Fermented dairy product cooling system testing method, device, electronic equipment and storage medium

Abstract

The present application relates to the technical field of cooling system testing, and discloses a method, device, electronic device and storage medium for testing a cooling system for fermented dairy products, the method comprising: obtaining a pressure drop setting value for dairy products; obtaining parameter information of each component of the cooling system; the parameter information including component type and component size parameters; obtaining a predicted pressure drop value of each component in the cooling system through a pressure drop prediction model based on the parameter information of each component in the cooling system, and summing the predicted pressure drop values ​​of each component to obtain a total pressure drop value; if the total pressure drop value of the cooling system is greater than the pressure drop setting value, the cooling system is determined to have failed; a pressure reduction adjustment is performed on the parameter information of each component in the cooling system that has failed, and the total pressure drop value of the adjusted cooling system is calculated again until the calculated total pressure drop value is less than the pressure drop setting value; the design cycle and design cost of the cooling system for dairy products can be shortened.

Description

Technical Field

[0001] The present application relates to the technical field of cooling system testing, and in particular to a method, device, electronic device and storage medium for testing a cooling system for fermented dairy products. Background Art

[0002] Dairy products refer to various foods made from cow's milk or goat's milk and their processed products as the main raw materials, which undergo a series of processing (such as pasteurization, sterilization, fermentation, drying, etc.); the viscosity of dairy products is a complex physical property that is affected by many factors and plays an important role in the processing and quality control of dairy products; therefore, during the production and processing of dairy products, we need to pay close attention to changes in viscosity and take corresponding measures to ensure the quality of dairy products and processing efficiency.

[0003] In the related art, in the production process of dairy products, a cooling system is usually used to cool the fermented dairy products to stop the continued fermentation of yogurt and ensure the quality of dairy products; the cooling system is usually designed differently according to the type and characteristics of the dairy products, the demand for dairy products, and other factors.

[0004] However, the design of the cooling system is usually based on structural design experience. It is often the case that the newly designed cooling system will cause excessive viscosity loss and poor texture quality after cooling the dairy products. Therefore, the cooling system needs to be readjusted and verified again until the quality of the dairy products meets the requirements after cooling. This results in a long design cycle and high design cost for the cooling system. Summary of the Invention

[0005] The present application provides a method, device, electronic equipment and storage medium for testing a fermented dairy product cooling system, which can shorten the design cycle and design cost of the fermented dairy product cooling system.

[0006] In one aspect, the present application provides a method for testing a fermented dairy product cooling system, which is applied to testing software, and the method comprises:

[0007] Get the pressure drop setpoint for dairy products;

[0008] Obtain parameter information of each component of the cooling system; the parameter information includes component type and component size parameters;

[0009] According to the parameter information of each component in the cooling system, the predicted pressure drop value of each component in the cooling system is obtained through the pressure drop prediction model, and the predicted pressure drop values ​​of each component are summed to obtain the total pressure drop value.

[0010] If the total pressure drop value of the cooling system is greater than the pressure drop set value, the cooling system is determined to have failed;

[0011] The parameter information of each component in the cooling system that fails is adjusted for pressure reduction, and the total pressure drop value of the adjusted cooling system is calculated again until the calculated total pressure drop value is less than the pressure drop set value.

[0012] Beneficial effects: The predicted pressure drop value of each part in the cooling system is obtained through the pressure drop prediction model, and then the total pressure drop value in the cooling system is calculated to compare with the preset pressure drop value of the dairy product, so as to determine whether the cooling system passes. If not, the parameter information of at least part of the parts in the cooling system is adjusted to reduce the total pressure drop value of the cooling system; then the total pressure drop value of the adjusted cooling system is calculated again until the total pressure drop value of the cooling system is less than the pressure drop set value; the cooling system is tested and optimized by the above method, which can reduce the probability that the newly designed cooling system will cause large viscosity loss and poor tissue quality of dairy products after cooling, thereby reducing the number of verifications of the cooling system, thereby shortening the development cycle of the dairy cooling system and design costs.

[0013] At the same time, the above method can also break through the industry problem that dairy products cannot be reduced to below 18°C, thereby optimizing the production process of dairy products.

[0014] In an optional embodiment, before obtaining the pressure drop set value of the dairy product, it is first determined that the dairy product is in a laminar flow state in the cooling system.

[0015] In an optional embodiment, the process of determining that the dairy product is in a laminar flow state in the cooling system includes:

[0016] Get the density of dairy products ρ (kg / m 3 ), the flow velocity v (m / s) of the dairy product in the cooling system, the pipe diameter D (m) of the cooling system, and the dynamic viscosity μ (Pa·s) of the dairy product;

[0017] The Reynolds coefficient Re of dairy products is calculated by the formula Re = ρvD / μ;

[0018] If the Reynolds coefficient Re of the dairy product is less than 2300, it is confirmed that the dairy product is in a laminar flow state in the cooling system.

