Intelligent flow control system based on mold temperature controller and control method thereof

Abstract

The invention discloses an intelligent flow control system based on a mold temperature controller and a control method thereof, and relates to the technical field of mold temperature controllers, and the system comprises the following modules: a mold monitoring module for obtaining the appearance of a mold groove, selecting a temperature reference area according to the appearance of the mold groove, obtaining the temperature of the mold temperature reference area, and marking the temperature as a mold temperature coefficient; according to the scheme, the cooling liquid, flowing to the mold temperature controller, of the mold is detected through the cooling liquid detection module, and the temperature of the mold is comprehensively judged by combining the flow, pressure and temperature of the liquid, so that the temperature of the mold is indirectly mastered conveniently, and further the future temperature of the mold is accurately predicted subsequently according to the temperature of the mold; further, the mold temperature controller can adjust the temperature of the mold in advance, the problem of slow temperature control response of the mold temperature controller can be avoided, and finally, the mold temperature can be adjusted in advance to facilitate molding of products in the mold.

Description

Technical Field

[0001] The present invention relates to the technical field of mold temperature controllers, and in particular to an intelligent flow control system based on a mold temperature controller and a control method thereof. Background Art

[0002] The mold temperature controller, also known as the mold temperature controller, was originally used in the temperature control industry of injection molds. Later, with the development of the machinery industry, it was used more and more widely. Now the mold temperature controller is generally divided into water temperature controller and oil temperature controller. The temperature control accuracy can reach ±0.1℃. The mold temperature controller consists of a water tank, a heating and cooling system, a power transmission system, a liquid level control system, a temperature sensor, an injection port and other devices. Under normal circumstances, the pump in the power transmission system allows the hot fluid to reach the mold from the water tank equipped with a built-in heater and cooler, and then return from the mold to the water tank; the temperature sensor measures the temperature of the hot fluid and transmits the data to the controller of the control part; the controller adjusts the temperature of the hot fluid, thereby indirectly adjusting the temperature of the mold.

[0003] At present, most mold temperature controllers first obtain the mold temperature through sensors during the temperature control process, and then control the flow and flow rate of the mold temperature controller to adjust the temperature according to the obtained temperature. Since the temperature changes of the mold in the injection molding process will affect the molding effect of the product surface texture, however, this temperature control method has lag, and the temperature control response is slow, making it difficult to achieve timely adjustment of the mold temperature. Therefore, we propose an intelligent flow control system based on a mold temperature controller and a control method thereof. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the deficiencies in the prior art, the present invention provides an intelligent flow control system based on a mold temperature controller and a control method thereof to solve the above-mentioned problems in the prior art.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent flow control system based on a mold temperature controller, comprising the following modules:

[0008] The mold monitoring module obtains the mold groove appearance, selects the temperature reference area according to the mold groove appearance, obtains the temperature of the mold temperature reference area and marks it as the mold temperature coefficient;

[0009] The coolant detection module obtains the heat exchange liquid flow of the mold temperature machine, obtains the heat exchange liquid pressure of the mold temperature machine, obtains the indirect temperature value through the heat exchange liquid flow of the mold temperature machine and the heat exchange liquid pressure of the mold temperature machine, obtains the heat exchange liquid temperature of the mold temperature machine, and obtains the liquid temperature coefficient through the heat exchange liquid temperature of the mold temperature machine and the indirect temperature value;

[0010] The temperature prediction module obtains the temperature reference coefficient through the mold temperature coefficient and the liquid temperature coefficient, establishes a historical temperature database through the temperature reference coefficient, obtains the temperature prediction value through the temperature reference coefficient in the historical temperature database using a linear regression model, and incorporates the temperature prediction value into the historical temperature database;

[0011] The temperature control module obtains the historical temperature prediction value from the historical temperature database, compares the historical temperature prediction value with the temperature prediction value, and adjusts the flow rate of the heat exchange liquid of the mold temperature controller according to the comparison result.

[0012] Preferably, the mold groove appearance is obtained in the mold detection module, and the temperature reference area is selected according to the mold groove appearance, specifically:

[0013] Step 1: Take pictures of the mold grooves of the two molds respectively to obtain reference pictures, capture all bending points of the mold grooves in the reference pictures, capture the narrowest point of the mold grooves in the reference pictures, and capture the widest point of the mold grooves in the reference pictures;

[0014] Step 2: Set the range preset threshold, mark all the bending temperature measurement areas with all the bending points as the center and the range preset threshold as the radius, mark the narrow point temperature measurement area with the narrowest point as the center and the range preset threshold as the radius, mark the wide point temperature measurement area with the widest point as the center and the range preset threshold as the radius, and the narrow point temperature measurement area, wide point temperature measurement area and all the bending temperature measurement areas are collectively referred to as temperature reference areas.

