CN114253159A - Control method and system for electric appliance test environment - Google Patents

Control method and system for electric appliance test environment Download PDF

Info

Publication number
CN114253159A
CN114253159A CN202111505252.6A CN202111505252A CN114253159A CN 114253159 A CN114253159 A CN 114253159A CN 202111505252 A CN202111505252 A CN 202111505252A CN 114253159 A CN114253159 A CN 114253159A
Authority
CN
China
Prior art keywords
environment
data
adjusted
environmental data
module
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202111505252.6A
Other languages
Chinese (zh)
Other versions
CN114253159B (en
Inventor
徐余德
华少忠
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Anhui Cheari Zhirui Technology Co ltd
Original Assignee
Anhui Cheari Zhirui Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Anhui Cheari Zhirui Technology Co ltd filed Critical Anhui Cheari Zhirui Technology Co ltd
Priority to CN202111505252.6A priority Critical patent/CN114253159B/en
Publication of CN114253159A publication Critical patent/CN114253159A/en
Application granted granted Critical
Publication of CN114253159B publication Critical patent/CN114253159B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Air Conditioning Control Device (AREA)

Abstract

The embodiment of the specification provides a control method and a control system for an electric appliance testing environment, wherein the method comprises the steps of collecting environmental data in a target environment, wherein the target environment is the environment for testing an electric appliance; judging whether the environmental data meet preset conditions or not; in response to the preset condition not being satisfied, determining an adjustment value based on the environmental data; controlling the operation of the environment adjusting device based on the adjustment value so that the environmental data in the adjusted target environment satisfies a preset condition.

Description

Control method and system for electric appliance test environment
Technical Field
The specification relates to the field of electrical equipment, in particular to a control method and a control system for an electrical testing environment.
Background
The energy consumption of the electrical equipment is different under different environments. In order to obtain the energy consumption of the electrical equipment in a user environment (such as a factory, a hotel, a home of a user, etc.), various tests on the electrical equipment need to be performed by simulating such user environment in a laboratory environment. In order to accurately simulate the user environment, a laboratory needs a series of methods for controlling variables such as ambient temperature and humidity, and common control methods include electric heating/cooling, electric humidification, use of a fan and the like, so that the temperatures of a plurality of points indoors and outdoors reach preset targets.
Therefore, it is desirable to provide a method for controlling an electrical appliance testing environment, which integrally controls an environment adjusting device through a neural network model, thereby improving the accuracy and efficiency of the experiment and reducing the energy consumption.
Disclosure of Invention
One embodiment of the present specification provides a method for controlling an electrical appliance test environment. The control method of the electric appliance test environment comprises the following steps: acquiring environmental data in a target environment, wherein the target environment is the environment of a test electric appliance; judging whether the environmental data meet preset conditions or not; in response to the preset condition not being satisfied, determining an adjustment value based on the environmental data; controlling the operation of an environment adjusting device based on the adjustment value so that the adjusted environment data in the target environment satisfies the preset condition.
One of the embodiments of the present specification provides a control system for an electrical appliance testing environment, where the system includes a data acquisition module, a judgment module, an adjustment module, and a control module; the data acquisition module is used for acquiring environmental data in a target environment, and the target environment is the environment of the test electric appliance; the judging module is used for judging whether the environmental data meet preset conditions or not; the adjusting module is used for responding to the condition that the preset condition is not met and determining an adjusting value based on the environment data; the control module is used for controlling the operation of an environment adjusting device based on the adjusting value, so that the adjusted environment data in the target environment meets the preset condition.
One of the embodiments of the present specification provides a control apparatus for an appliance test environment, including a processor, where the processor is configured to execute a control method for the appliance test environment.
One of the embodiments of the present specification provides a computer-readable storage medium, where the storage medium stores computer instructions, and when the computer reads the computer instructions in the storage medium, the computer executes a control method for an electrical appliance test environment.
Drawings
The present description will be further explained by way of exemplary embodiments, which will be described in detail by way of the accompanying drawings. These embodiments are not intended to be limiting, and in these embodiments like numerals are used to indicate like structures, wherein:
FIG. 1 is a schematic diagram of an application scenario of a control system of an appliance testing environment according to some embodiments of the present description;
FIG. 2 is an exemplary flow chart of a method of controlling an appliance test environment according to some embodiments shown herein;
FIG. 3 is another exemplary flow chart of a method of controlling an appliance test environment, shown in accordance with some embodiments of the present description;
FIG. 4 is a schematic diagram of a graph neural network model, shown in accordance with some embodiments of the present description;
FIG. 5 is an exemplary block diagram of a control system of an appliance testing environment, shown in accordance with some embodiments of the present description;
FIG. 6 is a schematic diagram of intelligent feedback regulation of an environmental regulation device in accordance with some embodiments of the present description;
FIG. 7 is a schematic diagram of a sequencing of operating conditions setup procedure for a test appliance, according to some embodiments described herein.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only examples or embodiments of the present description, and that for a person skilled in the art, the present description can also be applied to other similar scenarios on the basis of these drawings without inventive effort. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.
It should be understood that "system", "apparatus", "unit" and/or "module" as used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.
As used in this specification and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.
Flow charts are used in this description to illustrate operations performed by a system according to embodiments of the present description. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to the processes, or a certain step or several steps of operations may be removed from the processes.
