CN117367023B - Energy consumption control method, system, equipment and storage medium for refrigerated cabinet - Google Patents
Energy consumption control method, system, equipment and storage medium for refrigerated cabinet Download PDFInfo
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- CN117367023B CN117367023B CN202311391506.5A CN202311391506A CN117367023B CN 117367023 B CN117367023 B CN 117367023B CN 202311391506 A CN202311391506 A CN 202311391506A CN 117367023 B CN117367023 B CN 117367023B
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- 238000005265 energy consumption Methods 0.000 title claims abstract description 59
- 238000000034 method Methods 0.000 title claims abstract description 42
- 230000008030 elimination Effects 0.000 claims abstract description 8
- 238000003379 elimination reaction Methods 0.000 claims abstract description 8
- 230000007704 transition Effects 0.000 claims description 63
- 238000004590 computer program Methods 0.000 claims description 16
- 238000012544 monitoring process Methods 0.000 claims description 12
- 230000000694 effects Effects 0.000 claims description 9
- 230000003044 adaptive effect Effects 0.000 claims description 6
- 238000005070 sampling Methods 0.000 claims description 5
- 230000006870 function Effects 0.000 claims description 4
- 238000010586 diagram Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 4
- 238000001816 cooling Methods 0.000 description 3
- 238000009792 diffusion process Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000009920 food preservation Methods 0.000 description 1
- 238000007710 freezing Methods 0.000 description 1
- 230000008014 freezing Effects 0.000 description 1
- 238000009413 insulation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000000825 pharmaceutical preparation Substances 0.000 description 1
- 229940127557 pharmaceutical product Drugs 0.000 description 1
- 238000005057 refrigeration Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
- F25D29/00—Arrangement or mounting of control or safety devices
- F25D29/008—Alarm devices
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25D—REFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
- F25D2600/00—Control issues
- F25D2600/06—Controlling according to a predetermined profile
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- Devices That Are Associated With Refrigeration Equipment (AREA)
Abstract
The application provides a method, a system, equipment and a storage medium for controlling energy consumption of a refrigerated cabinet, which are characterized in that gas flow suspicious data are determined according to gas flow data and a preset gas flow threshold value, a plurality of gas flow suspicious data centers are determined according to the gas flow suspicious data, all the gas flow suspicious data centers are used for carrying out suspicious data delineating on the gas flow suspicious data to obtain a plurality of gas flow suspicious ring clusters, further, the gas flow suspicious characteristic value of each gas flow suspicious ring cluster is determined, suspicious elimination is carried out on each gas flow suspicious characteristic value to obtain a plurality of gas flow characteristic values, and when the gas flow characteristic total value exceeds the preset gas flow characteristic threshold value, an alarm signal is sent to a user, so that energy consumption loss of the refrigerated cabinet can be reduced.
Description
Technical Field
The application relates to the technical field of energy consumption control of refrigerated cabinets, in particular to a method, a system, equipment and a storage medium for controlling energy consumption of a refrigerated cabinet.
Background
Refrigerated cabinets are a device for storing and maintaining low temperatures, commonly used for refrigerating and freezing food, pharmaceutical products, chemicals and other items requiring low temperature storage, and the main features and uses of the refrigerated cabinet include: temperature control, food preservation, medical use, household use, etc., the design of refrigerated cabinets typically includes insulation, compressors, cooling systems, temperature controllers, and storage spaces, and different types of refrigerated cabinets have different characteristics and additional functions to meet the needs of different applications.
The energy consumption control of the refrigerated cabinet is to manage and reduce the energy consumption of the refrigerated cabinet by various technical means, and aims to improve the energy efficiency of the refrigerated cabinet, reduce the energy cost of the refrigerated cabinet and have smaller influence on the environment, and common energy consumption control methods and strategies of the refrigerated cabinet are as follows: in rapid development of refrigerated cabinets, people often control energy to achieve the purpose of reducing energy consumption by controlling energy consumption, but neglect the problem of energy consumption loss.
Disclosure of Invention
Accordingly, there is a need for a method, system, apparatus, and storage medium for controlling energy consumption of a refrigerator to reduce energy consumption loss of the refrigerator.
In order to solve the technical problems, the application adopts the following technical scheme:
In a first aspect, the present application provides a method for controlling energy consumption of a refrigerated cabinet, comprising the steps of:
Starting energy consumption monitoring of the refrigerated cabinet, and collecting gas flow data of the refrigerated cabinet;
Determining gas flow suspicious data according to the gas flow data and a preset gas flow threshold value, determining a plurality of gas flow suspicious data centers according to the gas flow suspicious data, and performing suspicious data delineation on the gas flow suspicious data by all the gas flow suspicious data centers to obtain a plurality of gas flow suspicious delineation clusters;
determining the gas flow suspicious upper bias boundary and the gas flow suspicious lower bias boundary of each gas flow suspicious ring cluster, and further determining the gas flow suspicious characteristic value of each gas flow suspicious ring cluster;
performing suspicious elimination on each gas flow suspicious characteristic value to obtain a plurality of gas flow characteristic values, and determining a gas flow characteristic total value according to all the gas flow characteristic values;
And when the total value of the gas flow characteristics exceeds a preset gas flow characteristic threshold value, sending an alarm signal to a user.
