CN117367023A - 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 PDF

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Publication number
CN117367023A
CN117367023A CN202311391506.5A CN202311391506A CN117367023A CN 117367023 A CN117367023 A CN 117367023A CN 202311391506 A CN202311391506 A CN 202311391506A CN 117367023 A CN117367023 A CN 117367023A
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gas flow
suspicious
value
data
characteristic
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傅松青
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Guangdong Xinyan Intelligent Equipment Technology Co ltd
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Guangdong Xinyan Intelligent Equipment Technology Co ltd
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Priority to CN202311391506.5A priority Critical patent/CN117367023A/en
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    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25DREFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
    • F25D29/00Arrangement or mounting of control or safety devices
    • F25D29/008Alarm devices
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F25REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
    • F25DREFRIGERATORS; COLD ROOMS; ICE-BOXES; COOLING OR FREEZING APPARATUS NOT OTHERWISE PROVIDED FOR
    • F25D2600/00Control issues
    • F25D2600/06Controlling according to a predetermined profile

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  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Physics & Mathematics (AREA)
  • Mechanical Engineering (AREA)
  • Thermal Sciences (AREA)
  • General Engineering & Computer Science (AREA)
  • Devices That Are Associated With Refrigeration Equipment (AREA)

Abstract

The application provides a refrigerator energy consumption control method, a system, equipment and a storage medium, wherein 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, the gas flow characteristic total value is determined according to all the 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 the refrigerator energy consumption loss can be reduced.

