Unfreezing time prediction method, unfreezing machine and storage medium

Abstract

The invention relates to an unfreezing time prediction method, an unfreezing machine and a storage medium, and the method comprises the steps: obtaining the state attributes of an unfreezing medium and a frozen product, the state attributes at least comprise the temperature of the unfreezing medium, the quality of the unfreezing medium, the type of the frozen product, and the number of the frozen products corresponding to the type of the frozen product, the type of the frozen product is associated with the thawing coefficient of the frozen product and the heat absorption amount required for thawing the single product; according to the state attribute, the accumulated heat absorption capacity of the frozen product about time is obtained; the time when the accumulated heat absorption capacity reaches the target heat absorption capacity needed by unfreezing is estimated, the predicted time needed by unfreezing is obtained, and the target heat absorption capacity is determined according to the heat absorption capacity needed by unfreezing of a single product and the number of the frozen products; by adopting the method provided by the invention, the thawing time of the frozen product can be predicted.

Description

Technical Field

[0001] The present application relates to the technical field of thawing machines, and in particular to a thawing time prediction method, a thawing machine and a storage medium. Background Art

[0002] In milk tea stores, various frozen products such as frozen juice need to be thawed, but the staff cannot predict the thawing completion time. If the thawing time is too short, the food may not be completely thawed, and if the thawing time is too long, the flavor of the juice may be reduced. Therefore, manual attention and inspection are required during thawing, resulting in unnecessary waiting, low efficiency and even quality control. Summary of the invention

[0003] Based on this, a thawing time prediction method, a thawing machine and a storage medium are provided to improve the problem of difficulty in predicting the thawing time in the prior art.

[0004] In one aspect, a thawing time prediction method is provided, which is applied to a thawing system including frozen products and a thawing medium, and the method comprises: Acquire the state attributes of the thawing medium and the frozen product, wherein the state attributes at least include the temperature of the thawing medium, the quality of the thawing medium, the type of frozen product, and the number of frozen products corresponding to the type of frozen product, wherein the type of frozen product is associated with the thawing coefficient of the frozen product and the amount of heat required for thawing the single product; According to the state attribute, obtaining the cumulative heat absorption of the frozen product over time; The time when the cumulative heat absorption reaches the target heat absorption required for thawing is estimated to obtain the predicted time required for thawing, wherein the target heat absorption is determined based on the heat absorption required for thawing of the single product and the quantity of the frozen product.

[0005] In one embodiment, obtaining the cumulative heat absorption of the frozen product over time according to the state attribute includes: According to the state attributes, a predicted temperature sequence of the thawing medium and the frozen product is obtained; According to the thawing coefficient and the amount of frozen products, determining the heat absorption rate at each temperature difference corresponding to the temperature sequence of the thawing medium and the frozen products; The cumulative heat absorption of the frozen product over time is obtained according to the temperature sequence and the heat absorption rate.

[0006] In one embodiment, obtaining the predicted temperature sequence of the thawing medium and the frozen product comprises: According to the initial temperature of the thawing medium and the frozen product in the current evaluation period, the temperature difference in the current evaluation period is obtained; Determining the heat absorption rate of the current evaluation period according to the thawing coefficient, the amount of frozen products and the temperature difference of the current evaluation period; determining a heat absorption amount of the current evaluation period based on the heat absorption rate of the current evaluation period; Determining the predicted final temperature of the thawing medium and the frozen product according to the heat absorption during the current evaluation period; Using the end-of-period temperature as the initial temperature of the next evaluation period; The temperature sequence is obtained according to a combination of initial temperatures of a plurality of evaluation periods.

[0007] In one embodiment, after obtaining the predicted time required for thawing, the method further includes: Acquiring a real-time temperature sequence of the thawing medium; According to the real-time temperature sequence, a corresponding actual heat absorption is obtained; According to the actual amount of heat absorption, correct the heat absorption rate; Correcting the predicted temperature sequence of the thawing medium and the frozen product according to the corrected heat absorption rate; According to the revised predicted temperature sequence and the revised heat absorption rate, the cumulative heat absorption of the frozen product over time is obtained to obtain a revised predicted duration.

[0008] In one embodiment, when the number of types of frozen products with different heat absorption rates is greater than or equal to 2, obtaining the predicted temperature sequence of the thawing medium and the frozen product includes: According to the initial temperature of the thawing medium and the initial temperature of each type of frozen product in the current evaluation period, the temperature difference corresponding to each type of frozen product in the current evaluation period is obtained; Determining the heat absorption rate corresponding to each type of frozen product in the current evaluation period based on the temperature difference corresponding to each type of frozen product and the thawing coefficient corresponding to the type of frozen product; Based on the heat absorption rate corresponding to each type of frozen product, determine the amount of heat absorption of each type of frozen product in the current evaluation period to determine the end-of-period temperature of each type of frozen product; Determine the final temperature of the thawing medium according to the sum of the heat absorbed by each type of frozen product during the current evaluation period; The final temperature of the thawing medium and the final temperature of each type of frozen product are used as the initial temperature of the next evaluation period.

[0009] In one embodiment, obtaining the predicted time required for thawing includes: Accumulate the heat absorption corresponding to each type of frozen product separately to obtain the accumulated heat absorption corresponding to each type of frozen product; The time when the cumulative heat absorption reaches the target heat absorption corresponding to the frozen product type is determined as the predicted time corresponding to the type.

