Intelligent partition management system for refrigerator

Abstract

The invention belongs to the technical field of inventory management, and particularly discloses a refrigerator intelligent partition management system which comprises a partition sales management detection module, a refrigerator partition regulation and control module, a data monitoring analysis module and a prediction evaluation early warning module. According to the invention, the sales condition of each partition in the refrigerator within the preset time period T is monitored, and the moving distance prediction evaluation value Pem of the corresponding layered plate is obtained according to the two partitions with the maximum sales volume and the minimum sales volume, so that the corresponding layered plate in the refrigerator can be accurately and effectively adjusted according to the moving distance prediction evaluation value Pem, and the adjustment accuracy of the refrigerator is improved. The volume of the subarea with small sales volume is reduced, so that the volume of the subarea with large sales volume is expanded, reasonable utilization and management of the limited space in the refrigerator are realized, the sales trend of different types of goods in the future is coped, and the intelligent design of the management system is embodied.

Description

Technical Field

[0001] The invention belongs to the technical field of inventory management, and in particular relates to an intelligent partition management system for refrigerators. Background Art

[0002] Refrigerator management technology refers to an application technology that uses various technical means and methods to effectively manage and monitor refrigerators. The main purpose is to ensure the good condition of the temperature, hygiene, cargo storage and other aspects inside the refrigerator, and improve the efficiency and safety of the refrigerator. The zoning management inside the refrigerator can be implemented according to different needs and situations. For example, the refrigerated area, frozen area and normal temperature area are divided according to temperature requirements, and the meat area, vegetable area or beverage area are divided according to the classification of goods. Each area can be equipped with specific temperature control equipment, shelves or storage tools to better store and manage different types of goods. The zoning management inside the refrigerator can also be combined with other technical means, such as barcode or RFID tag recognition, temperature control system, pipeline layout, etc., to achieve real-time monitoring and data management of different areas.

[0003] When dealing with the actual storage of food goods, refrigerators are needed for storage. Different types of goods need to be stored in partitions in the refrigerator to ensure smooth handling of goods and reduce the occurrence of wrong taking. However, when managing the refrigerator in partitions, due to the fact that a certain type of goods is popular in reality, the original storage space is insufficient. If the goods in the refrigerator are frequently replenished, the time of contact between the goods in the refrigerator and the outside world will increase, which in turn increases the possibility of contamination of the environment in the refrigerator. The specific status of the sanitary environment in the refrigerator is usually manually observed and controlled. If there is a misjudgment, it will lead to further cross-contamination of the hygiene in the refrigerator, resulting in more losses. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent partition management system for refrigerators, which can achieve reasonable utilization and management of limited space in the refrigerators to cope with future sales trends of different types of goods.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a refrigerator intelligent partition management system, comprising: The partition sales management detection module is used to detect and obtain the daily sales volume of each partition within a preset time period T, and summarize the total sales volume of each partition within the time period T, marking the partitions with the largest and smallest total sales volume, wherein the partition is to set a number of partitioning layers in the refrigerator to divide the refrigerator into several partitions; The refrigerator partition control module is used to obtain the maximum total sales volume and the minimum total sales volume after preprocessing according to the marking results, calculate and generate the moving distance prediction evaluation value Pem, and perform the adjustment control of the corresponding layered plate according to the moving distance prediction evaluation value Pem; The data monitoring and analysis module is used to obtain the bacterial concentration in the refrigerator, the number of times the refrigerator door is opened and closed, and the continuous working time of the ultraviolet light in the refrigerator within a day under the condition that the temperature and humidity in the refrigerator are within the corresponding standard range values, and extract the sales volume of the goods in the refrigerator on that day, and calculate and generate the hygienic assessment index Hai of the refrigerator on that day; The prediction evaluation and early warning module compares the hygienic evaluation index Hai of the refrigerator on that day with the preset evaluation threshold group, which includes the first evaluation threshold and the second evaluation threshold ,and ,exist When the first level warning signal is issued, the preset first management strategy will be implemented; A secondary warning signal is issued and the preset second management strategy is executed.

[0006] Preferably, the layered plates in the refrigerator in the initial state divide the space in the refrigerator equally, so that the same type of goods are stored in each partition, and the types of goods stored in each partition are different.

