A processing control method for pet freeze-dried food

Abstract

The present invention discloses a processing control method for freeze-dried pet food, relating to the field of food processing technology. The method comprises obtaining thermal property data of a target water-containing material; performing a pre-freezing temperature analysis to obtain a pre-freezing temperature range; performing a drying temperature analysis to obtain a drying temperature range; performing a control deviation analysis on the equipment based on the pre-freezing temperature range and the drying temperature range to generate pre-freezing control parameters and drying control parameters; optimizing the vacuum control parameters based on the impact of the vacuum control parameters on the freezing rate, drying rate, and product quality, with the goal of shortening the freeze-drying time, to obtain an optimal vacuum control parameter combination; and performing processing control on the target water-containing material based on the pre-freezing control parameters, drying control parameters, and the optimal vacuum control parameter combination to generate the target freeze-dried food. This method solves the technical problem of low production efficiency due to the influence of control parameters in the prior art, and achieves the technical effect of automatically adjusting parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of food processing, and in particular to a processing control method for freeze-dried pet food. Background Art

[0002] In today's society, pets have become an integral part of family life. To meet the nutritional and health needs of pets, a wide variety of pet foods and health supplements are emerging. Among them, freeze-dried pet food, as a highly nutritious, easy-to-store, and convenient food, is increasingly popular among pet owners. Freeze-dried pet food is produced by freezing fresh ingredients such as meat, vegetables, and fruit. The resulting product is nutritious, tastes good, and easily stored. The key advantage of this food is that it retains the nutrients and taste of the ingredients while offering high rehydration and easy storage, making it convenient for pet owners to use and carry. However, the production process of freeze-dried pet food requires strict control over parameters such as raw material quality, processing methods, and freezing and drying temperatures to ensure product quality and safety. Therefore, developing effective process control methods is crucial. The long freezing and drying processes result in long production cycles and low production efficiency. Summary of the Invention

[0003] The embodiment of the present application provides a processing control method for pet freeze-dried food, which solves the technical problem of inaccurate correction effect in complex scenarios in the prior art.

[0004] In view of the above problems, an embodiment of the present application provides a processing control method for pet freeze-dried food.

[0005] A first aspect of the embodiments of the present application provides a method for controlling the processing of freeze-dried pet food, the method comprising:

[0006] Acquiring thermal property data of a target water-containing material, wherein the thermal property data includes a eutectic point and a eutectic point;

[0007] Performing a pre-freezing temperature analysis based on the eutectic point to obtain a pre-freezing temperature range;

[0008] Perform drying temperature analysis based on the eutectic point to obtain a drying temperature range;

[0009] Based on the pre-freezing temperature range and the drying temperature range, performing control deviation analysis on the freezing equipment and the drying and dehydration equipment to generate pre-freezing control parameters and drying control parameters;

[0010] According to the influence of vacuum control parameters on freezing speed, drying speed and product quality, with the goal of shortening freeze-drying time, the vacuum control parameters are optimized to obtain the optimal vacuum control parameter combination;

[0011] According to the combination of the pre-freezing control parameter, the drying control parameter and the optimal vacuum control parameter, the processing control of the target water-containing material is performed to produce the target freeze-dried food.

[0012] A second aspect of the embodiments of the present application provides a processing control system for pet freeze-dried food, the system comprising:

[0013] A data module, the data module is used to obtain thermal property data of the target water-containing material, wherein the thermal property data includes a eutectic point and a eutectic point;

[0014] a pre-freezing temperature analysis module, configured to perform pre-freezing temperature analysis based on the eutectic point to obtain a pre-freezing temperature range;

[0015] a drying temperature analysis module, configured to perform drying temperature analysis based on the eutectic point to obtain a drying temperature range;

[0016] a parameter module, the parameter module being used to perform control deviation analysis on the freezing equipment and the drying and dehydration equipment based on the pre-freezing temperature range and the drying temperature range, and to generate pre-freezing control parameters and drying control parameters;

[0017] An optimization module is used to optimize the vacuum control parameters based on their effects on freezing speed, drying speed, and product quality, with the goal of shortening the freeze-drying time, to obtain an optimal combination of vacuum control parameters;

[0018] A control module is used to control the processing of the target water-containing material according to the combination of the pre-freezing control parameter, the drying control parameter and the optimal vacuum control parameter to generate the target freeze-dried food.