[0015] Preferably, the temperature of the mold temperature reference area is obtained in the mold detection module and marked as the mold temperature coefficient, specifically:

[0016] Step 1: obtain the temperature of the narrow point temperature measurement area in the temperature reference area, mark it as the narrow point temperature, obtain the temperature of the wide point temperature measurement area, mark it as the wide point temperature, obtain the temperature of all the bending temperature measurement areas respectively, mark it as the bending temperature;

[0017] Step 2: Delete the repeated temperatures in all bending temperatures, arrange the remaining bending temperatures in ascending order, delete the minimum and maximum values ​​to obtain all bending temperatures after data cleaning, and mark them as cleaning bending temperatures, and sum and average all cleaning bending temperatures to obtain the bending mean temperature;

[0018] Step 3: Obtain the temperature of the temperature reference area through the bending mean temperature, narrow point temperature and wide point temperature, and mark the temperature of the temperature reference area as the mold temperature coefficient.

[0019] Preferably, the mold temperature coefficient is calculated as follows:

[0020]

[0021] Among them, Cw represents the temperature of the temperature reference area, Wz represents the mean bending temperature, Zd represents the narrow point temperature, Kd represents the wide point temperature, δ1, δ2 and δ3 are all weights, 1>δ1>0, 1>δ2>0, 1>δ3>0.

[0022] Preferably, in the coolant detection module, an indirect temperature value is obtained by the heat exchange liquid flow of the mold temperature controller and the heat exchange liquid pressure of the mold temperature controller, specifically:

[0023] Step 1: Obtain the heat exchange liquid flow rate of the mold temperature controller, set a preset threshold value of the heat exchange liquid flow rate, and obtain a flow difference by subtracting the heat exchange liquid flow rate of the mold temperature controller from the preset threshold value of the heat exchange liquid flow rate;

[0024] Step 2: Obtain the heat exchange liquid pressure of the mold temperature controller, set a preset threshold value of the heat exchange liquid pressure, and obtain a pressure difference by subtracting the heat exchange liquid pressure of the mold temperature controller from the preset threshold value of the heat exchange liquid pressure;

[0025] Step 3: Take the weighted sum of the flow difference and the pressure difference to obtain the indirect temperature value.

[0026] Preferably, the temperature of the heat exchange liquid of the mold temperature controller is obtained in the coolant detection module, and the liquid temperature coefficient is obtained by the heat exchange liquid temperature of the mold temperature controller and the indirect temperature value, specifically:

[0027] Step 1: Get the liquid temperature of the mold temperature controller before heat exchange, marked as the temperature before exchange, and get the liquid temperature of the mold temperature controller after heat exchange, marked as the temperature after exchange;

[0028] Step 2: Set a preset threshold value for cooling the temperature of the heat exchange liquid, obtain a temperature difference by subtracting the temperature after the exchange from the temperature before the exchange, and obtain the temperature of the heat exchange liquid of the mold temperature controller by summing the temperature difference and the preset threshold value for cooling the temperature of the heat exchange liquid;

[0029] Step 3: Obtain the indirect temperature value, and obtain the liquid temperature coefficient by taking the weighted average of the indirect temperature value and the heat exchange liquid temperature of the mold temperature controller.

[0030] Preferably, the temperature reference coefficient is calculated in the temperature prediction module as follows:

[0031]

[0032] Where Ws is the temperature reference coefficient, Cw is the mold temperature coefficient, and Yw is the liquid temperature coefficient. and are weights,

[0033] Preferably, in the temperature prediction module, the temperature prediction value is obtained by using a linear regression model through the temperature reference coefficient in the historical temperature database, specifically:

[0034] Step 1: Obtain the temperature reference coefficient, mold temperature coefficient and liquid temperature coefficient of the mold temperature controller in the past 3 hours from the historical temperature database, set a preset time interval threshold, and divide the temperature reference coefficient, mold temperature coefficient and liquid temperature coefficient of the mold temperature controller in the past 3 hours into multiple continuous reference values ​​with the preset time interval threshold as the length, so as to obtain multiple sections of temperature reference coefficient, multiple sections of mold temperature coefficient and multiple sections of liquid temperature coefficient;

[0035] Step 2: Delete the maximum and minimum values ​​in each temperature coefficient respectively, sum and average the remaining temperature coefficients in each section to obtain multiple temperature coefficient averages, delete the maximum and minimum values ​​in each mold temperature coefficient respectively, sum and average the remaining mold temperature coefficients in each section to obtain multiple mold temperature coefficient averages, delete the maximum and minimum values ​​in each liquid temperature coefficient respectively, sum and average the remaining liquid temperature coefficients in each section to obtain multiple liquid temperature coefficient averages;

[0036] Step 3: Arrange multiple temperature coefficient means in chronological order, and make a difference between each two adjacent temperature coefficient means to obtain multiple adjacent temperature coefficient difference values; arrange multiple mold temperature coefficient means in chronological order, and make a difference between each two adjacent mold temperature coefficient means to obtain multiple adjacent mold temperature coefficient difference values; arrange multiple liquid temperature coefficient means in chronological order, and make a difference between each two adjacent liquid temperature coefficient means to obtain multiple adjacent liquid temperature coefficient difference values;