[0007] Preferably, the process of detecting and obtaining the daily sales volume in each partition is as follows: a weighing sensor is embedded under each partition to measure the weight of the goods stored in the upper partition. The daily sales volume in each partition is the difference between the initial weight of the partition when it is fully stored with goods and the weight of the goods stored at the end of the day.

[0008] Preferably, the process of preprocessing the maximum total sales volume and the minimum total sales volume is: performing dimensionless processing on the maximum total sales volume and the minimum total sales volume, and calculating the adjustment coefficient Aco of the layered plate before generating the moving distance prediction evaluation value Pem; According to the maximum total sales volume and the minimum total sales volume after preprocessing, the formula for generating the adjustment coefficient Aco of the layered board is as follows: ; In the formula, Indicates the maximum total sales volume of the corresponding partition, Indicates the minimum total sales volume for the corresponding partition.

[0009] Preferably, the moving distance prediction evaluation value Pem is generated according to the adjustment coefficient Aco of the layered plate, and the formula based on it is as follows: ; In the formula, is a constant correction factor.

[0010] Preferably, the bacterial concentration in the refrigerator is detected by a biosensor at a fixed time of the day, the number of times the refrigerator door is opened and closed is detected by installing a door magnetic sensor on the refrigerator door, and the continuous working time of the ultraviolet lamp in the refrigerator is obtained by installing an ultraviolet lamp sensor in the ultraviolet lamp to monitor the switch status of the ultraviolet lamp and configuring a timer to record the switch interval time.

[0011] Preferably, after dimensionless processing of the bacteria concentration in the refrigerator, the number of times the refrigerator door is opened and closed, the continuous working time of the ultraviolet lamp in the refrigerator, and the sales volume of the goods in the refrigerator on that day, the hygienic assessment index Hai of the refrigerator on that day is generated, and the calculation formula is as follows: ; In the formula, Xn represents the bacterial concentration in the refrigerator, Cs represents the number of times the refrigerator door is opened and closed, Zg represents the continuous working time of the ultraviolet light in the refrigerator, and Xl represents the sales volume of the goods in the refrigerator on that day. are the preset ratio coefficients of the concentration of bacteria in the refrigerator, the number of times the refrigerator door is opened and closed, the continuous working time of the ultraviolet light in the refrigerator, and the sales volume of the goods in the refrigerator on that day, and , is a constant correction factor.

[0012] Preferably, after comparing the hygienic evaluation index Hai of the refrigerator on that day with the preset evaluation threshold group, if , no response action is taken.

[0013] Preferably, the preset first management strategy is: based on the health assessment index Hai of the refrigerator on that day and the first assessment threshold The difference between the values ​​of and is used to generate the inspection frequency prediction value Cfp of the corresponding refrigerator. The formula is as follows: ; In the formula, A represents the initial inspection frequency of the corresponding refrigerator, that is, the current inspection frequency, e represents the natural constant, and B represents the adjustment factor. Represents the difference in health assessment index.

[0014] Preferably, the preset second management strategy is: after emptying the goods in the refrigerator and cleaning and disinfecting the refrigerator, check the emptied goods, and put the goods that have passed the inspection back into the refrigerator. When checking the emptied goods, the goods whose packaging is not damaged and have no peculiar smell are qualified goods, otherwise they are unqualified goods.

[0015] The present invention has the following beneficial effects: The present invention monitors the sales situation of each partition in the refrigerator within a preset time period T, and obtains the movement distance prediction evaluation value Pem of the corresponding layer plate according to the two partitions with the largest and smallest sales volumes, so that the corresponding layer plate in the refrigerator can be accurately and effectively adjusted according to the movement distance prediction evaluation value Pem, and the volume of the partition with small sales volume is reduced to expand the volume of the partition with large sales volume, thereby realizing the rational use and management of the limited space in the refrigerator to cope with the future sales trends of different types of goods, which reflects the intelligent design of the management system.