[0019] In an optional embodiment, the process of obtaining the pressure drop set value of the dairy product includes:

[0020] Obtain the viscosity M of the same type of dairy product when cooled to a set temperature, and the viscosity N of the same type of dairy product after being cooled by its existing cooling system and then reduced to the set temperature, and calculate the viscosity difference MN; wherein the viscosity of the dairy product is measured by a rheometer;

[0021] According to the viscosity difference MN, a pressure drop set value is obtained through a pressure drop output model; wherein the pressure drop output model is composed of viscosity difference values ​​and pressure drop values ​​corresponding to multiple dairy products of the same type as samples, obtained through artificial intelligence training and verification, or obtained through linear regression processing.

[0022] In an optional embodiment, the pressure drop prediction model is a mapping database formed by the pressure drop values ​​corresponding to different types of dairy products of various components in the cooling system.

[0023] In an optional embodiment, the parameter information further includes component temperature;

[0024] The pressure drop prediction model is a mapping database formed by the pressure drop values ​​corresponding to different types of dairy products and different component temperatures of various components in the cooling system.

[0025] In an optional embodiment, the method further includes:

[0026] If the total pressure drop value of the cooling system is less than 60% of the set value, it is determined that the performance of the cooling system exceeds the standard;

[0027] The parameter information of each component in the cooling system with excessive performance is adjusted to increase the pressure, and the total pressure drop value of the adjusted cooling system is calculated again until the calculated total pressure drop value is greater than 60% of the set value and less than the set value.

[0028] In a second aspect, the present application further provides a fermented dairy product cooling system testing device, the device comprising:

[0029] An acquisition module is used to obtain a set value of the pressure drop of the dairy product and parameter information of each component of the cooling system; the parameter information includes component type and component size parameters;

[0030] a processing and calculation module, configured to obtain, based on parameter information of each component in the cooling system and through a pressure drop prediction model, a predicted pressure drop value of each component in the cooling system, and sum the predicted pressure drop values ​​of each component to obtain a total pressure drop value;

[0031] a judgment module, configured to judge that the cooling system fails if the total pressure drop value of the cooling system is greater than the pressure drop set value;

[0032] The adjustment module is used to adjust the pressure drop of the parameter information of each component in the cooling system that fails, and calculate the total pressure drop value of the adjusted cooling system again until the calculated total pressure drop value is less than the pressure drop set value.

[0033] In a third aspect, the present application also provides an electronic device comprising a memory and a processor, wherein the memory and the processor are connected; computer instructions are stored in the memory, and the processor executes the fermented dairy product cooling system testing method in any one of the embodiments of the first aspect by executing the computer instructions.

[0034] In a fourth aspect, the present application further provides a computer-readable storage medium having computer instructions stored thereon, wherein the computer instructions are used to enable a computer to execute the fermented dairy product cooling system testing method in any one of the embodiments in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the specific implementation methods of this application or the technical solutions in related technologies, the following is a brief introduction to the drawings required for use in the specific implementation methods or related technical descriptions. Obviously, the drawings described below are some implementation methods of this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0036] Figure 1 This is a flow chart of a method for testing a fermented dairy product cooling system according to an embodiment of the present application;

[0037] Figure 2 This is a flow chart of another method for testing a fermented dairy product cooling system according to an embodiment of the present application;

[0038] Figure 3 This is a flow chart of another method for testing a fermented dairy product cooling system according to an embodiment of the present application;

[0039] Figure 4 This is a flow chart of an embodiment of the present application for determining that dairy products are in a laminar flow state in a cooling system;

[0040] Figure 5 This is a flow chart of obtaining a pressure drop set value for dairy products according to an embodiment of the present application;

[0041] Figure 6 This is a schematic diagram of a fermented dairy product cooling system testing device according to an embodiment of the present application;

[0042] Figure 7 A schematic diagram of an electronic device according to an embodiment of the present application.

[0043] Description of reference numerals:

[0044] 100, confirmation module; 200, acquisition module; 300, processing and calculation module; 400, judgment module; 500, adjustment module;

[0045] 10. Processor; 20. Memory; 30. Input device; 40. Output device. DETAILED DESCRIPTION

[0046] To make the purpose, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of this application.

[0047] In the related art, in the production process of dairy products, a cooling system is usually used to cool the fermented dairy products to stop the continued fermentation of yogurt and ensure the quality of dairy products; the cooling system is usually designed differently according to the type and characteristics of the dairy products, the demand for dairy products, and other factors.

