Cold-pressed terminal processing control method and system and related equipment

Abstract

The invention relates to the technical field of terminal processing, in particular to a cold-pressed terminal processing control method and system and related equipment, and the method comprises the steps: determining the temperature fluctuation intensity of each position point at each collection moment; determining a noise elimination weight of each position point at each acquisition moment; determining the melt temperature difference of any section at each acquisition moment, and determining the temperature control response capability of the heating element in any section at each acquisition moment in combination with the change trend of the temperature fluctuation intensity of each position point at each acquisition moment and all adjacent moments thereof; and the temperature of the charging barrel of the injection molding machine is regulated and controlled by combining the significant conditions of the gray values of all the pixel points in the gray-scale map of the plastic cold-pressed terminal. By comprehensively analyzing the temperature of the plastic melt in the charging barrel, the precision of temperature control in the processing process of the plastic cold-pressed terminal is improved.

Description

Technical Field

[0001] The present application relates to the field of terminal processing technology, and in particular to a cold-pressed terminal processing control method, system and related equipment. Background Art

[0002] Plastic cold-pressed terminals are accessories for electrical connections. Polypropylene (PP) offers high-temperature resistance, electrical insulation, and chemical stability. As a non-metallic cold-pressed terminal, these PP injection-molded terminals are lightweight, insulating, and corrosion-resistant. The injection molding process for these terminals requires extremely high precision. Fluctuations and temperature differences in the melt temperature can cause residual stress in the plastic, uneven strength at various points, and warping. Therefore, barrel temperature control is often employed to regulate the melt temperature.

[0003] The fuzzy PID control algorithm can adapt to changes in injection molding parameters and external disturbances. It uses fuzzy logic and certain fuzzy rules to optimize PID parameters, overcoming the shortcomings of traditional PID control algorithms, which cannot adjust PID parameters in real time. However, during the injection molding process of plastic cold-pressed terminals, factors such as frictional heat generation and raw material quality can easily affect the actual barrel temperature, resulting in significant dynamic changes. Traditional fuzzy PID control algorithms use a fixed-range fuzzy domain, which is unable to quickly respond to dynamic changes in barrel temperature, reducing the accuracy of temperature control during the plastic cold-pressed terminal processing. Summary of the Invention

[0004] In a first aspect, an embodiment of the present application provides a cold-pressed terminal processing control method, the method comprising the following steps: During the processing of plastic cold-pressed terminals, at each point in any section of the injection molding machine barrel, temperature data is obtained at each acquisition moment and all acquisition moments within a preset time period before each acquisition moment, as well as a grayscale image of the plastic cold-pressed terminal at the acquisition moment before each acquisition moment. All acquisition moments within the preset time period before each acquisition moment are recorded as adjacent times to each acquisition moment. At each location point, fit the temperature data at each acquisition moment and all adjacent moments, and determine the temperature fluctuation intensity of each location point at each acquisition moment based on the difference between the temperature data at each acquisition moment and all adjacent moments and the corresponding fitting results; Based on the change trend of the temperature fluctuation intensity of each position point at each acquisition moment and all adjacent moments, the temperature change trend of the injection molding machine barrel at each acquisition moment is determined, and the noise exclusion weight of each position point at each acquisition moment is determined in combination with the temperature fluctuation intensity; In any section, based on the difference in temperature data between two locations at each acquisition moment, and the difference in all temperature data between two locations at each acquisition moment and all adjacent moments, the melt temperature difference of any section at each acquisition moment is determined. In combination with the change trend of the temperature fluctuation intensity of each location at each acquisition moment and all adjacent moments, and the noise exclusion weight, the temperature control response capability of the heating element in any section at each acquisition moment is determined. Based on the significance of the grayscale values ​​of all pixels in the grayscale image of the plastic cold-pressed terminal and the temperature control response capability, the expansion factor of any section at each acquisition moment is determined to regulate the temperature of the injection molding machine barrel.

[0005] Preferably, the method for determining the temperature fluctuation intensity at each location at each acquisition moment is: At each position point on the barrel of the injection molding machine, the temperature data of all adjacent moments of each acquisition moment are fitted to obtain the temperature fitting curve of each position point at each acquisition moment. The average of the differences between the temperature data of all adjacent moments of each acquisition moment and the corresponding fitting values ​​on the temperature fitting curve is taken as the temperature fluctuation intensity of each position point at each acquisition moment.

[0006] Preferably, the method for determining the temperature change trend of the injection molding machine barrel at each collection moment is: At each location point, the temperature fluctuation intensity of all adjacent moments at each acquisition moment is used as the input of the trend detection algorithm, and the slope value of each location point at each acquisition moment is output; The temperature change trend of the injection molding machine barrel at each sampling moment is the normalized result of the average of the absolute values ​​of the slope values ​​of all position points in the injection molding machine barrel at each sampling moment.

[0007] Preferably, the noise exclusion weight of each location point at each acquisition moment is expressed as follows: Where, represents the noise exclusion weight of point j at acquisition time i; Indicates the temperature change trend of the injection molding machine barrel at the acquisition time i; Indicates the temperature fluctuation intensity of point j at acquisition time i.