[0010] In one embodiment, the obtaining of the state attributes of the thawing medium and the frozen product further comprises: Obtain the movement frequency and movement amplitude of frozen products; According to the movement frequency and movement amplitude, the thawing coefficient corresponding to the frozen product type is determined from a preset association relationship.

[0011] In one embodiment, the obtaining of the state attributes of the thawing medium and the frozen product further comprises: The increase or decrease of the external heat energy of the thawing medium is obtained to correct the predicted duration according to the increase or decrease of the external heat energy.

[0012] In another aspect, a thawing machine is provided, the thawing machine comprising: The body is configured with a receiving chamber, wherein the receiving chamber is used to receive a thawing medium and at least one type of frozen product; A controller, used to obtain a predicted time required for thawing the frozen product; a prompting unit, connected to the controller, for prompting the predicted time corresponding to the frozen product; Wherein, when the controller is running, the state attributes of the thawing medium and the frozen product are obtained, and the state attributes include at least the temperature of the thawing medium, the quality of the thawing medium, the type of frozen product and the number of frozen products corresponding to the frozen product type, wherein the frozen product type is associated with the thawing coefficient of the frozen product and the amount of heat absorption required for thawing of a single product; according to the state attributes, the cumulative heat absorption of the frozen product with respect to time is obtained; the time when the cumulative heat absorption reaches the target heat absorption required for thawing is estimated, and the predicted time required for thawing is obtained, wherein the target heat absorption is determined based on the heat absorption required for thawing of a single product and the number of frozen products.

[0013] A computer-readable storage medium is also provided, on which a computer program is stored, and when the computer program is executed by a processor, the method described above is implemented.

[0014] The above-mentioned thawing time prediction method, thawing machine and storage medium realize thawing by heat exchange between frozen products and medium, and obtain the state attributes of the thawing medium and the frozen products, and then obtain the cumulative heat absorption of the frozen products with respect to time according to the state attributes, that is, predict the relationship between the cumulative heat absorption of the frozen products and time, so as to estimate the time when the cumulative heat absorption reaches the target heat absorption required for thawing, and obtain the predicted time required for thawing; by predicting the time required for thawing, it helps users to arrange the thawing plan reasonably. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A diagram showing an application environment of a thawing time prediction method in an embodiment; Figure 2 A schematic diagram of a process of predicting a thawing time in one embodiment; Figure 3 Schematic diagram of the sub-steps of step S2 in one embodiment; Figure 4 is a structural block diagram of a thawing time prediction device in one embodiment; Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0017] Existing milk tea stores and juice stores have a demand for thawing frozen products. For example, frozen orange juice, coconut water and other juices need to be thawed. The current thawing method is natural thawing, but the thawing time is long. It can also be thawed by a thawing machine.

[0018] However, in the existing thawing methods, the time required for thawing is difficult to predict and requires human judgment, which wastes manpower costs and is extremely inconvenient.

[0019] The present application provides a thawing time prediction method, which predicts the cumulative heat absorption of frozen products over time and predicts the time it takes for the cumulative heat absorption of the frozen products to reach the target heat absorption required for thawing. This method can provide staff with a prediction of the time required for thawing at the beginning of thawing, help staff to reasonably arrange thawing work, and reduce waste of manpower costs.

[0020] In one embodiment, the thawing time prediction method is applied to Figure 1 The thawing system shown, in particular, the frozen product is immersed in a thawing medium, and the heat conduction is concentrated between the frozen product and the thawing medium, thereby reducing the prediction error. The type of the thawing medium is, for example, common water. The method is as follows Figure 2 As shown, the following steps are included: Step S1, obtaining the state attributes of the thawing medium and the frozen product.

[0021] State attributes refer to the performance and characteristics of the thawing medium and frozen products in various dimensions in the thawing scenario. For example, the state attributes include at least the temperature of the thawing medium, the quality of the thawing medium, the type of frozen product, and the number of frozen products corresponding to the type of frozen product.

[0022] The temperature of the thawing medium, for example, the actual temperature of the thawing medium at the start of thawing, can be detected by a temperature sensing unit disposed inside the thawing machine.

[0023] The mass of the thawing medium can be calculated based on the volume and density of the thawing medium, and for a thawing machine containing chamber with a fixed capacity, the mass of the thawing medium is relatively fixed.

[0024] In milk tea-type stores, frozen products are packaged and frozen according to fixed specifications. Frozen products with the same packaging specifications, packaging forms, same contents, and freezing conditions can be regarded as one type of frozen products, otherwise they are regarded as different types. For example, bagged orange juice and apple juice of the same capacity can be regarded as different types; bagged orange juice and bottled orange juice of the same capacity can be regarded as different types.

[0025] The quantity of frozen products, such as the number of bags of bagged orange juice or the number of bottles of bottled orange juice.

[0026] In the thawing machine, the type of frozen product is associated with the thawing coefficient of the frozen product, the amount of heat absorbed by the frozen product required for thawing the single product, the initial temperature of the frozen product, the individual mass of the frozen product, and other information related to the frozen product.