In some embodiments, determining the gas flow suspicious data according to the gas flow data and a preset gas flow threshold specifically includes:
selecting one gas flow value in the gas flow data and comparing the selected gas flow value with a preset gas flow threshold value;
If the gas flow value exceeds a preset gas flow threshold value, taking the gas flow value as a gas flow suspicious value;
and traversing each gas flow value in the gas flow data, and repeating the steps to obtain the gas flow suspicious data.
In some embodiments, determining a plurality of gas flow suspicious data centers from the gas flow suspicious data specifically includes:
sampling each gas flow suspicious value in the gas flow suspicious data according to the number of preset gas flow suspicious data centers to obtain a plurality of gas flow suspicious data transition centers;
Performing transition delineation on each gas flow suspicious value in the gas flow suspicious data according to each gas flow suspicious data transition center to obtain a plurality of gas flow suspicious delineation transition clusters;
and further determining a gas flow suspicious data center for each gas flow suspicious delineating a transition cluster.
In some embodiments, performing transition delineation on each gas flow suspicious value in the gas flow suspicious data according to each gas flow suspicious data transition center, and obtaining a plurality of gas flow suspicious delineation transition clusters specifically includes:
Determining a transition circle value of each gas flow suspicious value in the gas flow suspicious data and each gas flow suspicious data transition center;
Selecting one gas flow suspicious value in the gas flow suspicious data, and dividing the gas flow suspicious value into a transition cluster corresponding to a minimum transition circle defined value corresponding to the gas flow suspicious value;
And repeating the steps, and dividing all the gas flow suspicious values to obtain a plurality of gas flow suspicious delineating transition clusters.
In some embodiments, determining the gas flow suspicious characteristic value for each gas flow suspicious cluster is accomplished by:
Determining an adaptive cold air activity H n at a temperature n in the refrigerated cabinet;
Determining a convection impact coefficient omega nm between the temperature in the refrigerated cabinet and the outside temperature m;
Acquiring suspicious upper boundary of gas flow of suspicious circle cluster of the first gas flow
Acquiring a suspicious lower boundary of a gas flow of a suspicious circle cluster of a first gas flow
Based on the adaptive cold air activity H n, the convection impact coefficient omega nm, the gas flow suspicious upper boundaryAnd the suspected lower boundary/>, of the gas flowDetermining a gas flow suspicious characteristic value of a first gas flow suspicious cluster, wherein the gas flow suspicious characteristic value can be determined by adopting the following formula:
wherein T l represents a gas flow suspicious characteristic value of a first gas flow suspicious cluster, P 0 represents an external atmospheric pressure value, exp represents an exponential function based on e.
In some embodiments, performing suspicious elimination on each gas flow suspicious characteristic value to obtain a plurality of gas flow characteristic values specifically includes:
calculating the average value of all the suspicious characteristic values of the gas flow to obtain the average value of the suspicious characteristic values of the gas flow;
Determining a gas flow characteristic threshold according to the gas flow suspicious characteristic mean value;
Selecting a gas flow suspicious characteristic value, deleting the gas flow suspicious characteristic value if the gas flow suspicious characteristic value is smaller than a gas flow characteristic threshold value, and taking the gas flow suspicious characteristic value as a gas flow characteristic value if the gas flow suspicious characteristic value exceeds the gas flow characteristic threshold value;
repeating the steps, and continuously comparing the residual gas flow suspicious characteristic values with the gas flow characteristic threshold value to obtain a plurality of gas flow characteristic values.
In some embodiments, the gas flow data consists of a plurality of gas flow values.
In a second aspect, the present application provides a refrigerated merchandiser energy consumption control system comprising:
The gas flow data acquisition module is used for acquiring gas flow data of the refrigerated cabinet after starting energy consumption monitoring of the refrigerated cabinet;
The gas flow suspicious cluster acquisition module is used for determining gas flow suspicious data according to the gas flow data and a preset gas flow threshold value, determining a plurality of gas flow suspicious data centers according to the gas flow suspicious data, and carrying out suspicious data delineation on the gas flow suspicious data by all the gas flow suspicious data centers to obtain a plurality of gas flow suspicious clusters;
The gas flow suspicious characteristic value determining module is used for determining the gas flow suspicious upper boundary and the gas flow suspicious lower boundary of each gas flow suspicious ring cluster, and further determining the gas flow suspicious characteristic value of each gas flow suspicious ring cluster;
The gas flow characteristic total value determining module is used for performing suspicious elimination on each gas flow suspicious characteristic value to obtain a plurality of gas flow characteristic values, and determining the gas flow characteristic total value according to all the gas flow characteristic values;
and the alarm control module is used for sending an alarm signal to a user when the total value of the gas flow characteristics exceeds a preset gas flow characteristic threshold value.
In a third aspect, the application provides a computer device comprising a memory storing a computer program and a processor implementing the steps of the method for controlling energy consumption of a refrigerated cabinet of any of the above-mentioned aspects when the computer program is executed by the processor.
In a fourth aspect, the present application provides a computer readable storage medium storing a computer program which when executed by a processor performs the steps of a method of controlling energy consumption of a refrigerated cabinet as described in any of the preceding claims.
