Method for confirming freshness of fresh food, refrigeration appliance and control method of refrigeration appliance

Abstract

The invention discloses a method for confirming freshness of fresh food, a refrigeration appliance and a control method of the refrigeration appliance. The method for confirming the freshness of the fresh food comprises the following steps: in each sampling period, scoring a freshness influence factor of each fresh food in a storage space; calculating the freshness of each fresh food based on the score and the weight of each freshness influence factor of each fresh food; wherein the weight change condition of the fresh food is obtained by the following steps: when each fresh food is put in for the first time, calculating to obtain the independent initial weight of each fresh food; in each sampling period, the current total weight of fresh food in the storage space is obtained; estimating the independent current weight of each fresh food based on the current total weight of the fresh food, the independent initial weight of each fresh food and the water loss rate model in the current environment; and according to the independent current weight and the independent initial weight of each fresh food, calculating to obtain the weight change condition of each fresh food. According to the method, the independent freshness of the fresh food can be obtained, and a more accurate data basis is provided for fresh food preservation.

Description

Technical Field

[0001] This invention relates to the technical field of storage control of refrigeration appliances, and more particularly to a method for confirming the freshness of fresh produce, as well as a refrigeration appliance that uses the fresh produce freshness and its control method. Background Technology

[0002] As people's demands for food freshness and safety continue to increase, fresh produce preservation technology has become an important research method. Fresh produce generally refers to primary agricultural products, whose core characteristics are high water activity, live metabolism, and perishability, including fruits and vegetables, meat, seafood, and dairy products. Fruits and vegetables, in particular, are typically stored for extended periods using refrigeration, making fruit and vegetable preservation technology a crucial research direction in the field of food storage.

[0003] Traditional refrigerators or preservation devices typically only have basic temperature and humidity control functions, lacking the ability to determine the freshness of fresh produce. They struggle to dynamically adjust based on the freshness, type, and spoilage mechanism of the produce, leading to poor preservation and nutrient loss. For example, prior art (CN119063373B) discloses a method for controlling the ripening of food, which controls the temperature and humidity within the cavity based on the rate of weight change of the food. The main technical problems with this prior art include the following:

[0004] First, existing preservation methods are generally difficult to use for preserving single types of fresh produce, because a storage space usually contains more than one type of food. For example, a storage space may not only contain apples, but also other fruits such as strawberries and kiwis. Therefore, when weighing fresh produce in a storage space, existing technologies have difficulty distinguishing the specific weight changes of each type of produce, which makes it difficult to apply these existing technologies.

[0005] Secondly, the existing technology only considers the weight change of fresh produce. In reality, the weight change of many fruits is very slight. For example, for fragile fresh produce such as strawberries, the weight change between a fresh, undamaged strawberry and a fresh strawberry that has been severely bruised is negligible. Therefore, it is obviously impossible to determine the freshness of fresh produce by relying solely on weight.

[0006] The freshness of fresh produce is particularly crucial for preservation technologies, and therefore, determining the freshness of fresh produce is a technical problem that urgently needs to be solved. Summary of the Invention

[0007] In order to solve the technical problem that the freshness of various fresh foods is difficult to determine due to the lack of data in the prior art, the present invention proposes a method for confirming the freshness of fresh foods, a refrigeration appliance and its control method.

[0008] The method for confirming the freshness of fresh produce proposed in this invention includes:

[0009] Within each sampling period, the freshness influencing factors of each fresh food item in the storage space are scored; the freshness influencing factors include changes in the weight of the fresh food and changes in its image.

[0010] The freshness of each fresh food is calculated based on the scores and weights of the various freshness influencing factors.

[0011] The weight change of the fresh produce was obtained using the following steps:

[0012] When each fresh food item is placed into the storage space for the first time, the total weight of the fresh food items in the storage space is weighed. Based on the total weight of the fresh food items in the previous weighing, the independent initial weight of each fresh food item when it is first placed into the storage space is calculated.

[0013] Within each sampling period, the current total weight of fresh produce in the storage space is obtained;

[0014] Based on the current total weight of fresh produce, the independent initial weight of each fresh produce, and the water loss rate model under the current environment, estimate the independent current weight of each fresh produce.

[0015] The weight change of each fresh produce is calculated based on its current independent weight and initial independent weight.

[0016] Furthermore, based on the current total weight of fresh produce, the independent initial weight of each fresh produce, and the water loss rate model under the current environment, the independent current weight of each fresh produce is estimated as follows:

[0017] Based on the water loss rate model of each fresh food, the current ambient temperature, humidity, and storage time of each fresh food, the theoretical weight loss of each fresh food is calculated.

[0018] Subtract the theoretical weight loss from the individual initial weight of each fresh produce to obtain the individual theoretical weight of each fresh produce, as well as the total theoretical weight of the fresh produce in the storage space.

[0019] Subtract the total theoretical weight of the fresh produce from the current total weight of the fresh produce in the storage space to obtain the total weight deviation;

[0020] Based on the proportion of the independent theoretical weight of each fresh produce in the total theoretical weight of fresh produce, the total weight deviation is allocated to the independent theoretical weight of each fresh produce to obtain the independent current weight of each fresh produce.

[0021] Furthermore, based on the independent current weight and independent initial weight of each fresh produce, formula L is used. w,norm = min(max((L w - L w,fresh ) / (L w,spoiled - L w,freshThe weight changes of each fresh produce were calculated using the formulas ), 0, and 1), L. w,norm For weight loss normalized degradation, L w L represents the current weight loss rate. w,fresh L represents the weight loss rate in the fresh state. w,spoiled This represents the weight loss rate under putrefactive conditions.

[0022] Furthermore, the image changes are calculated using the following steps:

[0023] Within each sampling period, an independent current image of each fresh produce is acquired, and current image features of each fresh produce are extracted. The image features include at least one of color saturation and texture.