[0019] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0020] To obtain the thermal properties of the target hydrous material, including the eutectic point and eutectic melting point, these properties must first be measured and analyzed. Pre-freezing temperature analysis based on the eutectic point can determine the pre-freezing temperature range. Drying temperature analysis based on the eutectic point can determine the drying temperature range. After determining the pre-freezing and drying temperature ranges, control deviation analysis can be performed on the freezing and drying equipment to generate pre-freezing and drying control parameters. To shorten the freeze-drying time, the vacuum control parameters are optimized. Vacuum control parameters significantly influence freezing and drying speeds, as well as product quality. Through experimental and simulation analysis, the optimal combination of vacuum control parameters can be found. Finally, based on the pre-freezing, drying, and optimal vacuum control parameter combinations, processing control of the target hydrous material is performed to produce the target freeze-dried food. This method overcomes the prior art problem of low production efficiency due to the influence of control parameters, achieving the technical effect of automatically adjusting parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 A schematic flow chart of a processing control method for freeze-dried pet food provided in an embodiment of the present application;

[0023] Figure 2 This is a schematic diagram of the structure of a processing control system for pet freeze-dried food provided in an embodiment of the present application.

[0024] Description of the accompanying drawings: data module 11, pre-freezing temperature analysis module 12, drying temperature analysis module 13, parameter module 14, optimization module 15, control module 16. DETAILED DESCRIPTION

[0025] The embodiments of the present application solve the technical problem of inaccurate correction effect in complex scenarios in the prior art by providing a processing control method for pet freeze-dried food.

[0026] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0027] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0028] Example 1

[0029] like Figure 1 As shown, the embodiment of the present application provides a processing control method for pet freeze-dried food, wherein the method includes:

[0030] Acquiring thermal property data of a target water-containing material, wherein the thermal property data includes a eutectic point and a eutectic point;

[0031] Freeze-dried pet food is processed using vacuum freeze-drying technology. With the continuous development of vacuum freeze-drying technology and increased awareness of pet health, freeze-dried pet food has gradually become popular in the market. The main feature of freeze-dried pet food is that it retains the original nutrients, taste, and flavor of the ingredients while removing harmful substances such as bacteria, thereby improving food safety. Due to its high nutritional value, ease of digestion, and portability, freeze-dried food is highly favored by pet owners. To ensure food quality, improve production efficiency, and reduce energy consumption, a processing and control method for freeze-dried pet food is provided to meet the market demand for high-quality freeze-dried pet food.

[0032] First, a temperature scan is performed on the target water-containing material to determine its eutectic point and eutectic melting point. The eutectic point is the temperature at which water in the material begins to crystallize, while the eutectic point is the temperature at which the water in the material completely melts. Obtaining these thermal property data is crucial for analyzing pre-freezing and drying temperatures.

[0033] Furthermore, the method for obtaining thermal property data of the target water-containing material includes:

[0034] Obtaining a material sample of the target water-containing material;

[0035] Connecting to a thermal analysis device to measure the thermal properties of the material sample and obtain temperature change data and thermal response data;

[0036] Property analysis is performed based on the temperature change data and thermal response data to obtain the eutectic point and eutectic point of the target water-containing material.

[0037] To obtain material samples of the target water-containing material, samplers or manual sampling methods can be used to collect material samples from different parts and different time periods. These samples should be representative and able to reflect the overall situation of the target water-containing material. After obtaining the material sample, the sample needs to be properly processed, such as crushing, grinding, etc., for subsequent thermal property measurement. Then, a thermal analysis device needs to be connected to the material sample, and a thermal analysis instrument such as DSC or TGA can be used. The thermal analysis device can program the temperature of the material sample and record temperature change data and thermal response data. After the thermal property measurement is performed, the measured data needs to be analyzed for properties. By heating and cooling the material, recording the temperature and thermal enthalpy changes of the material, the eutectic point and eutectic point of the material can be obtained based on the temperature change data and thermal response data. These data reflect the thermal properties and crystallization behavior of the material during the temperature change process, which is crucial for the subsequent freeze-drying process design.