[0027] The thawing coefficient represents the amount of heat absorbed by a unit amount of frozen food under a unit temperature difference and per unit time (unit: J / ℃×s), which affects the heat absorption rate of the frozen food. In one possible implementation, by measuring the frozen food, the heat absorption rate under a known motion state is directly proportional to the temperature difference. When conducting a calibration test, the frozen food is moved at a certain motion frequency and amplitude to allow it to fully contact and exchange heat with the thawing medium, and the thawing coefficient of the frozen food is measured. Different types of frozen food may have different thawing coefficients. It is understandable that in the calibration test, different types of frozen food are tested separately to obtain the thawing coefficients, and stored in the thawing machine. During actual thawing, the type of frozen food is input to call the corresponding thawing coefficient.

[0028] It is understandable that for frozen products such as juice and drinks, the temperature of the frozen products before thawing is relatively fixed. Therefore, the main factor affecting the thawing coefficient is the temperature of the thawing medium. During calibration, measurement and actual application, the frozen product temperature can be set to a fixed value such as 0°C.

[0029] In another possible implementation, the thawing coefficient of frozen products may be different under different movement states. Through calibration tests, the correlation between the thawing coefficient and the movement frequency and movement amplitude is established for each type of frozen product. During the actual thawing process, the frozen products are still moved at a certain frequency and amplitude to obtain the actual movement frequency and movement amplitude of the frozen products. The thawing coefficient is determined from a preset correlation based on the movement frequency and movement amplitude.

[0030] The amount of heat absorbed by a single product for thawing refers to the amount of heat required for a single frozen product to be thawed from the initial frozen state to completion, which can be obtained through calibration.

[0031] Step S2, obtaining the cumulative heat absorption of the frozen product over time according to the state attributes.

[0032] In one embodiment, in a thawing system consisting of frozen products and thawing medium, the temperature change and instantaneous heat absorption of the thawing medium can be used to screen out effective factors affecting heat absorption (such as the aforementioned state attributes) through correlation analysis, and mathematical statistics methods are used to predict that under a specified initial temperature and the same frozen product conditions, the temperature of the thawing medium will change according to a fixed rule. Through multiple calibration tests, the heat release law of the thawing medium and the heat absorption law of the frozen product under different state attributes are statistically analyzed, and a functional relationship between the cumulative heat absorption of the frozen product and time is established. The functional relationship is stored in the thawing machine, and in actual use, it is called based on the actual state attributes.

[0033] It can be understood that the above-mentioned cumulative heat absorption is the total heat absorption of several items of the same type.

[0034] S3, estimating the time when the accumulated heat absorption reaches the target heat absorption required for thawing, and obtaining the predicted time required for thawing.

[0035] The target heat absorption required for thawing, that is, the total heat required for thawing of the entire type or several frozen products, can be obtained by multiplying the heat absorption required for thawing a single product by the number of frozen products.

[0036] Based on the functional relationship between the cumulative heat absorption and time, the time from the cumulative heat absorption being 0 to the target heat absorption is calculated, and the time can be output as a result to the prompt unit to prompt the user. At the same time, the thawing machine starts timing synchronously. When the timing reaches the predicted time, the reminder measure is started.

[0037] The target heat absorption required for thawing can be obtained through calibration tests on frozen products of different types and specifications.

[0038] Through steps S1 to S3, the thawing machine can provide the user with predicted duration information, making it convenient for the user to plan the thawing work.

[0039] The above step S2 can also be implemented through the following sub-steps: Figure 3 As shown: Sub-step 21, obtaining a predicted temperature sequence of the thawing medium and the frozen product according to the state attribute.

[0040] In this sub-step 21, for some types of frozen products, the temperature sequence of the frozen products can be regarded as a pre-set fixed value sequence; in some cases, if the temperature of the frozen products changes greatly during thawing, which directly affects the heat absorption rate of the frozen products, the temperature difference can be calculated by predicting the temperature of the frozen products, and then the heat absorption rate can be calculated.

[0041] It can be understood that in the thawing system composed of frozen products and thawing medium, the temperature changes of frozen products and thawing medium can be screened out through correlation analysis to identify effective factors affecting water temperature changes (such as the aforementioned state attributes), and mathematical statistics methods can be used to predict that under the specified initial temperature and the same frozen product conditions, the temperature of the thawing medium and the temperature of the frozen product will change according to a fixed rule. Through multiple calibration tests, the temperature change rules of the thawing medium and the temperature change rules of the frozen product under different state attributes are statistically calculated, and the relationship between the temperature change of the thawing medium and the frozen product and time is established, and stored in the form of a sequence for call during actual use.

[0042] Sub-step 22, determining the heat absorption rate at each temperature difference corresponding to the temperature sequence of the thawing medium and the frozen product according to the thawing coefficient and the amount of the frozen product.

[0043] The heat absorption rate of frozen products characterizes the heat absorption speed (unit: J / s) of frozen products under specified conditions (specified thawing medium quality, frozen product quantity, environmental conditions, motion conditions, etc.), and the heat absorption rate is related to the temperature difference between the thawing medium and the frozen products and the number of frozen products. Generally, the higher the temperature difference and the more frozen products there are, the greater the heat absorption rate of the frozen products. In actual implementation, the heat absorption rate of frozen products under different temperature differences and frozen product quantities can be obtained based on calibration experiments. The calibration data can be pre-stored in the storage device of the thawing machine, and then searched and called based on the real-time temperature difference or the predicted temperature difference. In this embodiment, the heat absorption rate can be obtained by multiplying the thawing coefficient, the number of frozen products, and the temperature difference.