[0016] While automatically zoning the refrigerator, the present invention also monitors the daily sanitary status of the refrigerator in real time. Under the condition of ensuring that the temperature and humidity in the refrigerator are reasonable, various factors reflecting the sanitary conditions in the refrigerator are comprehensively considered, and the sales volume data used when zoning the refrigerator is also utilized to further ensure the rationality and accuracy of the generated sanitary evaluation index Hai. After comparing and evaluating the sanitary evaluation index Hai, the specific situation of the current sanitary status in the refrigerator can be efficiently determined, and targeted strategies can be given to strengthen the management of the refrigerator to ensure that the refrigerator remains in normal use. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the modular structure of the intelligent partition management system of refrigerators in the present invention; Figure 2 This is a schematic diagram of the partition state in the refrigerator of the present invention; Figure 3 The figure is a flowchart of the overall steps of the method for intelligent zoning management of refrigerators in the present invention. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the accompanying drawings.

[0019] Example 1: Figure 1 and Figure 2 As shown, a refrigerator intelligent zoning management system includes a zoning sales management detection module, a refrigerator zoning control module, a data monitoring and analysis module, and a prediction, evaluation and early warning module. The application scenario of the entire system is to perform zoning adjustment management on the sales volume of goods in each zone in the refrigerator and to perform early warning or inspection management according to the sanitary conditions in the refrigerator. The goods in the refrigerator are usually foods wrapped in cartons, so accurate and intelligent zoning management is required to ensure the safety of the storage process.

[0020] The partition sales management detection module is used to detect and obtain the daily sales volume of each partition within a preset time period T, and summarize the total sales volume of each partition within the time period T, marking the partitions with the largest and smallest total sales volume, wherein the partition is to set a number of partitioning layers in the refrigerator to divide the refrigerator into several partitions; Among them, the partitions in the refrigerator adopt a multi-layer partition method. Figure 2 It can be seen that each layer board installed in the refrigerator is used to support and store the same type of food goods. The volume of each partition in the initial state is consistent, and the types of food goods stored in each partition are different. Figure 2 Among them, Z1, Z2, and Z3 represent partitions respectively.

[0021] The preset time period T is set according to the actual storage time of the refrigerator.

[0022] The process of detecting and obtaining the daily sales volume in each partition is as follows: Weighing sensors are embedded and installed under each partition. For example, except for the bottom partition, the weighing sensors installed in each layer plate are used to measure the weight of the goods stored in the upper partition. The bottom partition needs to install a weighing sensor in the refrigerator to complete the detection of the weight of the goods stored in the upper partition. The daily sales volume in each partition is the difference between the initial weight of the goods stored in the partition and the weight of the goods stored at the end of the day. The difference is the daily sales volume of the corresponding partition.

[0023] Since the storage capacity of the freezer is large, the total sales volume of each partition within the time period T can be summarized without replenishing, which means the cumulative sum of the sales volume of the corresponding partitions every day within the time period T. For example, the total sales volume values ​​of each partition distributed from top to bottom are 70kg, 30kg, 50kg, and 20kg, respectively. The top partition is marked as the partition with the largest total sales volume, and the bottom partition is marked as the partition with the smallest total sales volume.

[0024] The refrigerator partition control module is used to obtain the maximum total sales volume and the minimum total sales volume after preprocessing according to the marking results, calculate and generate the moving distance prediction evaluation value Pem, and perform adjustment and control of the corresponding layered plate according to the moving distance prediction evaluation value Pem.

[0025] The process of preprocessing the maximum total sales volume and the minimum total sales volume is as follows: dimensionlessly processing the maximum total sales volume and the minimum total sales volume and removing data units to facilitate subsequent calculation and processing.

[0026] The process of generating the moving distance prediction evaluation value Pem is as follows: S101. Generate the adjustment coefficient Aco of the layered board according to the maximum total sales volume and the minimum total sales volume after preprocessing, and the formula based on it is as follows: ; In the formula, Indicates the maximum total sales volume of the corresponding partition, Indicates the minimum total sales volume of the corresponding partition; S102, based on the adjustment coefficient Aco of the layered plate, generate a moving distance prediction evaluation value Pem, the formula is as follows: ; In the formula, is a constant correction coefficient, the specific value of which can be adjusted by the user or generated by analytical function fitting, and The value range is 0~1.