[0038] Performing a pre-freezing temperature analysis based on the eutectic point to obtain a pre-freezing temperature range;

[0039] Perform drying temperature analysis based on the eutectic point to obtain a drying temperature range;

[0040] After obtaining thermal property data, a pre-freezing temperature analysis can be performed based on the eutectic point. Pre-freezing rapidly freezes the moisture in the material to preserve its nutritional content and flavor. The pre-freezing temperature range can be determined based on the material's eutectic point and the freeze-drying process requirements. Generally, the pre-freezing temperature range should be below the material's eutectic point to ensure complete freezing of the moisture. Next, a drying temperature analysis can be performed based on the eutectic point. Drying is the process of removing moisture from the material, achieved through vacuum sublimation drying technology. The drying temperature range can be determined based on the material's eutectic point and the freeze-drying process requirements. Generally, the drying temperature range should be above the material's eutectic point to ensure complete moisture removal. It is important to note that the pre-freezing and drying temperature ranges must be determined based on the specific material properties and freeze-drying process requirements. These temperature ranges can be obtained through experimental and empirical data, or they can be predicted and optimized through simulation analysis. By analyzing pre-freezing and drying temperatures based on the eutectic and eutectic points, more accurate and reliable freeze-drying process parameters can be obtained, thereby improving the quality and production efficiency of freeze-dried products.

[0041] Based on the pre-freezing temperature range and the drying temperature range, performing control deviation analysis on the freezing equipment and the drying and dehydration equipment to generate pre-freezing control parameters and drying control parameters;

[0042] After determining the pre-freezing temperature range and the drying temperature range, a control deviation analysis can be performed on the freezing equipment and the drying and dehydrating equipment to generate pre-freezing control parameters and drying control parameters. These control parameters include time, temperature, vacuum degree, etc., which are used to guide the operation and control of the equipment. The control deviation analysis refers to analyzing the control parameters of the freezing equipment and the drying and dehydrating equipment during the freeze-drying process to determine the differences between them and the set parameters. The purpose of the control deviation analysis is to ensure the stability and accuracy of the freeze-drying process, thereby improving the quality and production efficiency of the freeze-dried products. The pre-freezing control parameters are the parameters used to control the freezing equipment during the freeze-drying process, including pre-freezing time, pre-freezing temperature, etc. The pre-freezing time refers to the time the material spends in the pre-freezing stage, and the pre-freezing temperature refers to the temperature the material reaches during the pre-freezing stage. The drying control parameters are the parameters used to control the drying and dehydrating equipment during the freeze-drying process, including drying time, drying temperature, vacuum degree, etc. The drying time refers to the time the material spends in the drying stage, and the drying temperature refers to the temperature the material reaches during the drying stage.

[0043] Specifically, based on the pre-freezing temperature range, the control deviation of the pre-freezing equipment can be determined. The control deviation of the pre-freezing equipment includes time deviation and temperature deviation. Time deviation refers to the difference between the pre-freezing time and the set time, while temperature deviation refers to the difference between the pre-freezing temperature and the set temperature. Through control deviation analysis, reasonable pre-freezing control parameters such as pre-freezing time and pre-freezing temperature can be generated. Next, based on the drying temperature range, the control deviation of the drying and dehydration equipment can be determined. The control deviation of the drying and dehydration equipment includes time deviation and temperature deviation. Time deviation refers to the difference between the drying time and the set time, while temperature deviation refers to the difference between the drying temperature and the set temperature. Through control deviation analysis, reasonable drying control parameters such as drying time and drying temperature can be generated. Through control deviation analysis based on the pre-freezing temperature range and the drying temperature range, reasonable pre-freezing control parameters and drying control parameters can be generated, thereby improving the quality and production efficiency of freeze-dried products.