[0044] In the temperature sequence, the temperature difference at that instant is obtained by subtracting the temperature of the thawing medium from the temperature of the frozen product at the same time, and then the heat absorption rate at that instant is obtained.

[0045] Sub-step 23, obtaining the cumulative heat absorption of the frozen product over time according to the temperature sequence and the heat absorption rate.

[0046] According to the temperature series, the functional relationship of the temperature difference with respect to time is obtained, and then the relationship of the heat absorption rate with respect to time is obtained. The heat absorption rate is integrated on the time scale to obtain the cumulative heat absorption over a period of time.

[0047] For sub-step 21, in another embodiment, a prediction model is established by kinetic and thermal equations, and a prediction is made after numerical solution is performed according to given initial conditions and boundary conditions. For example, the evaluation period is divided into a certain time length (e.g., 5 s), and the temperature of the thawing medium and the temperature of the frozen product in an evaluation period are regarded as constant. The temperature of the thawing medium and the temperature of the frozen product when the next evaluation period arrives are calculated based on the amount of heat absorbed. The prediction process is exemplified as follows: Step 211, obtaining the temperature difference of the current evaluation period according to the thawing medium and the initial temperature of the frozen product in the current evaluation period. Generally, the initial temperature of the frozen product can be preset to 0°C; Step 212, determining the heat absorption rate of the current evaluation period according to the thawing coefficient, the amount of frozen products and the temperature difference of the current evaluation period; Step 213, determining the amount of heat absorbed during the current evaluation period based on the heat absorption rate during the current evaluation period; Step 214, determining the predicted end-of-period temperatures of the thawing medium and the frozen product according to the amount of heat absorbed during the current evaluation period; Step 215, using the end-of-period temperature as the initial temperature of the next evaluation period.

[0048] For steps 211 to 215, the duration of the evaluation period is exemplarily Take this as an example, the description is as follows: At the initial stage of thawing, the initial temperature of the thawing medium was obtained. , initial temperature of frozen products , and then get the temperature difference of the current evaluation period .

[0049] According to the temperature difference of the current evaluation period , thawing coefficient, the amount of frozen food, and calculate the corresponding heat absorption rate under this temperature difference (Unit: J / s).

[0050] The thawing medium and frozen products in the current evaluation period are considered to be at a constant temperature and the heat absorption within 5 seconds is calculated. .

[0051] Frozen products are absorbing After the heat, the temperature rises to , and the increase range can be found based on the calibration data, or in other words, it can be calculated in real time according to the specific heat capacity and mass of the frozen product. The specific calculation method will not be described in detail here.

[0052] In a thawing system without considering external heating and external heat loss, the heat loss of the thawing medium is equal to the heat absorbed by the frozen product, and the temperature of the thawing medium drops to , and the decrease range can be found based on the calibration data, or in other words, it can be calculated in real time according to the specific heat capacity of the thawing medium and the mass of the thawing medium. The specific calculation method will not be described in detail here.

[0053] Then, , As the initial temperature of the next evaluation period, repeat the above process and calculate the temperature difference of the next evaluation period again. , the corresponding heat absorption rate , Heat absorption within 5s and the temperature at the end of the next evaluation period , .

[0054] Through steps 211 to 215, the initial temperatures of n evaluation periods are obtained, and the temperature sequence of the thawing medium can be obtained by combining them. , and the temperature series of frozen products .

[0055] In the above steps 211 to 215, the heat absorption corresponding to each evaluation period is also obtained synchronously. , ...accumulate the calculation to obtain the cumulative heat absorption .

[0056] When the cumulative heat Greater than or equal to the target heat absorption required for thawing , the thawing is considered to be completed, and the duration of the evaluation period is accumulated , get the predicted time required for thawing .

[0057] In the above process, the temperature of the thawing medium and the frozen product is continuously predicted, the temperature difference between the two is continuously recorded, and the heat absorption of the frozen product over time is calculated, so as to obtain the cumulative heat absorption of the frozen product after a period of time, and further predict the time when the cumulative heat absorption reaches the target heat absorption, which is used as the predicted time required for thawing. The method provided in the present application can quickly obtain the predicted time at the beginning of thawing based on the temperature of the thawing medium, the quality of the thawing medium, the number of frozen products, and the thawing coefficient corresponding to the type of frozen product, so as to provide prediction assistance for the user of the thawing machine and help him arrange the thawing time reasonably.

[0058] In the actual implementation process, the predicted time can be corrected in combination with the increase or decrease in external thermal energy of the thawing medium. For example, based on the preliminary prediction, the frozen product can be thawed after time t. Based on the heating power and heat loss rate, the increase or decrease in external thermal energy after time t is calculated. If the increase or decrease in external thermal energy is positive, indicating that heat is obtained from the outside, the predicted time can be appropriately reduced. Otherwise, the predicted time can be increased. The specific value of increase or decrease is determined based on the calibration result.

[0059] In another possible implementation, the temperature sequence of the thawing medium and the frozen product is corrected according to the increase or decrease of external heat energy. For example, a heating step is added during the thawing process, and the heating unit is heated according to the power P. The increase of external heat energy provided by the heating unit during the evaluation period is calculated. At the same time, the heat energy lost to the outside of the thawing medium during the evaluation period can be obtained based on the calibration test, which is used as the decrease of external heat energy. When calculating the temperature of the thawing medium at the end of the evaluation period, the actual decrease of heat energy of the thawing medium is calculated in combination with the increase of external heat energy, the decrease of external heat energy, and the heat absorption of the frozen product, so as to correct the end-of-period temperature of the thawing medium; in the next evaluation period, the temperature difference is obtained based on the corrected end-of-period temperature, and the corrected heat absorption and the corrected temperature sequence of the frozen product are calculated. Finally, the correction of the predicted duration is achieved.