FIG. 1 is a schematic diagram of an application scenario of a control system of an appliance testing environment according to some embodiments of the present description.
As shown in fig. 1, an application scenario 100 of a control system of an appliance test environment may include a processor 110, a network 120, a storage device 130, an environment adjusting apparatus 140, and a target environment 150.
The control system of the electric appliance test environment can control the electric appliance test environment and adjust the working environment of the electric appliance by implementing the method and/or the process disclosed in the specification. In some embodiments, a control system of an appliance testing environment may be used to simulate a user environment in a laboratory environment to perform various tests on an appliance, where the user environment may include an appliance usage environment such as a factory, hotel, or home. In some embodiments, the control system of the appliance test environment may be applied to a test environment that controls general and safety testing of appliances. For example, the control system of the electric appliance testing environment can be used in various laboratories such as a refrigerator performance laboratory, an air conditioner enthalpy difference laboratory, a washing machine performance laboratory, a compressor calorimeter test bed, a compressor life and start-up test device, an electric fan performance test device, a range hood energy efficiency test device and the like.
The processor 110 may be used to acquire data and/or transmit data. For example, processor 110 may access information and/or data stored in environment adjustment apparatus 140, target environment 150, and/or storage device 130 via network 120. Processor 110 refers to a system having computing capabilities. The processor 110 can be used for adjusting the corresponding adjustment value of the environment adjusting device 140 to achieve the environment required by the appliance test. For example, the processor 110 may determine an adjustment value for an operating parameter of the environmental adjustment device 140 based on environmental data of the target environment 150, the operating parameter of the environmental adjustment device 140. In some embodiments, the processor 110 may be a single server or a group of servers. In some embodiments, the processor 110 may be local or remote. In some embodiments, the processor 110 may be deployed on a cloud platform.
Network 120 may include any network over which control systems suitable for an appliance testing environment exchange information and/or data. In some embodiments, one or more components of the control system of the appliance testing environment (e.g., the processor 110, the environmental conditioning device 140, the sensors 152 and the storage device 130 in the target environment 150, etc.) may exchange information and/or data with one or more components of the control system of the appliance testing environment via the network 120. Network 120 may include one or a combination of public networks (e.g., the internet), private networks (e.g., Local Area Networks (LANs), Wide Area Networks (WANs), etc.), local area networks, Wireless Local Area Networks (WLANs), Metropolitan Area Networks (MANs), and the like.
Storage device 130 may store data and/or instructions. In some embodiments, storage device 130 may store data obtained from environmental conditioning apparatus 140, sensors 152 in target environment 150, and/or processor 110. For example, the storage device 130 may store environmental data acquired from the sensors 152. As another example, storage device 130 may store operational data obtained from climate regulating device 140. In some embodiments, storage device 130 may store data and/or instructions that processor 110 may execute or use to perform the example methods described herein.
In some embodiments, storage device 130 may be connected to network 120 to communicate with processor 110, sensors 152 in target environment 150, and/or environmental conditioning apparatus 140. The processor 110, the sensors 152 in the target environment 150, and/or the environmental conditioning apparatus 140 may access data or instructions stored in the storage device 130 via the network 120. In some embodiments, the storage device 130 may be directly connected to or in communication with the processor 110, the sensors 152 in the target environment 150, and/or the environmental conditioning apparatus 140. In some embodiments, the storage device 130 may be part of the processor 110, the sensors 152 in the target environment 150, and/or the environmental conditioning apparatus 140, or may be separate.
The environment conditioning device 140 refers to a device for conditioning the environment. In some embodiments, the environment adjusting device 140 may adjust the operation parameter such that the appliance test environment data satisfies the preset condition. In some embodiments, the environment conditioning device 140 may condition various types of environmental data, such as temperature, humidity, and air volume. The environmental conditioning device 140 may include a compressor, a fan, a bypass damper, an air cooler, and the like. In some embodiments, the environmental conditioning device 140 may be located inside the target environment 150 or outside the target environment 150.
The target environment 150 is an environment in which the test appliance is tested. Target environment 150 includes test electronics 151 and sensors 152. The test appliance 151 refers to an appliance, such as an air conditioner, a washing machine, or a refrigerator, which requires performance to be tested. The sensor 152 is used to detect environmental data of the target environment 150, such as monitoring parameters of temperature, humidity, and/or air volume. The sensor 152 may include various types of temperature sensors, humidity sensors, and/or air volume sensors.
FIG. 2 is an exemplary flow chart of a method of controlling an appliance test environment, shown in accordance with some embodiments of the present description. As shown in fig. 2, the process 200 includes the following steps.
At step 210, environmental data in the target environment 150 is collected. In some embodiments, step 210 may be performed by data acquisition module 510 or processor 110.
Target environment 150 refers to an environment for testing a test appliance. By testing the test appliance in the target environment 150, it may be determined whether the performance of the test appliance meets requirements, further determining whether the test appliance may be in actual use or requires maintenance. The test appliance may be an appliance that has been used by a user, an appliance that has not been used, is ready for sale, or the like. For example, by testing the refrigerator in a target environment 150, it is determined whether the power consumption of the refrigerator meets the standard while the refrigerator is at a guaranteed internal temperature.
In some embodiments, the target environments 150 of different appliances may be different or the same.
The environmental data refers to values of various environmental factors collected in the target environment 150. For example, the environmental data may include one or more of a temperature value, a humidity value, an air volume value, and an illumination intensity of target environment 150.