The technical scheme provided by the embodiment of the application has the following beneficial effects:
In the energy consumption control method, the system, the equipment and the storage medium of the refrigerated cabinet, firstly, the energy consumption monitoring of the refrigerated cabinet is started, gas flow data of the refrigerated cabinet are collected, gas flow suspicious data are determined according to the gas flow data and a preset gas flow threshold, a plurality of gas flow suspicious data centers are determined according to the gas flow suspicious data, the gas flow suspicious data are subjected to suspicious data delineation by all the gas flow suspicious data centers, a plurality of gas flow suspicious ring clusters are obtained, the upper limit of the gas flow suspicious in each gas flow suspicious ring cluster and the lower limit of the gas flow suspicious in each gas flow suspicious ring cluster are determined, the gas flow suspicious characteristic values of each gas flow suspicious ring cluster are further determined, the suspicious removal is carried out on each gas flow suspicious characteristic value, a plurality of gas flow characteristic values are obtained, and a gas flow characteristic total value is determined according to all the gas flow characteristic values, when the gas flow characteristic total value exceeds the preset gas flow characteristic threshold, an alarm signal is sent to a user, compared with the prior art, the method is characterized in that the gas flow suspicious ring clusters are determined according to the gas flow suspicious ring clusters, the gas flow characteristic values are determined, and the characteristic values are compared with the total gas flow characteristic values of the refrigerated cabinet, and the refrigerating cabinet is further, the characteristic value is determined, and the refrigerating cabinet is closed, and the refrigerating cabinet is convenient to find the characteristic value is closed, and the refrigerating cabinet is convenient to open, and has good to open and has good quality, is beneficial to reducing energy consumption loss.
Drawings
FIG. 1 is a flow chart of a method for controlling energy consumption of a cooling cabinet according to some embodiments of the application;
FIG. 2 is a block diagram of a cooling cabinet energy consumption control system in accordance with some embodiments of the application;
fig. 3 is an internal block diagram of a computer device in some embodiments of the application.
Detailed Description
The application has the core that the energy consumption monitoring of the refrigerated cabinet is started, gas flow data of the refrigerated cabinet are collected, gas flow suspicious data are determined according to the gas flow data and a preset gas flow threshold, a plurality of gas flow suspicious data centers are determined according to the gas flow suspicious data, the gas flow suspicious data are subjected to suspicious delineation by all the gas flow suspicious data centers to obtain a plurality of gas flow suspicious ring-shaped clusters, the gas flow suspicious upper and lower partial boundaries of each gas flow suspicious ring-shaped cluster are determined, then the gas flow suspicious characteristic value of each gas flow suspicious ring-shaped cluster is determined, a plurality of gas flow characteristic values are obtained, all the gas flow characteristic values are determined according to the gas flow characteristic values, when the gas flow characteristic value is smaller than the preset gas flow characteristic threshold, an alarm signal is sent to a user when the gas flow characteristic value exceeds the preset gas flow characteristic threshold, compared with the prior art, thereby determining whether the gas flow characteristic value of the refrigerated cabinet is closed or not is compared with the gas flow characteristic value of the current technology, the air flow characteristic value is determined, and therefore, the air flow characteristic value is determined, and the air flow characteristic value is compared with the air flow characteristic value is determined, and the air flow characteristic value is determined, is beneficial to reducing energy consumption loss.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments. Referring to fig. 1, which is an exemplary flowchart of a method of controlling energy consumption of a refrigerated cabinet according to some embodiments of the application, the method 100 of controlling energy consumption of a refrigerated cabinet generally comprises the steps of:
at step 101, refrigerated cabinet energy consumption monitoring is initiated and refrigerated cabinet gas flow data is collected.
When the method is concretely implemented, after the energy consumption monitoring of the refrigerated cabinet is started, the wind speed sensors are uniformly distributed at the closed position of the refrigerated cabinet according to the same distance, a two-dimensional coordinate system is established at the closed position of the refrigerated cabinet according to the wind speed sensors, the air flow quantity at the closed position of the refrigerated cabinet is collected according to a certain time, the value of the air flow quantity collected by the wind speed sensors is used as a gas flow value, and the collection of all the gas flow values is used as gas flow data, namely, in the method, the gas flow data is composed of a plurality of gas flow values, and the description is omitted.
In the application, a plane at the closed position of the refrigerator is taken as a plane of a two-dimensional coordinate system, a vertical ground is taken as a Y axis, a parallel ground is taken as an X axis, and a two-dimensional coordinate system is established, wherein the coordinate of each gas flow value is the coordinate of a wind speed sensor corresponding to the gas flow value.
In step 102, determining gas flow suspicious data according to the gas flow data and a preset gas flow threshold, determining a plurality of gas flow suspicious data centers according to the gas flow suspicious data, and performing suspicious data delineation on the gas flow suspicious data by all the gas flow suspicious data centers to obtain a plurality of gas flow suspicious delineation clusters.
In some embodiments, determining the gas flow suspicious data based on the gas flow data and the preset gas flow threshold may be performed by:
selecting one gas flow value in the gas flow data and comparing the selected gas flow value with a preset gas flow threshold value;
If the gas flow value exceeds a preset gas flow threshold value, taking the gas flow value as a gas flow suspicious value;
And traversing each gas flow value in the gas flow data, and repeating the steps to obtain all the suspicious gas flow data.