[0027] For example, if the refrigerator has three layers, from top to bottom, they are A layer, B layer, C layer (i.e. Z1, Z2, Z3), the initial weight and change of each partition are: A layer: initial weight is 100kg, change is 10kg, B layer: initial weight is 120kg, change is 15kg, C layer: initial weight is 150kg, change is 5kg, so the adjustment coefficient Aco=(15-5) / (15+5)=0.5, at this time the actual constant correction coefficient If the value is 0.1, the moving distance prediction evaluation value Therefore, the layering plate between the B layer and the C layer is moved down by 0.12m, so that the storage capacity of the B layer corresponding to the large change becomes larger, and the storage capacity of the C layer corresponding to the small change becomes smaller, so as to better manage and organize the layout of goods. A large change means that the corresponding type of goods is selling well. Through layout adjustment, according to the prediction of the future sales of goods, it is guaranteed that the best-selling goods have sufficient quantity and storage space.

[0028] For the configuration of each layer plate in the refrigerator, stepping mechanisms are installed on both sides of the layer plates. The screw rod in the stepping mechanism passes through the layer plate, and is driven by the stepping motor to rotate the screw rod. By changing the rotation direction of the stepping motor, the corresponding layer plate moves up and down in the refrigerator. The distance of up and down movement can be determined according to the number of rotations of the stepping motor. Since the stepping mechanism and other structures belong to conventional settings, they are not marked in the figure.

[0029] By monitoring the sales situation of each partition in the refrigerator within a preset time period T, the moving distance prediction evaluation value Pem of the corresponding layer plate is obtained according to the two partitions with the largest and smallest sales volume. The corresponding layer plate in the refrigerator can be accurately and effectively adjusted according to the moving distance prediction evaluation value Pem, and the volume of the partition with small sales volume can be reduced to expand the volume of the partition with large sales volume, thereby realizing the rational utilization and management of the limited space in the refrigerator to cope with the future sales trends of different types of goods, which reflects the intelligent design of the management system.

[0030] The data monitoring and analysis module is used to obtain the bacterial concentration in the refrigerator, the number of times the refrigerator door is opened and closed, and the continuous working time of the ultraviolet light in the refrigerator within a day under the condition that the temperature and humidity in the refrigerator are within the corresponding standard range values, and extract the sales volume of the goods in the refrigerator on that day, and calculate and generate the hygienic assessment index Hai of the refrigerator on that day; Among them, the temperature in the freezer is an important parameter that affects the storage and preservation of food and goods. Generally speaking, the temperature of the freezer should be kept between 0℃ and 4℃. Too high or too low a temperature may cause food to deteriorate, rot or freeze. Therefore, the standard range value corresponding to the temperature is 0~4℃. For example, if the temperature in the freezer is 8℃, which exceeds the suitable storage temperature range of food, it will cause vegetables to lose water faster and fruits to become soft and rotten. The humidity in the freezer also plays an important role in the storage and preservation of food. The humidity in the freezer should be kept at 75%~85%. The appropriate humidity can maintain the moisture of the food and prevent the food from drying out or being too wet. For example, if the humidity in the freezer is 61%, the surface of the food will be dehydrated and the texture will become hard. On the contrary, too high humidity may cause the food to become damp and breed mold. Therefore, when the temperature and humidity in the freezer exceed the corresponding standard range, the freezer will automatically send an early warning signal and adjust the temperature or humidity in time to ensure the smooth storage of the freezer.

[0031] The bacterial concentration in the refrigerator indicates the bacterial concentration in the refrigerator after a day's operation at a fixed time of the day, such as 12 o'clock in the morning. The bacterial concentration in the refrigerator can be detected by installing a biosensor in the refrigerator. The biosensor usually uses biological materials and biological components to interact with bacteria, and quantitatively or qualitatively detects the bacterial concentration by measuring the signals generated by biological reactions. The biosensors used include immunosensors, enzyme sensors, and cell sensors. In this application, enzyme sensors are used to effectively detect the bacterial concentration in the refrigerator; the bacterial concentration in the cabinet is an important parameter for measuring the sanitary condition of the refrigerator. Excessive bacterial concentration may cause food contamination and spread diseases. For example, the bacterial concentration in the refrigerator is 100 cfu / cm², which is low and meets food safety standards. The quality and safety of food are guaranteed.