[0024] Using formula S i,norm = min(max((S i,current - S i,fresh ) / (S i,spoiled - S i,fresh The image changes are calculated using the formulas ),0),1); S i,norm S is a normalized score for image degradation of fresh produce. i,current S represents the current image features of fresh produce. i,fresh S represents the image features of fresh produce in its fresh state. i,spoiled Image features of fresh produce in a rotten state.

[0025] Furthermore, the factors affecting freshness also include changes in the ethylene concentration within the storage space;

[0026] The change in ethylene concentration is expressed by formula E. norm = min(max((E current - E background ) / (E threshold - E background E is calculated as follows: ),0),1) norm E represents the normalized degradation degree of ethylene concentration. current E represents the measured ethylene concentration within the current sampling period. background E represents the ethylene concentration value of fresh produce in the storage space under fresh conditions. threshold This represents the threshold value for ethylene concentration within the storage space.

[0027] Furthermore, E background The average ethylene concentration value of each fresh food item in its fresh state within the storage space, and / or, E threshold This represents the minimum ethylene concentration threshold for each type of fresh food within the storage space.

[0028] Furthermore, the factors affecting freshness also include changes in VOC concentration within the storage space;

[0029] The VOCs concentration change is expressed by formula V norm = min( max((V current - V background ) / (V threshold - V background V is calculated as follows: ),0),1) norm VOCs concentration normalized degradation degree, V current V represents the measured concentration of VOCs within the current sampling period. background VOCs concentration value of fresh produce in the storage space under fresh conditions. threshold The threshold value for VOCs concentration within the storage space.

[0030] Furthermore, V background The average VOCs concentration value is the value of each fresh food item in its fresh state within the storage space. threshold This refers to the minimum VOCs concentration threshold for each type of fresh food within the storage space.

[0031] The control method for refrigeration appliances proposed in this invention includes:

[0032] The freshness of each fresh food item in each storage space is calculated using the above-mentioned technical solution to confirm the freshness of fresh food.

[0033] The system determines whether the freshness of each fresh food item is below its freshness threshold. If the freshness of a certain fresh food item is below its freshness threshold, the system will notify the user and lower the temperature, increase the humidity, and perform photocatalysis and sterilization treatments in the storage space where the fresh food item is located.

[0034] Furthermore, if the freshness of each fresh food is greater than its freshness threshold, then it is determined in turn whether the freshness influencing factor of each fresh food exceeds its corresponding threshold. If it does, then a corresponding control strategy is adopted. The control strategy includes at least one of the following: a water retention strategy for regulating temperature and humidity, a gas purification strategy for removing corresponding gases in the storage space, and a sterilization strategy for sterilizing the storage space.

[0035] The refrigeration appliance proposed in this invention includes a controller, at least one storage space for storing fresh food, and a detection device for detecting factors affecting freshness within the storage space. The controller controls the air environment of the corresponding storage space based on the detection data from the detection device and employs the control method of the refrigeration appliance described above.

[0036] Furthermore, the storage space includes multiple storage spaces, each storing one type of fresh produce.

[0037] This invention, when calculating the freshness of fruits and vegetables, sets corresponding identifiers (i) for different types of fresh produce to facilitate independent weight tracking. This not only solves the core problem of inaccurate weight monitoring caused by mixed storage of multiple batches, ensuring the reliability of the key indicator of weight loss rate even in complex scenarios, but also considers image changes in addition to the weight loss rate in freshness calculation. This allows for a more accurate assessment of the freshness of different types of produce based on their characteristics. Furthermore, in a further technical solution of this invention, some solutions monitor ethylene concentration and classify the threshold values ​​of ethylene concentration, employing a low-power decomposition mode for low concentrations and a high-power decomposition mode for high concentrations. Other solutions monitor the concentration of characteristic VOCs gases and classify the threshold values ​​of VOCs gas concentrations into low, medium, and high concentration ranges, applying corresponding low, medium, and high decomposition modes. In a preferred technical solution, this invention monitors and predicts potential risks to fruits and vegetables by measuring the acceleration of weight loss, the acceleration of VOCs growth, and the acceleration of ethylene growth, and then makes corresponding adjustments. It integrates the weight loss rate, multispectral image degradation, ethylene, and VOCs characteristic gas concentrations into a weighted comprehensive freshness index (F), and establishes a dynamic evaluation model. Based on the comprehensive freshness index F, it judges the current state of fruits and vegetables (water loss-dominated spoilage, gas-dominated spoilage, and microbial-dominated spoilage) and makes targeted adjustments, resulting in the technical effects of time-series synergistic control of multiple intervention methods and closed-loop optimization of strategies based on historical effect feedback. Attached Figure Description

[0038] The present invention will now be described in detail with reference to the embodiments and accompanying drawings, wherein:

[0039] Figure 1 This is a simplified flowchart of an embodiment of the present invention.

[0040] Figure 2 This is a flowchart illustrating the acquisition of weight changes according to an embodiment of the present invention.

[0041] Figure 3 This is a flowchart of obtaining the current independent weight of fresh produce according to an embodiment of the present invention.

[0042] Figure 4 This is a structural layout diagram of the storage space of a refrigeration device according to an embodiment of the present invention.

[0043] Figure 5 This is a block diagram of the preservation structure of a refrigeration device according to an embodiment of the present invention.

[0044] Figure 6 This is a schematic diagram of the storage space structure of a refrigeration device according to an embodiment of the present invention.

[0045] Figure 7This is a flowchart of the preservation process of a refrigeration device according to an embodiment of the present invention.

[0046] Figure 8 This is a flowchart illustrating the main process of a refrigeration device according to freshness control in an embodiment of the present invention.

[0047] Figure 9 This is a control flowchart of a water retention strategy for a refrigeration device according to an embodiment of the present invention.

[0048] Figure 10 This is a control flowchart of a refrigeration device performing a purification strategy according to an embodiment of the present invention.

[0049] Figure 11 This is a control flowchart of a sterilization strategy for a refrigeration device according to an embodiment of the present invention.

