CN112199860A - Refrigerator variable-temperature zone setting optimization method based on big data - Google Patents
Refrigerator variable-temperature zone setting optimization method based on big data Download PDFInfo
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Abstract
The invention discloses a method for setting and optimizing a variable temperature zone of a refrigerator based on big data, which comprises the following steps: counting the corresponding quantity of the temperature setting frequency P of … … n year in the 1 st year and the 2 nd year of the temperature changing zone of the refrigerator; drawing a histogram of the number of the corresponding refrigerators of each gear along with the change of the number of the refrigerators in the year, and analyzing the histogram; dividing temperature setting gears of a temperature changing area of the refrigerator, selecting a time point for data of the first year, and counting the number of the refrigerators in each setting gear to obtain the proportion of the number of the refrigerators in different setting gears to the total number of the refrigerators; data from year 2 and year 3, year … …, year n were statistically analyzed according to Stp 12. According to the method, the refrigerator data are analyzed and processed by the cloud data analysis system, and the using condition of a user on the refrigerator variable-temperature area is known by analyzing the cloud data; the specific temperature setting range of the refrigerator variable temperature area by a user is known through analysis of cloud data; the setting range of the temperature zone is optimized, and the requirements of users are better met.
Description
Technical Field
The invention belongs to the technical field of refrigerators, and particularly relates to a method for setting and optimizing a variable temperature zone of a refrigerator based on big data.
Background
The refrigerator is a device which is commonly used by users in daily life for storing food so as to prolong the freshness date of the food. The principle of food preservation of the refrigerator is to reduce the temperature of air in the refrigerator through heat exchange so as to achieve the purposes of inhibiting bacterial reproduction and prolonging the food preservation period. At present, the temperature zone design of the refrigerator generally comprises a refrigerating chamber and a freezing chamber. The temperature range of the refrigerating chamber is 2-8 ℃ generally, and the refrigerating chamber is used for storing foods such as fruits and vegetables which do not need to be frozen. The temperature of the freezing chamber is generally in the range of-16 ℃ to-24 ℃ and is used for storing foods such as meat and the like which need to be frozen and preserved. In order to facilitate the use of some types of refrigerators by users, a temperature-changing chamber is designed, the temperature of the temperature-changing chamber can be set automatically according to the actual needs of the users, and the temperature range is generally-16 ℃ to 5 ℃. If the refrigerating section of the refrigerator at the home of the user is not enough, the temperature of the temperature area can be set as the temperature range of the refrigerating section; if the freezing section of the refrigerator at the user's home is not enough, the temperature of the temperature zone can be set to the temperature range of the freezing section. The set temperature of the refrigerator with the temperature-changing chamber is uniform when the refrigerator leaves a factory, and after a user purchases the refrigerator at home, the refrigerator manufacturer cannot obtain related data about the use condition of the temperature zone (such as whether the set temperature is adjusted, which set temperature is commonly used, and the like) for the conventional refrigerator without a wireless communication function. Due to the popularization and application of the current intelligent refrigerator, a refrigerator manufacturer can obtain the specific use condition of a user on the variable-temperature zone of the refrigerator through the analysis of cloud data, and the temperature zone setting range of the refrigerator is optimized.
Disclosure of Invention
The invention aims to provide a method for setting and optimizing a variable temperature zone of a refrigerator based on big data, wherein a cloud data analysis system is arranged to analyze and process refrigerator data, and the using condition of a user on the variable temperature zone of the refrigerator is known through analyzing the cloud data; the specific temperature setting range of the refrigerator variable temperature area by a user is known through analysis of cloud data; the setting range of the temperature zone is optimized, and the requirements of users are better met.