[0032] A door magnetic sensor is installed on the refrigerator door to record each door opening and closing action. A UV lamp sensor is installed in the UV lamp to monitor the lamp status and record the switch time of the lamp by configuring a timer. Each sensor transmits data to the database and extracts the number of times the refrigerator door is opened and closed and the duration of continuous operation of the UV lamp in the refrigerator. The sales volume of the goods in the refrigerator on that day represents the sum of the sales volume of the goods in each partition of the refrigerator, that is, the sum of the difference between the weight of each partition from the initial moment when the goods are fully stored and the weight of the goods stored at the end of the day.

[0033] After dimensionless processing of the bacteria concentration in the refrigerator, the number of times the refrigerator door is opened and closed, the continuous working time of the ultraviolet light in the refrigerator, and the sales volume of the goods in the refrigerator on that day, the hygienic assessment index Hai of the refrigerator on that day is generated. The calculation formula is as follows: ; In the formula, Xn represents the bacterial concentration in the refrigerator, Cs represents the number of times the refrigerator door is opened and closed, Zg represents the continuous working time of the ultraviolet light in the refrigerator, and Xl represents the sales volume of the goods in the refrigerator on that day. are the preset ratio coefficients of the concentration of bacteria in the refrigerator, the number of times the refrigerator door is opened and closed, the continuous working time of the ultraviolet light in the refrigerator, and the sales volume of the goods in the refrigerator on that day, and In this embodiment, , is a constant correction coefficient, the specific value of which can be adjusted by the user or generated by analytical function fitting, and The value range is 0~1; The higher the bacteria concentration Xn in the refrigerator, the worse the sanitary state in the refrigerator, and the higher the sanitary assessment index Hai of the refrigerator on that day. Therefore, the bacteria concentration Xn in the refrigerator is proportional to the sanitary assessment index Hai of the refrigerator on that day. The more times Cs the refrigerator door is opened and closed, the longer the refrigerator is in contact with the outside air, the higher the possibility of contamination in the refrigerator, and the higher the sanitary assessment index Hai of the refrigerator on that day. Therefore, the number of times Cs the refrigerator door is opened and closed is proportional to the sanitary assessment index Hai of the refrigerator on that day. The longer the continuous working time Zg of the ultraviolet lamp in the refrigerator, the better the sanitary state in the refrigerator may be, and the lower the sanitary assessment index Hai of the refrigerator on that day. Therefore, the continuous working time Zg of the ultraviolet lamp in the refrigerator is inversely proportional to the sanitary assessment index Hai of the refrigerator on that day. The more the sales volume Xl of goods in the refrigerator on that day, the more frequent the door opening and closing and the number of times the goods in the cabinet are contacted increase, which increases the risk of bacterial transmission, and the sanitary state in the refrigerator may be worse. Therefore, the sales volume Xl of goods in the refrigerator on that day is proportional to the sanitary assessment index Hai of the refrigerator on that day.

[0034] The prediction evaluation and early warning module compares the hygienic evaluation index Hai of the refrigerator on that day with the preset evaluation threshold group, which includes the first evaluation threshold and the second evaluation threshold ,and ; if , it means that the sanitary status of the refrigerator is normal on that day, and the system does not respond; if , it means that the sanitary status of the refrigerator may be abnormal on that day, a first-level warning signal is issued, and the preset first management strategy is executed; if , it means that there is an abnormality in the hygiene status of the refrigerator on that day, a second-level warning signal is issued, and the preset second management strategy is executed; the severity of the first-level warning signal is less than that of the second-level warning signal. For example, the first-level warning signal is manifested as a flashing yellow light, flashing at 10Hz, 10 times per second, and the second-level warning signal is manifested as a flashing red light, flashing at 20Hz, 20 times per second.

[0035] Among them, the preset first management strategy is: based on the refrigerator's hygiene assessment index Hai and the first assessment threshold The difference between the values ​​of and is used to generate the inspection frequency prediction value Cfp of the corresponding refrigerator. The formula is as follows: ; In the formula, A represents the initial inspection frequency of the corresponding refrigerator, that is, the current inspection frequency, which is customized according to actual conditions and needs, e represents the natural constant, and B represents the adjustment factor, which is used to control the difference in the hygiene assessment index. The relationship between B and the inspection frequency prediction value Cfp. Its specific value can be adjusted and set by the user, or generated by analytical function fitting, and the value range of B is 1~3.