[0048] However, the design of the cooling system is usually based on structural design experience. It is often the case that the newly designed cooling system will cause excessive viscosity loss and poor texture quality after cooling the dairy products. Therefore, the cooling system needs to be readjusted and experiments need to be conducted again until the quality of the dairy products meets the requirements after cooling. As a result, the design cycle of the cooling system is long and the design cost is high.

[0049] Therefore, the present application provides a method, device, electronic equipment and storage medium for testing a fermented dairy product cooling system, which can shorten the design cycle and design cost of the fermented dairy product cooling system.

[0050] The following combination Figures 1 to 7 , describing the embodiments of the present application.

[0051] According to an embodiment of the present application, on the one hand, a method for testing a fermented dairy product cooling system is provided, which is applied to testing software, such as Figure 1 As shown, the method includes:

[0052] Step S102: Obtain the pressure drop setting value of the dairy product.

[0053] It should be noted that pressure drop refers to: the pressure value lost by dairy products after passing through the cooling system; the pressure drop set value refers to the pressure value lost by dairy products after passing through the cooling system, estimated through simulation calculations or design experience.

[0054] Specifically, the process of obtaining the pressure drop set value of dairy products includes:

[0055] like Figure 5As shown, step S1021: obtain the viscosity M of the same type of dairy product when cooled to the set temperature, and the viscosity N of the same type of dairy product after being cooled by its existing cooling system and then reduced to the set temperature state, and calculate the viscosity difference MN; wherein, the viscosity of the dairy product is measured by a rheometer.

[0056] It should be noted that the set temperature is generally lower than the temperature of the same type of dairy products after passing through its existing cooling system. Specifically, it can be 5°C to 15°C, specifically, any one of 5°C, 6°C, 7°C, 8°C, 9°C, 10°C, 11°C, 12°C, 13°C, 14°C and 15°C. Of course, it can also be other values, which can be selected and set according to actual needs.

[0057] It should be noted that the same type of dairy products refers to dairy products in the same series, with the same or similar main formulas, and some auxiliary ingredients with certain differences in the formula type or content; specifically, flavored yogurt with different taste and viscosity developed for different age groups, etc., belong to the same type of dairy products.

[0058] The viscosity N of the same type of dairy product after being cooled by its existing cooling system and then reduced to the set temperature state, wherein the existing cooling system is a cooling system that has been designed and put into production for the same type of dairy product, and does not refer to the cooling system to be tested in this application.

[0059] During the specific test process, the rheometer used is the RheolabQC rheometer, which is a commercially available rheometer. The RheolabQC rheometer is equipped with a high-precision encoder and a high-performance EC DC motor (EC, Electronically Commutated). The shear rate is measured by the high-precision encoder, and the shear stress is measured by the high-performance EC DC motor. The measurement temperature is controlled by the rheometer's built-in temperature detection system, and the viscosity (shear stress / shear rate) is calculated using Newton's law.

[0060] If the temperature of a dairy product before cooling is 42°C, and the temperature after cooling by its existing cooling system is 18°C, and the set temperature is 10°C, then the dairy product at 42°C after fermentation is cooled to 10°C in a 10°C refrigerator, and then the rheometer model 27 rotor is used with a shear rate of 64r / s, and the temperature is tested for 10 seconds at a temperature of 10±0.5°C to form a viscosity curve of the dairy product at 42°C. The value is read to obtain the viscosity value M of the dairy product at 10°C; a dairy product sample of the same type of dairy product at 18°C ​​after passing through its existing cooling system is cooled to 10°C in a refrigerator, and is taken out after stabilization for 5 minutes. The rheometer model 27 rotor is used with a shear rate of 64r / s, and the temperature is tested for 10 seconds at a temperature of 10±0.5°C to form a viscosity curve of the dairy product at 18°C. The value is read to obtain the viscosity value N of the dairy product at 10°C.

[0061] The viscosity difference is calculated as MN.

[0062] Step S1022: Obtain a pressure drop set value through a pressure drop output model based on the viscosity difference MN; wherein the pressure drop output model is composed of viscosity difference values ​​and pressure drop values ​​corresponding to multiple dairy products of the same type as samples, obtained through artificial intelligence training and verification, or obtained through linear regression processing.

[0063] It should be noted that multiple dairy products of the same type can be understood as dairy products of the same series. The main formula of the dairy products is the same or similar, and the formula type or content of some auxiliary ingredients have certain differences; specifically, flavored yogurt with different taste and viscosity developed for different age groups belongs to the same type of dairy products.