[0044] Furthermore, control deviation analysis is performed on refrigeration equipment and drying and dehydration equipment, and the methods include:

[0045] Obtain historical operation data of refrigeration equipment and drying and dehydration equipment for control;

[0046] Analyzing the historical operating data, calculating the deviation between the actual temperature and the preset temperature, and obtaining a deviation coefficient;

[0047] Based on the deviation coefficient, a temperature deviation minimization calculation is performed on the pre-freezing temperature range and the drying temperature range to obtain a pre-freezing control parameter and a drying control parameter.

[0048] Preferably, the historical operation data for controlling the freezing equipment and the drying and dehydration equipment are obtained through a recorder or a data acquisition system. These data generally include parameters such as the time, temperature, and vacuum degree of the equipment operation. Based on the historical operation data, analysis is performed, the deviation between the actual temperature and the preset temperature is calculated, and the deviation coefficient is obtained. The deviation coefficient refers to the difference between the actual temperature and the preset temperature, which can be obtained by calculating the temperature data in the historical operation data. Based on the deviation coefficient, the pre-freezing temperature range and the drying temperature range are calculated to minimize the temperature deviation, and the pre-freezing control parameters and the drying control parameters are obtained. The minimization of temperature deviation calculation refers to minimizing the temperature deviation by adjusting the temperature data in the pre-freezing temperature range and the drying temperature range. Specifically, a curve that best represents the temperature trend of the equipment operation can be obtained by fitting the temperature data in the historical operation data. Then, based on the curve, the temperature deviation at each time point in the pre-freezing temperature range and the drying temperature range can be calculated, and a weighted average or least squares fitting method can be performed on them to obtain the minimized temperature deviation. Finally, based on the results of minimizing temperature deviation, the pre-freezing control parameters and drying control parameters can be adjusted to minimize the difference between the actual temperature and the preset temperature, thereby improving the quality and production efficiency of the freeze-dried product.

[0049] According to the influence of vacuum control parameters on freezing speed, drying speed and product quality, with the goal of shortening freeze-drying time, the vacuum control parameters are optimized to obtain the optimal vacuum control parameter combination;

[0050] During the freeze-drying process, vacuum control parameters significantly impact freezing rate, drying rate, and product quality. These parameters include vacuum degree and pumping speed. To shorten the freeze-drying time, it is necessary to optimize these parameters to obtain the optimal combination.

[0051] Furthermore, the method for optimizing the vacuum control parameters includes:

[0052] Interactive vacuum pump model, obtaining the parameter control range of the vacuum control parameter, wherein the parameter control range includes the vacuum pumping speed range and the holding time range;

[0053] Establishing a parameter control interval based on the vacuuming speed range and the holding time range;

[0054] A plurality of initial vacuum control parameter combinations are randomly generated within the parameter control range, and optimization is performed to obtain the optimal vacuum control parameter combination with the goal of shortening the freeze-drying time and improving product quality.

[0055] Obtain relevant information about the interactive vacuum pump model from the technical manual or specification sheet provided by the manufacturer of the vacuum pump to understand the vacuum pumping speed range and holding time range of the model. Based on the vacuum pumping speed range and holding time range, establish a parameter control interval, including setting parameters such as minimum value, maximum value and step size. Generate multiple initial vacuum control parameter combinations by random combination within the parameter control interval. Through experiments or simulation analysis, with the goal of shortening the freeze-drying time and improving product quality, compare the freeze-drying time and product quality under different parameter combinations to find the optimal vacuum control parameter combination. Based on the results of the experiments or simulation analysis, select the optimal vacuum control parameter combination. The optimal vacuum control parameter combination is a parameter combination that can minimize the freeze-drying time while maintaining high product quality.

[0056] Furthermore, to obtain the optimal vacuum control parameter combination, the method further includes:

[0057] randomly selecting a first vacuum control parameter combination from the multiple initial vacuum control parameter combinations as a current optimal combination;

[0058] Performing a vacuuming simulation according to the first vacuum control parameter combination to obtain a first vacuuming simulation result;

[0059] Establishing an evaluation function to perform fitness evaluation on the first vacuuming simulation result to generate a first fitness;

[0060] Randomly generating a second vacuum control parameter combination different from the first vacuum control parameter combination from the parameter control interval, performing a vacuuming simulation, and performing a fitness evaluation to generate a second fitness;

[0061] determining whether the second fitness is greater than the first fitness, and if so, taking a second vacuum control parameter combination corresponding to the second fitness as a current optimal combination;

[0062] Continue iterating and optimizing until the preset number of iterations is reached to obtain the final optimal vacuum control parameter combination.