[0008] Preferably, the method for determining the melt temperature difference of any section at each collection time is: In any section of the injection molding machine barrel, the difference in temperature data between two points at each sampling moment is recorded as the first difference of any section at each sampling moment; The difference of all temperature data between two points in any section at each acquisition moment and its adjacent moments is recorded as the second difference of any section at each acquisition moment; The melt temperature difference of any section of the injection molding machine barrel at each sampling moment is the product of the first difference and the second difference of any section at each sampling moment.

[0009] Preferably, the expression for the temperature control response capability of the heating element in any section at each acquisition moment is: Where, Indicates the temperature control response capability of the heating element in section u at the acquisition time i; It represents the mean of the slope values ​​of two points in section u at the acquisition time i; Indicates the melt temperature difference of section u at acquisition time i; It represents the mean of the noise exclusion weights of two points in section u at the acquisition time i.

[0010] Preferably, the method for determining the expansion and contraction factor of any section at each collection moment is: The grayscale image of the plastic cold-pressed terminal at the previous acquisition moment of each acquisition moment is used as the input of the saliency detection algorithm, and a saliency map is output. The cumulative saliency values ​​of all pixels in the saliency map are used as the terminal color factor at each acquisition moment. The expansion factor of section u at the acquisition time i The expression is: Where, Indicates the preset stretch constant; represents the terminal color factor at the acquisition time i; norm( ) represents the normalization function.

[0011] Preferably, the temperature of the injection molding machine barrel is controlled, comprising: Calculate the difference between the temperature data of each position point in any section at each collection time and the preset temperature, and take the average of the difference between two position points in any section as the temperature error of any section at each collection time; Calculate the difference in temperature error of any section between each acquisition moment and the previous acquisition moment as the temperature error change rate of any section at each acquisition moment; The temperature error and temperature error change rate of any section at each acquisition moment are used as the input of the fuzzy PID controller, wherein the expansion factor of any section at each acquisition moment is multiplied by each element in the preset initial fuzzy domain of the temperature error and each element in the preset initial fuzzy domain of the temperature error change rate, and the multiplication results are used as the temperature error fuzzy domain and the temperature error change rate fuzzy domain of any section at each acquisition moment, respectively. The membership function of the fuzzy PID controller adopts a triangular membership function, outputs the gain coefficient of any section at each acquisition moment, and transmits the gain coefficient to the corresponding section of the injection molding machine barrel, so as to regulate the temperature data of the heating element in the corresponding section on the injection molding machine barrel at each acquisition moment.

[0012] In a second aspect, an embodiment of the present application provides a cold-pressed terminal processing control system, the system comprising: The temperature data acquisition module is used to acquire temperature data at each acquisition moment and all acquisition moments within a preset time period before each acquisition moment at each position point in any section of the injection molding machine barrel during the processing of plastic cold-pressed terminals. The module also acquires a grayscale image of the plastic cold-pressed terminals at the acquisition moment before each acquisition moment, and records all acquisition moments within a preset time period before each acquisition moment as adjacent times to each acquisition moment. A weight acquisition module is used to fit the temperature data of each acquisition moment and all adjacent moments at each location point, and determine the temperature fluctuation intensity of each location point at each acquisition moment based on the difference between the temperature data of each acquisition moment and all adjacent moments and the corresponding fitting results; Based on the change trend of the temperature fluctuation intensity of each position point at each acquisition moment and all adjacent moments, the temperature change trend of the injection molding machine barrel at each acquisition moment is determined, and the noise exclusion weight of each position point at each acquisition moment is determined in combination with the temperature fluctuation intensity; In any section, based on the difference in temperature data between two locations at each acquisition moment, and the difference in all temperature data between two locations at each acquisition moment and all adjacent moments, the melt temperature difference of any section at each acquisition moment is determined. In combination with the change trend of the temperature fluctuation intensity of each location at each acquisition moment and all adjacent moments, and the noise exclusion weight, the temperature control response capability of the heating element in any section at each acquisition moment is determined. The control module is used to determine the expansion and contraction factor of any section at each acquisition time based on the significance of the grayscale values ​​of all pixels in the grayscale image of the plastic cold-pressed terminal and the temperature control response capability, and to control the temperature of the injection molding machine barrel.

[0013] In a third aspect, an embodiment of the present application also provides a cold-pressed terminal processing control-related device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above-mentioned cold-pressed terminal processing control methods when executing the computer program.