In some embodiments, environmental data of the target environment 150 may be collected by different sensors 152. The sensor 152 may be a separate device separately installed outside the test appliance, or may be a part of the test appliance. For example, an independent temperature sensor can be arranged in the working environment of the test air conditioner to collect the temperature data of the environment; or, an ambient temperature sensor arranged in the air conditioner can be tested, and the system can acquire the temperature data of the temperature sensor.
In some embodiments, the sensor 152 may begin or end collecting data based on a set time, or may collect data based on a set time interval. For example, the sensor 152 may start collecting data at 8 am every day and stop collecting data at 17 am every 30 minutes. The environment data of 8:00, 8:30, 9:00 and 9:30 … … 17:00 can be obtained according to the setting.
In some embodiments, temperature data of the target environment 150 may be collected by a temperature sensor; acquiring humidity data of the target environment 150 by a humidity sensor; the air volume data of the target environment 150 is collected by the air volume sensor. For more on the sensor 152, reference may be made to fig. 1 and its associated description.
Step 220, judging whether the environmental data meet preset conditions. In some embodiments, step 220 may be performed by the determination module 520 or the processor 110.
The preset condition refers to environmental data required for testing the electrical appliance. In some embodiments, the preset condition may be composed of a numerical range of one or more of environmental data such as temperature, humidity, and air volume. For example, if the environment required for testing the electrical appliance A is at a temperature of 23-28 ℃ and a humidity of 35-45% RH, the preset conditions may be set to a temperature of 23-28 ℃ and a humidity of 35-45% RH.
In some embodiments, whether the environmental data meets the preset condition may be determined by comparing whether the environmental data is within a numerical range corresponding to the preset condition. In some embodiments, it is necessary to perform comprehensive judgment on all the environmental data related to the preset condition to judge whether the obtained environmental data is in a value range corresponding to the preset condition. For example, if one or more types of data of the environment are not within a predetermined range, it may be determined that the predetermined condition is not satisfied.
Illustratively, if the temperature of the environmental data of the test appliance a is 25 ℃, the humidity is 38% RH, and the set of values is within the range of the preset condition, the environmental data of the current test appliance is considered to satisfy the preset condition. For another example, if the temperature of the environmental data of the tested electrical appliance a is 32 ℃, the humidity is 25% RH, and the set of values is outside the range of the preset condition, it is determined that the environmental data of the current tested electrical appliance does not satisfy the preset condition, and the next operation will be performed.
In response to the preset condition not being met, an adjustment value is determined 230 based on the environmental data. In some embodiments, step 230 may be performed by adjustment module 530 or processor 110.
The adjustment value is a value obtained by adjusting an operation parameter of the environment adjusting apparatus 140, and the adjustment value is used to enable the environment data of the target environment 150 to satisfy a preset condition. The adjustment values may include adjustment values for a plurality of operating parameters, for example, the operating parameters may include power, air volume, and the like. The operating parameters may be determined in particular in accordance with the environmental conditioning means 140.
The environment adjusting device 140 is a device that adjusts an environmental parameter of the target environment 150. In some embodiments, environmental adjustment device 140 may adjust the operating parameter based on the adjustment value to effect adjustment of the environmental parameter. The environmental conditioning device 140 may be an air conditioner, a fresh air machine, a fan, a humidifier, etc. For more on the environmental conditioning device 140, refer to fig. 1 and its associated description.
In some embodiments, processor 110 may determine an adjustment value for environmental adjustment device 140 based on the rules and the environmental data. For example, a correspondence may be set between environmental data and operating parameters, corresponding operating parameters determined based on the environmental data, and adjustment values determined based on current operating parameters. The processor 110 may also determine the adjustment value based on the model, see fig. 4 and the detailed description thereof, which are not described herein.
And step 240, controlling the operation of the environment adjusting device 140 based on the adjustment value, so that the adjusted environment data of the target environment 150 satisfies the preset condition. In some embodiments, step 240 may be performed by control module 540 or processor 110.
The operation of the environment adjusting means 140 refers to an operation of adjusting the environment data in the target environment 150. In some embodiments, the operation of the environmental conditioning device 140 may include one or more of temperature control, humidity control, and wind control, among others.
Temperature control refers to the regulation and control of temperature data in the target environment 150. In some embodiments, the temperature of the target environment 150 may be controlled by adjusting the power level of the electrical chiller in the environment conditioning device 140. For example, if the temperature data in the target environment 150 exceeds a preset condition, the power of the electric refrigerator may be controlled such that the temperature in the target environment 150 satisfies the preset condition.
Humidity control refers to the regulation of humidity data in the target environment 150. In some embodiments, the humidity level of the target environment 150 may be controlled by adjusting the power level of an electric humidifier in the environment conditioning apparatus 140. For example, if the humidity data in the target environment 150 is not within the numerical range of the preset condition, the power of the electric humidifier may be controlled such that the humidity in the target environment 150 satisfies the preset condition.
The wind control is to adjust and control the amount of wind in the target environment 150. In some embodiments, the air volume level of the target environment 150 may be controlled by adjusting the power of the fan in the environment adjusting device 140. For example, if the air volume data in the target environment 150 does not satisfy the preset condition, the power of the fan may be adjusted by the environment adjusting device 140 so that the air volume in the target environment 150 satisfies the preset condition.