[0063] Preferably, the process for optimizing the optimal vacuum control parameter combination is as follows: randomly selecting a combination from multiple initial vacuum control parameter combinations, denoted as the first vacuum control parameter combination, and using this combination as the current optimal combination. A vacuuming simulation is performed based on the first vacuum control parameter combination to obtain a first vacuuming simulation result. The first vacuuming simulation result refers to the results of the vacuuming process obtained through simulation analysis under the given first vacuum control parameter combination, including indicators such as freezing rate, drying rate, and product quality. An evaluation function is established to perform a fitness evaluation on the first vacuuming simulation result to generate a first fitness. The first fitness represents the overall performance of the first vacuuming simulation result across all evaluation indicators and is used to evaluate the quality of the first vacuum control parameter combination. A second vacuum control parameter combination, different from the first vacuum control parameter combination, is randomly generated within the parameter control range and denoted as the second vacuum control parameter combination. A vacuuming simulation is performed on the second vacuum control parameter combination and fitness evaluation is performed to generate a second fitness. The second fitness represents the overall performance of the second vacuuming simulation result across all evaluation indicators and is used to evaluate the quality of the second vacuum control parameter combination. The first fitness is compared with the second fitness. If the second fitness is greater than the first, the second vacuum control parameter combination corresponding to the second fitness is used as the current optimal combination. This process is repeated until the preset number of iterations is reached. During each iteration, a vacuum simulation and fitness evaluation are performed based on the current optimal combination to find a more optimal combination. The final optimal vacuum control parameter combination is the optimal combination obtained in the last iteration.

[0064] Furthermore, the evaluation function is formulated as follows:

[0065]

[0066] Among them, g i is the fitness value of the i-th initial vacuum control parameter combination, w1 is the first weight, w2 is the second weight, T i is the freeze-drying time of the i-th initial vacuum control parameter combination, Q i is the product quality of the i-th initial vacuum control parameter combination.

[0067] Furthermore, to determine whether the second fitness is greater than the first fitness, the method further includes:

[0068] If it is less than or equal to, the second vacuum control parameter combination corresponding to the second fitness is used as the current optimal combination according to probability. The calculation formula of the probability is as follows:

[0069]

[0070] Among them, g1 is the first fitness, g2 is the second fitness, and k is a constant that decreases as the number of optimization iterations increases.

[0071] Preferably, a probability is added to the fitness assessment so that even a relatively low second fitness may be judged as excellent, thus avoiding falling into a local optimum. The probability formula determines the selection probability based on the fitness value. If the second fitness is better than the first, then when selecting the optimal combination, the probability of the second vacuum control parameter combination being selected increases. The extent of this probability increase depends on the difference between g2 and g1, as well as the value of k. Specifically, if g2 is greater than g1, the value of P will be greater than 1, indicating that the probability of the second vacuum control parameter combination being selected exceeds that of the first. If g2 is smaller than g1, the value of P will be less than 1, indicating that the probability of the second vacuum control parameter combination being selected is lower than that of the first. Furthermore, the value of k also affects the value of P. As the number of optimization iterations increases, the value of k decreases, which causes the value of P to gradually increase. This means that during the optimization process, as the number of iterations increases, the algorithm will gradually favor combinations with higher fitness, while the probability of combinations with lower fitness being selected will gradually decrease.

[0072] According to the combination of the pre-freezing control parameter, the drying control parameter and the optimal vacuum control parameter, the processing control of the target water-containing material is performed to produce the target freeze-dried food.