[0014] As can be seen from the above embodiments, the cold-pressed terminal processing control method provided in the embodiments of the present application has at least the following beneficial effects: The present application fits the temperature data of each acquisition moment and all adjacent moments at each position point, determines the temperature fluctuation intensity of each position point at each acquisition moment based on the difference between the temperature data of each acquisition moment and all adjacent moments and the corresponding fitting result, and determines the noise exclusion weight of each position point at each acquisition moment in combination with the changing trend of the temperature fluctuation intensity of each position point at each acquisition moment and all adjacent moments. The beneficial effect of this application is that it can eliminate the influence of frictional heat generated by granular PP plastic and the injection molding machine barrel wall on the temperature analysis of the injection molding machine barrel, thereby improving the accuracy of temperature analysis. This application determines the melt temperature difference in any section at each acquisition moment based on the difference in temperature data between two locations in any section at each acquisition moment, as well as the difference in all temperature data between two locations at each acquisition moment and all adjacent moments. Furthermore, the application combines the trend of the temperature fluctuation intensity at each location at each acquisition moment and all adjacent moments, as well as the noise exclusion weight, to determine the temperature control response capability of the heating element in any section at each acquisition moment. This has the beneficial effect of improving the control over the melting and flow processes of the plastic, eliminating melt temperature differences, preventing large temperature differences in the plastic melt during injection, and improving the quality of plastic cold-pressed terminals. This application is based on the significant situation of the grayscale values ​​of all pixels in the grayscale image of the plastic cold-pressed terminal and the temperature control response capability, determines the expansion and contraction factor of any work section at each acquisition moment, and regulates the temperature of the injection molding machine barrel. Its beneficial effect is that it can quickly respond to the dynamic changes in the barrel temperature, provide a fast response capability when the barrel temperature change characteristics are strong, eliminate the interference of frictional heat when the barrel temperature is stable, and improve the accuracy of temperature control during the processing of plastic cold-pressed terminals. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0016] Figure 1 A flowchart of a cold-pressed terminal processing control method provided in one embodiment of the present application; Figure 2 A schematic diagram of a noise exclusion weight extraction process provided in one embodiment of the present application; Figure 3 A schematic diagram of a process for obtaining a scaling factor according to an embodiment of the present application; Figure 4 A block diagram of a cold-pressed terminal processing control system provided in one embodiment of the present application. DETAILED DESCRIPTION

[0017] To further illustrate the technical means and effectiveness of this application to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a cold-pressed terminal processing control method, system, and related equipment proposed in this application. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0018] 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.

[0019] The following describes in detail a cold-pressed terminal processing control method, system, and related equipment provided by the present application with reference to the accompanying drawings.

[0020] See also Figure 1 , which shows a flowchart of a cold-pressed terminal processing control method provided by an embodiment of the present application, the method comprising the following steps: Step S1: During the processing of the plastic cold-pressed terminal, at each position point in any section on the barrel of the injection molding machine, obtain the temperature data of each acquisition moment and all acquisition moments within a preset time period before each acquisition moment, as well as the grayscale image of the plastic cold-pressed terminal at the acquisition moment before each acquisition moment.

[0021] The injection molding machine barrel used in the production of plastic cold-pressed terminals can be divided into three sections: the conveying section, the compression section, and the homogenization section. The correspondence between each section and the temperature sensor location is as follows: two points near the hopper are in the conveying section, two points near the nozzle are in the homogenization section, and two points in the middle of the barrel are in the compression section. A temperature sensor is installed at each point in the barrel, and the temperatures of the conveying section, the compression section, and the homogenization section are set to A, B, and C, respectively.

[0022] It should be noted that the values ​​of temperatures A, B, and C are all set manually. In this embodiment, temperatures A, B, and C are set to 180°C, 195°C, and 210°C, respectively. The implementer can also set them according to the specific situation. This embodiment does not impose any special restrictions.

[0023] At each position point on the barrel of the injection molding machine, temperature data of each acquisition moment and all acquisition moments before it within a preset time period are obtained, and the data sampling interval is set to T; and a grayscale image of the plastic cold-pressed terminal at the previous acquisition moment of each acquisition moment is obtained. Among them, the values ​​of the preset time period and the data sampling interval T are both manually set. In this embodiment, the value of the preset time period is 5 minutes, and the value of the data sampling interval T is 1 second. The implementer can also set it by himself according to the specific situation. This embodiment does not impose any special restrictions. The process of obtaining the grayscale image is a well-known technology, and the specific process will not be repeated.

[0024] Step S2: At each location point, fit the temperature data at each acquisition moment and all adjacent moments, and determine the temperature fluctuation intensity of each location point at each acquisition moment based on the difference between the temperature data at each acquisition moment and all adjacent moments and the corresponding fitting results.

[0025] During the injection molding process of cold-pressed plastic terminals, frictional heat is generated by the mixing of PP plastic with the barrel wall and screw. This is easily affected by factors such as frictional heat and raw material quality, resulting in significant dynamic changes in the actual barrel temperature. Temperature sensors can detect temperature data at various points in the barrel, reflecting temperature variations at each location. However, temperature sensors have a high sampling frequency and a complex sampling environment. These abnormal temperature variations may also be caused by noise, which can easily reduce the accuracy of subsequent temperature analysis.

[0026] Therefore, in order to improve the accuracy of temperature analysis and the precision of temperature control during the processing of plastic cold-pressed terminals, the temperature fluctuation intensity of each location at each acquisition time is determined by analyzing the difference between the temperature data at each acquisition time and all adjacent times and the corresponding fitting results. Specifically, At each position point on the barrel of the injection molding machine, all sampling moments within a preset period before each sampling moment are taken as adjacent moments of each sampling moment. At each position point on the barrel of the injection molding machine, the temperature data of all adjacent moments of each sampling moment are fitted to obtain a temperature fitting curve for each position point at each sampling moment. The mean of the difference between the temperature data of all adjacent moments of each sampling moment and the corresponding fitting value on the temperature fitting curve is calculated and recorded as the temperature fluctuation intensity of each position point at each sampling moment.