In order to solve the technical problems, the invention is realized by the following technical scheme:
the invention relates to a method for setting and optimizing a variable temperature zone of a refrigerator based on big data, which comprises the following steps:
the method comprises the following steps: analyzing the temperature setting frequency of the temperature changing zone;
stp01, setting frequency P of the temperature of a first annual variable temperature zone of the refrigerator, and counting corresponding quantity according to four gears of P being 0, P being more than 0 and less than or equal to 3, P being more than 3 and less than or equal to 6 and P being more than 6;
stp02, setting the corresponding quantity of the frequency statistics for the temperature of the temperature changing zone of the refrigerator in the 2 nd year and the 3 rd year … … nth year according to the method of Stp 1;
stp03, counting according to four gears P0, P0-3, P3-6 and P6, and drawing a histogram of the number of the corresponding refrigerators of each gear along with the change of the year according to the corresponding data counted;
stp04, counting the gear division data of the year n and the temperature setting frequency P of the temperature varying zone, and analyzing the use condition of the temperature varying function of the temperature varying zone by a user according to the statistical data; if the statistical result frequency P is less than or equal to 3, canceling or optimizing the design; if the statistical result frequency P is more than 3, the optimization design is reserved or continued;
step two: analyzing the temperature setting gear of the temperature changing zone;
stp11, dividing temperature setting gears of a temperature changing zone of the refrigerator, dividing the temperature changing zone of the refrigerator according to four gears of T being more than-16 ℃ and less than-10 ℃, T being more than-10 ℃ and less than-4 ℃, T being more than 4 ℃ and less than 2 ℃ and T being more than 2 ℃ and less than 5 ℃ for the temperature changing zone of-16 ℃ and 5 ℃;
stp12, selecting a time point for the data of the first year to count the number of the refrigerators in each set gear to obtain the proportion of the number of the refrigerators in different set gears to the total number of the refrigerators;
stp13, counting data of 2 nd year and 3 rd year … … nth year according to Stp 12;
stp14, drawing the change condition of the proportion of different temperature-changing room temperature setting gears along with time according to the data obtained by Stp12 and Stp 13; if the proportion of a certain set gear is smaller and smaller, the design is cancelled or optimized; if the proportion of a certain set gear is larger and larger, the optimal design is reserved or continued.
Further, the optimization method comprises an optimization system, wherein the optimization system comprises a refrigerator and a cloud data analysis system;
a wireless communication module is installed on the refrigerator; the wireless communication module of the refrigerator transmits refrigerator data to the cloud data analysis system;
the cloud data analysis system comprises a data communication module, a data processing module, a user management module, a product management module, a data storage module and a data analysis module;
the data processing module is used for encrypting/decrypting data of the refrigerator;
the user management module is used for managing user information using the refrigerator, and the user information comprises an account number, a password and corresponding product information;
the product management module is used for recording the state information of the refrigerator, wherein the state information of the refrigerator comprises the refrigerator model, the refrigerator bar code, the purchase time, the user information, the refrigerator setting function, the refrigerator setting temperature and the like;
the data storage module is used for storing data information of the refrigerator, wherein the data information of the refrigerator comprises a setting function, a setting temperature, running state data of each device of the refrigerator and the like;
the data analysis module is used for analyzing and processing the running state data of the refrigerator;
the cloud data analysis system performs information interaction with the refrigerator through the data communication module.
Further, the refrigerator data includes compressor start and stop information, compressor running time information, temperature information of each compartment, and a cooling fan running state.
The invention has the following beneficial effects:
according to the method, the refrigerator data are analyzed and processed by the cloud data analysis system, and the using condition of a user on the refrigerator variable-temperature area is known through the analysis of the cloud data; the specific temperature setting range of the refrigerator variable temperature area by a user is known through analysis of cloud data; the setting range of the temperature zone is optimized, and the requirements of users are better met.
Of course, it is not necessary for any product in which the invention is practiced to achieve all of the above-described advantages at the same time.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a system block diagram of a temperature-changing temperature zone setting optimization system of a refrigerator based on big data.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "opening," "upper," "lower," "thickness," "top," "middle," "length," "inner," "peripheral," and the like are used in an orientation or positional relationship that is merely for convenience in describing and simplifying the description, and do not indicate or imply that the referenced component or element must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be considered as limiting the present invention.