[0064] Specifically, as shown in Table 1, the figure shows the corresponding samples of the sub-series of dairy products A, dairy products B, dairy products C and dairy products D; if the same type of dairy product A has different sub-series, such as A1, A2, ..., A100, then A1 has a corresponding viscosity difference and a pressure drop value of the system during its production, A2 has a corresponding viscosity difference and a pressure drop value of the system during its production, ..., A100 has a corresponding viscosity difference and a pressure drop value of the system during its production; the above samples can form samples of the same type of dairy product A, which can be obtained through training and verification by artificial intelligence (such as convolutional neural networks, etc.), or can be obtained through linear regression processing.

[0065] Table 1

[0066]

[0067] Of course, the pressure drop setting value for dairy products can also be directly set based on empirical values.

[0068] Step S103: Obtain parameter information of each component of the cooling system; the parameter information includes component type and component size parameters.

[0069] The parameter information of the parts includes, for example, the inner diameter and length of the pipe in the cooling system, the inner diameter and bend-to-diameter ratio of the elbow, the type and inner diameter of the pump, the inner diameter of the tee, the type and inner diameter of the valve, and the inner diameter and length of the heat exchange pipeline in the heat exchange assembly.

[0070] Step S104: Based on the parameter information of each component in the cooling system, the predicted pressure drop value of each component in the cooling system is obtained through the pressure drop prediction model, and the predicted pressure drop values ​​of each component are summed to obtain the total pressure drop value.

[0071] It should be noted that when dairy products pass through the cooling system and pass through various parts in the cooling system, each part will cause a pressure drop on the dairy products individually; and the pressure drop prediction model is a mapping model formed by experimentally measuring the loss pressure drop of different parts passing through different dairy products, or further building a model through linear regression to estimate the pressure drop generated when different parts pass through different dairy products, thereby forming a predicted pressure drop value for each part.

[0072] Specifically, the pressure drop prediction model is formed by a mapping database of the pressure drop values ​​corresponding to different types of dairy products for various components in the cooling system.

[0073] Some samples are as follows:

[0074] The 5D elbow corresponds to dairy products F1, F2, ... F100, each corresponding to a pressure drop value.

[0075] The 4D elbow corresponds to dairy products F1, F2, ... F100, each corresponding to a pressure drop value.

[0076] The butterfly valve with a diameter of 100 mm corresponds to dairy products F1, F2, ... F100, and each corresponds to a predicted pressure drop value.

[0077] The above samples can be obtained by setting pressure sensors at the input and output ends of the component and passing different types of dairy products through them for actual measurement.

[0078] Step S105: If the total pressure drop value of the cooling system is greater than the pressure drop set value, it is determined that the cooling system fails.

[0079] Specifically, for example, if the total pressure drop value of the cooling system is 0.8 bar and the pressure drop setting value is 0.6 bar, the total pressure drop value is greater than the pressure drop setting value, and the cooling system is determined to have failed, and step S106 is continued; for another example, if the total pressure drop value of the cooling system is 0.5 bar and the pressure drop setting value is 0.6 bar, the total pressure drop value is less than the pressure drop setting value, and the cooling system is determined to have passed, and the test is stopped.

[0080] Step S106: adjusting the pressure drop of the parameter information of each component in the cooling system that fails, and recalculating the total pressure drop value of the adjusted cooling system until the calculated total pressure drop value is less than the pressure drop set value.

[0081] It should be noted that the parameter information of each component in the cooling system that does not pass the pressure reduction adjustment is performed, that is, the parameter information of each component is adjusted, such as using a pipe with a larger inner diameter, optimizing and shortening the length of the pipeline, replacing the type of heat exchange component with lower pressure drop, reducing the number of valves in the cooling system, etc., to reduce the total pressure drop of the system.

[0082] It should be noted that, in the above method, step S102 may be located after step S103 or after step S104.

[0083] In this embodiment, the predicted pressure drop value of each part in the cooling system is obtained by the pressure drop prediction model, and then the total pressure drop value in the cooling system is calculated to compare with the preset pressure drop value of the dairy product, so as to determine whether the cooling system passes. If not, the parameter information of at least a part of the parts in the cooling system is adjusted to reduce the total pressure drop value of the cooling system; then the total pressure drop value of the adjusted cooling system is calculated again until the total pressure drop value of the cooling system is less than the pressure drop set value; the cooling system is tested and optimized by the above method, which can reduce the probability that the newly designed cooling system will cause large viscosity loss and tissue quality difference of dairy products after cooling, thereby reducing the number of verifications of the cooling system, thereby shortening the development cycle and design cost of the dairy cooling system.