[0037] Step 4: Set a preset threshold value of a temperature standard value, and obtain a temperature prediction value through the preset threshold value of the temperature standard value, a plurality of adjacent temperature coefficient differences, a plurality of adjacent mold temperature coefficient differences, and a plurality of adjacent liquid temperature coefficient differences;

[0038] The temperature prediction value is calculated as follows:

[0039]

[0040] Among them, Yu represents the temperature prediction value, Bz represents the temperature standard value preset threshold, Dc n Expressed as the difference between the nth adjacent temperature coefficients, Mc n Expressed as the difference in temperature coefficients of the nth adjacent molds, Yc n It is expressed as the difference in temperature coefficients of the nth adjacent liquids, where n=1, 2, 3, ..., θ1, θ2 and θ3 are all weights, 1>θ1>0, 1>θ2>0, 1>θ3>0.

[0041] Preferably, the temperature control module is specifically:

[0042] Step 1: Obtain the current temperature prediction value, obtain the adjacent historical temperature prediction value closest to the current temperature prediction value in the historical temperature database, and make a difference between the current temperature prediction value and the adjacent historical temperature prediction value to obtain the temperature prediction difference;

[0043] Step 2: Compare the relationship between the predicted temperature difference and 0. If the predicted temperature difference is greater than 0, increase the flow rate of the heat exchange liquid of the mold temperature controller. If the predicted temperature difference is less than 0, reduce the flow rate of the heat exchange liquid of the mold temperature controller.

[0044] An intelligent flow control method based on a mold temperature controller comprises the following steps:

[0045] Step 1: Obtain the appearance of the mold groove, select the temperature reference area according to the appearance of the mold groove, obtain the temperature of the mold temperature reference area and mark it as the mold temperature coefficient;

[0046] Step 2: Obtain the heat exchange liquid flow rate of the mold temperature controller, obtain the heat exchange liquid pressure of the mold temperature controller, obtain the indirect temperature value through the heat exchange liquid flow rate of the mold temperature controller and the heat exchange liquid pressure of the mold temperature controller, obtain the heat exchange liquid temperature of the mold temperature controller, and obtain the liquid temperature coefficient through the heat exchange liquid temperature of the mold temperature controller and the indirect temperature value;

[0047] Step 3: Obtain the temperature reference coefficient through the mold temperature coefficient and the liquid temperature coefficient, establish a historical temperature database through the temperature reference coefficient, obtain the temperature prediction value through the temperature reference coefficient in the historical temperature database using a linear regression model, and incorporate the temperature prediction value into the historical temperature database;

[0048] Step 4: Obtain the historical temperature prediction value in the historical temperature database, compare the historical temperature prediction value with the temperature prediction value, and adjust the flow rate of the heat exchange liquid of the mold temperature controller according to the comparison result.

[0049] (III) Beneficial effects

[0050] The present invention provides an intelligent flow control system based on a mold temperature controller and a control method thereof, which have the following beneficial effects:

[0051] (1) In this solution, the coolant detection module detects the coolant flowing from the mold to the mold temperature controller, and the temperature of the mold is comprehensively judged by combining the flow rate, pressure and temperature of the liquid, so as to indirectly grasp the temperature of the mold, and further facilitate the subsequent accurate prediction of the future temperature of the mold based on the temperature of the mold, and further facilitate the mold temperature controller to adjust the temperature of the mold in advance, which is further beneficial to avoid the problem of slow temperature control response of the mold temperature controller, and finally facilitate the early adjustment of the mold temperature is beneficial to the molding of the product in the mold;

[0052] (2) In this scheme, the temperature reference coefficient is obtained by combining the mold temperature coefficient and the liquid temperature coefficient through the temperature prediction module, which is beneficial to improve the accuracy of obtaining the mold temperature, and further facilitates the prediction of the upcoming temperature change of the mold. By establishing a historical temperature database to record the temperature change of the mold, and then using the linear regression model to predict the future temperature of the mold, it is convenient for the mold temperature controller to adjust the temperature of the mold in advance, which is beneficial to avoid the problem of slow temperature control response of the mold temperature controller. Finally, it is convenient to adjust the mold temperature in advance, which is beneficial to the molding of the product in the mold. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a structural schematic diagram of an intelligent flow control system based on a mold temperature controller of the present invention;

[0054] Figure 2 The present invention is a flowchart of an intelligent flow control method based on a mold temperature controller. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] See also Figure 1-Figure 2 The present invention provides an intelligent flow control system based on a mold temperature controller, comprising the following modules:

[0057] The mold monitoring module obtains the mold groove appearance, selects the temperature reference area according to the mold groove appearance, obtains the temperature of the mold temperature reference area and marks it as the mold temperature coefficient;

[0058] The coolant detection module obtains the heat exchange liquid flow of the mold temperature machine, obtains the heat exchange liquid pressure of the mold temperature machine, obtains the indirect temperature value through the heat exchange liquid flow of the mold temperature machine and the heat exchange liquid pressure of the mold temperature machine, obtains the heat exchange liquid temperature of the mold temperature machine, and obtains the liquid temperature coefficient through the heat exchange liquid temperature of the mold temperature machine and the indirect temperature value;