Specifically, when the method is implemented, the random sampling method in the prior art is used for selecting gas flow data, a gas flow value is selected and obtained, the gas flow value is compared with a preset gas flow threshold value, if the gas flow value exceeds the preset gas flow threshold value, the gas flow value is used as a gas flow suspicious value, if the gas flow value is lower than the preset gas flow threshold value, the gas flow value is marked as normal, each gas flow value in the gas flow data is traversed, the steps are repeated, a plurality of gas flow suspicious values can be obtained, and the set of all the gas flow suspicious values is used as the gas flow suspicious data.
It should be noted that, the gas flow threshold in the present application may be preset by measuring the gas flow values at the closing positions of a large number of refrigerators, and using forty percent of the average value of all the gas flow values as the gas flow threshold, and in other embodiments, the gas flow threshold may be preset by other methods, which is not limited herein.
In some embodiments, determining a plurality of gas flow suspicious data centers from the gas flow suspicious data may be accomplished by:
sampling each gas flow suspicious value in the gas flow suspicious data according to the number of preset gas flow suspicious data centers to obtain a plurality of gas flow suspicious data transition centers;
Performing transition delineation on each gas flow suspicious value in the gas flow suspicious data according to each gas flow suspicious data transition center to obtain a plurality of gas flow suspicious delineation transition clusters;
and further determining a gas flow suspicious data center for each gas flow suspicious delineating a transition cluster.
When the method is concretely implemented, if the number of the preset gas flow suspicious data centers is E, E gas flow suspicious values are extracted from the gas flow suspicious data by adopting an equidistant sampling method in the prior art, and each extracted gas flow suspicious value is used as a gas flow suspicious data transition center; selecting one gas flow suspicious data center, calculating the average value of all the gas flow suspicious values in the gas flow suspicious delineating transition cluster, taking the gas flow suspicious value closest to the average value as the gas flow suspicious data center of the gas flow suspicious delineating transition cluster, traversing all the gas flow suspicious delineating transition clusters, and repeating the steps to obtain the gas flow suspicious data center of each gas flow suspicious delineating transition cluster.
It should be noted that the number of the suspicious data centers for gas flow may be preset through historical experimental data, and may be preset by other methods in other embodiments, which is not limited herein.
It should be noted that each gas flow suspicious data transition center corresponds to one transition cluster.
In some embodiments, according to each gas flow suspicious data transition center, performing transition delineation on each gas flow suspicious value in the gas flow suspicious data to obtain a plurality of gas flow suspicious delineation transition clusters, the following steps are adopted to achieve:
Determining a transition circle value of each gas flow suspicious value in the gas flow suspicious data and each gas flow suspicious data transition center;
Selecting one gas flow suspicious value in the gas flow suspicious data, and dividing the gas flow suspicious value into a transition cluster corresponding to a minimum transition circle defined value corresponding to the gas flow suspicious value;
And repeating the steps, and dividing all the gas flow suspicious values to obtain a plurality of gas flow suspicious delineating transition clusters.
It should be noted that, the transition delineation in the present application means that each gas flow suspicious value in the gas flow suspicious data is divided into transition clusters of the gas flow suspicious delineation.
In some embodiments, determining the transition delineation value of each gas flow suspicious data and the respective gas flow suspicious data transition center may be accomplished by:
Acquiring an ith gas flow suspicious value K' i in the gas flow suspicious data;
Acquiring a gas flow suspicious value Z' j corresponding to a j-th gas flow suspicious data transition center;
Determining a gas flow suspicious maximum value K max and a gas flow suspicious minimum value K min of the gas flow suspicious data;
determining a gas flow gain factor alpha;
Determining a limit distance D Δ of a suspicious value of the gas flow;
Acquiring a spatial distance D ij between the ith gas flow suspicious value and the jth gas flow suspicious data transition center;
determining a gas flow influencing factor beta;
Determining a transition circle set value of the ith gas flow suspicious value and the jth gas flow suspicious data transition center according to the ith gas flow suspicious value K 'i, the gas flow suspicious value Z' j corresponding to the jth gas flow suspicious data transition center, the gas flow suspicious maximum value K max, the gas flow suspicious minimum value K min, the gas flow gain factor alpha, the limit distance D Δ of the gas flow suspicious value, the spatial distance D ij between the ith gas flow suspicious value and the jth gas flow suspicious data transition center and the gas flow influence factor beta, wherein the transition circle set value can be determined by adopting the following formula:
wherein Q' ij represents a transition circle value of the ith gas flow suspicious value and the jth gas flow suspicious data transition center, α+β=1.
In concrete implementation, taking the maximum gas flow suspicious value in the gas flow suspicious data as a gas flow suspicious maximum value; taking the minimum gas flow suspicious value in the gas flow suspicious data as a gas flow suspicious minimum value; taking the maximum distance between two gas flow suspicious values in the gas flow suspicious data on a two-dimensional coordinate system as the limit distance of the gas flow suspicious values; the gas flow gain factor and the gas flow influencing factor were increased from 0 to 1 according to the experimental requirements, and α+β=l.
The air flow gain factor in the application reflects the importance degree of the air flow suspicious value in the transition limit value, the air flow influence factor reflects the influence of the distance between the air flow suspicious value and the air flow suspicious data transition center on the cold air loss in the refrigerated cabinet, and the distance between the air flow suspicious value and the air speed sensor corresponding to the air flow suspicious data transition center on the refrigerated cabinet is taken as the space distance between the air flow suspicious value and the air flow suspicious data transition center.