[0084] At the same time, the above method can also break through the industry problem that dairy products cannot be reduced to below 18°C, thereby optimizing the production process of dairy products.

[0085] In one embodiment, Figure 2 As shown, before obtaining the pressure drop set value of the dairy product, step S101 is first performed: determining that the dairy product is in a laminar flow state in the cooling system.

[0086] In this embodiment, by determining that the dairy product is in a laminar state in the cooling system, the viscosity of the dairy product can be guaranteed, and then the tissue state of the dairy product can be guaranteed, non-laminar flow transportation in the dairy product cooling system can be avoided, the deviation of subsequent test results can be reduced, the accuracy of the test results can be improved, and the number of verifications of the cooling system can be further reduced, thereby shortening the development cycle and design cost of the dairy product cooling system.

[0087] In a specific embodiment, Figure 4 As shown, step S101: determining that the dairy product is in a laminar flow state in the cooling system includes:

[0088] Step S1011: Obtain the density of dairy products (kg / m 3 ), the flow velocity v (m / s) of the dairy product in the cooling system, the pipe diameter D (m) of the cooling system, and the dynamic viscosity μ (Pa·s) of the dairy product;

[0089] Step S1012: Calculate the Reynolds coefficient Re of the dairy product using the formula Re=ρvD / μ;

[0090] Step S1013: If the Reynolds coefficient Re of the dairy product is less than 2300, it is confirmed that the dairy product is in a laminar flow state in the cooling system.

[0091] In this embodiment, the laminar flow state of the dairy product in the cooling system is determined by calculating the Reynolds coefficient of the dairy product in the cooling system. This method is simple and fast.

[0092] In an embodiment not shown, motion simulation analysis can be used to analyze whether the dairy product is in a laminar flow state in the cooling system. This method is slow and complex to operate.

[0093] In one embodiment, the parameter information also includes component temperature; the pressure drop prediction model is a mapping database formed by the corresponding pressure drop values ​​of various components in the cooling system for different types of dairy products at different temperatures.

[0094] Some samples are as follows:

[0095] The 5D elbow corresponds to dairy products F1, F2, ... F100, and at 15°C, each corresponds to a pressure drop value.

[0096] The 5D elbow corresponds to dairy products F1, F2, ... F100, and at 16°C, each corresponds to a pressure drop value.

[0097] …

[0098] The 5D elbow corresponds to dairy products F1, F2, ... F100, and at 50 ° C, each corresponds to a pressure drop value.

[0099] The 4D elbow corresponds to dairy products F1, F2, ... F100, and at 15°C, each corresponds to a pressure drop value.

[0100] The 4D elbow corresponds to dairy products F1, F2, ... F100, and at 16°C, each corresponds to a pressure drop value.

[0101] …

[0102] The 4D elbow corresponds to dairy products F1, F2, ... F100, and at 50 ° C, each corresponds to a pressure drop value.

[0103] The butterfly valve with a diameter of 100 mm corresponds to dairy products F1, F2, ... F100, and at 15°C, each corresponds to a predicted pressure drop value.

[0104] The butterfly valve with a diameter of 100 mm corresponds to dairy products F1, F2, ... F100, and at 16°C, each corresponds to a predicted pressure drop value.

[0105] …

[0106] The butterfly valve with a diameter of 100 mm corresponds to dairy products F1, F2, ... F100, and at 50°C, each corresponds to a predicted pressure drop value.

[0107] The above samples can be obtained by setting pressure sensors at the input and output ends of the component, and passing different types of dairy products at different temperatures through them for actual measurement.

[0108] Of course, it is also possible to measure partial values ​​and complete the values ​​through interpolation or linear regression.

[0109] In this embodiment, by introducing the temperature variable, the predicted pressure drop values ​​of the input pipeline located in front of the heat exchange component and the output pipeline located behind the exchange component in the cooling system can be made more accurate, further improving the test results of the test method.

[0110] In one embodiment, Figure 3 As shown, the method further includes: Step S107: if the total pressure drop value of the cooling system is less than 60% of the set value, it is determined that the performance of the cooling system exceeds the standard.

[0111] Step S108: Boost and adjust the parameter information of each component in the cooling system with excessive performance, and recalculate the total pressure drop value of the adjusted cooling system until the calculated total pressure drop value is greater than 60% of the set value and less than the set value; wherein the performance reduction parameters include component type and component size parameters.

[0112] It should be noted that the parameter information of each part in the cooling system with excessive performance is adjusted to increase the pressure, that is, the parameter information of each component is adjusted, such as using a pipe with a smaller inner diameter, replacing the type of heat exchange component with a higher pressure drop, increasing the number of valves in the cooling system to achieve more functional monitoring, etc., to increase the total pressure drop of the system.