[0027] It should be noted that there are many commonly used fitting methods. In this embodiment, nonlinear least squares method is used to fit the temperature data. The implementer can also use other fitting methods such as polynomial function fitting. This embodiment does not impose any special restrictions on the selection of fitting methods.

[0028] Among them, the nonlinear least squares method is a well-known technology, and the specific fitting principle will not be described in detail.

[0029] Furthermore, according to the temperature fluctuation intensity of each location point at each acquisition moment, it can be understood that when the sampling frequency of the temperature sensor is high, the difference between the temperature data at adjacent moments and the fitted value is greater, and the temperature fluctuation intensity is greater, which means that the temperature data at adjacent moments of the current sampling moment is more likely to be interfered by noise, thereby destroying the overall characteristics of the adjacent temperature data; conversely, when the sampling frequency of the temperature sensor is low, the difference between the adjacent temperature data and the fitted value is lower, and the temperature fluctuation intensity is lower.

[0030] Step S3: Based on the change trend of the temperature fluctuation intensity of each position point at each acquisition moment and all adjacent moments, determine the temperature change trend of the injection molding machine barrel at each acquisition moment, and combine the temperature fluctuation intensity to determine the noise exclusion weight of each position point at each acquisition moment.

[0031] During the injection molding process of plastic cold-pressed terminals, loose granular PP plastic is fed into the hopper of the injection molding machine, heated and melted in the barrel to gradually form a viscous melt. Driven by the screw, it is injected through the nozzle into the closed mold with a lower temperature. After a period of pressure holding, cooling and shaping, the mold is opened and demolded to obtain the plastic cold-pressed terminal. By repeating the above steps, plastic cold-pressed terminals can be continuously manufactured.

[0032] When solid PP plastic pellets are first fed into the barrel of an injection molding machine, friction between the pellets and the barrel wall and screw generates heat, causing the barrel temperature to fluctuate dramatically. After continuous heating by the heating element, the pellets transform into a viscous melt, at which point the barrel temperature changes more slowly. The barrel temperature changes with significant periodicity, and the barrel temperature is affected by the conveying and heating of the pellets, which can easily cause the actual barrel temperature to fluctuate significantly.

[0033] Therefore, in order to eliminate the influence of frictional heat generated between PP granules and the barrel wall and screw on the barrel temperature, the temperature variation trend of the injection molding machine barrel at each sampling moment and all adjacent moments is analyzed to determine the temperature variation trend of the injection molding machine barrel at each sampling moment. In combination with the temperature fluctuation intensity, the noise exclusion weight of each position point at each sampling moment is determined. Specifically: (1) At each location point, the temperature fluctuation intensity of all adjacent moments at each acquisition time is used as the input of the trend detection algorithm, and the slope value of each location point at each acquisition time is output.

[0034] It should be noted that there are many commonly used trend test algorithms. In this embodiment, the Theil-Sen Median slope estimation algorithm is used to obtain the noise exclusion weight of each location point at each acquisition time. The implementer can also use the Mann-Kendall trend test algorithm to analyze the changing trend of the temperature fluctuation intensity of each location point. This embodiment does not impose any special restrictions on the selection of the trend test algorithm.

[0035] The Theil-Sen Median slope estimation algorithm is a well-known technology, and the specific process of estimating the slope of a set of data will not be described in detail.

[0036] (2) Furthermore, the normalized result of the average of the absolute values ​​of the slope values ​​of all position points in the barrel of the injection molding machine at each sampling moment is taken as the temperature change trend of the barrel of the injection molding machine at each sampling moment.

[0037] According to the temperature change trend of the injection molding machine barrel at each sampling moment, it can be understood that when the temperature variation trend of the PP plastic at the location point is less obvious, the temperature change trend is smaller, and the barrel temperature tends to be more stable. The adjacent moments of the current sampling moment should be in the period when the solid granular PP plastic is just fed into the injection molding machine barrel. The actual barrel temperature changes strongly, resulting in a larger temperature fluctuation intensity, but the possibility of being interfered by noise is actually lower; on the contrary, when the temperature variation trend of the PP plastic at the location point is more obvious, the temperature change trend is greater.

[0038] (3) Further, based on the temperature change trend of the injection molding machine barrel at each acquisition time and the temperature fluctuation intensity, the noise exclusion weight of each position point at each acquisition time is determined, specifically: Noise exclusion weight of location j at acquisition time i The expression is: Where, Indicates the temperature change trend of the injection molding machine barrel at the acquisition time i; Indicates the temperature fluctuation intensity of point j at acquisition time i.

[0039] Furthermore, according to the noise exclusion weight of each position point at each sampling moment, it can be understood that when the temperature fluctuation intensity is smaller, it means that the abnormal temperature change at the adjacent moments of the current sampling moment is not prominent, and the more likely there is no noise interference. At the same time, when the temperature change trend is smaller, it means that the barrel temperature tends to be more stable. Its beneficial effect is to avoid the problem that the actual barrel temperature changes strongly during the repeated processing of the injection molding machine, which is greatly affected by the transportation and heating of the granular PP plastic, but is easily mistaken for noise interference. The temperature variation coefficient is corrected, and the greater the noise exclusion weight; On the contrary, when the temperature fluctuation intensity is greater, it means that the abnormal temperature change at the adjacent moments of the current sampling moment is more prominent, and the possibility of being interfered by noise is greater. At the same time, when the temperature change trend is greater, it means that the barrel temperature is more unstable and the noise exclusion weight is greater.