[0050] Explanation of reference numerals in the attached figures:

[0051] 1. Refrigerator compartment; 2. Fruit and vegetable drawer; 3. Leafy vegetable drawer; 4. Freezer compartment; 5. Root and tuber drawer; 6. Low-temperature refrigerated fruit drawer; 7. Temperature and humidity sensor; 8. Ultraviolet-ozone (UV-O3) synergistic sterilization module; 9. Multispectral camera; 10. Temperature and humidity controller; 11. Photocatalytic decomposition device; 12. Gas sensor array; 13. High-precision weighing sensor. Detailed Implementation

[0052] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0053] Therefore, a feature pointed out in this specification is used to describe one feature of one embodiment of the invention, and does not imply that every embodiment of the invention must have the described feature. Furthermore, it should be noted that this specification describes many features. Although certain features may be combined to illustrate possible system designs, these features may also be used in other combinations not explicitly stated. Therefore, unless otherwise stated, the described combinations are not intended to be limiting.

[0054] In order to provide a basis for fresh food preservation technology, this invention proposes a corresponding method for confirming the freshness of fresh food, so that preservation measures can be dynamically adjusted according to the freshness of fresh food during the preservation process, so as to achieve a more reasonable preservation technology.

[0055] like Figure 1 As shown, the method for confirming the freshness of fresh produce according to the present invention mainly includes two steps.

[0056] Step 1: In each sampling period, score the freshness influencing factors of each fresh food item in the storage space; the freshness influencing factors include the weight change and image change of the fresh food items.

[0057] Step 2: Calculate the freshness of each fresh produce based on the scores and weights of the various freshness influencing factors.

[0058] In the two steps described above, in addition to collecting data on changes in the weight of the fresh produce, this invention also collects data on changes in the image, and comprehensively examines the freshness of the fresh produce, thereby enabling a more accurate assessment of its freshness.

[0059] like Figure 2 As shown, the most crucial step in step 1 above is to obtain the weight changes of each fresh produce. The weight changes of each fresh produce are obtained using the following steps.

[0060] Step 11: When each fresh food is placed into the storage space for the first time, the total weight of the fresh food in the storage space is weighed. At this time, the current total weight of the other fresh food and the fresh food placed for the first time can be obtained. Then, based on the previous total weight of the fresh food, that is, the previous total weight of other fresh food, the current total weight can be subtracted from the previous total weight of other fresh food to obtain the independent initial weight of the fresh food placed for the first time.

[0061] Step 12: Within each sampling period, obtain the current total weight of fresh produce in the storage space. The previous total weight of fresh produce in Step 11 may be derived from the current total weight of fresh produce in the storage space obtained in the most recent sampling period. If the user places multiple fresh produce items into the storage space during a single opening period, the calculation of the independent initial weight of the first fresh produce item will use the current total weight of fresh produce in the storage space obtained in the most recent sampling period. However, the independent initial total weight of the second fresh produce item and the nth fresh produce item placed during this opening period will be calculated by subtracting the total weight obtained during the previous placement from the current total weight obtained during this placement.

[0062] Step 13: Estimate the independent current weight of each fresh produce based on the total current weight of the fresh produce, the independent initial weight of each fresh produce, and the water loss rate model of each fresh produce under the current environment. That is, the independent current weight of a fresh produce can be obtained by subtracting the water loss amount obtained by the water loss rate model of that fresh produce in each sampling period from its independent initial weight.

[0063] Step 14: Based on the independent current weight and independent initial weight of each fresh produce, calculate the weight change of each fresh produce. For example, the weight loss rate and acceleration of the weight loss rate of each fresh produce can be calculated, and those skilled in the art can perform the corresponding calculations.

[0064] Based on the above technical solution, it is possible to obtain the weight changes of each fresh food item within a storage space. This allows for the determination of the freshness of each item based on its weight changes and image changes, enabling targeted control. For example, the freshness control of the least fresh food can be based on specific criteria. Compared to existing technologies, this provides a more precise basis for the freshness of each fresh food item, further enhancing the accuracy of preservation technology control.

[0065] like Figure 3 As shown, in a preferred embodiment, the above technical solution, based on the current total weight of fresh produce, the independent initial weight of each fresh produce, and the water loss rate model under the current environment, may further include the following steps to calibrate the estimated fresh produce weight.

[0066] Step 131: Calculate the theoretical weight loss of each fresh food based on the water loss rate model of each fresh food, the current ambient temperature and humidity, and the storage time of each fresh food.

[0067] Step 132: Subtract the theoretical weight loss from the independent initial weight of each fresh food to obtain the independent theoretical weight of each fresh food, and the total theoretical weight of the fresh food in the storage space.

[0068] Step 133: Subtract the total theoretical weight of fresh produce from the current total weight of fresh produce in the storage space to obtain the total weight deviation;

[0069] Step 134: Based on the proportion of the independent theoretical weight of each fresh produce in the total theoretical weight of the fresh produce, allocate the total weight deviation to the independent theoretical weight of each fresh produce to obtain the independent current weight of each fresh produce.

[0070] Through the above steps, the estimated total weight deviation is redistributed to the independent theoretical weight of each fresh produce, thereby allowing the current weight of each fresh produce to be calibrated, providing a more accurate basis for freshness data.

[0071] In one specific embodiment, the weight change of the present invention is specifically the weight loss normalized deterioration degree, which is calculated based on the independent current weight and independent initial weight of each fresh produce using formula L. w,norm = min( max((L w - L w,fresh ) / (L w,spoiled - L w,fresh The weight changes of each fresh produce are calculated using the formula (L). In other embodiments, the formula (L) can also be used. w - L w,fresh ) / (L w,spoiled - L w,freshThis can be used to calculate the weight loss rate to quantify weight variables, and / or to calculate the weight loss acceleration, etc., to quantify weight changes.

[0072] L w,norm Normalized degradation degree for weight loss;

[0073] L w This represents the current weight loss rate.

[0074] L w,fresh This represents the weight loss rate in its fresh state.

[0075] L w,spoiled This represents the weight loss rate under putrefactive conditions.