[0036] The preset second management strategy is: after emptying the goods in the refrigerator and cleaning and disinfecting the refrigerator, check the emptied goods and put the qualified goods back into the refrigerator. When checking the emptied goods, the goods are qualified if the packaging is not damaged and there is no peculiar smell, otherwise they are unqualified.

[0037] While automatically zoning the refrigerator, the daily hygiene status of the refrigerator is monitored in real time. While ensuring that the temperature and humidity in the refrigerator are reasonable, various factors reflecting the hygiene conditions in the refrigerator are comprehensively considered. The sales volume data used when zoning the refrigerator is also utilized to further ensure the rationality and accuracy of the generated hygiene assessment index Hai. After comparing and evaluating the hygiene assessment index Hai, the specific situation of the current hygiene status in the refrigerator can be efficiently determined, and targeted strategies can be given to strengthen the management of the refrigerator and ensure that the refrigerator remains in normal use.

[0038] Example 2: Figure 3 The method for intelligent zoning management of refrigerators is based on the system in Example 1 and includes the following specific steps: S1. A plurality of partitioning boards are arranged in the refrigerator. Within a preset time period T, the daily sales volume of each partition is detected and obtained, and the total sales volume of each partition within the time period T is summarized, and the partitions with the largest and smallest total sales volume are marked; S2. According to the marking result, the maximum total sales volume and the minimum total sales volume after preprocessing are obtained, the moving distance prediction evaluation value Pem is calculated and generated, and the adjustment control of the corresponding layered plate is performed according to the moving distance prediction evaluation value Pem; S3. Under the condition that the temperature and humidity in the refrigerator are within the corresponding standard range, obtain the bacterial concentration in the refrigerator, the number of times the refrigerator door is opened and closed, and the continuous working time of the ultraviolet light in the refrigerator within one day, and extract the sales volume of the goods in the refrigerator on that day, and calculate and generate the hygienic assessment index Hai of the refrigerator on that day; S4, comparing the hygienic assessment index Hai of the refrigerator on that day with a preset assessment threshold group, where the assessment threshold group includes a first assessment threshold and a second assessment threshold, and the first assessment threshold is less than the second assessment threshold; If Hai is less than the first evaluation threshold, it means that the sanitary status in the refrigerator is normal on that day and no response action is taken; if the first evaluation threshold ≤ Hai ≤ the second evaluation threshold, it means that the sanitary status in the refrigerator on that day may be abnormal, a first-level warning signal is issued, and the first management strategy is executed; if the second evaluation threshold is less than Hai, it means that the sanitary status in the refrigerator on that day is abnormal, a second-level warning signal is issued, and the second management strategy is executed.

[0039] In the application, the several formulas involved are all calculated by removing the dimension and taking their numerical values, and the formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The formula is set by technicians in this field according to the actual situation. The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

Claims

1. A refrigerator intelligent partition management system, characterized in that: include: The partition sales management detection module is used to detect and obtain the daily sales volume of each partition within a preset time period T, and summarize the total sales volume of each partition within the time period T, marking the partitions with the largest and smallest total sales volume, wherein the partition is to set a number of partitioning layers in the refrigerator to divide the refrigerator into several partitions; The refrigerator partition control module is used to obtain the maximum total sales volume and the minimum total sales volume after preprocessing according to the marking results, calculate and generate the moving distance prediction evaluation value Pem, and perform the adjustment control of the corresponding layered plate according to the moving distance prediction evaluation value Pem; The data monitoring and analysis module is used to obtain the bacterial concentration in the refrigerator, the number of times the refrigerator door is opened and closed, and the continuous working time of the ultraviolet light in the refrigerator within a day under the condition that the temperature and humidity in the refrigerator are within the corresponding standard range values, and extract the sales volume of the goods in the refrigerator on that day, and calculate and generate the hygienic assessment index Hai of the refrigerator on that day; The prediction evaluation and early warning module compares the hygienic evaluation index Hai of the refrigerator on that day with the preset evaluation threshold group, which includes the first evaluation threshold and the second evaluation threshold ,and ,exist A first-level warning signal is issued and the preset first management strategy is implemented; exist A secondary warning signal is issued and the preset second management strategy is executed.