It should be noted that, in the present application, each gas flow suspicious data center corresponds to one gas flow suspicious empty cluster, in some embodiments, all gas flow suspicious data centers perform suspicious data delineation on the gas flow suspicious data, and the obtaining a plurality of gas flow suspicious delineation clusters may be determined by adopting the following steps:
Determining each gas flow suspicious value in the gas flow suspicious data and a gas flow suspicious circle value of each gas flow suspicious data center;
Selecting one gas flow suspicious value in the gas flow suspicious data, and dividing the gas flow suspicious value into gas flow suspicious empty clusters corresponding to the minimum gas flow suspicious delineation value corresponding to the gas flow suspicious value;
Repeating the steps, and dividing all the gas flow suspicious values to obtain a plurality of gas flow suspicious delineation clusters.
It should be noted that, the suspicious data ring in the present application indicates that the suspicious values of the gas flow are divided into the corresponding suspicious air clusters of the gas flow according to the suspicious data center of the gas flow.
In some embodiments, determining each gas flow suspect value in the gas flow suspect data with a gas flow suspect delineation value for a respective gas flow suspect data center may be accomplished by:
Acquiring an ith gas flow suspicious value K' i in the gas flow suspicious data;
Determining a gas flow suspicious maximum value K max and a gas flow suspicious minimum value K min of the gas flow suspicious data;
determining a gas flow suspicious value Z l corresponding to the first gas flow suspicious data center;
determining a gas flow gain factor alpha;
Determining a limit distance D Δ of a suspicious value of the gas flow;
Acquiring suspicious distances d il between the ith gas flow suspicious value and the ith gas flow suspicious data center:
determining a gas flow influencing factor beta;
Determining a gas flow suspicious value of the ith gas flow suspicious value and the first gas flow suspicious data center according to an ith gas flow suspicious value K' i in the gas flow suspicious data, a gas flow suspicious value Z l corresponding to the first gas flow suspicious data center, the gas flow suspicious maximum value K max, the gas flow suspicious minimum value K min, the gas flow gain factor alpha, a limit distance D Δ of the gas flow suspicious value, a suspicious distance D il between the ith gas flow suspicious value and the first gas flow suspicious data center and the gas flow influence factor beta, wherein the gas flow suspicious value can be determined by adopting the following formula:
Wherein Q il represents the i-th gas flow suspect and the gas flow suspect for the l-th gas flow suspect data center, α+β=1.
The distance between the gas flow suspicious value and the wind speed sensor corresponding to the gas flow suspicious data center on the refrigerator cabinet is used as the suspicious distance between the gas flow suspicious value and the gas flow suspicious data center.
In step 103, the upper suspected boundary and the lower suspected boundary of each gas flow suspected of being clustered are determined, and further, the gas flow suspected characteristic value of each gas flow suspected of being clustered is determined.
When the method is concretely implemented, a gas flow suspicious delineating cluster is selected, and the largest gas flow suspicious value in the gas flow suspicious delineating cluster is used as the upper suspicious boundary of the gas flow suspicious delineating cluster; and taking the smallest gas flow suspicious value in the gas flow suspicious cluster as the gas flow suspicious lower bound of the gas flow suspicious cluster, traversing all the gas flow suspicious clusters, and repeating the steps to obtain the gas flow suspicious upper bound and the gas flow suspicious lower bound of each gas flow suspicious cluster.
In some embodiments, determining the gas flow suspicious characteristic value for each gas flow suspicious cluster may be accomplished by:
Determining an adaptive cold air activity H n at a temperature n in the refrigerated cabinet;
Determining a convection impact coefficient omega nm between the temperature in the refrigerated cabinet and the outside temperature m;
Acquiring suspicious upper boundary of gas flow of suspicious circle cluster of the first gas flow
Acquiring a suspicious lower boundary of a gas flow of a suspicious circle cluster of a first gas flow
Based on the adaptive cold air activity H n, the convection impact coefficient omega nm, the gas flow suspicious upper boundaryAnd the suspected lower boundary/>, of the gas flowDetermining a gas flow suspicious characteristic value of a first gas flow suspicious cluster, wherein the gas flow suspicious characteristic value can be determined by adopting the following formula:
wherein T l represents a gas flow suspicious characteristic value of a first gas flow suspicious cluster, P 0 represents an external atmospheric pressure value, exp represents an exponential function based on e.
The self-adaptive cold air activity and the convection impact coefficient in the application are determined by a large amount of experimental data; the self-adaptive cold air activity reflects the diffusion speed of cold air in the refrigerator to the outside, and the higher the self-adaptive cold air activity is, the higher the diffusion speed of cold air in the refrigerator to the outside is; the convection impact coefficient reflects the flow direction index of cold air in the refrigerator when the cold air leaks and is compatible with the external temperature, if the convection impact coefficient is larger, the cold air in the refrigerator is indicated to be easier to enter the outside, otherwise, the cold air is indicated to be easier to enter the refrigerator, the external temperature enters the refrigerator to cause the temperature unbalance of the refrigerator, more energy consumption is required to be consumed for refrigeration, and the suspicious characteristic value of gas flow indicates the parameter value of the suspicious speed of cold air loss of the refrigerator.