In some embodiments, there is a complex inherent relationship as there may be a correlation between air volume and temperature, air volume and humidity, temperature and humidity, etc. (e.g., the magnitude of the former may affect the latter). In some embodiments, the adjustment sequence of temperature control, humidity control, and air control may be adjusted based on the influence relationship between temperature, humidity, and air volume. For example, an excessive increase in the air volume may affect the temperature and humidity adjustment effect, and may cause unnecessary energy loss, but if the air volume is controlled within a reasonable range, it is helpful to uniformly adjust the temperature and humidity in a certain space. Therefore, the proper adjusting value and the adjusting sequence can be selected according to the actual situation.
As shown in fig. 6, when there are multiple environment adjustment devices in the target environment, the ratio of the environmental adjustment devices to be put into use may be determined based on a numerical comparison between current environmental data of the target environment and environmental data satisfying a preset condition. In some embodiments, the numerical comparison may be characterized by a currently corresponding enthalpy value for the target environment. In some embodiments, the ratio of commissioning may be a ratio of output power of each climate control device and/or a ratio of the various climate control devices being enabled.
For example, an environment conditioning device in a target environment includes a plurality of refrigeration devices and heating devices, compares the current temperature and humidity of the current room with the set temperature and humidity, and determines the percentage of the refrigeration devices and the heating devices that are respectively turned on according to the enthalpy value. In some embodiments, the enthalpy value can be calculated according to the inside and outside wet and dry spheres, if the humidity is not required, the enthalpy value can be calculated according to the distributed humidity of the dry sphere temperature interval (0 > dry sphere is calculated according to RH 45%, 0 is equal to or less than dry sphere is equal to or less than 25 is calculated according to RH 40%, 25 is less than dry sphere is calculated according to RH 30%), the enthalpy value can be differentiated from all enthalpy values in the set working condition according to the current temperature and humidity detected outdoors, the minimum value is selected according to the difference value, when the outdoor enthalpy value is equal to or close to (within 3-5), then the indoor enthalpy value can be selected according to the minimum difference value in the same method.
For example, the 3HP unit configured in the refrigerator performance laboratory has a large margin of refrigerating capacity under different environmental conditions, and at the moment, the electric heating input heating capacity needs to be balanced, and the larger the margin of the output part of the unit is, the larger the input heating output proportion is, and the more energy is consumed. The percentage is converted by PID according to the difference between the current temperature and the set temperature of the room, the output of the variable frequency refrigerator and the adjustable heater is controlled and adjusted simultaneously for refrigeration and heating, and the variable frequency refrigerator is connected with a variable frequency speed regulation device, a refrigeration compressor, an evaporator and the like; the adjustable heating component power adjuster, the fin heating pipe and the like are connected; the proportion of the frequency conversion refrigerator and the adjustable heater of the refrigerator in use is adjusted by controlling the refrigerating and heating input amount through the PID table and controlling the heat exchange capacity of the evaporator.
In some embodiments of the present description, the ratio of the environmental adjustment devices to be put into use is determined based on a numerical comparison between the current environmental data of the target environment and the environmental data meeting the preset conditions, so that the environmental adjustment devices can be combined and operated with higher efficiency, the intelligent automation degree of the equipment can be improved, the manpower input can be saved, and the energy consumption can be reduced.
In some embodiments, processor 110 may implement the operation of environmental adjustment device 140 based on the adjustment value. Controlling operation of climate adjustment device 140 based on the adjustment value may be processor 110 adjusting climate adjustment device 140 based on the adjustment value such that an operating parameter of climate adjustment device 140 changes based on the adjustment value. For example, the processor 110 sends an adjustment command, which includes an adjustment value, and the environmental conditioning device 140 automatically updates the operating parameters after receiving the adjustment command. For example, the fan automatically updates the wind speed gear, etc.
In some embodiments, performance of the operation of environmental conditioning device 140 may include inputting or selecting a number of operating conditions of the conditioning apparatus based on the conditioning values. The working condition refers to the production running state of the production device and the facility. When multiple devices are operating simultaneously, the operating conditions may be adjusted based on the adjustment values.
After the system provides the automatic sorting button based on the adjustment value, the user can click the automatic sorting button, and the working conditions are self-sorted. The user may also manually adjust the sequence of operating conditions. For example, a certain adjustment value includes that a power adjustment value of the compressor 1 is a, a fan ventilation parameter adjustment value is b, and a power adjustment value of the compressor 2 is c, and a user clicks an automatic sequencing button or a manual adjustment sequence to achieve the effect of adjusting the compressor 1, the fan, and the compressor 2 according to the adjustment value and the adjustment sequence. In some embodiments, the system may implement self-adjustment based on the generated adjustment value.
Fig. 7 shows a schematic diagram of a process flow of sequencing the operating conditions of the test appliance. In the process of setting multiple condition parameters for multiple test electrical appliances as shown in fig. 7, each condition setting content includes one or more of a prototype name, a condition type, a dry bulb temperature, a wet bulb temperature, a relative humidity (below zero), a stabilization duration, a static pressure, and the like, and any combination thereof, and in some embodiments, the setting content may also be set based on a product use manual of the test electrical appliances or related parameter records in other data. In some embodiments, the behavior representation may be performed by a table, a list, or a document.