[0073] Specifically, the target water-containing material is pre-frozen. According to the pre-freezing control parameters, the material's temperature, time, cooling rate, and other parameters during the pre-freezing process are controlled to achieve the optimal pre-freezing effect. Next, according to the drying control parameters, the pre-frozen material is dried, and the vacuum level, temperature, humidity, and other parameters are controlled during the drying process to achieve the optimal drying effect. Finally, according to the requirements of the optimal vacuum control parameter combination, the dried material is finally optimized, and parameters such as the vacuum level and temperature are further adjusted to achieve the optimal vacuum control effect. Ultimately, the target freeze-dried food is produced, achieving optimal pre-freezing, drying, and vacuum control effects.

[0074] In summary, the embodiments of the present application have at least the following technical effects:

[0075] To obtain the thermal properties of the target hydrous material, including the eutectic point and eutectic melting point, these properties must first be measured and analyzed. Pre-freezing temperature analysis based on the eutectic point can determine the pre-freezing temperature range. Drying temperature analysis based on the eutectic point can determine the drying temperature range. After determining the pre-freezing and drying temperature ranges, control deviation analysis can be performed on the freezing and drying equipment to generate pre-freezing and drying control parameters. To shorten the freeze-drying time, the vacuum control parameters are optimized. Vacuum control parameters significantly influence freezing and drying speeds, as well as product quality. Through experimental and simulation analysis, the optimal combination of vacuum control parameters can be found. Finally, based on the pre-freezing, drying, and optimal vacuum control parameter combinations, processing control of the target hydrous material is performed to produce the target freeze-dried food. This method overcomes the prior art problem of low production efficiency due to the influence of control parameters, achieving the technical effect of automatically adjusting parameters.

[0076] Example 2

[0077] Based on the same inventive concept as the processing control method of a pet freeze-dried food in the above embodiment, Figure 2 As shown, the present application provides a processing control system for pet freeze-dried food. The system and method embodiments in the present application are based on the same inventive concept. The system includes:

[0078] Data module 11, pre-freezing temperature analysis module 12, drying temperature analysis module 13, parameter module 14, optimization module 15, control module 16.

[0079] A data module 11 is used to obtain thermal property data of a target water-containing material, wherein the thermal property data includes a eutectic point and a eutectic point;

[0080] a pre-freezing temperature analysis module 12, configured to perform a pre-freezing temperature analysis based on the eutectic point to obtain a pre-freezing temperature range;

[0081] A drying temperature analysis module 13 is configured to perform drying temperature analysis based on the eutectic point to obtain a drying temperature range;

[0082] a parameter module 14 configured to perform control deviation analysis on the freezing equipment and the drying and dehydration equipment based on the pre-freezing temperature range and the drying temperature range, and generate pre-freezing control parameters and drying control parameters;

[0083] An optimization module 15 is used to optimize the vacuum control parameters based on their effects on freezing speed, drying speed, and product quality, with the goal of shortening the freeze-drying time, to obtain an optimal combination of vacuum control parameters;

[0084] The control module 16 is used to control the processing of the target water-containing material according to the combination of the pre-freezing control parameter, the drying control parameter and the optimal vacuum control parameter to generate the target freeze-dried food.

[0085] Furthermore, the data module 11 is used to execute the following method:

[0086] Obtaining a material sample of the target water-containing material;

[0087] Connecting to a thermal analysis device to measure the thermal properties of the material sample and obtain temperature change data and thermal response data;

[0088] Property analysis is performed based on the temperature change data and thermal response data to obtain the eutectic point and eutectic point of the target water-containing material.

[0089] Furthermore, the parameter module 14 is used to execute the following method:

[0090] Obtain historical operation data of refrigeration equipment and drying and dehydration equipment for control;

[0091] Analyzing the historical operating data, calculating the deviation between the actual temperature and the preset temperature, and obtaining a deviation coefficient;

[0092] Based on the deviation coefficient, a temperature deviation minimization calculation is performed on the pre-freezing temperature range and the drying temperature range to obtain a pre-freezing control parameter and a drying control parameter.

[0093] Furthermore, the optimization module 15 is used to perform the following method:

[0094] Interactive vacuum pump model, obtaining the parameter control range of the vacuum control parameter, wherein the parameter control range includes the vacuum pumping speed range and the holding time range;

[0095] Establishing a parameter control interval based on the vacuuming speed range and the holding time range;

[0096] A plurality of initial vacuum control parameter combinations are randomly generated within the parameter control range, and optimization is performed to obtain the optimal vacuum control parameter combination with the goal of shortening the freeze-drying time and improving product quality.