[0113] In this embodiment, by increasing the pressure of the cooling system with excessive performance, the expensive parts in the cooling system can be replaced to reduce the cost of the cooling system; monitoring components can also be added to achieve more functions, etc.

[0114] The above method will be further described below by taking the test of the cooling system of dairy product A as an example.

[0115] Among them, the temperature of dairy product A after fermentation is 42°C, and a cooling system is required to reduce it to 10°C.

[0116] Step G101: Determine that the dairy product is in a laminar flow state in the cooling system, corresponding to step S101 in the above method.

[0117] Step G1011: Obtain the density ρ of the dairy product as 1.04 kg / m 3, the flow velocity v of the dairy product in the cooling system is 0.5 m / s, the pipe diameter D of the cooling system is 0.101 m, and the dynamic viscosity μ of the dairy product is 0.54 Pa·G to 0.67 Pa· s , corresponding to step S1011 in the above method.

[0118] Step G1012: Calculate the Reynolds coefficient (Re) of the dairy product to be 0.077 to 0.096 using the formula Re=ρvD / μ, corresponding to step S1012 in the above method;

[0119] Step G1013: If the Reynolds coefficient Re of the dairy product is between 0.077 and 0.096, which is much smaller than 2300, it is confirmed that the dairy product is in a laminar flow state in the cooling system, which corresponds to step S1013 in the above method.

[0120] Step G102: Obtaining a pressure drop setting value for the dairy product, corresponding to step S102 in the above method.

[0121] Specifically, the process of obtaining the pressure drop set value of dairy products includes:

[0122] Step G1021: Obtain the viscosity M of the same type of dairy product when cooled to the set temperature, and the viscosity N of the same type of dairy product after being cooled by its existing cooling system and then reduced to the set temperature state, and calculate the viscosity difference MN; wherein, the viscosity of the dairy product is measured by a rheometer, corresponding to step S1021 in the above method.

[0123] During the specific testing process, the rheometer used was RheolabQC rheometer.

[0124] The temperature of dairy product A before cooling is 42°C, and the temperature after cooling is 10°C. The dairy product at 42°C after fermentation is cooled to 8°C in an 8°C refrigerator and taken out after stabilization for 5 minutes. The rheometer 27 model rotor is used with a shear rate of 64r / s and a temperature of 8±0.5°C for 10 seconds to form a viscosity curve of the dairy product at 42°C. The value is read to obtain the viscosity value M1 of the dairy product at 8°C.

[0125] Dairy product A is cooled to 10°C using its existing cooling system, then cooled to 8°C in an 8°C refrigerator and stabilized for 5 minutes before being taken out. A rheometer with a 27-model rotor and a shear rate of 64 r / s is used to measure the viscosity of the dairy product at 8±0.5°C for 10 seconds to form a viscosity curve of the dairy product at 10°C. The value is read to obtain the viscosity value N1 of the dairy product at 8°C.

[0126] The viscosity difference is calculated as M1-N1.

[0127] Step G1022: Obtain the pressure drop setting value H through the pressure drop output model based on the viscosity difference M1-N1; wherein the pressure drop output model is obtained by linear regression processing using the viscosity difference and pressure drop values ​​corresponding to multiple dairy products of the same type as samples, corresponding to step S1022 in the above method.

[0128] Table 2

[0129]

[0130] Step G103: Obtain parameter information of each component of the cooling system; the parameter information includes component type and component size parameters. The specific parameters are shown in Table 2, corresponding to step S103 in the above method.

[0131] Step G104: Based on the parameter information of each component in the cooling system, the predicted pressure drop value of each component in the cooling system is obtained through the pressure drop prediction model, and the predicted pressure drop values ​​of each component are summed to obtain the total pressure drop value E, which corresponds to step S104 in the above method.

[0132] Step G105: If the total pressure drop value E of the cooling system is greater than the pressure drop set value H, the cooling system is determined to have failed, which corresponds to step S105 in the above method.

[0133] Step G106: Adjust the pressure drop of the parameter information of each component in the cooling system that fails, and calculate the total pressure drop value of the adjusted cooling system again until the calculated total pressure drop value E1 is less than the pressure drop set value H, corresponding to step S106 in the above method.

[0134] The pressure reduction adjustments for the parameter information of each component in the cooling system that is not passed include: selecting pipes with larger inner diameters, optimizing and shortening the length of the pipelines, replacing the type of heat exchange components with lower pressure drop, reducing the number of valves in the cooling system, etc.