In step 104, suspicious elimination is performed on each gas flow suspicious characteristic value, so as to obtain a plurality of gas flow characteristic values, and a gas flow characteristic total value is determined according to all the gas flow characteristic values.
In some embodiments, the suspicious characteristic value of each gas flow is removed, so as to obtain a plurality of gas flow characteristic values, which can be realized by the following steps:
calculating the average value of all the suspicious characteristic values of the gas flow to obtain the average value of the suspicious characteristic values of the gas flow;
Determining a gas flow characteristic threshold according to the gas flow suspicious characteristic mean value;
Selecting a gas flow suspicious characteristic value, deleting the gas flow suspicious characteristic value if the gas flow suspicious characteristic value is smaller than a gas flow characteristic threshold value, and taking the gas flow suspicious characteristic value as a gas flow characteristic value if the gas flow suspicious characteristic value exceeds the gas flow characteristic threshold value;
repeating the steps, and continuously comparing the residual gas flow suspicious characteristic values with the gas flow characteristic threshold value to obtain a plurality of gas flow characteristic values.
In specific implementation, forty percent of the average value of all the gas flow suspicious characteristic values of the history is selected as a gas flow characteristic threshold; and repeating the steps, continuously comparing the residual gas flow suspicious characteristic values with the gas flow characteristic threshold value, and taking all the gas flow suspicious characteristic values exceeding the gas flow characteristic threshold value as the gas flow characteristic values.
It should be noted that, the gas flow characteristic value in the present application indicates the flow amount of the gas at the closed position of the refrigerator, and the larger the gas flow characteristic value is, the larger the flow amount of the gas at the closed position of the refrigerator, that is, the larger the cold air loss rate is.
In some embodiments, determining the gas flow characteristic total value from all of the gas flow characteristic values may be determined using the following equation:
wherein T represents a total gas flow characteristic value, T a represents an a-th gas flow characteristic value, a represents a total number of gas flow characteristic values, a=1, 2.
The total value of the gas flow characteristics in the application is a parameter value indicating the closing degree of the closed position of the refrigerator, and the greater the total value of the gas flow characteristics is, the smaller the closing degree of the closed position of the refrigerator is.
In step 105, an alarm signal is sent to the user when the gas flow characteristic total value exceeds a preset gas flow characteristic threshold.
According to the method, the closing degree of the closed position of the refrigerated cabinet corresponding to the total gas flow characteristic value can be determined according to historical experimental data, forty percent of the average value of the total gas flow characteristic values is selected as a gas flow characteristic threshold value, the gas flow characteristic threshold value is adjusted according to actual conditions, the gas flow characteristic threshold value is used as a critical value of closing tightness of the closed position of the refrigerated cabinet, when the total gas flow characteristic value is lower than the gas flow characteristic threshold value, the closed state of the closed position of the refrigerated cabinet is indicated to be tight, when the total gas flow characteristic value exceeds the gas flow characteristic threshold value, the closed state of the closed position of the refrigerated cabinet is indicated to be loose, when the total gas flow characteristic value is 0, the closed position of the refrigerated cabinet is indicated to be completely closed, in addition, when the total gas flow characteristic value is smaller than the preset gas flow characteristic threshold value, an early warning signal can be sent to a user for early warning, and when the method is specifically implemented, the color of a Light Emitting Diode (LED) lamp emitting an early warning signal is set to be yellow, and the color of the LED lamp emitting the warning signal is set to be red, and the color of the early warning signal is not repeated herein.
It should be noted that, in the present application, when the total value of the gas flow characteristics exceeds the preset gas flow characteristic threshold, monitoring data may be sent to the user at the same time, and in specific implementation, the monitoring data sent to the user may include a cold air leakage position and an excessive energy consumption calculated according to the total value of the gas flow characteristics, where the excessive energy consumption may be calculated by using an energy consumption analysis method in the prior art, and is not described herein.
Additionally, in another aspect of the present application, in some embodiments, the present application provides a refrigerated cabinet energy consumption control system, referring to FIG. 2, which is a schematic diagram of exemplary hardware and/or software of a refrigerated cabinet energy consumption control system according to some embodiments of the present application, the refrigerated cabinet energy consumption control system 200 comprising: the gas flow data acquisition module 201, the gas flow suspicious cluster capture module 202, the gas flow suspicious feature value determination module 203, the gas flow feature total value determination module 204 and the alarm control module 205 are respectively described as follows:
the gas flow data acquisition module 201 is mainly used for acquiring gas flow data of the refrigerated cabinet after starting energy consumption monitoring of the refrigerated cabinet;
The gas flow suspicious cluster delineating acquisition module 202 is mainly used for determining gas flow suspicious data according to the gas flow data and a preset gas flow threshold value, determining a plurality of gas flow suspicious data centers according to the gas flow suspicious data, and carrying out suspicious data delineating on the gas flow suspicious data by all the gas flow suspicious data centers to obtain a plurality of gas flow suspicious clusters delineating;
the gas flow suspicious characteristic value determining module 203 is mainly used for determining the gas flow suspicious upper boundary and the gas flow suspicious lower boundary of each gas flow suspicious ring-shaped cluster, so as to determine the gas flow suspicious characteristic value of each gas flow suspicious ring-shaped cluster;
The gas flow characteristic total value determining module 204 is mainly used for performing suspicious elimination on each gas flow suspicious characteristic value to obtain a plurality of gas flow characteristic values, and determining the gas flow characteristic total value according to all the gas flow characteristic values;
The alarm control module 205, in the present application, the alarm control module 205 is mainly configured to send an alarm signal to a user when the total value of the gas flow characteristics exceeds a preset gas flow characteristic threshold.