[0059] The temperature prediction module obtains the temperature reference coefficient through the mold temperature coefficient and the liquid temperature coefficient, establishes a historical temperature database through the temperature reference coefficient, obtains the temperature prediction value through the temperature reference coefficient in the historical temperature database using a linear regression model, and incorporates the temperature prediction value into the historical temperature database;

[0060] The temperature control module obtains the historical temperature prediction value from the historical temperature database, compares the historical temperature prediction value with the temperature prediction value, and adjusts the flow rate of the heat exchange liquid of the mold temperature controller according to the comparison result;

[0061] The calculation method of the temperature reference coefficient in the temperature prediction module is as follows:

[0062]

[0063] Where Ws is the temperature reference coefficient, Cw is the mold temperature coefficient, and Yw is the liquid temperature coefficient. and are weights,

[0064] In this embodiment, in this scheme, a plurality of temperature measurement areas are selected in the mold groove by the mold monitoring module, and then the mold temperature coefficient is obtained by calculating the temperature of the plurality of temperature measurement areas, so as to facilitate understanding the temperature of the mold, and then facilitate accurate prediction of the future temperature of the mold according to the temperature of the mold, and then facilitate the mold temperature controller to adjust the temperature of the mold in advance, and then help to avoid the problem of slow temperature control response of the mold temperature controller, and finally facilitate to adjust the mold temperature in advance, which is beneficial to the molding of the product in the mold;

[0065] In this solution, the coolant detection module is used to detect the coolant flowing from the mold to the mold temperature controller, and the temperature of the mold is comprehensively judged by combining the flow rate, pressure and temperature of the liquid, so as to indirectly grasp the temperature of the mold, and further facilitate the subsequent accurate prediction of the future temperature of the mold based on the temperature of the mold, and further facilitate the mold temperature controller to adjust the temperature of the mold in advance, which is further beneficial to avoid the problem of slow temperature control response of the mold temperature controller, and finally facilitate the early adjustment of the mold temperature is beneficial to the molding of the product in the mold;

[0066] In this solution, the temperature reference coefficient is obtained by combining the mold temperature coefficient and the liquid temperature coefficient through the temperature prediction module, which is beneficial to improve the accuracy of obtaining the mold temperature, and further facilitates the prediction of the upcoming temperature change of the mold. By establishing a historical temperature database to record the temperature change of the mold, and then using the linear regression model to predict the future temperature of the mold, it is convenient for the mold temperature controller to adjust the temperature of the mold in advance, which is beneficial to avoid the problem of slow temperature control response of the mold temperature controller, and finally facilitates the early adjustment of the mold temperature, which is beneficial to the molding of the product in the mold;

[0067] In this solution, the flow rate of the coolant of the mold temperature controller is controlled by the temperature control module, so as to control the flow rate of the mold temperature controller according to the prediction results, thereby facilitating the temperature adjustment of the mold;

[0068] It is worth mentioning that the weight values ​​in this scheme can be obtained through the hierarchical analysis method, and the values ​​of the preset thresholds in this scheme can be obtained through the weight analysis method, which will not be elaborated here.

[0069] In the mold inspection module, the mold groove appearance is obtained, and the temperature reference area is selected according to the mold groove appearance, specifically:

[0070] Step 1: Take pictures of the mold grooves of the two molds respectively to obtain reference pictures, capture all bending points of the mold grooves in the reference pictures, capture the narrowest point of the mold grooves in the reference pictures, and capture the widest point of the mold grooves in the reference pictures;

[0071] Step 2: Set the range preset threshold, mark all the bending temperature measurement areas with all the bending points as the center and the range preset threshold as the radius, mark the narrow point temperature measurement area with the narrowest point as the center and the range preset threshold as the radius, mark the wide point temperature measurement area with the widest point as the center and the range preset threshold as the radius, and the narrow point temperature measurement area, wide point temperature measurement area and all the bending temperature measurement areas are collectively referred to as temperature reference areas.

[0072] In this embodiment, the shape of the mold groove is grasped by taking a picture of the mold groove, and the temperature of the bend, narrowest part and widest part in the mold groove is captured, so as to accurately judge the overall temperature of the mold, and then accurately predict the temperature of the mold, and then adjust the coolant flow of the mold temperature controller in advance to control the temperature of the mold.