Description

Energy consumption control method, system, equipment and storage medium for refrigerated cabinet
Technical Field
The present application relates to the technical field of energy consumption control of a refrigerator, and in particular, to a method, a system, a device and a storage medium for controlling energy consumption of a refrigerator.
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
In view of the foregoing, it is desirable to provide 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 adaptive cold air activity H at a temperature n in a refrigerated cabinet n
Determining the convection impact coefficient omega for a temperature n in a refrigerated cabinet and an outside temperature m nm
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
According to the adaptive cold air activity H n The convection impact coefficient omega nm Upper boundary of the gas flowAnd the suspicious lower boundary of the gas flow +.>Determining 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 is l Representing the suspicious characteristic value of the gas flow of the suspicious cluster of the first gas flow, P 0 Representing the external atmospheric pressure value, exp represents the exponential function underlying 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 present 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 partial boundary and the lower partial boundary of the gas flow suspicious ring clusters are determined, the gas flow suspicious characteristic values of each gas flow suspicious ring cluster are 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, compared with the prior art, the method is convenient for determining whether the gas flow characteristic values of the refrigerated cabinet are closed according to the control energy consumption monitoring method, the method is convenient, and the method is convenient for determining the final characteristic value of the closed, and the air flow characteristic value of the refrigerated cabinet, 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 present application;
FIG. 2 is a block diagram of a cooling cabinet energy consumption control system in some embodiments of the present application;
fig. 3 is an internal block diagram of a computer device in some embodiments of the present application.
Detailed Description
The core of the application is to start energy consumption monitoring of the refrigerated cabinet, collect gas flow data of the refrigerated cabinet, determine gas flow suspicious data according to the gas flow data and a preset gas flow threshold, determine a plurality of gas flow suspicious data centers according to the gas flow suspicious data, and when the gas flow suspicious data center performs suspicious delineation on the gas flow suspicious data to obtain a plurality of gas flow suspicious ring-shaped clusters, determine gas flow suspicious upper and lower partial boundaries of each gas flow suspicious ring-shaped cluster, further determine gas flow suspicious characteristic values of each gas flow suspicious ring-shaped cluster, perform suspicious elimination on each gas flow suspicious characteristic value to obtain a plurality of gas flow characteristic values, determine gas flow characteristic total values according to all gas flow characteristic values, send an alarm signal to a user when the gas flow characteristic total value is smaller than the preset gas flow characteristic threshold, send an alarm signal to the user when the gas flow characteristic total value exceeds the preset gas flow characteristic threshold, and compare the alarm signal with the current technology to determine whether the gas flow suspicious ring-shaped clusters have been closed or not, thereby determine whether the gas flow characteristic values of the refrigerated cabinet are closed according to the gas flow characteristic values of the current technology, and determine whether the air flow characteristic values of the refrigerator is closed or not, and the air flow characteristic values of the refrigerator is determined in time, and the air flow characteristic values of the refrigerator is determined, and the air flow characteristic value is compared with the total value of the air flow characteristic value of the air, 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 present 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 specifically 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 are composed of a plurality of gas flow values, and are not repeated here.
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 coordinate of each gas flow value is a 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, in other embodiments, 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 'in the gas flow suspicious data' i
Acquiring a gas flow suspicious value Z 'corresponding to a j-th gas flow suspicious data transition center' j
Determining a gas flow suspicious maximum K of the gas flow suspicious data max And a suspected minimum value of gas flow K min
Determining a gas flow gain factor alpha;
determining a limiting distance D of a suspicious value of a gas flow Δ
Acquiring a spatial distance D between an ith gas flow suspicious value and a jth gas flow suspicious data transition center ij
Determining a gas flow influencing factor beta;
according to the ith gas flow suspicious value K 'in the gas flow suspicious data' i Gas flow suspicious value Z 'corresponding to jth gas flow suspicious data transition center' j A suspicious maximum value K of the gas flow max A suspected minimum value K of the gas flow min A gas flow gain factor alpha, a limit distance D of the gas flow suspicious value Δ The spatial distance D between the ith gas flow suspicious value and the jth gas flow suspicious data transition center ij And determining a transition circle value of the ith gas flow suspicious value and the jth gas flow suspicious data transition center by the gas flow influence factor beta, wherein the transition circle value can be determined by adopting the following formula:
wherein Q' ij And (3) representing the transition circle value of the ith gas flow suspicious value and the jth gas flow suspicious data transition center, wherein alpha+beta=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.
It should be noted that, the gas flow gain factor in the present application reflects the importance degree of the gas flow suspicious value in the transition defined value, the gas flow influence factor reflects the influence of the distance between the gas flow suspicious value and the gas flow suspicious data transition center on the cold air loss in the refrigerator, and the distance between the gas flow suspicious value and the wind speed sensor corresponding to the gas flow suspicious data transition center on the refrigerator is taken as the spatial distance between the gas flow suspicious value and the gas flow suspicious data transition center.
It should be noted that, in this application, each gas flow suspicious data center corresponds to one gas flow suspicious empty cluster, and in some embodiments, all gas flow suspicious data centers perform suspicious data delineation on the gas flow suspicious data, so as to obtain a plurality of gas flow suspicious delineation clusters, which 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 'in the gas flow suspicious data' i
Determining a gas flow suspicious maximum K of the gas flow suspicious data max And a suspected minimum value of gas flow K min