[0097] Furthermore, the optimization module 15 is used to perform the following method:

[0098] randomly selecting a first vacuum control parameter combination from the multiple initial vacuum control parameter combinations as a current optimal combination;

[0099] Performing a vacuuming simulation according to the first vacuum control parameter combination to obtain a first vacuuming simulation result;

[0100] Establishing an evaluation function to perform fitness evaluation on the first vacuuming simulation result to generate a first fitness;

[0101] Randomly generating a second vacuum control parameter combination different from the first vacuum control parameter combination from the parameter control interval, performing a vacuuming simulation, and performing a fitness evaluation to generate a second fitness;

[0102] determining whether the second fitness is greater than the first fitness, and if so, taking a second vacuum control parameter combination corresponding to the second fitness as a current optimal combination;

[0103] Continue iterating and optimizing until the preset number of iterations is reached to obtain the final optimal vacuum control parameter combination.

[0104] Furthermore, the optimization module 15 is used to perform the following method:

[0105]

[0106] Among them, g i is the fitness value of the i-th initial vacuum control parameter combination, w1 is the first weight, w2 is the second weight, T i is the freeze-drying time of the i-th initial vacuum control parameter combination, Q i is the product quality of the i-th initial vacuum control parameter combination.

[0107] Furthermore, the optimization module 15 is used to perform the following method:

[0108] If it is less than or equal to, the second vacuum control parameter combination corresponding to the second fitness is used as the current optimal combination according to probability. The calculation formula of the probability is as follows:

[0109]

[0110] Among them, g1 is the first fitness, g2 is the second fitness, and k is a constant that decreases as the number of optimization iterations increases.

[0111] It should be noted that the above-mentioned order of the embodiments of the present application is for descriptive purposes only and does not represent the superiority or inferiority of the embodiments. The above description is of specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0112] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0113] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. A processing control method for pet freeze-dried food, characterized in that: include: Acquiring thermal property data of a target water-containing material, wherein the thermal property data includes a eutectic point and a eutectic point; Performing a pre-freezing temperature analysis based on the eutectic point to obtain a pre-freezing temperature range; Perform drying temperature analysis based on the eutectic point to obtain a drying temperature range; Based on the pre-freezing temperature range and the drying temperature range, performing control deviation analysis on the freezing equipment and the drying and dehydration equipment to generate pre-freezing control parameters and drying control parameters; According to the influence of vacuum control parameters on freezing speed, drying speed and product quality, with the goal of shortening freeze-drying time, the vacuum control parameters are optimized to obtain the optimal vacuum control parameter combination; Performing processing control on the target water-containing material according to the combination of the pre-freezing control parameter, the drying control parameter, and the optimal vacuum control parameter to produce the target freeze-dried food; The optimization of the vacuum control parameters includes: Interactive vacuum pump model, obtaining the parameter control range of the vacuum control parameter, wherein the parameter control range includes the vacuum pumping speed range and the holding time range; Establishing a parameter control interval based on the vacuuming speed range and the holding time range; Randomly generate multiple initial vacuum control parameter combinations within the parameter control range, and optimize them with the goal of shortening the freeze-drying time and improving product quality to obtain the optimal vacuum control parameter combination; Among them, include: randomly selecting a first vacuum control parameter combination from the multiple initial vacuum control parameter combinations as a current optimal combination; Performing a vacuuming simulation according to the first vacuum control parameter combination to obtain a first vacuuming simulation result; Establishing an evaluation function to perform fitness evaluation on the first vacuuming simulation result to generate a first fitness; Randomly generating a second vacuum control parameter combination different from the first vacuum control parameter combination from the parameter control interval, performing a vacuuming simulation, and performing a fitness evaluation to generate a second fitness; determining whether the second fitness is greater than the first fitness, and if so, taking a second vacuum control parameter combination corresponding to the second fitness as a current optimal combination; Continue iterating and optimizing until the preset number of iterations is reached to obtain the final optimal vacuum control parameter combination; The evaluation function formula is as follows: ; in, is the fitness value of the i-th initial vacuum control parameter combination, is the first weight, is the second weight, is the freeze-drying time of the i-th initial vacuum control parameter combination, is the product quality of the i-th initial vacuum control parameter combination.