[0076] The above formula limits the normalized deterioration degree of each weight loss to between 0 and 1, which facilitates the calculation of freshness. Moreover, since the weight loss rate in the fresh state and the weight loss rate in the spoiled state are different for different varieties of fresh produce, the normalized deterioration degree of weight loss calculated for each variety of fresh produce will be different. This allows for a more accurate calculation of the normalized deterioration degree of weight loss for different varieties of fresh produce, thus enabling a more accurate assessment of the freshness of different varieties of fresh produce.

[0077] In a further embodiment, the image changes of the present invention are calculated using the following steps.

[0078] Within each sampling period, an independent current image of each fresh produce is acquired, and the current image features of each fresh produce are extracted. The image features include, but are not limited to, at least one of color saturation and texture.

[0079] Using formula S i,norm = min(max((S i,current - S i,fresh ) / (S i,spoiled - S i,fresh The image changes are calculated using the formula (S), 0), 1); in other embodiments, other calculation methods can also be used to quantify the image changes, such as using the formula (S). i,current - S i,fresh ) / (S i,spoiled - S i,fresh This is used to calculate changes in the image.

[0080] S i,norm Normalize the scoring for image degradation of fresh produce;

[0081] S i,current The current image features of fresh produce;

[0082] S i,fresh Image features of fresh produce in its fresh state;

[0083] S i,spoiled Image features of fresh produce in a rotten state.

[0084] The above formula limits the image degradation normalization score of each fresh food to between 0 and 1, which facilitates the calculation of freshness. Moreover, since the image characteristics of different varieties of fresh food are different in the fresh state and the image characteristics in the spoiled state, the focus of the image characteristics of different varieties of fresh food can also be different. Therefore, the image degradation normalization score calculated for each fresh food is different, so as to obtain a more accurate freshness of different varieties of fresh food.

[0085] In addition to weight and image, other factors may be further considered. In one embodiment, the freshness influencing factors of the present invention also include the variation of ethylene concentration in the storage space.

[0086] The change in ethylene concentration is expressed by formula E. norm = min(max((E current - E background ) / (E threshold - E background The formula (E) is calculated as follows: 0), 1); in other embodiments, formula (E) can also be used. current - E background ) / (E threshold - E background This can be used to calculate the change in ethylene concentration, and can also be used to calculate the acceleration of the change in ethylene concentration for corresponding scoring.

[0087] E norm The degree of degradation is normalized to the ethylene concentration.

[0088] E current The measured value of ethylene concentration within the current sampling period;

[0089] E background The ethylene concentration value of fresh produce in the storage space under fresh conditions;

[0090] E threshold This represents the ethylene concentration threshold within the storage space.

[0091] This embodiment also incorporates the ethylene concentration in each storage space into the freshness calculation. When the ethylene concentration in a storage space exceeds the standard, it will have a certain impact on the freshness of some fresh produce, especially fruits and vegetables, requiring timely purification. When calculating the ethylene concentration, the normalized degradation degree of the ethylene concentration in the storage space is also limited to between 0 and 1 to facilitate the calculation of freshness.

[0092] Because the concentration of ethylene released by fruits and vegetables within a storage space varies, or in other words, they are sensitive to different concentrations of ethylene, in one embodiment, when considering the concentration of ethylene released by fruits and vegetables, E background The average ethylene concentration value of each fresh food item in its fresh state within the storage space, and / or, E threshold This represents the average threshold value of ethylene concentration released by each fresh food item within the storage space. In other embodiments, E threshold The ethylene concentration threshold is the threshold value for the most perishable fruits and vegetables in the storage space, i.e., the minimum ethylene concentration threshold value for each type of fresh produce, etc.

[0093] Depending on the variety of fresh produce, those skilled in the art can consider different ethylene concentration treatments as needed, and can take the average value for easier calculation.

[0094] In one embodiment, the freshness influencing factor of the present invention may also take into account the changes in VOCs concentration within the storage space.

[0095] VOCs concentration changes are expressed by the formula V norm = min( max((V current - V background ) / (V threshold - V background The formula (V) is calculated as follows: 0), 1); in other embodiments, the formula (V) can also be used. current -V background ) / (V threshold - V background This is used to calculate the changes in VOCs concentration.

[0096] V norm The normalized degradation degree of VOCs concentration;

[0097] V current The measured VOCs concentration values ​​obtained within the current sampling period;

[0098] V background The concentration of VOCs in fresh produce within the storage space;

[0099] V threshold The threshold value for VOCs concentration within the storage space.

[0100] This embodiment also incorporates the concentration of volatile organic compounds (VOCs) in each storage space into the freshness calculation. By collecting data on the changes in VOCs concentration within a single storage space, it can more accurately reflect the physiological state and quality deterioration process of fruits and vegetables. This embodiment also normalizes the VOCs concentration in the storage space to a deterioration degree between 0 and 1, facilitating the calculation of freshness.

[0101] In one embodiment, V backgroundThe average VOCs concentration value is the value of each fresh food item in its fresh state within the storage space. threshold The VOCs concentration threshold is the lowest VOCs concentration threshold for each type of fresh food in the storage space, which is the most perishable fresh food in the storage space.

[0102] Those skilled in the art can select different V based on the variety of fresh produce stored in a storage space. background and V threshold The value of makes the technical concept of the present invention more in line with practical needs.

[0103] The present invention also protects a control method for refrigeration appliances, comprising the following steps.

[0104] The freshness of each fresh food item in each storage space is calculated using any of the above technical solutions to confirm the freshness of fresh food.

[0105] Determine whether the freshness of each fresh food item is below its freshness threshold. If the freshness of a certain fresh food item is below its freshness threshold, it means that the fresh food item is no longer fresh. The user should be notified, and the temperature in the storage space where the fresh food item is located should be lowered, the humidity increased, and photocatalysis and sterilization treatments should be carried out.

[0106] Lowering the temperature can slow down the ripening process of fresh produce, while increasing humidity helps retain moisture. Photocatalysis can remove excess ethylene, and sterilization can remove harmful bacteria. By maintaining the current state of fresh produce as much as possible, the preservation effect can be achieved.