[0040] Preferably, the noise exclusion weight extraction process diagram provided in this embodiment is as follows: Figure 2 shown.

[0041] Step S4: In any section, based on the difference in temperature data between two positions at each acquisition moment and the difference in all temperature data between two positions at each acquisition moment and all adjacent moments, the melt temperature difference of any section at each acquisition moment is determined. In combination with the change trend of the temperature fluctuation intensity of each position at each acquisition moment and all adjacent moments, and the noise exclusion weight, the temperature control response capability of the heating element in any section at each acquisition moment is determined.

[0042] Each section of the injection molding machine barrel has its own preset temperature and heating element. Within each barrel section, there are two temperature sensors. The higher the correlation between the barrel temperature data at these two locations within a section, the better the temperature transfer within the barrel section and the more stable the melt temperature. The lower the correlation between the barrel temperature data at these two locations within a section, the more significant differences in the plastic melt temperature can be found at different locations within the same section.

[0043] Therefore, in order to more effectively control the melting and flow process of the plastic and prevent large temperature differences in the plastic melt during injection, greater control efforts should be adopted to eliminate the differences in melt temperature. Specifically: (1) In any section of the injection molding machine barrel, analyze the difference in temperature data between two points at each acquisition time, and record it as the first difference of any section at each acquisition time; (2) Further, the differences in temperature data at all adjacent moments between two points in any section at each acquisition time are analyzed and recorded as the second difference of any section at each acquisition time; It should be noted that there are many methods for measuring differences between data sets. In this embodiment, the temperature difference between two location points at each collection time is measured by calculating the DTW distance of the temperature data of all adjacent time points between the two location points at each collection time. Implementers may use other methods for measuring differences between data sets, such as Euclidean distance and Manhattan distance. This embodiment does not impose any special restrictions on the selection of methods for measuring differences between data sets.

[0044] The calculation process of the DTW distance is a well-known technology, and its specific calculation steps are not repeated here.

[0045] (3) Furthermore, it can be obtained from the first difference and the second difference that the melt temperature difference of any section of the barrel of the injection molding machine at each sampling moment is the product of the first difference and the second difference of any section at each sampling moment.

[0046] According to the melt temperature difference of any section of the injection molding machine barrel at each collection moment, it can be understood that when the difference between the temperature data of the two position points is greater, that is, the first difference is greater, it means that the temperature difference of the plastic melt at different positions in the barrel section at the current collection moment is large, and at the same time, when the difference between the temperature data of all adjacent moments between the two position points is greater, that is, the second difference is greater, it means that the correlation of the barrel temperature data in the barrel section is worse, the degree of difference in the plastic melt temperature inside the barrel section is higher, and the melt temperature difference of the section is greater; conversely, when the difference between the temperature data of the two position points is smaller, that is, the first difference is smaller, it means that the temperature difference of the plastic melt at different positions in the barrel section at the current collection moment is small, and at the same time, when the difference between the temperature data of all adjacent moments between the two position points is smaller, that is, the second difference is smaller, it means that the correlation of the barrel temperature data in the barrel section is better, the degree of difference in the plastic melt temperature inside the barrel section is lower, and the melt temperature difference of the section is smaller.

[0047] (4) Further, based on the difference in melt temperature in any section at each acquisition moment, combined with the change trend of the temperature fluctuation intensity of each position point at each acquisition moment and all adjacent moments, and the noise exclusion weight, the temperature control response capability of the heating element in any section at each acquisition moment is determined, specifically: The temperature control response capability of section u at time i is collected The expression is: Where, It represents the mean of the slope values ​​of two points in section u at the acquisition time i; It represents the difference in melt temperature of section u at the acquisition time i; It represents the mean of the noise exclusion weights of two points in section u at the acquisition time i.

[0048] According to the temperature control response capability of section u at each sampling moment, it can be understood that the greater the difference in melt temperature of the section, the higher the difference in plastic melt temperature within the same barrel section, and the less the barrel temperature data at the location point is affected by environmental noise, the more the heating element should increase the adjustment force to eliminate the melt temperature difference, and the greater the temperature control response capability; when the barrel temperature changes more drastically at the current sampling moment of the location point, the greater the average of the slope values ​​of the two location points in the section, indicating that the current sampling moment is more likely to be in the period when solid granular PP plastic has just been fed into the barrel of the injection molding machine, The heating element needs to respond quickly to dynamic barrel temperature changes to promote the melting of PP plastic into a melt, and the temperature control response capability of the section is greater; conversely, when the melt temperature difference of the section is smaller, it means that the temperature difference of the plastic melt inside the same barrel section is lower, and the barrel temperature data at the position point is more affected by environmental noise, the heating element can appropriately reduce the adjustment force and eliminate the melt temperature difference, and the temperature control response capability is smaller; when the barrel temperature changes more slowly at the current sampling moment of the position point, the smaller the average of the slope values ​​of the two position points in the section, the temperature control response capability of the section is smaller.

