fluctuation intensities between adjacent minimum values, the collection time corresponding to the half-peak value, and the extreme difference value. The peak value and the half-peak value between adjacent minimum values ​​constitute each oscillation sequence at the current moment; the peak value ratio, the half-peak value ratio and the extreme difference ratio between adjacent oscillation sequences at the current moment constitute each oscillation set at the current moment, and constitute each oscillation set at the current moment. Among them, the half-peak value is half of the corresponding peak value.

[0061] Furthermore, in order to evaluate the regularity of the oscillation behavior in the current temperature control process and adjust the various parameters in the PID control algorithm, the fluctuation difference of each oscillation set at the current moment is determined based on the difference between the peak value ratio, half-wave peak value ratio and range ratio in each oscillation set at the current moment, so as to monitor the law of temperature change and identify and reduce the over-adjustment phenomenon in the control system, specifically:

[0062] The fluctuation difference of each oscillation set at the current moment is the result of the fusion of the difference between the peak value ratio, the half-peak value ratio and the range ratio in each oscillation set at the current moment.

[0063] It should be understood that fusion refers to combining two or more indicators by adding or multiplying them together in order to obtain a comprehensive indicator, thereby more comprehensively and accurately evaluating a phenomenon or problem. This fusion method is not limited to simple arithmetic operations, but can also include more complex statistical models and analysis methods. The implementer can choose according to the specific situation, and this embodiment does not impose any special restrictions.

[0064] Preferably, in the present embodiment, the fluctuation difference of each oscillation set at the current moment is the cumulative result of the differences between the ratio of peak value, the ratio of half-peak value and the ratio of extreme value in each oscillation set at the current moment; in actual application, as other embodiments, the fluctuation difference of each oscillation set at the current moment is an exponential function value with a natural constant as the base and the sum of the differences between the ratio of peak value, the ratio of half-peak value and the ratio of extreme value in each oscillation set at the current moment as the independent variable.

[0065] The more similar the changing trends of the two oscillation sequences are, the higher the regularity of the elements in the two oscillation sequences, that is, the closer the ratio of the peak values, the ratio of the half-peak values, and the ratio of the extreme values ​​are, the smaller the difference between the elements in the oscillation sets between the two oscillation sequences is, and thus the smaller the value of the fluctuation difference is; conversely, the greater the difference between the two oscillation sequences, the lower the regularity of the elements in the two oscillation sequences, that is, the greater the difference between the ratio of the peak values, the ratio of the half-peak values, and the ratio of the extreme values, and thus the greater the value of the fluctuation difference is.

[0066] Step S4: Based on all the fluctuation differences and in combination with the fluctuation of all historical temperature data at the current moment, determine the temperature fluctuation regularity at the current moment.

[0067] In order to quantify the regularity of temperature fluctuations and the change of amplitude, to more accurately adjust PID parameters, thereby reducing temperature overshoot and vibration, improving the stability and efficiency of temperature control, and ensuring the stability and quality of polyurethane foam products, based on all the fluctuation differences, combined with the fluctuation of all historical temperature data at the current moment, the temperature fluctuation regularity at the current moment is determined, specifically:

[0068] Analyze the mean of the fluctuation difference of all oscillation sets at the current moment, and record it as the first temperature fluctuation at the current moment;

[0069] Analyze the extreme difference of all historical temperature data at the current moment and record it as the second temperature fluctuation at the current moment;

[0070] Analyze the ratio of the second temperature fluctuation at the current moment to the maximum value of all historical temperature data at the current moment, and record it as the first ratio at the current moment;

[0071] The oscillation regularity at the current moment is the product of the first temperature fluctuation degree at the current moment and the first ratio.