[0107] In a further embodiment, if the freshness of each fresh food is greater than its freshness threshold, that is, the fresh food is relatively fresh, then it is determined in turn whether the freshness influencing factor of each fresh food exceeds its corresponding threshold. If it exceeds, a corresponding control strategy is adopted. The control strategy includes at least one of the following: a water retention strategy for adjusting temperature and humidity, a gas purification strategy for removing corresponding gases in the storage space, and a sterilization strategy for sterilizing the storage space.

[0108] This embodiment detects factors affecting the freshness of fresh produce from different dimensions while the produce is still relatively fresh. Based on the factors found, corresponding measures are then taken to achieve dynamic and precise preservation methods as much as possible.

[0109] This invention also protects a refrigeration appliance, which includes a controller, at least one storage space for storing fresh produce, and a detection device for detecting factors affecting freshness within the storage space. The controller of the refrigeration appliance, based on the detection data from the detection device, uses the control method of the refrigeration appliance described above to control the air environment of the corresponding storage space. The air environment referred to herein includes at least one of the following: temperature, humidity, ethylene concentration, and VOCs concentration of the storage space.

[0110] The control method of this invention can achieve a better preservation effect.

[0111] In a further embodiment, the storage space includes multiple storage spaces, each storing one type of fresh produce.

[0112] This embodiment places different categories of products in one space, which is more conducive to control and avoids the situation where fresh produce with different factors affecting freshness is stored together, which could lead to inaccurate control.

[0113] The main concept of this invention will be explained below with reference to a specific application example. This application example mainly focuses on the preservation of fruits and vegetables.

[0114] like Figure 4 As shown, the refrigeration appliance in this application example is a refrigerator, which has a refrigerator compartment 1, a fruit and vegetable drawer 2, a leafy vegetable drawer 3, a freezer compartment 4, a root vegetable drawer 5, and a low-temperature refrigerated fruit drawer 6. In other words, the refrigerator has multiple storage spaces (drawers) for storing different types of fresh produce.

[0115] like Figure 5 As shown, the refrigerator also features an intelligent vegetable preservation system, which is mainly built with software to control the preservation process. It also includes a fruit and vegetable category database and various hardware components, including but not limited to a central processing unit (controller), multispectral imaging sensor, gas sensor array, temperature and humidity sensor, high-precision weighing sensor, UV-O3 synergistic sterilization module, zoned temperature and humidity controller, photocatalytic decomposition device, user interaction and early warning module, storage unit, and power module.

[0116] Multispectral imaging sensors are used for non-contact detection of changes in color, texture, moisture distribution, and even early signs of spoilage on the surface of vegetables, enabling a quantitative assessment of vegetable freshness.

[0117] A gas sensor array monitors the concentrations of putrefactive gases such as ethylene (C2H4), carbon dioxide (CO2), ozone (O3), and characteristic gases of volatile organic compounds (VOCs) (ethanol, acetaldehyde, acetone, etc.).

[0118] Temperature and humidity sensors capture changes in the microenvironment during fruit and vegetable storage.

[0119] The refrigerator's storage drawers can be independently controlled for temperature and humidity, thanks to the zoned temperature and humidity controller.

[0120] High-precision weighing sensors can directly and quantitatively monitor the weight changes of fruits and vegetables over time.

[0121] The fruit and vegetable category database pre-stores parameters such as optimal storage temperature and humidity, weight loss threshold, ethylene sensitivity, and "safe VOCs benchmark value" for each type of fruit and vegetable.

[0122] The UV-O3 synergistic sterilization module uses a specific wavelength of UVC-LED and a controllable ozone generator for sterilization and disinfection, inhibiting the growth of microorganisms.

[0123] Photocatalytic decomposition device: A photocatalyst (such as TiO2) and an ultraviolet lamp are placed in the air duct to decompose ethylene into carbon dioxide and water.

[0124] The user interaction and early warning module provides users with fruit and vegetable freshness reports and spoilage warnings via a mobile app or refrigerator door screen.

[0125] The central processing unit, acting as the system's brain, integrates multimodal sensor data to assess current freshness; it also runs decision-making algorithms to coordinate the work of each module.

[0126] The power module supplies power to all electronic components.

[0127] like Figure 6 As shown, taking a drawer (storage space) as an example, the drawer is equipped with an ultraviolet-ozone (UV-O3) synergistic sterilization module 8, a multispectral imaging sensor (multispectral camera 9), temperature and humidity control, a photocatalytic decomposition device 11, a gas sensor array 12, a high-precision weighing sensor 13, and a temperature and humidity sensor 7.

[0128] like Figure 7 As shown, the main preservation control process of the refrigerator is as follows.

[0129] When the system is powered on or the user opens the door, fresh fruits and vegetables are placed in the corresponding drawer. First, the type of fruits and vegetables is identified by a multispectral imaging sensor, or the type of fruits and vegetables is input by the user. Then, the weight is weighed, the independent initial weight of the placed fruits and vegetables is calculated, and an initial image is taken. Then, the system waits for the door to open to trigger the event. If fresh fruits and vegetables are placed in again, the previous steps are repeated to obtain the independent initial weight of the newly placed fruits and vegetables.

[0130] If no door opening event is triggered, the timer reaches a sampling period, collects the freshness influencing factors in the drawer, calculates the score of the freshness influencing factors, then calculates the freshness of each fruit and vegetable in the drawer, and then makes targeted intelligent decisions and interventions.

[0131] like Figure 8 As shown, the main process of intelligent control based on the freshness of fruits and vegetables is as follows.

[0132] The freshness of fruits and vegetables, also known as the comprehensive freshness index (F), is a weighted function of multiple parameters such as weight loss rate, image morphological change score, ethylene concentration in the storage space, and VOCs concentration.

[0133] The specific calculation formula is F = 100 - (W) weight ×L w_norm + I _weight ×S i_norm + E weight ×E norm + V weight ×V norm ).

[0134] F represents freshness, ranging from 0 to 100, with higher values ​​indicating fresher products.