The above-mentioned energy consumption control method of refrigerated cabinet system can be implemented by all or part of software, hardware and their combination. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In addition, in one embodiment, the present application provides a computer device, which may be a server, and an internal structure diagram thereof may be as shown in fig. 3. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of computer devices is used to store chiller energy consumption control data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a method of controlling energy consumption of a refrigerated cabinet.
It will be appreciated by those skilled in the art that the structure shown in FIG. 3 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor, when executing the computer program, performing the steps of the above-described embodiments of the method for controlling energy consumption of a refrigerated cabinet.
In one embodiment, a computer readable storage medium is provided, storing a computer program which when executed by a processor performs the steps of the energy consumption control method embodiments of a refrigerated cabinet described above.
In one embodiment, a computer program product or computer program is provided that includes computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium and executes the computer instructions to cause the computer device to perform the steps of the energy consumption control method embodiments of the refrigerated cabinet described above.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in various forms such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc.
In summary, in the energy consumption control method, system, equipment and storage medium of the refrigerated cabinet disclosed by the embodiment of the application, firstly, the energy consumption monitoring of the refrigerated cabinet is started, gas flow data of the refrigerated cabinet are collected, gas flow suspicious data are determined according to the gas flow data and a preset gas flow threshold, a plurality of gas flow suspicious data centers are determined according to the gas flow suspicious data, all the gas flow suspicious data are subjected to suspicious data delineation by the gas flow suspicious data centers, a plurality of gas flow suspicious ring clustering is obtained, the gas flow suspicious upper and gas flow suspicious lower partial boundaries of each gas flow suspicious ring clustering are determined, then the gas flow suspicious characteristic values of each gas flow suspicious ring clustering are determined, the suspicious characteristic values of each gas flow suspicious ring are removed, a plurality of gas flow characteristic values are obtained, and when the gas flow characteristic total value exceeds the preset gas flow characteristic threshold, an alarm signal and data are sent to a user, compared with the current technology, the current technology of controlling the energy source is subjected to suspicious data are subjected to suspicious clustering, the gas flow characteristic values are determined, and then the characteristic values of the gas flow suspicious ring clustering is determined, and compared with the current technology of the current technology, the current energy consumption of the gas flow suspicious data is detected, and then the current characteristic values of the current energy consumption of the gas flow is determined, and the current consumption of the current energy consumption of the refrigerating cabinet is high, and the energy consumption of the energy is low, and the energy consumption of the energy is low. Is beneficial to reducing energy consumption loss.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. The energy consumption control method for the refrigerated cabinet is characterized by comprising the following steps of:
Starting energy consumption monitoring of the refrigerated cabinet, and collecting gas flow data of the refrigerated cabinet;
Determining gas flow suspicious data according to the gas flow data and a preset gas flow threshold value, determining a plurality of gas flow suspicious data centers according to the gas flow suspicious data, and performing suspicious data delineation on the gas flow suspicious data by all the gas flow suspicious data centers to obtain a plurality of gas flow suspicious delineation clusters;
determining the gas flow suspicious upper bias boundary and the gas flow suspicious lower bias boundary of each gas flow suspicious ring cluster, and further determining the gas flow suspicious characteristic value of each gas flow suspicious ring cluster;
performing suspicious elimination on each gas flow suspicious characteristic value to obtain a plurality of gas flow characteristic values, and determining a gas flow characteristic total value according to all the gas flow characteristic values;
And when the total value of the gas flow characteristics exceeds a preset gas flow characteristic threshold value, sending an alarm signal to a user.
2. The method of claim 1, wherein determining gas flow suspicious data based on the gas flow data and a preset gas flow threshold value comprises:
selecting one gas flow value in the gas flow data and comparing the selected gas flow value with a preset gas flow threshold value;
If the gas flow value exceeds a preset gas flow threshold value, taking the gas flow value as a gas flow suspicious value;
and traversing each gas flow value in the gas flow data, and repeating the steps to obtain the gas flow suspicious data.
3. The method of claim 1, wherein determining a plurality of gas flow suspicious data centers from the gas flow suspicious data comprises:
sampling each gas flow suspicious value in the gas flow suspicious data according to the number of preset gas flow suspicious data centers to obtain a plurality of gas flow suspicious data transition centers;
And carrying out transition delineation on each gas flow suspicious value in the gas flow suspicious data according to each gas flow suspicious data transition center to obtain a plurality of gas flow suspicious delineation transition clusters, and further determining the gas flow suspicious data center of each gas flow suspicious delineation transition cluster.