2. The method according to claim 1, wherein Obtain thermal property data of target water-containing materials, including: Obtaining a material sample of the target water-containing material; Connecting to a thermal analysis device to measure the thermal properties of the material sample and obtain temperature change data and thermal response data; Property analysis is performed based on the temperature change data and thermal response data to obtain the eutectic point and eutectic point of the target water-containing material.

3. The method according to claim 1, wherein Conduct control deviation analysis on refrigeration equipment and drying and dehydration equipment, including: Obtain historical operation data of refrigeration equipment and drying and dehydration equipment for control; Analyzing the historical operating data, calculating the deviation between the actual temperature and the preset temperature, and obtaining a deviation coefficient; Based on the deviation coefficient, a temperature deviation minimization calculation is performed on the pre-freezing temperature range and the drying temperature range to obtain a pre-freezing control parameter and a drying control parameter.

4. The method according to claim 1, wherein Determining whether the second fitness is greater than the first fitness further includes: If it is less than or equal to, the second vacuum control parameter combination corresponding to the second fitness is used as the current optimal combination according to probability. The calculation formula of the probability is as follows: ； in, is the first fitness, is the second fitness, and k is a constant that decreases as the number of optimization iterations increases.

5. A processing control system for pet freeze-dried food, characterized in that: The system comprises: A data module, the data module is used to obtain thermal property data of the target water-containing material, wherein the thermal property data includes a eutectic point and a eutectic point; a pre-freezing temperature analysis module, configured to perform pre-freezing temperature analysis based on the eutectic point to obtain a pre-freezing temperature range; a drying temperature analysis module, configured to perform drying temperature analysis based on the eutectic point to obtain a drying temperature range; a parameter module, the parameter module being used to perform control deviation analysis on the freezing equipment and the drying and dehydration equipment based on the pre-freezing temperature range and the drying temperature range, and generate pre-freezing control parameters and drying control parameters; An optimization module is used to optimize the vacuum control parameters based on their effects on freezing speed, drying speed, and product quality, with the goal of shortening the freeze-drying time, to obtain an optimal combination of vacuum control parameters; a control module, configured to perform processing control of a target water-containing material to produce a target freeze-dried food according to a combination of the pre-freezing control parameter, the drying control parameter, and the optimal vacuum control parameter; The optimization of the vacuum control parameters includes: Interactive vacuum pump model, obtaining the parameter control range of the vacuum control parameter, wherein the parameter control range includes the vacuum pumping speed range and the holding time range; Establishing a parameter control interval based on the vacuuming speed range and the holding time range; Randomly generate multiple initial vacuum control parameter combinations within the parameter control range, and optimize them with the goal of shortening the freeze-drying time and improving product quality to obtain the optimal vacuum control parameter combination; Among them, include: randomly selecting a first vacuum control parameter combination from the multiple initial vacuum control parameter combinations as a current optimal combination; Performing a vacuuming simulation according to the first vacuum control parameter combination to obtain a first vacuuming simulation result; Establishing an evaluation function to perform fitness evaluation on the first vacuuming simulation result to generate a first fitness; Randomly generating a second vacuum control parameter combination different from the first vacuum control parameter combination from the parameter control interval, performing a vacuuming simulation, and performing a fitness evaluation to generate a second fitness; determining whether the second fitness is greater than the first fitness, and if so, taking a second vacuum control parameter combination corresponding to the second fitness as a current optimal combination; Continue iterating and optimizing until the preset number of iterations is reached to obtain the final optimal vacuum control parameter combination; The evaluation function formula is as follows: ; in, is the fitness value of the i-th initial vacuum control parameter combination, is the first weight, is the second weight, is the freeze-drying time of the i-th initial vacuum control parameter combination, is the product quality of the i-th initial vacuum control parameter combination.

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