[0135] W weight ,I weight E weight V weight : These are the weight coefficients for weight, image, ethylene, and VOCs, respectively, and their sum is 1;

[0136] Among them, the image weight coefficient for calculating the F-value of fruits in low-temperature refrigerated drawers is the largest for berries that are prone to water loss, while the weight loss weight coefficient is the largest for other fruits and vegetables.

[0137] L w,norm ,S i,norm E norm V norm These represent the normalized degradation degree of the corresponding parameter, ranging from 0 to 1 (0 = fresh, 1 = rotten).

[0138] When users place fruits and vegetables into designated drawers (storage spaces), they can manually select the types of fruits and vegetables via the refrigerator door panel or a mobile app, or the multispectral camera can automatically determine the types through image recognition and adjust the condition parameters inside the drawer according to the pre-stored optimal storage conditions. Based on the user's door opening action, a high-precision weighing sensor is automatically triggered to record the independent initial weight W0 of the placed fruits and vegetables, while the multispectral camera captures an independent initial image I0. The system uses this as a baseline for the quality and appearance of the placed fruits and vegetables and retrieves the optimal storage parameters from a preset knowledge graph.

[0139] The refrigerator's intelligent vegetable preservation system triggers sensor readings according to a sampling cycle, collecting data on the weight of fruits and vegetables, images, and gas levels in the drawer (e.g., data is collected every 2-4 hours), and generating a structured data packet containing a timestamp. A similar structured data packet containing a timestamp is generated when new fruits and vegetables are added. For example, if the drawer door is closed and the high-precision weighing sensor reading shows a significant positive change (e.g., an increase > 20g), the system determines that new fruits and vegetables have been added. The system automatically creates a new structured data packet containing a timestamp, including: batch ID (based on timestamp), category information (via image recognition or user selection), and an independent initial weight W. 0 i Initial recording time t 0 i , where i represents the serial number of the newly added fruits and vegetables.

[0140] The system can then score the freshness factors affecting each type of fresh produce based on structured data packets containing timestamps.

[0141] When the freshness influencing factor is weight change, the system performs the following processing at sampling time t in each sampling cycle.

[0142] Read current total weight: W total (t);

[0143] Calculate the independent theoretical weight W of each fruit and vegetable. est i (t); Since the fruits and vegetables in the same drawer cannot be directly physically separated and weighed, an estimation algorithm based on the theoretical water loss model and contribution allocation is used to calculate the independent theoretical weight of the fruits and vegetables.

[0144] For each fruit / vegetable i, based on its type and the current measured temperature and humidity in the drawer, query its theoretical water loss rate model f under this environment. i (T,H,t), temperature, humidity, and sampling time, to calculate the cumulative water loss ratio. This model can be built based on empirical formulas in the category knowledge base (e.g., the average daily water loss rate of leafy vegetables at 4°C and 90%RH is approximately 0.5%-1.5%).

[0145] Discrete integration yields the cumulative water loss ratio: ∫f i dk ≈ Σ [f i (T k H k ) × Δt k (k is for each sampling point);

[0146] Independent theoretical weight: W est i (t) = W 0 i × (1 - cumulative water loss percentage);

[0147] Calculate and estimate the total weight and deviation;

[0148] Estimated total weight: W est total (t) = Σ W est i (t) (the sum of the estimated weights of all fruits and vegetables).

[0149] Calculate the deviation between the actual and estimated total weight: Δ(t) = W total (t) - W est total (t).

[0150] If Δ(t)>0: it means that the actual total weight is heavier than the predicted weight, which may be due to newly added fruits and vegetables not being identified, or some fruits and vegetables losing water more slowly than expected;

[0151] If Δ(t) < 0: it means that the actual weight is lighter than predicted, some fruits and vegetables lose water faster, or there is unexpected loss (such as rotting or evaporation).

[0152] Disparities are allocated based on contribution.

[0153] The deviation Δ(t) is allocated proportionally to the estimated weight of each batch to obtain the corrected current independent theoretical weight of each fruit and vegetable:

[0154] W corr i (t) = W est i (t) + [W est_i (t) / W est total [(t)]×Δ(t);

[0155] Calculate the weight loss rate of each fruit and vegetable: L w i (t) = (W 0 i - W corr i (t)) / W 0 i ×100%.

[0156] Besides calculating the weight loss rate as a measure of weight change, the weight loss speed can also be calculated. For example, WL_r = L w / t;d²WL_r / dt²=Δ(WL_r) / Δt.

[0157] L w The weight loss rate of a certain fruit or vegetable;

[0158] t is the number of days;

[0159] WL_r is the weight loss rate;

[0160] ²WL_r / dt² represents the acceleration due to weight loss.

[0161] When there are multiple kinds of fruits and vegetables in a drawer, the preservation strategy corresponding to the fruit or vegetable with the lowest freshness F value is selected as the decision input.

[0162] When F≥F阈 Time (F) 阈 The threshold for F is used to determine the dominant factors that cause fruit and vegetable spoilage, which are weight, ethylene concentration, and VOCs concentration, in that order.

[0163] like Figure 9 As shown, when the weight loss rate L W >L 阈 At that time, it was labeled as "water loss-dominated" corruption, and water conservation strategies were implemented.

[0164] When the weight loss rate of fruits and vegetables is at (L) 阈 When the set temperature is L2, the weight loss rate is relatively low, slightly exceeding the threshold. At this point, you can choose to lower the set temperature or increase the set humidity for fine-tuning.

[0165] When the weight loss rate of fruits and vegetables is in the range of (L2~L1), the weight loss rate is moderate, and the set temperature can be slightly reduced and the set humidity increased.

[0166] When the weight loss rate of fruits and vegetables is greater than L1, it indicates that the water loss is too fast, and it is necessary to significantly reduce the set temperature and increase the set humidity.

[0167] After implementing the water retention strategy, a sterilization strategy can also be implemented.

[0168] The aforementioned increase in humidity or decrease in temperature can be set by those skilled in the art according to the control conditions corresponding to different types of fruits and vegetables.