[0135] Step G107: If the total pressure drop value E1 of the cooling system is less than 60% of the set value H, it is determined that the performance of the cooling system exceeds the standard, which corresponds to step S107 in the above method;

[0136] Step G108: Boost and adjust the parameter information of each component in the cooling system with excessive performance, and recalculate the total pressure drop value of the adjusted cooling system until the calculated total pressure drop value E2 is greater than 60% of the set value H and less than the set value H; wherein the performance reduction parameters include component type and component size parameters, corresponding to step S108 in the above method.

[0137] Specifically, the pressure adjustment of the parameter information of each component in the cooling system with excessive performance includes selecting pipes with smaller inner diameters, replacing the type of heat exchange components with higher pressure drops, and increasing the number of valves in the cooling system.

[0138] The parameters of the final cooling system are as follows: (1) The diameter of the dairy pipeline is ≥97 mm; (2) The pipeline elbow uses 5D elbows, and the number of elbows is ≤30; (3) The valve uses a spherical valve cavity with a valve cavity diameter of ≥97 mm; (4) The number of diameter changes of sensors, pumps, filters and other devices is ≤10; (5) There is no butterfly valve in the dairy pipeline; (6) The total length of the cooling system connecting line is ≤30 m.

[0139] According to an embodiment of the present application, on the other hand, a fermented dairy product cooling system testing device is provided, such as Figure 6 As shown, the device includes:

[0140] The acquisition module 200 is used to obtain the pressure drop setting value of the dairy product and to obtain parameter information of each component of the cooling system; the parameter information includes component type and component size parameters.

[0141] The processing and calculation module 300 is used to obtain the predicted pressure drop value of each component in the cooling system based on the parameter information of each component in the cooling system through the pressure drop prediction model, and sum the predicted pressure drop values ​​of each component to obtain the total pressure drop value.

[0142] The judgment module 400 is used to judge whether the total pressure drop value of the cooling system is greater than the pressure drop set value, and then judge that the cooling system fails;

[0143] The adjustment module 500 is used to adjust the pressure drop of the parameter information of each component in the cooling system that fails, and recalculate the total pressure drop value of the adjusted cooling system until the calculated total pressure drop value is less than the pressure drop set value.

[0144] In one embodiment, the fermented dairy product cooling system testing device further includes: a confirmation module 100, which is used to determine whether the dairy product is in a laminar flow state in the cooling system.

[0145] In one embodiment, the judgment module 400 is further configured to judge that the total pressure drop value of the cooling system is less than 60% of the set value, and then determine that the performance of the cooling system exceeds the standard.

[0146] The adjustment module 500 is also used to increase the pressure of the parameter information of each component in the cooling system with excessive performance, and recalculate the total pressure drop value of the adjusted cooling system until the calculated total pressure drop value is greater than 60% of the set value and less than the set value.

[0147] According to an embodiment of the present application, in a second aspect, an electronic device is provided, having the above Figure 6 The FCT test fixture strain simulation device shown.

[0148] See also Figure 7 , is a schematic diagram of the structure of an electronic device provided by an optional embodiment of the present invention, the electronic device comprising: one or more processors 10, a memory 20, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other by means of different buses for communication, and can be installed on a common mainboard or in other ways as needed. The processor can process instructions executed within the electronic device, including instructions stored in or on the memory to display graphical information of a GUI on an external input / output device (such as a display device coupled to the interface).

[0149] In some optional embodiments, multiple processors and / or multiple buses can be used with multiple memories and multiple storages if desired. Similarly, multiple electronic devices can be connected, with each device providing part of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). Figure 7 A processor 10 is taken as an example.

[0150] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0151] The memory 20 stores instructions that can be executed by at least one processor 10, so that the at least one processor 10 executes the fermented dairy product cooling system testing method shown in the above embodiment.

[0152] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and applications required for at least one function; the data storage area may store data created based on the use of the electronic device, etc. In addition, the memory 20 may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may include a memory remotely located relative to the processor 10, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0153] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0154] The electronic device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 7 The bus connection is taken as an example.

[0155] The input device 30 can receive input digital or character information and generate key signal input related to user settings and function control of the electronic device, such as a touch screen, a keypad, a mouse, a trackpad, a touch pad, an indicator stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 can include a display device, an auxiliary lighting device (e.g., an LED), and a tactile feedback device (e.g., a vibration motor). The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display, and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0156] An embodiment of the present invention also provides a computer-readable storage medium, and the above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded on a storage medium, or downloaded via a network and originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware.

[0157] The storage medium may be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium may include a combination of the aforementioned types of memory. It is understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the methods shown in the above embodiments are implemented.

[0158] Although the embodiments of the present application have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations shall fall within the scope defined by the appended claims.