Referring to fig. 1, the present invention is a method for setting and optimizing a variable temperature zone of a refrigerator based on big data, comprising the following steps:
the method comprises the following steps: analyzing the temperature setting frequency of the temperature changing zone;
stp01, setting frequency P of the temperature of a first annual variable temperature zone of the refrigerator, and counting corresponding quantity according to four gears of P being 0, P being more than 0 and less than or equal to 3, P being more than 3 and less than or equal to 6 and P being more than 6;
stp02, setting the corresponding quantity of the frequency statistics for the temperature of the temperature changing zone of the refrigerator in the 2 nd year and the 3 rd year … … nth year according to the method of Stp 1;
stp03, counting according to four gears P0, P0-3, P3-6 and P6, and drawing a histogram of the number of the corresponding refrigerators of each gear along with the change of the year according to the corresponding data counted;
stp04, counting the gear division data of the year n and the temperature setting frequency P of the temperature varying zone, and analyzing the use condition of the temperature varying function of the temperature varying zone by a user according to the statistical data; if the statistical result frequency P is less than or equal to 3, the design of the temperature-changing chamber is not consistent with the requirements of the user, and the design can be cancelled or optimized; if the statistical result frequency P is more than 3, the design of the temperature-changing chamber meets the requirements of users, and the design can be reserved or continuously optimized;
step two: analyzing the temperature setting gear of the temperature changing zone;
stp11, dividing temperature setting gears of a temperature changing zone of the refrigerator, dividing the temperature changing zone of the refrigerator according to four gears of T being more than-16 ℃ and less than-10 ℃, T being more than-10 ℃ and less than-4 ℃, T being more than 4 ℃ and less than 2 ℃ and T being more than 2 ℃ and less than 5 ℃ for the temperature changing zone of-16 ℃ and 5 ℃;
stp12, selecting a time point for the data of the first year to count the number of the refrigerators in each set gear to obtain the proportion of the number of the refrigerators in different set gears to the total number of the refrigerators;
stp13, counting data of 2 nd year and 3 rd year … … nth year according to Stp 12;
stp14, drawing the change condition of the proportion of different temperature-changing room temperature setting gears along with time according to the data obtained by Stp12 and Stp 13; if the proportion of a certain set gear is smaller and smaller, the temperature gear is unreasonable to set, and the design can be cancelled or optimized; if the proportion of a certain set gear is larger and larger, the temperature gear is reasonable to set, and the optimal design can be reserved or continued.
Further, the optimization method comprises an optimization system, wherein the optimization system comprises a refrigerator and a cloud data analysis system; a wireless communication module is arranged on the refrigerator; the wireless communication module of the refrigerator transmits refrigerator data to the cloud data analysis system; the refrigerator data comprises compressor start-stop information, compressor running time information, temperature information of each chamber and running state of a refrigerating fan;
the cloud data analysis system comprises a data communication module, a data processing module, a user management module, a product management module, a data storage module and a data analysis module; the data processing module is used for encrypting/decrypting data sent/received by the refrigerator, so that the safety of data communication and a cloud platform is ensured; the user management module is used for managing user information using the refrigerator, and the user information comprises an account number, a password and corresponding product information; the product management module is used for recording the state information of the refrigerator, wherein the state information of the refrigerator comprises the refrigerator model, the refrigerator bar code, the purchase time, the user information, the refrigerator setting function, the refrigerator setting temperature and the like; the data storage module is used for storing data information of the refrigerator, wherein the data information of the refrigerator comprises a setting function, a setting temperature, running state data of each device of the refrigerator and the like; the data analysis module is used for analyzing and processing the running state data of the refrigerator; and the cloud data analysis system performs information interaction with the refrigerator through the data communication module.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (3)
1. A method for setting and optimizing a variable temperature zone of a refrigerator based on big data is characterized by comprising the following steps: the method comprises the following steps:
the method comprises the following steps: analyzing the temperature setting frequency of the temperature changing zone;