In some embodiments, the sequencing may be performed in multiple operating modes after each operating mode is set. The sequencing can be carried out on the working condition sequence by the processing equipment according to the enthalpy value, the temperature continuity and the like of the indoor and outdoor temperature and humidity defined by the working condition. In some embodiments, the ordering may be performed automatically by the system or manually by the user. The sorted conditions may be displayed in a list, and the experimental progress status of the conditions may be marked with different colors, for example, red may be used to indicate a completed condition, green may be used to indicate a current condition, and yellow may be used to indicate a non-current condition.
In some embodiments, the experiments may be performed sequentially based on the order after the sequencing of the operating conditions is completed.
In some embodiments, conditions may be added as needed during the experiment and the non-experimented conditions may be reordered from the newly added conditions. The ordering may be as described above.
In some embodiments, the experimental result may be output when all the operating conditions of a certain test appliance are finished. Report content can be output independently for each working condition, and a user can select to inquire the working condition or print the working condition report. In some embodiments, historical experimental data of the same batch of test appliances may also be queried. In some embodiments, the operating condition data may be exported to the terminal device.
In some embodiments, after the working condition experiment of one test appliance is finished, the machine can be replaced or the current experiment can be finished. When the next test electrical appliance is replaced, the corresponding working conditions can be reordered by combining the current target environment.
In some embodiments of the present description, by automatic sequencing and optional operation of the operating conditions, the complexity of the operation can be reduced, the labor cost can be reduced, and the waste of energy and time can be reduced.
Examples of specific procedures for operating condition adjustments are provided below:
firstly, a user sets according to a working condition detailed design table, clicks a working condition configuration button to check all the existing working conditions, and carries out operations of adding, modifying and deleting working conditions and the like. The information to be filled in for each working condition includes, but is not limited to, a working condition name, a working condition type, a dry bulb temperature (indoor), a wet bulb temperature (indoor), a dry bulb temperature (outdoor), a wet bulb temperature (outdoor), a stable maintenance time, a static pressure, a first voltage change, a second voltage change, a voltage change repetition number, a power off interval, an outdoor temperature change number, an outdoor temperature change amplitude, and the like.
After the working condition setting is completed, experimental setting can be performed, and firstly, the working condition to be performed is determined, for example: the system comprises four working conditions of rapid voltage rise and fall (low-temperature heating), rapid voltage rise and fall (high-temperature refrigeration), electric shock (low-temperature heating) and electric shock (high-temperature refrigeration). And filling the related contents of the multi-working-condition setting completely, and confirming the detailed experimental process setting in the working-condition setting through the selection of the working-condition type. For example, selecting a fast ramp-up and ramp-down voltage (low temperature heating) condition brings out experimental detailed process settings such as a first voltage change, a second voltage change, a third voltage change, a fourth voltage change, and the number of voltage change repetitions.
After the working condition setting and the related contents are input in sequence, 4 working conditions are sequenced according to a mathematical method and a sequencing rule so as to achieve the result of least energy consumption, for example, the sequencing result is as follows: 1. fast voltage rise and fall (high temperature refrigeration), 2 electric shock (high temperature refrigeration), 3 electric shock (low temperature heating), and 4 fast voltage rise and fall (low temperature heating). And 4 working conditions are added into the working condition table according to the sequence, and the current time is taken as the current task group identifier, so that the re-sequencing is conveniently carried out after other working conditions are added in the experimental process.
After the sorting is finished, the installation and the distribution are carried out, after the laboratory arrangement is confirmed to be correct, a click start test is carried out to carry out an experiment of a first working condition (rapid voltage rise and drop (high-temperature refrigeration)), according to the test details, in this example, after the temperature of indoor and outdoor dry and wet balls is controlled to reach a preset value firstly under the first working condition, the first working condition is kept stable for 30 minutes, the processor 110 controls the power supply controller to adjust the voltage from the rated voltage to 115%, the preset operation time length is 1 minute, the rated voltage is adjusted back, the voltage is adjusted to 75% of the rated voltage after 1 minute, the rated voltage is adjusted back after 1 minute, and the operation is repeated for many times.
After the first working condition is completed, the judgment is carried out, the sample machine used in the next working condition is consistent with the previous working condition, when the working condition is stable, the first working condition experimental report (stored in the storage device 130) is derived, and meanwhile, historical data query can be carried out. And judging whether the heater and the compressor are turned on or not and the turning-on degree according to the difference value between the current temperature and the target temperature and humidity, and then carrying out a second working condition experiment (here, electric shock (high-temperature refrigeration)). And (3) prompting that the experiment is about to end, please prepare to remove the prototype or operate other machines 10-30 minutes before the first working condition is ended (determined according to user setting) when the prototype used in the next working condition is inconsistent with the previous working condition, and judging whether to turn on the heater and the compressor and the turn-on degree according to the difference value between the current temperature and the target temperature and humidity by clicking to start after changing the machine. The experiment was entered into the second condition, here electric shock (high temperature refrigeration).