Claims

1. A method for testing a cooling system for fermented dairy products, characterized in that: Applied to testing software, the method includes: Get the pressure drop setpoint for dairy products; Obtain parameter information of each component of the cooling system; the parameter information includes component type and component size parameters; According to the parameter information of each component in the cooling system, the predicted pressure drop value of each component in the cooling system is obtained through the pressure drop prediction model, and the predicted pressure drop values ​​of each component are summed to obtain the total pressure drop value; If the total pressure drop value of the cooling system is greater than the pressure drop set value, the cooling system is determined to have failed; Adjust the pressure drop of the parameter information of each component in the cooling system that fails, and recalculate the total pressure drop value of the adjusted cooling system until the calculated total pressure drop value is less than the pressure drop set value; The process of obtaining the pressure drop set value of the dairy product includes: Obtain the viscosity M of the same type of dairy product when cooled to a set temperature, and the viscosity N of the same type of dairy product after being cooled by its existing cooling system and then reduced to the set temperature, and calculate the viscosity difference MN; wherein the viscosity of the dairy product is measured by a rheometer; According to the viscosity difference MN, a pressure drop set value is obtained through a pressure drop output model; wherein the pressure drop output model is composed of viscosity difference values ​​and pressure drop values ​​corresponding to multiple dairy products of the same type as samples, obtained through artificial intelligence training and verification, or obtained through linear regression processing.

2. The fermented dairy product cooling system testing method according to claim 1, characterized in that: Before obtaining the pressure drop set value of the dairy product, it is first determined that the dairy product is in a laminar flow state in the cooling system.

3. The fermented dairy product cooling system testing method according to claim 2, characterized in that: The process of ensuring laminar flow of dairy products within the cooling system includes: Get the density of dairy products ρ (kg / m 3 ), the flow velocity v (m / s) of the dairy product in the cooling system, the pipe diameter D (m) of the cooling system, and the dynamic viscosity μ (Pa·s) of the dairy product; The Reynolds coefficient Re of dairy products is calculated by the formula Re = ρvD / μ; If the Reynolds coefficient Re of the dairy product is less than 2300, it is confirmed that the dairy product is in a laminar flow state in the cooling system.

4. The fermented dairy product cooling system testing method according to claim 1, characterized in that: The pressure drop prediction model is a mapping database formed by the pressure drop values ​​corresponding to different types of dairy products for various components in the cooling system.

5. The fermented dairy product cooling system testing method according to claim 4, characterized in that: The parameter information also includes component temperature; The pressure drop prediction model is a mapping database formed by the pressure drop values ​​corresponding to different types of dairy products and different component temperatures of various components in the cooling system.

6. The fermented dairy product cooling system testing method according to claim 1, characterized in that: The method further comprises: If the total pressure drop value of the cooling system is less than 60% of the set value, it is determined that the performance of the cooling system exceeds the standard; The parameter information of each component in the cooling system with excessive performance is adjusted to increase the pressure, and the total pressure drop value of the adjusted cooling system is calculated again until the calculated total pressure drop value is greater than 60% of the set value and less than the set value.

7. A fermented dairy product cooling system testing device, characterized in that: The device comprises: An acquisition module is used to obtain a set pressure drop value for the dairy product and parameter information of various components of the cooling system; the parameter information includes component type and component size parameters; and is also used to obtain the viscosity M of the same type of dairy product when cooled to a set temperature, and the viscosity N of the same type of dairy product when cooled by the existing cooling system and then reduced to the set temperature; wherein the viscosity of the dairy product is measured by a rheometer; a processing and calculation module for obtaining, based on parameter information of each component in the cooling system and using a pressure drop prediction model, a predicted pressure drop value for each component in the cooling system, and summing the predicted pressure drop values ​​for each component to obtain a total pressure drop value; and further for calculating a viscosity difference MN, and obtaining a pressure drop set value based on the viscosity difference MN using a pressure drop output model; wherein the pressure drop output model is obtained by artificial intelligence training and verification based on a sample of viscosity difference values ​​and pressure drop values ​​corresponding to multiple dairy products of the same type, or by linear regression processing; a judgment module, configured to judge that the cooling system fails if the total pressure drop value of the cooling system is greater than the pressure drop set value; The adjustment module is used to adjust the pressure drop of the parameter information of each component in the cooling system that fails, and calculate the total pressure drop value of the adjusted cooling system again until the calculated total pressure drop value is less than the pressure drop set value.

8. An electronic device, characterized in that: comprising a memory and a processor, wherein the memory and the processor are connected; The memory stores computer instructions, and the processor executes the fermented dairy product cooling system testing method according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the fermented dairy product cooling system testing method according to any one of claims 1 to 6.

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