[0049] Step S5: Based on the significance of the grayscale values ​​of all pixels in the grayscale image of the plastic cold-pressed terminal and the temperature control response capability, the expansion factor at each acquisition moment is determined to regulate the temperature of the injection molding machine barrel.

[0050] S501: Determine a scaling factor at each acquisition moment based on the significance of the grayscale values ​​of all pixels in the grayscale image of the plastic cold-pressed terminal and the temperature control response capability.

[0051] During the manufacturing process of plastic cold-pressed terminals, the appearance of the terminals is one of the direct criteria for evaluating quality. Only qualified injection molding control can produce plastic cold-pressed terminals with high color consistency. Increasing the barrel temperature can increase the melt temperature, which is beneficial to increasing melt fluidity. However, excessively high temperatures can lead to defects such as thermal degradation of PP plastic and yellowing and deterioration of the PP plastic melt.

[0052] The grayscale image of the plastic cold-pressed terminal is used as the input of the saliency detection algorithm, and a saliency map is output. The accumulated saliency values ​​of all pixels in the saliency map are used as the terminal color factor at each acquisition moment.

[0053] It should be noted that there are many commonly used saliency detection algorithms. In this embodiment, the ITTI visual saliency model is used to obtain the saliency map of the grayscale image of the plastic cold-pressed terminal. The implementer may also use other saliency detection algorithms such as the spectral residual algorithm. Regarding the selection of the saliency detection algorithm, this embodiment does not impose any special restrictions.

[0054] Among them, the ITTI visual saliency model is a well-known technology in the field of image processing, and its specific principles are not repeated here.

[0055] The higher the grayscale contrast of the pixels on the surface of the plastic cold-pressed terminal after injection molding, the worse the color consistency of the plastic cold-pressed terminal. It is more likely that the barrel temperature is too high, causing thermal degradation of the PP plastic and yellowing of the melt. Therefore, the barrel temperature during the injection molding process should be quickly adjusted.

[0056] Furthermore, a fuzzy PID control algorithm was used to control the injection molding machine barrel temperature. However, this algorithm uses a fixed-range fuzzy domain, making it unable to dynamically respond to the changing characteristics of the barrel temperature. The fuzzy subset, which serves as the quantized range of input and output variables in fuzzy PID control, has fixed upper and lower limits, which determine the accuracy and temperature responsiveness of fuzzy PID control. When the injection molding machine barrel temperature deviates significantly from the preset temperature value, the fuzzy PID control algorithm with a fixed-range fuzzy domain has poor temperature modulation capabilities, making it difficult to quickly control the barrel temperature to the preset value.

[0057] Therefore, based on the above analysis, the scaling factor at each acquisition moment is determined according to the terminal color factor and the temperature control response capability, specifically: The expansion factor of section u at the acquisition time i The expression is: Where, Indicates the preset stretch constant; represents the terminal color factor at the acquisition time i; norm( ) represents the normalization function.

[0058] It should be noted that the value of the preset stretching constant is manually set. In this embodiment, the value of the preset stretching constant is 3. The implementer can also set it by himself according to the specific situation. This embodiment does not impose any special restrictions.

[0059] According to the expansion and contraction factor of any section at each sampling moment, it can be understood that when the terminal color factor is larger, the color consistency of the plastic cold-pressed terminal is worse, the more likely it is that the barrel temperature is too high, resulting in thermal degradation of the PP plastic, and the barrel temperature in the injection molding process should be adjusted quickly. The larger the fuzzy domain range, the larger the expansion and contraction factor of the section; when the temperature control response ability is greater, it means that the difference between the barrel temperature and the preset temperature at the current sampling moment is greater, and the barrel temperature changes more drastically. A larger fuzzy domain range should be used to quickly adjust the barrel temperature, and the expansion and contraction factor of the section is larger; conversely, when the terminal color factor is smaller, the color consistency of the plastic cold-pressed terminal is better, the fuzzy domain range is smaller, and the expansion and contraction factor of the section is smaller; when the temperature control response ability is smaller, it means that the difference between the barrel temperature and the preset temperature at the current sampling moment is greater, and the barrel temperature changes more mildly. A smaller fuzzy domain range can be used to quickly adjust the barrel temperature, and the expansion and contraction factor of the section is smaller.

[0060] Preferably, the schematic diagram of the process of obtaining the scaling factor provided in this embodiment is as follows: Figure 3 shown.

[0061] S502: Based on the expansion and contraction factors at each acquisition moment, the temperature of the injection molding machine barrel is regulated.

[0062] Calculate the difference between the temperature data of each position point in any section at each collection time and the preset temperature, and take the average of the difference between two position points in any section as the temperature error of any section at each collection time; Furthermore, the difference in temperature error of any section between each acquisition moment and the previous acquisition moment is calculated as the temperature error change rate of any section at each acquisition moment; The temperature error and temperature error change rate of any section at each acquisition moment are used as the input of the fuzzy PID controller, wherein the expansion factor of any section at each acquisition moment is multiplied by each element in the preset initial fuzzy domain of the temperature error and each element in the preset initial fuzzy domain of the temperature error change rate, and the multiplication results are used as the temperature error fuzzy domain and the temperature error change rate fuzzy domain of any section at each acquisition moment, respectively. The membership function of the fuzzy PID controller adopts a triangular membership function, and outputs the gain coefficient of any section at each acquisition moment ( 、 、 ), the gain coefficient is transmitted to the corresponding section of the injection molding machine barrel, and the temperature data of the heating element in the corresponding section of the injection molding machine barrel at each collection moment is regulated.