[0072] When the temperature change of the polyurethane foam production equipment at the previous moment has a certain regularity in form, the first temperature fluctuation is small; the larger the ratio of the second temperature fluctuation to the maximum value at the current moment, the wider the distribution range of the historical temperature data at the current moment, and the greater the difference between the historical temperature data at the current moment, which makes the value of the temperature fluctuation regularity of the polyurethane foam production equipment larger. The larger the temperature fluctuation regularity, the greater the oscillation of the polyurethane foam production equipment, and the temperature change has a higher regularity in form. When the polyurethane foam production equipment is controlled by the PID algorithm in the next stage, the proportional coefficient of the PID algorithm needs to be reduced to ensure that when the temperature of the polyurethane foam production equipment is regulated, the temperature overshoot and oscillation are small, and the temperature of the polyurethane foam production equipment is kept fluctuating within a smaller range.

[0073] Preferably, the schematic diagram of the temperature fluctuation regularity extraction process provided in the present application is as follows: Figure 2 shown.

[0074] Step S5: Determine the proportional coefficient, integral coefficient and differential coefficient of the PID controller at the current moment based on the temperature fluctuation regularity at the current moment and the proportional coefficient, integral coefficient and differential coefficient of the PID controller at the previous moment of the current moment.

[0075] (1) When using the PID control algorithm to control the production temperature of the polyurethane foam production equipment, the oscillation is caused by the PID controller's excessive response to the temperature error. The proportional coefficient of the PID control should be reduced to reduce the system's response amplitude. Therefore, based on the temperature fluctuation regularity at the current moment and the proportional coefficient of the PID controller at the previous moment of the current moment, the proportional coefficient of the PID controller at the current moment is calculated.

[0076] The current moment is moved forward by a time corresponding to a preset time length, which is recorded as the forward time of the current moment.

[0077] The expression of the proportional coefficient of the PID controller at the current moment is: K p =K p ′×exp(-hf); where K p Indicates the proportional coefficient of the PID controller at the current moment; K p ′ represents the proportional coefficient of the forward-moving PID controller at the current moment; hf represents the regularity of temperature fluctuation at the current moment; exp() represents an exponential function with a natural constant as the base.

[0078] When the temperature oscillation of the polyurethane foam production equipment is greater, the value of the temperature fluctuation regularity of the polyurethane foam production equipment will be greater, and the proportional coefficient of the PID control should be reduced to weaken the temperature oscillation of the polyurethane foam production equipment and reduce the error between the temperature of the polyurethane foam production equipment and the preset target temperature value.

[0079] It should be noted that the value of the preset target temperature is manually set. In this embodiment, the value of the preset target temperature is 35° C. The specific preset target temperature needs to be set by the implementer according to the required temperature of the product produced by the polyurethane foaming production equipment.

[0080] (2) The integral coefficient is used to eliminate static errors. When the temperature of the oscillating polyurethane foaming production equipment cannot reach the preset target temperature, appropriately increasing the integral parameter can accelerate the error correction process, so that the temperature can quickly converge to the preset target temperature value. As time goes by, the number of PID algorithm runs increases. Since the integral coefficient controls the cumulative sum of errors, the integral coefficient control part becomes larger and larger, resulting in system instability. Therefore, it is necessary to reduce the integral coefficient according to time. Therefore, based on the temperature fluctuation regularity at the current moment and the integral coefficient of the PID controller at the forward moment of the current moment, the integral coefficient of the PID controller at the current moment is calculated.

[0081] The expression of the integral coefficient of the PID controller at the current moment is: In the formula, K I Indicates the integral coefficient of the PID controller at the current moment; K I ′ represents the integral coefficient of the forward-moving PID controller at the current moment; E represents the ratio of the temperature fluctuation regularity at the current moment to the sum of all temperature fluctuation regularities in the polyurethane foaming production process; x represents the number of iterations of the PID algorithm in the polyurethane foaming production up to the current moment.

[0082] As time goes by, the part controlled by the integral parameter in the PID control algorithm becomes larger and larger. Therefore, the number of PID runs is required to adjust the data integral coefficient. When the temperature oscillation in the temperature control system is stronger, the integral parameter should be increased to eliminate the static error in the temperature control system so that the temperature can quickly converge to the preset target temperature.

[0083] (3) The differential coefficient can predict the future behavior of the system and help reduce oscillations. If the oscillation is due to the system's overly sensitive response to changes, increasing the differential coefficient can suppress the oscillation. Therefore, based on the temperature fluctuation regularity at the current moment and the differential coefficient of the PID controller at the previous moment of the current moment, the differential coefficient of the PID controller at the current moment is calculated.