And after the second working condition is stable (namely the temperature and the power of the tested machine are stable at the same time), the tested machine is controlled by the processor 110 to cut off the power supply and then immediately switch on the power supply after running for 15 minutes, the machine is started and run for 10 minutes, the operation is repeated for 10 cycles, and after the working condition is stable again, the second working condition is finished. After the second working condition is completed, the judgment is carried out, the prototype used in the next working condition is consistent with the previous working condition, when the working condition is stable, the experimental report of the second working condition is derived (stored in the storage device 130), and meanwhile, historical data can be inquired through software. And judging whether the heater and the compressor are turned on or not and the turning-on degree according to the difference value between the current temperature and the target temperature and humidity, and then carrying out a third working condition experiment (electric shock (low-temperature heating)) on the heater and the compressor. And (3) prompting that the experiment is about to end, please prepare to remove the prototype or operate other machines 10-30 minutes before the second working condition is ended (determined according to user settings) when the prototype used in the next working condition is inconsistent with the previous working condition, and judging whether to turn on the heater and the compressor and the turn-on degree according to the difference value between the current temperature and the target temperature and humidity by clicking to start after the prototype is manually changed. The experiment was entered into the third condition, here electric shock (low temperature heating).
And after the third working condition is stable (namely the temperature and the power of the tested machine are stable at the same time), the tested machine is controlled by the processor 110 to cut off the power supply and then immediately switch on the power supply after running for 15 minutes, the machine is started and run for 10 minutes, the operation is repeated for 3 cycles, and after the working condition is stable again, the second working condition is completed. After the third working condition is completed, the judgment is carried out, the sample machine used in the next working condition is consistent with the previous working condition, and after the working condition is stable, an experimental report of the third working condition is derived (stored in the storage device 130), and meanwhile, historical data query can be carried out. According to the difference value between the current temperature and the target temperature, whether the heater and the compressor are turned on or not and the degree of turning on are judged, and then a fourth working condition experiment (here, rapid voltage rise and fall (low-temperature heating)) is carried out. And (3) prompting that the experiment is about to end 10-30 minutes before the first working condition is ended (determined according to user setting) when the prototype used in the next working condition is inconsistent with the previous working condition, and after the prototype is manually changed, clicking to start, judging whether a heater and a compressor are turned on or not and the opening degree according to the difference value between the current temperature and the target temperature and humidity, and entering a fourth working condition (here, the fourth working condition is a rapid voltage rise and fall (low-temperature heating)) experiment.
And under the fourth working condition, after the working condition is stable for 30 minutes, the processor 110 controls the power supply controller to regulate the power supply voltage from the rated voltage to 115 percent of the rated voltage, regulate the power supply voltage back to the rated voltage after 1 minute, regulate the power supply voltage back to 75 percent of the rated voltage after 1 minute, regulate the power supply voltage back to the rated voltage after 1 minute, and carry out the steps twice again. 10-30 minutes before the fourth working condition (the last working condition) is completed (determined according to user settings), prompting that the experiment is about to be finished, and please prepare to remove the prototype or operate other machines, if not, the experiment is completed, and a fourth working condition experiment report (stored in the storage device 130) is derived.
In the above steps, if the working condition addition is needed temporarily, the adding working condition button is clicked (which can be selected only in the experiment process), and the model machine name, the working condition type, the dry bulb temperature, the wet bulb temperature, the relative humidity (below zero), the stable duration, the static pressure and the like of the working condition to be added are set. And (4) filling a plurality of materials at one time, clicking to confirm after filling, reordering the remaining unfinished working conditions and the adding working conditions, and sequentially testing according to the steps.
In some embodiments of the present disclosure, the required adjustment value is obtained based on the environmental data and the process data of the target environment, and in the testing process of the electrical appliance to be tested, the manual intervention processes such as frequent manual changing of the operating conditions and manual changing of the operating modes are reduced by reasonably adjusting the operations of the environmental adjusting devices 140 such as temperature control, humidity control, wind control and the like, and real-time adjustment and/or automatic sequencing of the multiple operating conditions, so that the operations can be accurately and properly controlled, the testing efficiency can be effectively improved, the energy consumption can be reduced, and the automation and the intellectualization of the electrical appliance testing can be facilitated.
FIG. 3 is another exemplary flow chart of a method of controlling an appliance test environment, shown in accordance with some embodiments of the present description. As shown in fig. 3, the process 300 includes the following steps.
Step 310, after the operation of controlling the environment adjusting device 140 based on the adjustment value is completed, acquiring the adjusted environment data in the target environment 150. In some embodiments, step 310 may be performed by data acquisition module 510 or processor 110.
The adjusted environment data refers to environment data of the target environment 150 after the environment adjusting device 140 completes the operation based on the adjustment value. In some embodiments, the adjusted environmental data includes data adjusted for various factors in target environment 150, such as one or more of temperature values, humidity values, and air values.
The adjusted environmental data is collected in a manner similar to the manner in which the initial environmental data is collected, and reference may be made to step 210 and the detailed description thereof.
Step 320, determining whether the adjusted environment data in the target environment 150 satisfies a preset condition. In some embodiments, step 320 may be performed by the determination module 520 or the processor 110.
The content of the preset condition and the manner of determining whether the adjusted environment data in the target environment 150 satisfies the preset condition are similar to step 220 described in fig. 2, and specific content may refer to step 220 and its detailed description, which are not repeated herein.
And step 330, responding to the adjusted environmental data meeting the preset condition, and operating under the condition of keeping the environmental data stable. In some embodiments, step 330 may be performed by control module 530 or processor 110.
In some embodiments, the adjusted environmental data may satisfy a preset condition. For example, the initial value of the temperature in the target environment 150 of the test appliance B is 35 ℃, the temperature value of the target environment 150 is reduced to 26 ℃ by the operation of the environment adjusting device 140, and the adjusted environment data satisfies the preset condition at this time, when the preset condition is exceeded (for example, the preset condition is 20 ℃ to 27 ℃).