[0060] It is understandable that during the thawing process of frozen liquid products such as juice, there is a process of transformation from solid to liquid, and the temperature is maintained near the phase change temperature during the phase change process. The degree of thawing of the frozen product cannot be judged based on temperature alone. In this application, judging whether the frozen product is thawed based on the cumulative heat absorption can provide more accurate prediction results.

[0061] It is understandable that in some cases, during the thawing process of frozen products, the temperature of the frozen products remains stable in the early stage and changes in real time in the later stage. In this case, a correction threshold is set. When the cumulative heat absorption is less than the correction threshold, the temperature of the frozen product can be regarded as the phase change temperature. Typically, in the early stage of thawing, the temperature of the frozen product can be regarded as 0, and the corresponding value in the temperature sequence is configured as 0. When the cumulative heat absorption reaches the correction threshold, the temperature of the frozen product changes according to the heat absorption. The correction threshold is calibrated according to the specific situation and associated with the frozen product type.

[0062] In the actual implementation process, the thawing machine periodically detects the real-time temperature of the thawing medium and corrects the predicted time according to the real-time temperature. Exemplarily, the process includes: Step S4, obtaining the real-time temperature sequence of the thawing medium. For example, after thawing begins, the thawing machine starts synchronous timing. When a preset time (for example, 5 seconds) is reached, the current real-time temperature is collected and recorded through a temperature detection unit (for example, a temperature sensor), and stored in the form of a sequence.

[0063] Step S5, obtaining the corresponding actual heat absorption amount according to the real-time temperature sequence of the thawing medium.

[0064] Based on the initial temperature and the real-time temperature after 5 seconds, the temperature difference of the thawing medium in 5 seconds is obtained, and the heat reduction in 5 seconds is calculated according to the temperature difference, which is the actual heat absorption in 5 seconds; Step S6, correcting the heat absorption rate according to the actual heat absorption amount.

[0065] According to the ratio of the actual heat absorption and the preset time of 5s, a new heat absorption rate is obtained, and the new heat absorption rate is recorded in the thawing machine.

[0066] Step S7, correcting the predicted temperature sequence of the thawing medium and the frozen product according to the corrected heat absorption rate.

[0067] Using the corrected heat absorption rate, the heat absorption rate of the subsequent evaluation period is corrected proportionally according to the aforementioned steps 211 to 215, thereby correcting the temperature sequence. Alternatively, the heat absorption rate is corrected according to the actual heat absorption amount, and the thawing coefficient can be further corrected, and then the calculation is performed according to the corrected thawing coefficient.

[0068] Step S8, based on the corrected temperature sequence and the corrected heat absorption rate, continuously calculate the corrected heat absorption corresponding to the next evaluation period, and accumulate the cumulative heat absorption of the frozen product over time. When the cumulative heat absorption reaches the target heat absorption, add the evaluation period duration to obtain the corrected predicted duration.

[0069] The thawing machine periodically collects the real-time temperature of the thawing medium and continuously updates the predicted duration. Even if there are deviations in the number of thawed products and the initial conditions of the medium, the thawing prediction calculation can still complete the prediction correction of the completion time of the frozen product thawing.

[0070] In actual use, multiple types of frozen products may be thawed at the same time in the same thawing machine, for example, peach juice, orange juice, etc., and each type of frozen product has a different heat absorption rate. It is understandable that if various types of fruit juice drinks are thawed in different packaging forms, they still need to be regarded as two different types of frozen products because of their different heat absorption rates.

[0071] The following provides an implementation method for predicting the thawing time when the number of types of frozen products with different heat absorption rates is greater than or equal to 2: Step 310, based on the initial temperature of the thawing medium in the current evaluation period , the initial temperature of each type of frozen product (type A, type B, etc.) , ..., obtain the temperature difference corresponding to each type of frozen product in the current evaluation period , …….

[0072] Step 320: determining the heat absorption rate corresponding to each type of frozen product in the current evaluation period based on the temperature difference corresponding to each type of frozen product , ,…….

[0073] Step 330, based on the heat absorption rate corresponding to each type of frozen product , , ..., determine the heat absorption of each type of frozen food in the current evaluation period , ..., based on the heat absorption, the final temperature of each type of frozen food can be determined , ,…….

[0074] Step 340: sum the heat absorbed by each type of frozen food during the current evaluation period. , the total heat reduction of the thawing medium is obtained, thereby determining the final temperature of the thawing medium ; Step 350, the final temperature of the thawing medium , the final temperature of each type of frozen food , ,…, as the initial temperature of the next evaluation period.

[0075] Repeat steps 310 to 350 to obtain the temperature sequence of the thawing medium. 、Temperature series of type A frozen products 、Temperature series of type B frozen products .

[0076] In each evaluation period, the heat absorption of type A frozen products is also calculated. , , ..., the heat absorption of type B frozen products , ,…….

[0077] Cumulative heat absorption of type A frozen products , if after n1 evaluation periods, Greater than or equal to the target heat absorption of type A frozen products , it is assumed that type A frozen products are thawed, therefore, the duration corresponding to n1 evaluation periods is This is the predicted duration of frozen products of type A.