[0084] The expression of the differential coefficient of the PID controller at the current moment is: K d =K d ′×sig(hf); where K d Indicates the differential coefficient of the PID controller at the current moment; K d ′ represents the differential coefficient of the forward PID controller at the current moment; hf represents the temperature fluctuation regularity at the current moment; sig() represents the sigmoid function.

[0085] As PID control proceeds, the temperature error of the temperature control system (the difference between the current temperature of the foaming production equipment and the preset target temperature) becomes smaller and smaller, and the oscillation of the temperature control system weakens, making the value of the temperature fluctuation regularity of the polyurethane foaming production equipment smaller. The differential coefficient of the PID algorithm can be reduced so that the temperature of the polyurethane foaming production equipment reaches the optimal temperature.

[0086] The PID algorithm is improved by using the proportional coefficient, integral coefficient, and differential coefficient of the PID algorithm at the current moment obtained above. The improved algorithm can make the temperature of the polyurethane foam production equipment converge to the preset target temperature value quickly, and can make the products produced by the polyurethane foam production equipment have higher quality and less defective rate. Among them, the PID algorithm is a well-known technology, and the specific calculation process will not be repeated.

[0087] Step S6: Based on the proportional coefficient, integral coefficient and differential coefficient of the PID controller at the current moment, the temperature data at the current moment is regulated.

[0088] The temperature PID controller is connected to the polyurethane foam production equipment, and the temperature sensor is used to monitor the temperature data of the polyurethane foam production equipment at the current moment.

[0089] The current temperature data and the preset target temperature are used as the input of the PID controller, and the proportional coefficient, integral coefficient and differential coefficient of the current PID controller are used as the adaptive gain coefficient of the PID controller to obtain the current temperature control signal to regulate the current temperature data. The temperature of the polyurethane foam production equipment can quickly converge to the preset target temperature, and the temperature of the polyurethane foam production equipment is kept in a smaller range of fluctuations, thereby improving the quality of the product and reducing the defective rate, and realizing efficient and stable production of polyurethane foam products.

[0090] At this point, based on the proportional coefficient, integral coefficient and differential coefficient of the PID controller at the current moment, the temperature data at the current moment is regulated.

[0091] Preferably, the schematic diagram of the temperature control process of the polyurethane foaming production equipment provided in the present application is as follows Figure 3 shown.

[0092] Based on the same inventive concept as the above method, an embodiment of the present application also provides a temperature control system for polyurethane foaming production equipment, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of any one of the temperature control methods for polyurethane foaming production equipment are implemented.

[0093] It should be noted that the above sequence of the embodiments of the present application is for description only and does not represent the advantages and disadvantages of the embodiments. The above is a description of a specific embodiment of this specification. In addition, 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.

[0094] 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.

[0095] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application should be included in the protection scope of the present application.

Claims

1. A temperature control method for polyurethane foaming production equipment, characterized in that: The method comprises the following steps: Collect historical temperature data of all collection moments in the preset time period before the current moment of the polyurethane foam production equipment; In each historical temperature data at the current moment and its neighborhood, the fluctuation intensity of each historical temperature data at the current moment is determined according to the fluctuation of all historical temperature data and the difference of all adjacent historical temperature data; Get the minimum values ​​in the fluctuation intensity of all historical temperature data at the current moment. The peak value, half-peak value and range of all fluctuation intensity between adjacent minimum values ​​at the current moment constitute the oscillation sequences at the current moment; the ratio of the peak value, half-peak value and range between adjacent oscillation sequences at the current moment constitute the oscillation sets at the current moment; According to the differences between the peak value ratio, half-peak value ratio and range ratio of each oscillation set at the current moment, the fluctuation difference degree of each oscillation set at the current moment is determined; Based on all the fluctuation differences, combined with the fluctuation of all historical temperature data at the current moment, the temperature fluctuation regularity at the current moment is determined to control the temperature of the polyurethane foaming production equipment; The method for determining the temperature fluctuation regularity at the current moment is: Analyze the mean of the fluctuation difference of all oscillation sets at the current moment, and record it as the first temperature fluctuation at the current moment; Analyze the extreme difference of all historical temperature data at the current moment and record it as the second temperature fluctuation at the current moment; Based on the first temperature fluctuation degree and the second temperature fluctuation degree, combined with the maximum value of all historical temperature data at the current moment, determine the temperature fluctuation regularity at the current moment; The determining of the temperature fluctuation regularity at the current moment based on the first temperature fluctuation degree and the second temperature fluctuation degree in combination with the maximum value of all historical temperature data at the current moment further includes: Analyze the ratio of the second temperature fluctuation at the current moment to the maximum value of all historical temperature data at the current moment, and record it as the first ratio at the current moment; The temperature fluctuation regularity at the current moment is the product of the first temperature fluctuation degree at the current moment and the first ratio.