In some embodiments, when the adjusted environmental data meets the preset condition, the test may be kept running under the condition that the environmental data is stable. Under the condition that the external environment changes little (for example, the temperature difference is small, the humidity changes little, etc.), the change of the environmental data is also in a steady state, and the environmental adjustment device 140 generally only needs to keep the current power, the current gear and the current operation parameters running, that is, the state of running under the condition that the environmental data is stable is realized.
In some embodiments, the condition that the environmental data of the test appliance is stable may be judged based on a numerical change of the environmental data. For example, the condition under which the environmental data is stable may be one or more of the following conditions: a maximum deviation in temperature of less than 5 ℃ over one hour, or an average deviation in temperature of less than 0.2 ℃; under the condition of low temperature, the maximum deviation of the relative humidity is less than 5 percent, and the average deviation of the relative humidity is less than 3 percent; the power fluctuation of the test electric appliance is less than 2%, and the like.
In some embodiments of the present description, the environment data of the testing electrical appliance is stably judged and the testing electrical appliance is operated under the condition of keeping the environment data stable, and the operation condition of the testing electrical appliance is automatically uploaded to the server in time, so that the testing scheme of the testing electrical appliance is conveniently and properly adjusted in time, the good operation state of the testing electrical appliance is ensured, and abnormal conditions which may occur are predictably processed, so that the experimental data is more accurate and detailed, the experimental process is more continuous and smooth, the energy consumption is reduced, and the cost is reduced.
Step 340, responding to that the adjusted environment data does not meet the preset condition, and generating an adjustment value corresponding to the adjusted environment data. In some embodiments, step 340 may be performed by adjustment module 530 or processor 110.
In some embodiments, the adjusted environmental data may not satisfy the preset condition. For example, the initial value of the temperature in the target environment of the test appliance B is 35 ℃, the temperature exceeds the preset condition (for example, the preset condition is 20 ℃ to 27 ℃), the temperature value of the target environment is changed to 32 ℃ through the operation of the environment adjusting device 140, and the adjusted environment data still does not meet the preset condition.
In some embodiments, when the adjusted environmental data does not satisfy the preset condition, an adjustment value may be generated based on the current environmental data. For a relevant description of the regulating values, reference is made to fig. 2.
And step 350, responding to the condition that the adjusted environmental data do not meet the preset conditions and the change value is not in the preset range, and sending out an alarm prompt. In some embodiments, step 340 may be performed by the alert prompt module 550 or the processor 110.
The preset range refers to a numerical range of environment data corresponding to preset conditions of each environment element in environment adjustment and a time range within which the test electric appliance needs to reach the preset conditions within a set time.
In some embodiments, the test appliance may not be within a preset time range such that the change in the environmental data after adjustment is within a preset range. For example, the preset range of the temperature in the working environment of the air conditioner is 23-24 ℃, the target environment of the air conditioner before adjustment is 35 ℃, and the preset time range of the environmental data change after the air conditioner is adjusted can be 3h (e.g., 9: 00-12: 00). The environment value of the target environment of the air conditioner is changed to 32 ℃ 3h after adjustment, the preset condition is not met, and the change value is not in the preset range.
In some embodiments, an alarm prompt may be issued in response to the adjusted environmental data not meeting the preset condition and the change value not being within the preset range. In some embodiments, the alert prompt may be issued by a beep tone and/or flashing an alert light. In some embodiments, the alarm prompt can also be sent out by broadcasting the warning words. For example, the device may be regulated by "test appliance Environment abnormal! "and similar warning words to remind technicians that the environmental data after the current test of the electrical appliance is adjusted may be unfavorable for the work of testing the electrical appliance. The alarm prompt system used in some embodiments of the specification can find the abnormal working of the test electrical appliance in time and reduce unnecessary loss.
It should be noted that the above description of the flow is for illustration and description only and does not limit the scope of the application of the present specification. Various modifications and alterations to the flow may occur to those skilled in the art, given the benefit of this description. However, such modifications and variations are intended to be within the scope of the present description.
FIG. 4 is a schematic diagram of a graph neural network model, shown in accordance with some embodiments of the present description. As shown in fig. 4, the schematic diagram 400 includes a graph neural network 410.
In some embodiments, processor 110 may process the environmental data through a neural network model to determine the adjustment value. The neural network model may determine the adjustment values for the various environmental adjustment devices 140 based on processing environmental data in the target environment 150 at the current and previous points in time, operating parameters of the environmental adjustment devices 140 at the current and previous points in time, preset conditions, and points in time at which the preset conditions were reached. Wherein the time point at which the preset condition is reached may be preset, hereinafter simply referred to as "target time point".
In some embodiments, the neural network model may include machine learning models of various multi-layer neurons. The machine learning model of the multi-layered neuron includes a multi-layered perceptron.
In some embodiments, the neural network model may be a graph neural network 410. The graph neural network 410 is a neural network directly acting on a graph, and can enable each node in the graph to exchange attribute information with each other through edges based on an information propagation mechanism, so that the information of the node is continuously updated until a stop condition is met.