[0078] Cumulative heat absorption of type B frozen products , if after n2 evaluation periods, Greater than or equal to the target heat absorption of type B frozen products , it is considered that type B frozen products are thawed, therefore, the length of time corresponding to n2 evaluation periods . This is the predicted duration of frozen products of type B.

[0079] In the above process, a prediction of the thawing time of different types of frozen products in the same thawing machine is provided.

[0080] It should be understood that although Figure 2 , Figure 3The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2 , Figure 3 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0081] In one embodiment, Figure 4 As shown, a thawing time prediction device is provided, including: an acquisition module 410 and a prediction module 420, wherein: The acquisition module 410 is used to acquire the state attributes of the thawing medium and the frozen product, wherein the state attributes at least include the temperature of the thawing medium, the quality of the thawing medium, the type of the frozen product, and the number of frozen products corresponding to the type of frozen product, wherein the type of frozen product is associated with the thawing coefficient of the frozen product and the amount of heat required for thawing the single product; The prediction module 420 is used to obtain the cumulative heat absorption of the frozen product over time according to the state attributes; estimate the time when the cumulative heat absorption reaches the target heat absorption required for thawing, and obtain the predicted time required for thawing, wherein the target heat absorption is determined based on the heat absorption required for thawing of a single product and the quantity of the frozen product.

[0082] In one embodiment, a thawing machine is provided, the thawing machine comprising: The body is configured with a receiving chamber, wherein the receiving chamber is used to receive a thawing medium and at least one type of frozen product; A controller, used to obtain a predicted time required for thawing the frozen product; A prompting unit, connected to the controller, for prompting the predicted duration corresponding to the frozen product, the prompting unit can display a face, can display a numerical value, or can prompt in the form of voice; Wherein, when the controller is running, the state attributes of the thawing medium and the frozen product are obtained, and the state attributes include at least the temperature of the thawing medium, the quality of the thawing medium, the type of frozen product and the number of frozen products corresponding to the frozen product type, wherein the frozen product type is associated with the thawing coefficient of the frozen product and the amount of heat absorption required for thawing of a single product; according to the state attributes, the cumulative heat absorption of the frozen product with respect to time is obtained; the time when the cumulative heat absorption reaches the target heat absorption required for thawing is estimated, and the predicted time required for thawing is obtained, wherein the target heat absorption is determined based on the heat absorption required for thawing of a single product and the number of frozen products.

[0083] When the controller is running, it also obtains the predicted temperature sequence of the thawing medium and the frozen product based on the state attributes; determines the heat absorption rate at each temperature difference corresponding to the temperature sequence of the thawing medium and the frozen product based on the thawing coefficient and the number of frozen products; and obtains the cumulative heat absorption of the frozen product over time based on the temperature sequence and the heat absorption rate.

[0084] When the controller is running, the temperature difference of the current evaluation period is obtained according to the initial temperatures of the thawing medium and the frozen product in the current evaluation period; the heat absorption rate of the current evaluation period is determined according to the thawing coefficient, the amount of frozen products and the temperature difference of the current evaluation period; the amount of heat absorption of the current evaluation period is determined based on the heat absorption rate of the current evaluation period; the predicted end-of-period temperature of the thawing medium and the frozen product is determined according to the heat absorption of the current evaluation period; the end-of-period temperature is used as the initial temperature of the next evaluation period; and the temperature sequence is obtained according to a combination of the initial temperatures of multiple evaluation periods.

[0085] When the controller is running, after obtaining the predicted time required for thawing, the real-time temperature sequence of the thawing medium is also obtained; based on the real-time temperature sequence, the corresponding actual heat absorption is obtained; based on the actual heat absorption, the heat absorption rate is corrected; based on the corrected heat absorption rate, the predicted temperature sequence of the thawing medium and the frozen product is corrected; based on the corrected predicted temperature sequence and the corrected heat absorption rate, the cumulative heat absorption of the frozen product over time is obtained to obtain the corrected predicted time.

[0086] When the controller is running, the temperature difference corresponding to each type of frozen product in the current evaluation period is obtained according to the initial temperature of the thawing medium in the current evaluation period and the initial temperature of each type of frozen product; the heat absorption rate corresponding to each type of frozen product in the current evaluation period is determined based on the temperature difference corresponding to each type of frozen product and the thawing coefficient corresponding to the frozen product type; the heat absorption amount of each type of frozen product in the current evaluation period is determined based on the heat absorption rate corresponding to each type of frozen product to determine the end-of-period temperature of each type of frozen product; the end-of-period temperature of the thawing medium is determined according to the sum of the heat absorption amounts of each type of frozen product in the current evaluation period; the end-of-period temperature of the thawing medium and the end-of-period temperature of each type of frozen product are used as the initial temperature of the next evaluation period.

[0087] The heat absorption amount corresponding to each type of frozen product is accumulated separately to obtain the accumulated heat absorption amount corresponding to each type of frozen product; the time when the accumulated heat absorption amount reaches the target heat absorption amount corresponding to the type of frozen product is determined, which is the predicted duration corresponding to the type.

[0088] In some embodiments, the body is provided with a motion unit in the accommodating chamber, which drives the frozen product to move at a certain frequency and amplitude. When the controller is running, the motion frequency and amplitude of the frozen product are obtained; based on the motion frequency and amplitude, the thawing coefficient is determined from a preset correlation relationship.