[0073] In the mold detection module, the temperature of the mold temperature reference area is obtained and marked as the mold temperature coefficient, specifically:

[0074] Step 1: obtain the temperature of the narrow point temperature measurement area in the temperature reference area, mark it as the narrow point temperature, obtain the temperature of the wide point temperature measurement area, mark it as the wide point temperature, obtain the temperature of all the bending temperature measurement areas respectively, mark it as the bending temperature;

[0075] Step 2: Delete the repeated temperatures in all bending temperatures, arrange the remaining bending temperatures in ascending order, delete the minimum and maximum values ​​to obtain all bending temperatures after data cleaning, and mark them as cleaning bending temperatures, and sum and average all cleaning bending temperatures to obtain the bending mean temperature;

[0076] Step 3: Obtain the temperature of the temperature reference area through the bending mean temperature, narrow point temperature and wide point temperature, and mark the temperature of the temperature reference area as the mold temperature coefficient;

[0077] The calculation method of the mold temperature coefficient is as follows:

[0078]

[0079] Among them, Cw represents the temperature of the temperature reference area, Wz represents the mean bending temperature, Zd represents the narrow point temperature, Kd represents the wide point temperature, δ1, δ2 and δ3 are all weights, 1>δ1>0, 1>δ2>0, 1>δ3>0.

[0080] In this embodiment, data cleaning is performed on the bending mean temperature, narrow point temperature and wide point temperature, which is helpful to eliminate interference parameters and improve the accuracy of the prediction results. The temperature of the temperature reference area is then obtained through the bending mean temperature, narrow point temperature and wide point temperature, which is helpful to grasp the overall temperature of the mold in combination with the temperatures at different positions of the mold groove, thereby facilitating the subsequent accurate prediction of the mold temperature.

[0081] In the coolant detection module, the indirect temperature value is obtained through the heat exchange liquid flow of the mold temperature controller and the heat exchange liquid pressure of the mold temperature controller, specifically:

[0082] Step 1: Obtain the heat exchange liquid flow rate of the mold temperature controller, set a preset threshold value of the heat exchange liquid flow rate, and obtain a flow difference by subtracting the heat exchange liquid flow rate of the mold temperature controller from the preset threshold value of the heat exchange liquid flow rate;

[0083] Step 2: Obtain the heat exchange liquid pressure of the mold temperature controller, set a preset threshold value of the heat exchange liquid pressure, and obtain a pressure difference by subtracting the heat exchange liquid pressure of the mold temperature controller from the preset threshold value of the heat exchange liquid pressure;

[0084] Step 3: Take the weighted sum of the flow difference and the pressure difference to obtain the indirect temperature value.

[0085] In this embodiment, the temperature change of the mold is indirectly grasped by obtaining the pressure change and flow change of the coolant of the mold temperature controller. The indirect temperature value obtained by combining the pressure change and flow change of the coolant of the mold temperature controller facilitates more accurate grasp of the temperature of the mold, and then facilitates the subsequent prediction of the temperature of the mold.

[0086] The temperature of the heat exchange liquid of the mold temperature controller is obtained in the coolant detection module, and the liquid temperature coefficient is obtained through the heat exchange liquid temperature of the mold temperature controller and the indirect temperature value, which is specifically:

[0087] Step 1: Get the liquid temperature of the mold temperature controller before heat exchange, marked as the temperature before exchange, and get the liquid temperature of the mold temperature controller after heat exchange, marked as the temperature after exchange;

[0088] Step 2: Set a preset threshold value for cooling the temperature of the heat exchange liquid, obtain a temperature difference by subtracting the temperature after the exchange from the temperature before the exchange, and obtain the temperature of the heat exchange liquid of the mold temperature controller by summing the temperature difference and the preset threshold value for cooling the temperature of the heat exchange liquid;

[0089] Step 3: Obtain the indirect temperature value, and obtain the liquid temperature coefficient by taking the weighted average of the indirect temperature value and the heat exchange liquid temperature of the mold temperature controller.

[0090] In this embodiment, the temperature of the mold is determined by monitoring the change in the temperature of the coolant in the mold temperature controller, thereby facilitating a more accurate prediction of the mold temperature.

[0091] In the temperature prediction module, the temperature prediction value is obtained by using the linear regression model through the temperature reference coefficient in the historical temperature database, specifically:

[0092] Step 1: Obtain the temperature reference coefficient, mold temperature coefficient and liquid temperature coefficient of the mold temperature controller in the past 3 hours from the historical temperature database, set a preset time interval threshold, and divide the temperature reference coefficient, mold temperature coefficient and liquid temperature coefficient of the mold temperature controller in the past 3 hours into multiple continuous reference values ​​with the preset time interval threshold as the length, so as to obtain multiple sections of temperature reference coefficient, multiple sections of mold temperature coefficient and multiple sections of liquid temperature coefficient;

[0093] Step 2: Delete the maximum and minimum values ​​in each temperature coefficient respectively, sum and average the remaining temperature coefficients in each section to obtain multiple temperature coefficient averages, delete the maximum and minimum values ​​in each mold temperature coefficient respectively, sum and average the remaining mold temperature coefficients in each section to obtain multiple mold temperature coefficient averages, delete the maximum and minimum values ​​in each liquid temperature coefficient respectively, sum and average the remaining liquid temperature coefficients in each section to obtain multiple liquid temperature coefficient averages;