2. The intelligent partition management system for refrigerators according to claim 1 is characterized in that: In the initial state, the layered plates in the refrigerator evenly divide the space in the refrigerator, so that each partition stores the same type of goods, and the types of goods stored in each partition are different.

3. The intelligent partition management system for refrigerators according to claim 2 is characterized in that: The process of detecting and obtaining the daily sales volume in each partition is as follows: a weighing sensor is embedded under each partition to measure the weight of the goods stored in the upper partition. The daily sales volume in each partition is the difference between the initial weight of the partition when it is fully stored with goods and the weight of the goods stored at the end of the day.

4. The intelligent partition management system for refrigerators according to claim 3 is characterized in that: The process of preprocessing the maximum total sales volume and the minimum total sales volume is as follows: the maximum total sales volume and the minimum total sales volume are dimensionless processed, and the adjustment coefficient Aco of the layered board is calculated before generating the moving distance prediction evaluation value Pem; According to the maximum total sales volume and the minimum total sales volume after preprocessing, the formula for generating the adjustment coefficient Aco of the layered board is as follows: ； In the formula, Indicates the maximum total sales volume of the corresponding partition, Indicates the minimum total sales volume for the corresponding partition.

5. The intelligent partition management system for refrigerators according to claim 4 is characterized in that: According to the adjustment coefficient Aco of the layered plate, the predicted evaluation value Pem of the moving distance is generated, and the formula is as follows: ； In the formula, is a constant correction factor.

6. The intelligent partition management system for refrigerators according to claim 5, characterized in that: The bacterial concentration in the refrigerator is detected by biosensors at fixed times of the day, the number of times the refrigerator door is opened and closed is detected by installing a door magnetic sensor on the refrigerator door, and the continuous working time of the ultraviolet lamp in the refrigerator is obtained by installing an ultraviolet lamp sensor in the ultraviolet lamp to monitor the switch status of the ultraviolet lamp and configuring a timer to record the switch interval.

7. The intelligent partition management system for refrigerators according to claim 6, characterized in that: After dimensionless processing of the bacteria concentration in the refrigerator, the number of times the refrigerator door is opened and closed, the continuous working time of the ultraviolet light in the refrigerator, and the sales volume of the goods in the refrigerator on that day, the hygienic assessment index Hai of the refrigerator on that day is generated. The calculation formula is as follows: ； In the formula, Xn represents the bacterial concentration in the refrigerator, Cs represents the number of times the refrigerator door is opened and closed, Zg represents the continuous working time of the ultraviolet light in the refrigerator, and Xl represents the sales volume of the goods in the refrigerator on that day. are the preset ratio coefficients of the concentration of bacteria in the refrigerator, the number of times the refrigerator door is opened and closed, the continuous working time of the ultraviolet light in the refrigerator, and the sales volume of the goods in the refrigerator on that day, and , is a constant correction factor.

8. The intelligent partition management system for refrigerators according to claim 7 is characterized in that: After comparing the refrigerator's hygiene assessment index Hai on that day with the preset assessment threshold group, if , no response action is taken.

9. The intelligent partition management system for refrigerators according to claim 8, characterized in that: The preset first management strategy is: based on the refrigerator's hygiene assessment index Hai and the first assessment threshold The difference between and is used to generate the inspection frequency prediction value Cfp of the corresponding refrigerator. The formula is as follows: ； In the formula, A represents the initial inspection frequency of the corresponding refrigerator, that is, the current inspection frequency, e represents the natural constant, and B represents the adjustment factor. Represents the difference in health assessment index.

10. The intelligent partition management system for refrigerators according to claim 9, characterized in that: The preset second management strategy is: after emptying the goods in the refrigerator and cleaning and disinfecting the refrigerator, check the emptied goods and put the qualified goods back into the refrigerator. When checking the emptied goods, the goods are qualified if the packaging is not damaged and there is no peculiar smell, otherwise they are unqualified.

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