[0063] It should be noted that the value range of the preset initial fuzzy domain is artificially set. In this embodiment, the preset initial fuzzy domain of the temperature error and the preset initial fuzzy domain of the temperature error change rate are both [-3, 3], defined as {-3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3}. The implementer can also set it by himself according to the specific situation. This embodiment does not impose any special restrictions.

[0064] Among them, the fuzzy PID control principle is a well-known technology, and the specific process will not be repeated here.

[0065] Based on the same inventive concept as the above method, the embodiment of the present application further provides a cold-pressed terminal processing control system, comprising: The temperature data acquisition module is used to acquire temperature data at each acquisition moment and all acquisition moments within a preset time period before each acquisition moment at each position point in any section of the injection molding machine barrel during the processing of plastic cold-pressed terminals. The module also acquires a grayscale image of the plastic cold-pressed terminals at the acquisition moment before each acquisition moment, and records all acquisition moments within a preset time period before each acquisition moment as adjacent times to each acquisition moment. A weight acquisition module is used to fit the temperature data of each acquisition moment and all adjacent moments at each location point, and determine the temperature fluctuation intensity of each location point at each acquisition moment based on the difference between the temperature data of each acquisition moment and all adjacent moments and the corresponding fitting results; Based on the change trend of the temperature fluctuation intensity of each position point at each acquisition moment and all adjacent moments, the temperature change trend of the injection molding machine barrel at each acquisition moment is determined, and the noise exclusion weight of each position point at each acquisition moment is determined in combination with the temperature fluctuation intensity; In any section, based on the difference in temperature data between two locations at each acquisition moment, and the difference in all temperature data between two locations at each acquisition moment and all adjacent moments, the melt temperature difference of any section at each acquisition moment is determined. In combination with the change trend of the temperature fluctuation intensity of each location at each acquisition moment and all adjacent moments, and the noise exclusion weight, the temperature control response capability of the heating element in any section at each acquisition moment is determined. The control module is used to determine the expansion and contraction factor of any section at each acquisition time based on the significance of the grayscale values ​​of all pixels in the grayscale image of the plastic cold-pressed terminal and the temperature control response capability, and to control the temperature of the injection molding machine barrel.

[0066] The embodiment of the present application provides a block diagram of a cold-pressed terminal processing control system, such as Figure 4 shown.

[0067] Based on the same inventive concept as the above-mentioned method, an embodiment of the present application also provides a cold-pressed terminal processing control-related device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of any one of the above-mentioned cold-pressed terminal processing control methods are implemented.

[0068] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0069] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0070] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A cold pressed terminal processing control method, characterized in that: The method comprises the following steps: During the processing of plastic cold-pressed terminals, at each position point in any section of the injection molding machine barrel, the temperature data of each acquisition moment and all acquisition moments within a preset time period before it, as well as the grayscale image of the plastic cold-pressed terminal at the previous acquisition moment of each acquisition moment are obtained, and all acquisition moments within a preset time period before each acquisition moment are recorded as adjacent moments of each acquisition moment; At each location point, the temperature data at each acquisition moment and all adjacent moments are fitted, and based on the difference between the temperature data at each acquisition moment and all adjacent moments and the corresponding fitting result, the temperature fluctuation intensity of each location point at each acquisition moment is determined; Based on the change trend of the temperature fluctuation intensity of each position point at each acquisition moment and all adjacent moments, determine the temperature change trend of the injection molding machine barrel at each acquisition moment, and determine the noise exclusion weight of each position point at each acquisition moment in combination with the temperature fluctuation intensity; In any section, based on the difference of temperature data between two positions at each acquisition time, and the difference of all temperature data between two positions at each acquisition time and all adjacent moments, the melt temperature difference of any section at each acquisition time is determined, and combined with the change trend of the temperature fluctuation intensity of each position at each acquisition time and all adjacent moments, and the noise exclusion weight, the temperature control response capability of the heating element in any section at each acquisition time is determined; Based on the significance of the grayscale values ​​of all pixels in the grayscale image of the plastic cold-pressed terminal and the temperature control response capability, the expansion factor of any section at each acquisition moment is determined to regulate the temperature of the injection molding machine barrel.

2. A cold-pressed terminal processing control method as claimed in claim 1, characterized in that: The method for determining the temperature fluctuation intensity of each location point at each acquisition time is: At each position point on the barrel of the injection molding machine, the temperature data of all adjacent moments of each acquisition moment are fitted to obtain the temperature fitting curve of each position point at each acquisition moment, and the average of the differences between the temperature data of all adjacent moments of each acquisition moment and the corresponding fitting values ​​on the temperature fitting curve is taken as the temperature fluctuation intensity of each position point at each acquisition moment.

3. A cold pressed terminal processing control method as claimed in claim 1, characterized in that: The method for determining the temperature change trend of the injection molding machine barrel at each acquisition time is: At each location point, the temperature fluctuation intensity of all adjacent moments of each acquisition moment is used as the input of the trend detection algorithm, and the slope value of each location point at each acquisition moment is output; The temperature change trend of the injection molding machine barrel at each sampling time is the normalized result of the average of the absolute values ​​of the slope values ​​of all position points in the injection molding machine barrel at each sampling time.