[0094] Step 3: Arrange multiple temperature coefficient means in chronological order, and make a difference between each two adjacent temperature coefficient means to obtain multiple adjacent temperature coefficient difference values; arrange multiple mold temperature coefficient means in chronological order, and make a difference between each two adjacent mold temperature coefficient means to obtain multiple adjacent mold temperature coefficient difference values; arrange multiple liquid temperature coefficient means in chronological order, and make a difference between each two adjacent liquid temperature coefficient means to obtain multiple adjacent liquid temperature coefficient difference values;

[0095] Step 4: Set a preset threshold value of a temperature standard value, and obtain a temperature prediction value through the preset threshold value of the temperature standard value, a plurality of adjacent temperature coefficient differences, a plurality of adjacent mold temperature coefficient differences, and a plurality of adjacent liquid temperature coefficient differences;

[0096] The temperature prediction value is calculated as follows:

[0097]

[0098] Among them, Yu represents the temperature prediction value, Bz represents the temperature standard value preset threshold, Dc n Expressed as the difference between the nth adjacent temperature coefficients, Mc n Expressed as the difference in temperature coefficients of the nth adjacent molds, Yc nIt is expressed as the difference in temperature coefficients of the nth adjacent liquids, where n=1, 2, 3, ..., θ1, θ2 and θ3 are all weights, 1>θ1>0, 1>θ2>0, 1>θ3>0.

[0099] In this embodiment, by respectively obtaining the temperature reference coefficient, mold temperature coefficient and liquid temperature coefficient of the mold temperature controller in the past 3 hours from the historical temperature database, it is convenient to grasp the historical changes in the mold temperature, and by setting the time interval preset threshold, the temperature reference coefficient, mold temperature coefficient and liquid temperature coefficient of the mold temperature controller are divided into multiple time periods, and then the obtained parameters are cleaned to eliminate interference parameters, and the parameters are arranged in chronological order and the adjacent parameters are subtracted, so as to facilitate the temperature change of the mold in adjacent time periods. Finally, by combining the temperature reference coefficient, mold temperature coefficient and liquid temperature coefficient in the historical database, the future temperature of the mold is predicted and calculated, so that it is convenient for the mold temperature controller to adjust the temperature of the mold in advance, which is beneficial to avoid the problem of slow temperature control response of the mold temperature controller, and finally it is convenient to adjust the mold temperature in advance, which is beneficial to the molding of the product in the mold.

[0100] Temperature control module, specifically:

[0101] Step 1: Obtain the current temperature prediction value, obtain the adjacent historical temperature prediction value closest to the current temperature prediction value in the historical temperature database, and make a difference between the current temperature prediction value and the adjacent historical temperature prediction value to obtain the temperature prediction difference;

[0102] Step 2: Compare the relationship between the predicted temperature difference and 0. If the predicted temperature difference is greater than 0, increase the flow rate of the heat exchange liquid of the mold temperature controller. If the predicted temperature difference is less than 0, reduce the flow rate of the heat exchange liquid of the mold temperature controller.

[0103] In this embodiment, the temperature prediction difference is obtained by subtracting the current temperature prediction value from the adjacent historical temperature prediction value, and then the temperature prediction difference is compared with 0, so as to facilitate the judgment of whether the future temperature of the mold will increase or decrease, and then facilitate the mold temperature controller to adjust the flow rate of the coolant according to the judgment result, and then facilitate the mold temperature controller to control the temperature of the mold.

[0104] See also Figure 1-Figure 2 The present invention provides an intelligent flow control method based on a mold temperature controller, comprising the following steps:

[0105] Step 1: Obtain the appearance of the mold groove, select the temperature reference area according to the appearance of the mold groove, obtain the temperature of the mold temperature reference area and mark it as the mold temperature coefficient;

[0106] Step 2: Obtain the heat exchange liquid flow rate of the mold temperature controller, obtain the heat exchange liquid pressure of the mold temperature controller, obtain the indirect temperature value through the heat exchange liquid flow rate of the mold temperature controller and the heat exchange liquid pressure of the mold temperature controller, obtain the heat exchange liquid temperature of the mold temperature controller, and obtain the liquid temperature coefficient through the heat exchange liquid temperature of the mold temperature controller and the indirect temperature value;

[0107] Step 3: Obtain the temperature reference coefficient through the mold temperature coefficient and the liquid temperature coefficient, establish a historical temperature database through the temperature reference coefficient, obtain the temperature prediction value through the temperature reference coefficient in the historical temperature database using a linear regression model, and incorporate the temperature prediction value into the historical temperature database;

[0108] Step 4: Obtain the historical temperature prediction value in the historical temperature database, compare the historical temperature prediction value with the temperature prediction value, and adjust the flow rate of the heat exchange liquid of the mold temperature controller according to the comparison result.