[0089] In some embodiments, the controller obtains the increase or decrease of external thermal energy of the thawing medium to correct the predicted duration according to the increase or decrease of the external thermal energy.

[0090] The specific definition of the thawing time prediction device and the thawing machine can refer to the definition of the thawing time prediction method in the above text, which will not be repeated here. The above-mentioned thawing time prediction device and each module in the controller can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0091] In one embodiment, a computer device is provided. The computer device may be a control terminal of a thawing machine, and its internal structure diagram may be as shown in FIG. Figure 5 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a thawing time prediction method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0092] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0093] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: Acquire the state attributes of the thawing medium and the frozen product, wherein the state attributes at least include the temperature of the thawing medium, the quality of the thawing medium, the type of frozen product, and the number of frozen products corresponding to the type of frozen product, wherein the type of frozen product is associated with the thawing coefficient of the frozen product and the amount of heat required for thawing the single product; According to the state attribute, obtaining the cumulative heat absorption of the frozen product over time; The time when the cumulative heat absorption reaches the target heat absorption required for thawing is estimated to obtain the predicted time required for thawing, wherein the target heat absorption is determined based on the heat absorption required for thawing of the single product and the quantity of the frozen product.

[0094] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Acquire the state attributes of the thawing medium and the frozen product, wherein the state attributes at least include the temperature of the thawing medium, the quality of the thawing medium, the type of frozen product, and the number of frozen products corresponding to the type of frozen product, wherein the type of frozen product is associated with the thawing coefficient of the frozen product and the amount of heat required for thawing the single product; According to the state attribute, obtaining the cumulative heat absorption of the frozen product over time; The time when the cumulative heat absorption reaches the target heat absorption required for thawing is estimated to obtain the predicted time required for thawing, wherein the target heat absorption is determined based on the heat absorption required for thawing of the single product and the quantity of the frozen product.

[0095] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: The step of obtaining the accumulated heat absorption of the frozen product over time according to the state attribute includes: According to the state attributes, a predicted temperature sequence of the thawing medium and the frozen product is obtained; According to the thawing coefficient and the amount of frozen products, determining the heat absorption rate at each temperature difference corresponding to the temperature sequence of the thawing medium and the frozen products; The cumulative heat absorption of the frozen product over time is obtained according to the temperature sequence and the heat absorption rate.

[0096] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: The step of obtaining the predicted temperature sequence of the thawing medium and the frozen product comprises: According to the initial temperature of the thawing medium and the frozen product in the current evaluation period, the temperature difference in the current evaluation period is obtained; Determining the heat absorption rate of the current evaluation period according to the thawing coefficient, the amount of frozen products and the temperature difference of the current evaluation period; determining a heat absorption amount of the current evaluation period based on the heat absorption rate of the current evaluation period; Determining the predicted final temperature of the thawing medium and the frozen product according to the heat absorption during the current evaluation period; Using the end-of-period temperature as the initial temperature of the next evaluation period; The temperature sequence is obtained according to a combination of initial temperatures of a plurality of evaluation periods.

[0097] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: After obtaining the predicted time required for thawing, the method further includes: Acquiring a real-time temperature sequence of the thawing medium; According to the real-time temperature sequence, a corresponding actual heat absorption is obtained; According to the actual amount of heat absorption, correct the heat absorption rate; Correcting the predicted temperature sequence of the thawing medium and the frozen product according to the corrected heat absorption rate; According to the revised predicted temperature sequence and the revised heat absorption rate, the cumulative heat absorption of the frozen product over time is obtained to obtain a revised predicted duration.

[0098] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: When the number of types of frozen products with different heat absorption rates is greater than or equal to 2, obtaining the predicted temperature sequence of the thawing medium and the frozen product includes: According to the initial temperature of the thawing medium and the initial temperature of each type of frozen product in the current evaluation period, the temperature difference corresponding to each type of frozen product in the current evaluation period is obtained; Determining the heat absorption rate corresponding to each type of frozen product in the current evaluation period based on the temperature difference corresponding to each type of frozen product and the thawing coefficient corresponding to the type of frozen product; Based on the heat absorption rate corresponding to each type of frozen product, determine the amount of heat absorption of each type of frozen product in the current evaluation period to determine the end-of-period temperature of each type of frozen product; Determine the final temperature of the thawing medium according to the sum of the heat absorbed by each type of frozen product during the current evaluation period; The final temperature of the thawing medium and the final temperature of each type of frozen product are used as the initial temperature of the next evaluation period.

[0099] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: Accumulate the heat absorption corresponding to each type of frozen product separately to obtain the accumulated heat absorption corresponding to each type of frozen product; The time when the cumulative heat absorption reaches the target heat absorption corresponding to the frozen product type is determined as the predicted time corresponding to the type.

[0100] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: Obtain the movement frequency and movement amplitude of frozen products; According to the movement frequency and the movement amplitude, a thawing coefficient is determined from a preset association relationship, so that the heat absorption rate is determined according to the thawing coefficient and the temperature difference between the thawing medium and the frozen product.

[0101] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: The increase or decrease of the external heat energy of the thawing medium is obtained, so as to correct the predicted time according to the increase or decrease of the external heat energy.