4. The method of claim 3, wherein performing transition delineation on each gas flow suspicious value in the gas flow suspicious data according to each gas flow suspicious data transition center, obtaining a plurality of gas flow suspicious delineation transition clusters specifically comprises:
Determining a transition circle value of each gas flow suspicious value in the gas flow suspicious data and each gas flow suspicious data transition center;
Selecting one gas flow suspicious value in the gas flow suspicious data, and dividing the gas flow suspicious value into a transition cluster corresponding to a minimum transition circle defined value corresponding to the gas flow suspicious value;
And repeating the steps, and dividing all the gas flow suspicious values to obtain a plurality of gas flow suspicious delineating transition clusters.
5. The method of claim 1, wherein determining the gas flow suspicious characteristic value for each gas flow suspicious cluster is accomplished by:
determining an adaptive cold air activity H n at a temperature n in the refrigerated cabinet;
Determining a convection impact coefficient omega nm between the temperature in the refrigerated cabinet and the outside temperature m;
Acquiring suspicious upper boundary of gas flow of suspicious circle cluster of the first gas flow
Acquiring a suspicious lower boundary of a gas flow of a suspicious circle cluster of a first gas flow
Based on the adaptive cold air activity H n, the convection impact coefficient omega nm, the gas flow suspicious upper boundaryAnd the suspected lower boundary/>, of the gas flowDetermining a gas flow suspicious characteristic value of a first gas flow suspicious cluster, wherein the gas flow suspicious characteristic value is determined by adopting the following formula:
wherein T l represents a gas flow suspicious characteristic value of a first gas flow suspicious cluster, P 0 represents an external atmospheric pressure value, exp represents an exponential function based on e.
6. The method of claim 1, wherein performing suspicious culling on each gas flow suspicious characteristic value to obtain a plurality of gas flow characteristic values comprises:
calculating the average value of all the suspicious characteristic values of the gas flow to obtain the average value of the suspicious characteristic values of the gas flow;
Determining a gas flow characteristic threshold according to the gas flow suspicious characteristic mean value;
Selecting a gas flow suspicious characteristic value, deleting the gas flow suspicious characteristic value if the gas flow suspicious characteristic value is smaller than a gas flow characteristic threshold value, and taking the gas flow suspicious characteristic value as a gas flow characteristic value if the gas flow suspicious characteristic value exceeds the gas flow characteristic threshold value;
repeating the steps, and continuously comparing the residual gas flow suspicious characteristic values with the gas flow characteristic threshold value to obtain a plurality of gas flow characteristic values.
7. The method of claim 1, wherein the gas flow data consists of a plurality of gas flow values.
8. A chiller energy consumption control system comprising:
The gas flow data acquisition module is used for acquiring gas flow data of the refrigerated cabinet after starting energy consumption monitoring of the refrigerated cabinet;
The gas flow suspicious cluster acquisition module is used for determining gas flow suspicious data according to the gas flow data and a preset gas flow threshold value, determining a plurality of gas flow suspicious data centers according to the gas flow suspicious data, and carrying out suspicious data delineation on the gas flow suspicious data by all the gas flow suspicious data centers to obtain a plurality of gas flow suspicious clusters;
The gas flow suspicious characteristic value determining module is used for determining the gas flow suspicious upper boundary and the gas flow suspicious lower boundary of each gas flow suspicious ring cluster, and further determining the gas flow suspicious characteristic value of each gas flow suspicious ring cluster;
The gas flow characteristic total value determining module is used for performing suspicious elimination on each gas flow suspicious characteristic value to obtain a plurality of gas flow characteristic values, and determining the gas flow characteristic total value according to all the gas flow characteristic values;
and the alarm control module is used for sending an alarm signal to a user when the total value of the gas flow characteristics exceeds a preset gas flow characteristic threshold value.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method for controlling energy consumption of a refrigerated cabinet according to any of claims 1 to 7.
10. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor performs the steps of the method of controlling energy consumption of a refrigerated cabinet according to any of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108932658A (en) * | 2018-07-13 | 2018-12-04 | 北京京东金融科技控股有限公司 | Data processing method, device and computer readable storage medium |
| EP3564636A2 (en) * | 2018-04-11 | 2019-11-06 | ChillServices GmbH | Refrigerated furniture |
| CN110895526A (en) * | 2019-11-29 | 2020-03-20 | 南京信息工程大学 | Method for correcting data abnormity in atmosphere monitoring system |
| CN111598863A (en) * | 2020-05-13 | 2020-08-28 | 北京阿丘机器人科技有限公司 | Defect detection method, device, equipment and readable storage medium |
| WO2021143237A1 (en) * | 2020-01-15 | 2021-07-22 | 佳都新太科技股份有限公司 | Dynamic human face clustering method and apparatus, device, and storage medium |
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| EP3564636A2 (en) * | 2018-04-11 | 2019-11-06 | ChillServices GmbH | Refrigerated furniture |
| CN108932658A (en) * | 2018-07-13 | 2018-12-04 | 北京京东金融科技控股有限公司 | Data processing method, device and computer readable storage medium |
| CN110895526A (en) * | 2019-11-29 | 2020-03-20 | 南京信息工程大学 | Method for correcting data abnormity in atmosphere monitoring system |
| WO2021143237A1 (en) * | 2020-01-15 | 2021-07-22 | 佳都新太科技股份有限公司 | Dynamic human face clustering method and apparatus, device, and storage medium |
| CN111598863A (en) * | 2020-05-13 | 2020-08-28 | 北京阿丘机器人科技有限公司 | Defect detection method, device, equipment and readable storage medium |
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