[0109] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0110] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0111] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An intelligent flow control system based on a mold temperature controller, characterized in that: Includes the following modules: The mold monitoring module obtains the mold groove appearance, selects the temperature reference area according to the mold groove appearance, obtains the temperature of the mold temperature reference area and marks it as the mold temperature coefficient; The coolant detection module obtains the heat exchange liquid flow of the mold temperature machine, obtains the heat exchange liquid pressure of the mold temperature machine, obtains the indirect temperature value through the heat exchange liquid flow of the mold temperature machine and the heat exchange liquid pressure of the mold temperature machine, obtains the heat exchange liquid temperature of the mold temperature machine, and obtains the liquid temperature coefficient through the heat exchange liquid temperature of the mold temperature machine and the indirect temperature value; The temperature prediction module obtains the temperature reference coefficient through the mold temperature coefficient and the liquid temperature coefficient, establishes a historical temperature database through the temperature reference coefficient, obtains the temperature prediction value through the temperature reference coefficient in the historical temperature database using a linear regression model, and incorporates the temperature prediction value into the historical temperature database; The temperature control module obtains the historical temperature prediction value from the historical temperature database, compares the historical temperature prediction value with the temperature prediction value, and adjusts the flow rate of the heat exchange liquid of the mold temperature controller according to the comparison result.

2. According to claim 1, the intelligent flow control system based on the mold temperature controller is characterized in that: In the mold inspection module, the mold groove appearance is obtained, and the temperature reference area is selected according to the mold groove appearance, specifically: Step 1: Take pictures of the mold grooves of the two molds respectively to obtain reference pictures, capture all bending points of the mold grooves in the reference pictures, capture the narrowest point of the mold grooves in the reference pictures, and capture the widest point of the mold grooves in the reference pictures; Step 2: Set the range preset threshold, mark all the bending temperature measurement areas with all the bending points as the center and the range preset threshold as the radius, mark the narrow point temperature measurement area with the narrowest point as the center and the range preset threshold as the radius, mark the wide point temperature measurement area with the widest point as the center and the range preset threshold as the radius, and the narrow point temperature measurement area, wide point temperature measurement area and all the bending temperature measurement areas are collectively referred to as temperature reference areas.

3. According to claim 2, an intelligent flow control system based on a mold temperature controller is characterized in that: In the mold detection module, the temperature of the mold temperature reference area is obtained and marked as the mold temperature coefficient, specifically: Step 1: obtain the temperature of the narrow point temperature measurement area in the temperature reference area, mark it as the narrow point temperature, obtain the temperature of the wide point temperature measurement area, mark it as the wide point temperature, obtain the temperature of all the bending temperature measurement areas respectively, mark it as the bending temperature; Step 2: Delete the repeated temperatures in all bending temperatures, arrange the remaining bending temperatures in ascending order, delete the minimum and maximum values ​​to obtain all bending temperatures after data cleaning, and mark them as cleaning bending temperatures, and sum and average all cleaning bending temperatures to obtain the bending mean temperature; Step 3: Obtain the temperature of the temperature reference area through the bending mean temperature, narrow point temperature and wide point temperature, and mark the temperature of the temperature reference area as the mold temperature coefficient.

4. According to claim 3, the intelligent flow control system based on the mold temperature controller is characterized in that: The calculation method of the mold temperature coefficient is as follows: Among them, Cw represents the temperature of the temperature reference area, Wz represents the mean bending temperature, Zd represents the narrow point temperature, Kd represents the wide point temperature, δ1, δ2 and δ3 are all weights, 1>δ1>0, 1>δ2>0, 1>δ3>0.

5. The intelligent flow control system based on the mold temperature controller according to claim 1 is characterized in that: In the coolant detection module, the indirect temperature value is obtained through the heat exchange liquid flow of the mold temperature controller and the heat exchange liquid pressure of the mold temperature controller, specifically: Step 1: Obtain the heat exchange liquid flow rate of the mold temperature controller, set a preset threshold value of the heat exchange liquid flow rate, and obtain a flow difference by subtracting the heat exchange liquid flow rate of the mold temperature controller from the preset threshold value of the heat exchange liquid flow rate; Step 2: Obtain the heat exchange liquid pressure of the mold temperature controller, set a preset threshold value of the heat exchange liquid pressure, and obtain a pressure difference by subtracting the heat exchange liquid pressure of the mold temperature controller from the preset threshold value of the heat exchange liquid pressure; Step 3: Take the weighted sum of the flow difference and the pressure difference to obtain the indirect temperature value.

6. The intelligent flow control system based on the mold temperature controller according to claim 1 is characterized in that: The temperature of the heat exchange liquid of the mold temperature controller is obtained in the coolant detection module, and the liquid temperature coefficient is obtained through the heat exchange liquid temperature of the mold temperature controller and the indirect temperature value, which is specifically: Step 1: Get the liquid temperature of the mold temperature controller before heat exchange, marked as the temperature before exchange, and get the liquid temperature of the mold temperature controller after heat exchange, marked as the temperature after exchange; Step 2: Set a preset threshold value for cooling the temperature of the heat exchange liquid, obtain a temperature difference by subtracting the temperature after the exchange from the temperature before the exchange, and obtain the temperature of the heat exchange liquid of the mold temperature controller by summing the temperature difference and the preset threshold value for cooling the temperature of the heat exchange liquid; Step 3: Obtain the indirect temperature value, and obtain the liquid temperature coefficient by taking the weighted average of the indirect temperature value and the heat exchange liquid temperature of the mold temperature controller.