[0169] If the weight loss rate is less than the threshold, it can also be determined whether the weight loss acceleration is greater than the acceleration threshold. If so, an acceleration water retention strategy can be executed, which will lower the set temperature by ΔT' and raise the set humidity by ΔH'. ΔT' can be assigned a value of 0~2℃ and ΔH' can be assigned a value of 2~5%RH.

[0170] If the acceleration due to weight loss is less than or equal to the acceleration threshold, determine the ethylene concentration.

[0171] like Figure 10 As shown, if the ethylene concentration is greater than the ethylene concentration threshold, it is marked as "gas-dominant" corruption, and a gas purification strategy is implemented.

[0172] The ethylene concentration inside the drawer is at (C) E阈 ~ C E1 At that time, C E阈 To achieve the ethylene concentration threshold, the photocatalytic device operates intermittently at low power (running for t1 minutes / stopping for t2 minutes) to preventively regulate the ethylene concentration, i.e., the prevention mode.

[0173] When the ethylene concentration is greater than C E1In this situation, the photocatalytic device operates in emergency mode, running at high power continuously until the concentration drops to C. E2 The system then operates intermittently at low power to reduce energy consumption and extend catalyst life; a mild sterilization strategy is simultaneously executed during low-power operation: the UV-O3 synergistic sterilization module operates continuously at the lowest power.

[0174] Where C E1 >C E2 >C E阈 In one specific embodiment, the low power can be 30-50% of the rated power, and the high power can be 100% of the rated power.

[0175] model Power settings Operational strategy Applicable Scenarios Energy saving mode 0% (Off) Sensor powered only Concentration ≤ 0.5 ppm (e.g., newly stored immature fruits and vegetables) Prevention mode 30% of rated power 15-minute run / 45-minute shutdown Concentration 0.5-1.0 ppm (e.g., early stage of apple / pear processing) Emergency mode 100% rated power Continue operation until the concentration is ≤0.8 ppm. Concentration > 1.0 ppm (e.g., during the ripening period of bananas / kiwis)

[0176] Table 1. Operating modes of the photocatalytic device

[0177] When the ethylene concentration C E ≤C E阈 At that time, it is determined whether the acceleration of ethylene concentration growth d(RC) / dt is significantly positive, that is, whether it is greater than the threshold of ethylene concentration growth acceleration. RC is the rate of increase of ethylene concentration. If so, the system predicts "potential rapid over-ripening risk" and starts the acceleration gas purification strategy: the photocatalytic device operates intermittently at low power (runs for t1' minutes / stops for t2' minutes).

[0178] Among them, t1' < t1, t2' > t2, and t1' and t2' together total approximately 60 minutes.

[0179] like Figure 11 As shown, if the acceleration of ethylene concentration growth is not significantly positive, the VOCs concentration is further assessed. When the VOCs concentration exceeds the VOCs concentration threshold (C... V阈 When the spoilage is classified as "microbial-dominated," a sterilization strategy is implemented.

[0180] When the concentration of characteristic VOCs gases in the drawer is at (C V阈 C V1 When [the UV-O3 synergistic sterilization module is in operation, it operates continuously at the lowest power].

[0181] When the concentration is at (C) V1 C V2 At this time, the UV-O3 synergistic sterilization module operates continuously at medium power.

[0182] When the concentration is greater than C V2 During this period, the UV-O3 synergistic sterilization module operates at full power to rapidly kill surface microorganisms. The humidity controller remains off during this time to prevent the growth of microorganisms. Simultaneously, it is linked to ozone concentration monitoring; when the detected ozone concentration exceeds C... O1It automatically switches to medium power operation and simultaneously implements a gentle water retention strategy: the humidity controller is activated to perform a small humidification ΔH1 to compensate for possible moisture loss during sterilization.

[0183] Among them, C V2 >C V1 >C V阈 In one specific embodiment, C O1 It can be assigned a value of 0.04 ~ 0.05 ppm, and the minimum power can be 10. ~15% of rated power, medium power can be 50 ~55% of rated power, ΔH1 can be assigned a value of 0.4~0.6℃.

[0184] When the VOCs gas concentration C E ≤C E阈 When VOCs concentration increases, the system determines whether the acceleration d(RCv) / dt is significantly positive, i.e. whether it is greater than the VOCs concentration increase acceleration threshold. RCv is the rate of increase of VOCs gas concentration. If so, the system predicts "potential rapid spoilage risk" and activates the acceleration sterilization strategy: the UV-O3 synergistic sterilization module runs continuously at the lowest power.

[0185] When d(RCv) / dt is not significantly positive, it is marked as "state stable" and no intervention is required.

[0186] When the freshness F of a certain fruit or vegetable is less than the freshness threshold F 阈 When the vegetables are about to spoil, the system sends a consumption reminder to the user and activates the "compound intervention" mode: the temperature control device will lower the set temperature by ΔT, the humidity control device will increase the set humidity by ΔH, and the photocatalytic device and UV-O3 synergistic sterilization module will operate at full power.

[0187] The effects of all interventions are captured by data collection in the next cycle (e.g., "cooling ΔT1, humidification ΔH1, photocatalytic power P1 running for t1 minutes"), and mapped to the improvement rate of each spoilage indicator in the subsequent monitoring cycle, forming a strategy-effect history graph. When encountering similar fruit and vegetable types and spoilage diagnoses again, the system prioritizes calling and fine-tuning the best-performing strategy from the history graph, rather than starting with the default strategy each time, forming a closed-loop control. When a fruit or vegetable is removed, it is removed from the list.

[0188] Based on the above technical solutions, the specific optimal storage environment required by different fruits and vegetables (such as leafy vegetables requiring high humidity and bananas requiring low ethylene) can be precisely adjusted. Moreover, the weight of each fruit and vegetable can be monitored, and key spoilage factors such as ethylene gas (ripening agent) concentration and microbial (bacteria, mold) growth can be monitored and actively intervened. Furthermore, the power can be adjusted according to different concentrations, resulting in low energy consumption and minimal damage to fruits and vegetables.