[0102] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0103] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0104] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A thawing time prediction method, characterized in that: Applied to a thawing system including frozen products and a thawing medium, the method comprises: Acquire the state attributes of the thawing medium and the frozen product, wherein the state attributes at least include the temperature of the thawing medium, the quality of the thawing medium, the type of frozen product, and the number of frozen products corresponding to the type of frozen product, wherein the type of frozen product is associated with the thawing coefficient of the frozen product and the amount of heat required for thawing the single product; According to the state attribute, obtaining the cumulative heat absorption of the frozen product over time; The time when the cumulative heat absorption reaches the target heat absorption required for thawing is estimated to obtain the predicted time required for thawing, wherein the target heat absorption is determined based on the heat absorption required for thawing of the single product and the quantity of the frozen product.

2. The thawing time prediction method according to claim 1, characterized in that: The step of obtaining the accumulated heat absorption of the frozen product over time according to the state attribute includes: According to the state attributes, a predicted temperature sequence of the thawing medium and the frozen product is obtained; According to the thawing coefficient and the amount of frozen products, determining the heat absorption rate at each temperature difference corresponding to the temperature sequence of the thawing medium and the frozen products; The cumulative heat absorption of the frozen product over time is obtained according to the temperature sequence and the heat absorption rate.

3. The thawing time prediction method according to claim 2, characterized in that: The step of obtaining the predicted temperature sequence of the thawing medium and the frozen product comprises: According to the initial temperature of the thawing medium and the frozen product in the current evaluation period, the temperature difference in the current evaluation period is obtained; Determining the heat absorption rate of the current evaluation period according to the thawing coefficient, the amount of frozen products and the temperature difference of the current evaluation period; determining a heat absorption amount of the current evaluation period based on the heat absorption rate of the current evaluation period; Determining the predicted final temperature of the thawing medium and the frozen product according to the heat absorption during the current evaluation period; Using the end-of-period temperature as the initial temperature of the next evaluation period; The temperature sequence is obtained according to a combination of initial temperatures of a plurality of evaluation periods.

4. The thawing time prediction method according to claim 2, characterized in that: After obtaining the predicted time required for thawing, the method further includes: Acquiring a real-time temperature sequence of the thawing medium; According to the real-time temperature sequence, a corresponding actual heat absorption is obtained; According to the actual amount of heat absorption, correct the heat absorption rate; Correcting the predicted temperature sequence of the thawing medium and the frozen product according to the corrected heat absorption rate; According to the revised predicted temperature sequence and the revised heat absorption rate, the cumulative heat absorption of the frozen product over time is obtained to obtain a revised predicted duration.

5. The thawing time prediction method according to claim 2, characterized in that: When the number of types of frozen products with different heat absorption rates is greater than or equal to 2, obtaining the predicted temperature sequence of the thawing medium and the frozen product includes: According to the initial temperature of the thawing medium and the initial temperature of each type of frozen product in the current evaluation period, the temperature difference corresponding to each type of frozen product in the current evaluation period is obtained; Determining the heat absorption rate corresponding to each type of frozen product in the current evaluation period based on the temperature difference corresponding to each type of frozen product and the thawing coefficient corresponding to the type of frozen product; Based on the heat absorption rate corresponding to each type of frozen product, determine the amount of heat absorption of each type of frozen product in the current evaluation period to determine the end-of-period temperature of each type of frozen product; Determine the final temperature of the thawing medium according to the sum of the heat absorbed by each type of frozen product during the current evaluation period; The final temperature of the thawing medium and the final temperature of each type of frozen product are used as the initial temperature of the next evaluation period.

6. The thawing time prediction method according to claim 5, characterized in that: The predicted time required for thawing includes: Accumulate the heat absorption corresponding to each type of frozen product separately to obtain the accumulated heat absorption corresponding to each type of frozen product; The time when the cumulative heat absorption reaches the target heat absorption corresponding to the frozen product type is determined as the predicted time corresponding to the type.

7. The thawing time prediction method according to claim 1, characterized in that: The step of obtaining the state attributes of the thawing medium and the frozen product further includes: Obtain the movement frequency and movement amplitude of frozen products; According to the movement frequency and movement amplitude, the thawing coefficient corresponding to the frozen product type is determined from a preset association relationship.

8. The thawing time prediction method according to claim 1, characterized in that: The step of obtaining the state attributes of the thawing medium and the frozen product further includes: The increase or decrease of the external heat energy of the thawing medium is obtained to correct the predicted duration according to the increase or decrease of the external heat energy.

9. A thawing machine, characterized in that: The thawing machine comprises: The body is configured with a receiving chamber, wherein the receiving chamber is used to receive a thawing medium and at least one type of frozen product; A controller, used to obtain a predicted time required for thawing the frozen product; a prompting unit, connected to the controller, for prompting the predicted time corresponding to the frozen product; Wherein, when the controller is running, the state attributes of the thawing medium and the frozen product are obtained, and the state attributes include at least the temperature of the thawing medium, the quality of the thawing medium, the type of frozen product and the number of frozen products corresponding to the frozen product type, wherein the frozen product type is associated with the thawing coefficient of the frozen product and the amount of heat absorption required for thawing of a single product; according to the state attributes, the cumulative heat absorption of the frozen product with respect to time is obtained; the time when the cumulative heat absorption reaches the target heat absorption required for thawing is estimated, and the predicted time required for thawing is obtained, wherein the target heat absorption is determined based on the heat absorption required for thawing of a single product and the number of frozen products.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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