7. The intelligent flow control system based on a mold temperature controller according to claim 1 is characterized in that: The calculation method of the temperature reference coefficient in the temperature prediction module is as follows: Where Ws is the temperature reference coefficient, Cw is the mold temperature coefficient, and Yw is the liquid temperature coefficient. and are weights, 8. The intelligent flow control system based on a mold temperature controller according to claim 1, characterized in that: In the temperature prediction module, the temperature prediction value is obtained by using the linear regression model through the temperature reference coefficient in the historical temperature database, specifically: Step 1: Obtain the temperature reference coefficient, mold temperature coefficient and liquid temperature coefficient of the mold temperature controller in the past 3 hours from the historical temperature database, set a preset time interval threshold, and divide the temperature reference coefficient, mold temperature coefficient and liquid temperature coefficient of the mold temperature controller in the past 3 hours into multiple continuous reference values ​​with the preset time interval threshold as the length, so as to obtain multiple sections of temperature reference coefficient, multiple sections of mold temperature coefficient and multiple sections of liquid temperature coefficient; Step 2: Delete the maximum and minimum values ​​in each temperature coefficient respectively, sum and average the remaining temperature coefficients in each section to obtain multiple temperature coefficient averages, delete the maximum and minimum values ​​in each mold temperature coefficient respectively, sum and average the remaining mold temperature coefficients in each section to obtain multiple mold temperature coefficient averages, delete the maximum and minimum values ​​in each liquid temperature coefficient respectively, sum and average the remaining liquid temperature coefficients in each section to obtain multiple liquid temperature coefficient averages; Step 3: Arrange multiple temperature coefficient means in chronological order, and make a difference between each two adjacent temperature coefficient means to obtain multiple adjacent temperature coefficient difference values; arrange multiple mold temperature coefficient means in chronological order, and make a difference between each two adjacent mold temperature coefficient means to obtain multiple adjacent mold temperature coefficient difference values; arrange multiple liquid temperature coefficient means in chronological order, and make a difference between each two adjacent liquid temperature coefficient means to obtain multiple adjacent liquid temperature coefficient difference values; Step 4: Set a preset threshold value of a temperature standard value, and obtain a temperature prediction value through the preset threshold value of the temperature standard value, a plurality of adjacent temperature coefficient differences, a plurality of adjacent mold temperature coefficient differences, and a plurality of adjacent liquid temperature coefficient differences; The temperature prediction value is calculated as follows: Among them, Yu represents the temperature prediction value, Bz represents the temperature standard value preset threshold, Dc n Expressed as the difference between the nth adjacent temperature coefficients, Mc n Expressed as the difference in temperature coefficients of the nth adjacent molds, Yc n It is expressed as the difference in temperature coefficients of the nth adjacent liquids, where n=1, 2, 3, ..., θ1, θ2 and θ3 are all weights, 1>θ1>0, 1>θ2>0, 1>θ3>0.

9. The intelligent flow control system based on a mold temperature controller according to claim 1, characterized in that: Temperature control module, specifically: Step 1: Obtain the current temperature prediction value, obtain the adjacent historical temperature prediction value closest to the current temperature prediction value in the historical temperature database, and make a difference between the current temperature prediction value and the adjacent historical temperature prediction value to obtain the temperature prediction difference; Step 2: Compare the relationship between the predicted temperature difference and 0. If the predicted temperature difference is greater than 0, increase the flow rate of the heat exchange liquid of the mold temperature controller. If the predicted temperature difference is less than 0, reduce the flow rate of the heat exchange liquid of the mold temperature controller.

10. An intelligent flow control method based on a mold temperature controller, applied to an intelligent flow control system based on a mold temperature controller as claimed in any one of claims 1 to 9, characterized in that: The steps include: Step 1: Obtain the appearance of the mold groove, select the temperature reference area according to the appearance of the mold groove, obtain the temperature of the mold temperature reference area and mark it as the mold temperature coefficient; Step 2: Obtain the heat exchange liquid flow rate of the mold temperature controller, obtain the heat exchange liquid pressure of the mold temperature controller, obtain the indirect temperature value through the heat exchange liquid flow rate of the mold temperature controller and the heat exchange liquid pressure of the mold temperature controller, obtain the heat exchange liquid temperature of the mold temperature controller, and obtain the liquid temperature coefficient through the heat exchange liquid temperature of the mold temperature controller and the indirect temperature value; Step 3: Obtain the temperature reference coefficient through the mold temperature coefficient and the liquid temperature coefficient, establish a historical temperature database through the temperature reference coefficient, obtain the temperature prediction value through the temperature reference coefficient in the historical temperature database using a linear regression model, and incorporate the temperature prediction value into the historical temperature database; Step 4: Obtain the historical temperature prediction value in the historical temperature database, compare the historical temperature prediction value with the temperature prediction value, and adjust the flow rate of the heat exchange liquid of the mold temperature controller according to the comparison result.

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