2. A temperature control method for polyurethane foaming production equipment according to claim 1, characterized in that: The method for determining the fluctuation intensity of each historical temperature data at the current moment is: Analyze the range of each historical temperature data at the current moment and all historical temperature data in its neighborhood; Analyze the cumulative sum of differences between each historical temperature data at the current moment and all adjacent historical temperature data in its neighborhood, and record it as the first sum value of each historical temperature data at the current moment; The fluctuation intensity of each historical temperature data at the current moment is the ratio of the first sum value of each historical temperature data at the current moment to the range.

3. A temperature control method for polyurethane foaming production equipment according to claim 1, characterized in that: The fluctuation difference of each oscillation set at the current moment is the result of the fusion of the difference between each other among the ratio of the peak value, the ratio of the half-wave peak value and the ratio of the range in each oscillation set at the current moment.

4. A temperature control method for polyurethane foaming production equipment according to claim 1, characterized in that: The temperature of the polyurethane foaming production equipment is controlled, including: Move the current moment forward by a preset time length, and record it as the forward moment of the current moment; Based on the temperature fluctuation regularity at the current moment and the proportional coefficient, integral coefficient and differential coefficient of the PID controller at the previous moment, determine the proportional coefficient, integral coefficient and differential coefficient of the PID controller at the current moment; The temperature data of the polyurethane foaming production equipment at the current moment is obtained, and the temperature data at the current moment and the preset target temperature are used as the input of the PID controller. Combined with the proportional coefficient, integral coefficient and differential coefficient of the PID controller at the current moment, the temperature control signal at the current moment is obtained to regulate the temperature data at the current moment.

5. A temperature control method for polyurethane foaming production equipment as claimed in claim 4, characterized in that: The expression of the proportional coefficient of the PID controller at the current moment is: K p =K p ′×exp(-hf); where K p Indicates the proportional coefficient of the PID controller at the current moment; K p ′ represents the proportional coefficient of the forward-moving PID controller at the current moment; hf represents the regularity of temperature fluctuation at the current moment; exp() represents an exponential function with a natural constant as the base.

6. A temperature control method for polyurethane foaming production equipment as claimed in claim 4, characterized in that: The expression of the integral coefficient of the PID controller at the current moment is: In the formula, K I Indicates the integral coefficient of the PID controller at the current moment; K I ′ represents the integral coefficient of the forward-moving PID controller at the current moment; E represents the ratio of the temperature fluctuation regularity at the current moment to the sum of all temperature fluctuation regularities in the polyurethane foaming production process; x represents the number of iterations of the PID algorithm in the polyurethane foaming production up to the current moment.

7. A temperature control method for polyurethane foaming production equipment as claimed in claim 4, characterized in that: The expression of the differential coefficient of the PID controller at the current moment is: K d =K d ′×sig(hf); where K d Indicates the differential coefficient of the PID controller at the current moment; K d ′ represents the differential coefficient of the forward PID controller at the current moment; hf represents the temperature fluctuation regularity at the current moment; sig() represents the sigmoid function.

8. A temperature control system for polyurethane foam production equipment, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the temperature control method for polyurethane foaming production equipment as described in any one of claims 1-7 are implemented.

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