stp01, setting frequency P of the temperature of a first annual variable temperature zone of the refrigerator, and counting corresponding quantity according to four gears of P being 0, P being more than 0 and less than or equal to 3, P being more than 3 and less than or equal to 6 and P being more than 6;
stp02, setting the corresponding quantity of the frequency statistics for the temperature of the temperature changing zone of the refrigerator in the 2 nd year and the 3 rd year … … nth year according to the method of Stp 1;
stp03, counting according to four gears P0, P0-3, P3-6 and P6, and drawing a histogram of the number of the corresponding refrigerators of each gear along with the change of the year according to the corresponding data counted;
stp04, counting the gear division data of the year n and the temperature setting frequency P of the temperature varying zone, and analyzing the use condition of the temperature varying function of the temperature varying zone by a user according to the statistical data; if the statistical result frequency P is less than or equal to 3, canceling or optimizing the design; if the statistical result frequency P is more than 3, the optimization design is reserved or continued;
step two: analyzing the temperature setting gear of the temperature changing zone;
stp11, dividing temperature setting gears of a temperature changing zone of the refrigerator, dividing the temperature changing zone of the refrigerator according to four gears of T being more than-16 ℃ and less than-10 ℃, T being more than-10 ℃ and less than-4 ℃, T being more than 4 ℃ and less than 2 ℃ and T being more than 2 ℃ and less than 5 ℃ for the temperature changing zone of-16 ℃ and 5 ℃;
stp12, selecting a time point for the data of the first year to count the number of the refrigerators in each set gear to obtain the proportion of the number of the refrigerators in different set gears to the total number of the refrigerators;
stp13, counting data of 2 nd year and 3 rd year … … nth year according to Stp 12;
stp14, drawing the change condition of the proportion of different temperature-changing room temperature setting gears along with time according to the data obtained by Stp12 and Stp 13; if the proportion of a certain set gear is smaller and smaller, the design is cancelled or optimized; if the proportion of a certain set gear is larger and larger, the optimal design is reserved or continued.
2. The method for optimizing the temperature-changing temperature zone setting of the refrigerator based on the big data as claimed in claim 1, wherein the method for optimizing the temperature-changing temperature zone setting of the refrigerator comprises an optimizing system, the optimizing system comprises the refrigerator and a cloud data analyzing system;
a wireless communication module is installed on the refrigerator; the wireless communication module of the refrigerator transmits refrigerator data to the cloud data analysis system;
the cloud data analysis system comprises a data communication module, a data processing module, a user management module, a product management module, a data storage module and a data analysis module;
the data processing module is used for encrypting/decrypting data of the refrigerator;
the user management module is used for managing user information using the refrigerator, and the user information comprises an account number, a password and corresponding product information;
the product management module is used for recording the state information of the refrigerator, wherein the state information of the refrigerator comprises the refrigerator model, the refrigerator bar code, the purchase time, the user information, the refrigerator setting function, the refrigerator setting temperature and the like;
the data storage module is used for storing data information of the refrigerator, wherein the data information of the refrigerator comprises a setting function, a setting temperature, running state data of each device of the refrigerator and the like;
the data analysis module is used for analyzing and processing the running state data of the refrigerator;
the cloud data analysis system performs information interaction with the refrigerator through the data communication module.
3. The big data-based system for setting and optimizing the temperature and temperature varying region of the refrigerator according to claim 2, wherein the refrigerator data comprises compressor on/off information, compressor running time information, temperature information of each chamber, and running state of a cooling fan.
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| CN202011161437.5A CN112199860B (en) | 2020-10-27 | Refrigerator variable temperature zone setting optimization method based on big data |
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| CN202011161437.5A CN112199860B (en) | 2020-10-27 | Refrigerator variable temperature zone setting optimization method based on big data |
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| CN112199860B CN112199860B (en) | 2024-05-31 |
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| CN112815593A (en) * | 2021-01-15 | 2021-05-18 | 合肥美菱物联科技有限公司 | System and method for monitoring refrigerator function setting abnormity by using cloud data |
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