4. A cold pressed terminal processing control method as claimed in claim 1, characterized in that: The expression of the noise exclusion weight of each position point at each acquisition time is: ; In the formula, represents the noise exclusion weight of location j at acquisition time i; Indicates the temperature change trend of the injection molding machine barrel at the acquisition time i; Indicates the temperature fluctuation intensity at point j at acquisition time i.

5. A cold pressed terminal processing control method as claimed in claim 1, characterized in that: The method for determining the melt temperature difference of any section at each collection time is: In any section of the injection molding machine barrel, the difference in temperature data between two positions at each acquisition time is recorded as the first difference of any section at each acquisition time; The difference of all temperature data between two positions in any section at each acquisition time and its adjacent time is recorded as the second difference of any section at each acquisition time; The melt temperature difference of any section of the barrel of the injection molding machine at each sampling time is the product of the first difference and the second difference of any section at each sampling time.

6. A cold pressed terminal processing control method as claimed in claim 4, characterized in that: The expression of the temperature control response capability of the heating element in any section at each acquisition time is: ; In the formula, Indicates the temperature control response capability of the heating element in section u at the acquisition time i; It represents the mean of the slope values ​​of two points in section u at the acquisition time i; It represents the difference in melt temperature of section u at the acquisition time i; It represents the mean value of the noise exclusion weights of two points in section u at the acquisition time i.

7. A cold-pressed terminal processing control method as claimed in claim 6, characterized in that: The method for determining the expansion and contraction factor of any section at each acquisition time is as follows: The grayscale image of the plastic cold-pressed terminal at the previous acquisition moment of each acquisition moment is used as the input of the saliency detection algorithm, and the saliency map is output, and the cumulative result of the saliency values ​​of all pixels in the saliency map is used as the terminal color factor at each acquisition moment; The expansion factor of section u at the acquisition time i The expression is: ; In the formula, Indicates the preset stretch constant; represents the terminal color factor at the acquisition time i; norm( ) represents the normalization function.

8. A cold pressed terminal processing control method as claimed in claim 1, characterized in that: The temperature of the injection molding machine barrel is regulated, including: Calculate the difference between the temperature data of each position point in any section at each acquisition time and the preset temperature, and take the average of the difference between two position points in any section as the temperature error of any section at each acquisition time; Calculate the difference in temperature error of any section between each acquisition moment and the previous acquisition moment as the temperature error change rate of any section at each acquisition moment; The temperature error and temperature error change rate of any section at each collection moment are used as the input of the fuzzy PID controller, wherein the expansion factor of any section at each collection moment is multiplied with each element in the preset initial fuzzy domain of the temperature error and each element in the preset initial fuzzy domain of the temperature error change rate, and the multiplication results are used as the temperature error fuzzy domain and the temperature error change rate fuzzy domain of any section at each collection moment, respectively. The membership function of the fuzzy PID controller adopts a triangular membership function, outputs the gain coefficient of any section at each collection moment, transmits the gain coefficient to the corresponding section of the injection molding machine barrel, and regulates the temperature data of the heating element in the corresponding section on the injection molding machine barrel at each collection moment.

9. A cold-pressed terminal processing control system, realizing a cold-pressed terminal processing control method as described in claims 1-8, characterized in that: The system comprises: The temperature data acquisition module is used in the process of processing plastic cold-pressed terminals. At each position point in any section on the barrel of the injection molding machine, the temperature data of each acquisition moment and all acquisition moments within a preset time period before the acquisition moment, as well as the grayscale image of the plastic cold-pressed terminal at the previous acquisition moment, are acquired. All acquisition moments within a preset time period before each acquisition moment are recorded as adjacent moments of each acquisition moment. A weight acquisition module is used to fit the temperature data of each acquisition moment and all adjacent moments at each location point, and determine the temperature fluctuation intensity of each location point at each acquisition moment based on the difference between the temperature data of each acquisition moment and all adjacent moments and the corresponding fitting result; Based on the change trend of the temperature fluctuation intensity of each position point at each acquisition moment and all adjacent moments, determine the temperature change trend of the injection molding machine barrel at each acquisition moment, and determine the noise exclusion weight of each position point at each acquisition moment in combination with the temperature fluctuation intensity; In any section, based on the difference of temperature data between two positions at each acquisition time, and the difference of all temperature data between two positions at each acquisition time and all adjacent moments, the melt temperature difference of any section at each acquisition time is determined, and combined with the change trend of the temperature fluctuation intensity of each position at each acquisition time and all adjacent moments, and the noise exclusion weight, the temperature control response capability of the heating element in any section at each acquisition time is determined; The control module is used to determine the expansion factor of any section at each acquisition time based on the significant situation of the grayscale values ​​of all pixels in the grayscale image of the plastic cold-pressed terminal and the temperature control response capability, and to control the temperature of the injection molding machine barrel.

10. A cold-pressed terminal processing control-related device, 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 a cold-pressed terminal processing control method as described in any one of claims 1-8 are implemented.

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