Determining a gas flow suspicious value Z corresponding to the first gas flow suspicious data center l
Determining a gas flow gain factor alpha;
determining a limiting distance D of a suspicious value of a gas flow Δ
Acquiring suspicious distance d between suspicious value of ith gas flow and suspicious data center of ith gas flow il
Determining a gas flow influencing factor beta;
according to the ith gas flow suspicious value K 'in the gas flow suspicious data' i A gas flow suspicious value Z corresponding to the first gas flow suspicious data center l A suspicious maximum value K of the gas flow max A suspected minimum value K of the gas flow min A gas flow gain factor alpha, a limit distance D of the gas flow suspicious value Δ The suspicious distance d between the suspicious value of the ith gas flow and the suspicious data transition center of the ith gas flow il And determining an ith gas flow suspect and a ith gas flow suspect data center from the gas flow influencing factor betaWherein the gas flow suspicious circle value is determinable using the following formula:
Wherein Q is il The i-th gas flow suspicious value and the gas flow suspicious value of the l-th gas flow suspicious data center are represented, and 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 adaptive cold air activity H at a temperature n in a refrigerated cabinet n
Determining the convection impact coefficient omega for a temperature n in a refrigerated cabinet and an outside temperature m nm
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
According to the adaptive cold air activity H n The convection impact coefficient omega nm Upper boundary of the gas flowAnd the suspicious lower boundary of the gas flow +.>Determining 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 is l Representing the suspicious characteristic value of the gas flow of the suspicious cluster of the first gas flow, P 0 Representing the external atmospheric pressure value, exp represents the exponential function underlying e.
The 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 the total value of gas flow characteristics, T a The a-th gas flow characteristic value is indicated, a represents the total number of gas flow characteristic values, a=1, 2.
It should be noted that, the total value of the gas flow characteristics in the present application represents the parameter value of the closing degree of the closed position of the refrigerator, and the greater the total value of the gas flow characteristics, the smaller the closing degree of the closed position of the refrigerator.
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 value is selected as a gas flow characteristic threshold value, the gas flow characteristic threshold value is used as a critical value of closing tightness of the closed position of the refrigerated cabinet according to actual conditions, 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 which sends an alarm signal is set to be yellow, and the color of the LED lamp which sends the alarm signal is set to be red, and the color of the LED lamp which is not described in detail 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 refrigerator after the refrigerator energy consumption monitoring is started;
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, where the gas flow suspicious characteristic value determining module 203 is mainly used for determining a gas flow suspicious upper boundary and a gas flow suspicious lower boundary of each gas flow suspicious ring cluster, so as to determine a gas flow suspicious characteristic value of each gas flow suspicious ring cluster;
the gas flow characteristic total value determining module 204, where the gas flow characteristic total value determining module 204 is mainly configured to perform suspicious elimination on each gas flow suspicious characteristic value to obtain a plurality of gas flow characteristic values, and determine a gas flow characteristic total value according to all the gas flow characteristic values;
the alarm control module 205, herein, 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.
Additionally, in one embodiment, the present application provides a computer device, which may be a server, whose internal structure 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 application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain 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 the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like.
In summary, in the energy consumption control method, system, equipment and storage medium of the refrigerator disclosed in the embodiments of the present application, first, the energy consumption monitoring of the refrigerator is started, gas flow data of the refrigerator is collected, gas flow suspicious data is 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 gas flow suspicious data centers perform suspicious data delineation on the gas flow suspicious data, a plurality of gas flow suspicious ring clusters are obtained, a plurality of gas flow suspicious upper partial boundaries and gas flow suspicious lower partial boundaries of each gas flow suspicious ring cluster are determined, then the gas flow suspicious characteristic values of each gas flow suspicious ring cluster are determined, suspicious removal is performed on each gas flow suspicious characteristic value, a plurality of gas flow characteristic values are obtained, 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 existing technology, the current technology can control the current technology can reduce the gas flow suspicious ring suspicious data to obtain a plurality of gas flow suspicious ring clusters, and then the gas flow suspicious ring clusters can be removed, and then the characteristic values of each gas flow suspicious ring cluster can be determined, and then the gas flow characteristic values can be determined, and the gas flow characteristic values can be determined, when the current technology is compared with the current, and the current technology has the current state, 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 merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.

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 adaptive cold air activity H at a temperature n in a refrigerated cabinet n
Determining the convection impact coefficient omega for a temperature n in a refrigerated cabinet and an outside temperature m nm
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
According to the adaptive cold air activity H n The convection impact coefficient omega nm Upper boundary of the gas flowAnd the suspicious lower boundary of the gas flow +.>Determining 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 is l Representing the suspicious characteristic value of the gas flow of the suspicious cluster of the first gas flow, P 0 Representing the external atmospheric pressure value, exp represents the exponential function underlying 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.
CN202311391506.5A 2023-10-25 2023-10-25 Energy consumption control method, system, equipment and storage medium for refrigerated cabinet Pending CN117367023A (en)

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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

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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
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