[0189] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for confirming the freshness of fresh produce, characterized in that, include: Within each sampling period, the freshness influencing factors of each fresh food item in the storage space are scored; the freshness influencing factors include changes in the weight of the fresh food and changes in its image. The freshness of each fresh food is calculated based on the scores and weights of the various freshness influencing factors. The weight change of the fresh produce was obtained using the following steps: When each fresh food item is placed into the storage space for the first time, the total weight of the fresh food items in the storage space is weighed. Based on the total weight of the fresh food items in the previous weighing, the independent initial weight of each fresh food item when it is first placed into the storage space is calculated. Within each sampling period, the current total weight of fresh produce in the storage space is obtained; Based on the current total weight of fresh produce, the independent initial weight of each fresh produce, and the water loss rate model under the current environment, estimate the independent current weight of each fresh produce. The weight change of each fresh produce is calculated based on its current independent weight and initial independent weight.

2. The method for confirming the freshness of fresh produce as described in claim 1, characterized in that, Based on the current total weight of fresh produce, the independent initial weight of each fresh produce, and the water loss rate model under the current environment, the independent current weight of each fresh produce is estimated as follows: Based on the water loss rate model of each fresh food, the current ambient temperature, humidity, and storage time of each fresh food, the theoretical weight loss of each fresh food is calculated. Subtract the theoretical weight loss from the individual initial weight of each fresh produce to obtain the individual theoretical weight of each fresh produce, as well as the total theoretical weight of fresh produce in a storage space. Subtract the total theoretical weight of the fresh produce from the current total weight of the fresh produce in the storage space to obtain the total weight deviation; Based on the proportion of the independent theoretical weight of each fresh produce in the total theoretical weight of fresh produce, the total weight deviation is allocated to the independent theoretical weight of each fresh produce to obtain the independent current weight of each fresh produce.

3. The method for confirming the freshness of fresh produce as described in claim 1, characterized in that, Based on the independent current weight and independent initial weight of each fresh produce, the formula L is used. w,norm = min( max((L w - L w,fresh ) / (L w,spoiled - L w,fresh The weight changes of each fresh produce were calculated using the formulas ), 0, and 1), L. w,norm For weight loss normalized degradation, L w L represents the current weight loss rate. w,fresh L represents the weight loss rate in the fresh state. w,spoiled This represents the weight loss rate under putrefactive conditions.

4. The method for confirming the freshness of fresh produce as described in claim 1, characterized in that, The image changes were calculated using the following steps: Within each sampling period, an independent current image of each fresh produce is acquired, and current image features of each fresh produce are extracted. The image features include at least one of color saturation and texture. Using formula S i,norm = min(max((S i,current - S i,fresh ) / (S i,spoiled - S i,fresh The image changes are calculated using the formulas ),0),1); S i,norm S is a normalized score for image degradation of fresh produce. i,current S represents the current image features of fresh produce. i,fresh S represents the image features of fresh produce in its fresh state. i,spoiled Image features of fresh produce in a rotten state.

5. The method for confirming the freshness of fresh produce as described in any one of claims 1 to 4, characterized in that, The factors affecting freshness also include changes in ethylene concentration within the storage space; The change in ethylene concentration is expressed by formula E. norm = min(max((E current - E background ) / (E threshold - E background E is calculated as follows: ),0),1) norm E represents the normalized degradation degree of ethylene concentration. current E represents the measured ethylene concentration within the current sampling period. background E represents the ethylene concentration value of fresh produce in the storage space under fresh conditions. threshold This represents the threshold value for ethylene concentration within the storage space.

6. The method for confirming the freshness of fresh produce as described in claim 5, characterized in that, E background The average ethylene concentration value of each fresh food item in its fresh state within the storage space, and / or, E threshold This represents the minimum ethylene concentration threshold for each type of fresh food within the storage space.

7. The method for confirming the freshness of fresh produce as described in any one of claims 1 to 4, characterized in that, The factors affecting freshness also include changes in VOCs concentration within the storage space; The VOCs concentration change is expressed by formula V norm = min( max((V current - V background ) / (V threshold - V background V is calculated as follows: ),0),1) norm VOCs concentration normalized degradation degree, V current V represents the measured concentration of VOCs within the current sampling period. background VOCs concentration value of fresh produce in the storage space under fresh conditions. threshold The threshold value for VOCs concentration within the storage space.

8. The method for confirming the freshness of fresh produce as described in claim 7, characterized in that, V background The average VOCs concentration value is the value of each fresh food item in its fresh state within the storage space. threshold This refers to the minimum VOCs concentration threshold for each type of fresh food within the storage space.

9. A control method for a refrigeration appliance, characterized in that, include: The freshness of each fresh food in each storage space is calculated using the fresh food freshness confirmation method as described in any one of claims 1 to 7. The system determines whether the freshness of each fresh food item is below its freshness threshold. If the freshness of a certain fresh food item is below its freshness threshold, the system will notify the user and lower the temperature, increase the humidity, and perform photocatalysis and sterilization treatments in the storage space where the fresh food item is located.

10. The control method for a refrigeration appliance as described in claim 9, characterized in that, If the freshness of each fresh food is greater than its freshness threshold, then it is determined in turn whether the freshness influencing factor of each fresh food exceeds its corresponding threshold. If it does, then a corresponding control strategy is adopted. The control strategy includes at least one of the following: a water retention strategy for regulating temperature and humidity, a gas purification strategy for removing corresponding gases in the storage space, and a sterilization strategy for sterilizing the storage space.

11. A refrigeration appliance, comprising a controller, at least one storage space for storing fresh produce, and a detection device for detecting factors affecting freshness within the storage space, characterized in that, Based on the detection data from the detection device, the controller controls the air environment of the corresponding storage space using the control method for refrigeration appliances as described in claim 9 or 10.

12. The refrigeration appliance as claimed in claim 11, characterized in that, The storage space includes multiple compartments, each storing one type of fresh produce.

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