In some embodiments, the nodes of the graph neural network 410 include at least one control node and at least one test node. At least one control node corresponds to at least one environmental conditioning device 140 in a target environment 150. The control nodes can comprise a temperature control node, a humidity control node, a wind control node and the like. The temperature control node, the humidity control node, and the wind control node correspond to a temperature control device, a humidity control device, and a wind control device in the target environment 150, respectively, and the temperature control device, the humidity control device, and the wind control device are included in the environment adjusting device 140. The environment adjusting device 140 corresponding to the node may be in the target environment 150 or may be located outside the target environment 150. For example, the temperature control device may be outside of the target environment 150. The at least one test node corresponds to at least one sensor 152 in the target environment 150. The test nodes may include temperature test nodes, humidity test nodes, and the like. The temperature test node, the humidity test node correspond to a temperature sensor, a humidity sensor, etc. in the target environment 150.
In some embodiments, the edges of the graph neural network 410 are relationships between various nodes. The relationship between the nodes includes a spatial relationship and/or a positional relationship between devices (including the environment adjusting device 140 and the sensor 152) corresponding to the nodes, for example, whether the nodes are in the same indoor space, and for example, whether the distance between the nodes is smaller than a threshold value, and the like.
In some embodiments, the inputs to the neural network 410 model are maps and the outputs are adjustment values for the environmental conditioning device 140. A graph may be composed of nodes and edges.
The feature of the node may be a feature vector constructed based on a time series. The node characteristics of the control node may be represented by one or more first characteristic vectors, each element of the first characteristic vectors corresponding to a time point (a current time point and a previous time point) and representing an operation parameter of the corresponding environment adjusting device 140 at a certain time point of the control node. Time points corresponding to elements in the first feature vector may be preset, and the time points may be separated by a preset threshold.
For example, a temperature control node may be characterized as (C)1，C2……Cn-1) Wherein, C1Representing the power of the air conditioner corresponding to the temperature control node at time point 1, C2Representing the power of the air conditioner corresponding to the temperature control node at time point 2, Cn-1Representing the power of the air conditioner corresponding to the temperature control node at the time point n-1. Time points 1 and 2 may be previous time points, and time point n-1 may be a current time point.
In some embodiments, when the environment adjusting device 140 corresponding to the control node has a plurality of operating parameters, the first eigenvector of the control node is plural, each eigenvector corresponds to one operating parameter, and the plural first eigenvectors can be represented by the matrix S. A row in the matrix S represents the values of an operating parameter at various points in time.
The node characteristics of the test node may be represented by a second feature vector, each element of which corresponds to a time point (a current time point and a previous time point) and represents environmental data detected by the corresponding sensor 152 at a certain time point of the test node. The time point of the second feature vector is similar to the time point of the first feature vector.
In some embodiments, the second feature vector further includes environment data corresponding to the target time point, that is, the environment data is environment data in a preset condition.
For example, the second feature vector of a certain temperature test node is (T)1，T2……Tn-1，Tn) Wherein, T1Represents the temperature, T, detected by the corresponding temperature sensor at time point 1 of the temperature test node2Represents the temperature, T, detected by the corresponding temperature sensor at time point 2 of the temperature test noden-1Represents the temperature, T, detected by the corresponding temperature sensor at the time point n-1 of the temperature test nodenRepresenting the temperature value that needs to be reached at the target point in time in target environment 150.
In some embodiments, to distinguish between different nodes, an element may be added to the first feature vector and the second feature vector to represent the node type, e.g., the first element may be used to represent the node type.
The control/test nodes may be differentiated based on the representation of the node type, further determining the meaning of the corresponding element in each node feature vector. For example, a control node is denoted by 1, a test node is denoted by 2, if the first element in the feature vector of a certain node is 1, the node is the control node, and the elements except the first element in the feature vector are power values. If the first element in the feature vector of a certain node is 2, the node is a test node, and the other elements except the first element in the feature vector are environment data, and the last element is environment data requiring a preset condition.
It is understood that the node type may be multi-dimensional, for example, the node type may be represented by the type of the sensor 152. For example, a temperature sensor will be described with element 1, and a humidity sensor will be described with element 2. If the first element in the feature vector of a certain node is 1, the node is a temperature test node where the temperature sensor is located, and the other elements except the first element in the feature vector are temperature values; if the first element in the feature vector of a certain node is 2, the node is a humidity testing node where the humidity sensor is located, and the other elements except the first element in the feature vector are humidity values; and the last element is temperature and humidity data which need preset conditions respectively.
In some embodiments, the characteristics of the edges may be determined based on spatial relationships or/and positional relationships, and each edge may reflect multiple characteristics. In some embodiments, the characteristics of the edge may include node-based spatial dependencies 0 or 1. For example, whether the devices (including the environment adjusting device 140 or the sensor 152) corresponding to the two nodes of the building edge are located in the same space, if so, 1 is assigned, and otherwise, 0 is assigned. For another example, if the device distance corresponding to the two nodes of the constructed edge is smaller than the threshold, then 1 is assigned, otherwise 0 is assigned. In some embodiments, the assignments may be converted into vectors as third feature vectors of the edges by data binning or the like. In some embodiments, the characteristics of the edge may include a specific distance value.
In some embodiments, the graph is processed by the graph neural network 410 based on the nodes, edges, and corresponding feature constructs, and the adjustment values corresponding to the respective environment adjustment devices 140 can be output. Specifically, each control node in the graph neural network 410 outputs an adjustment value corresponding to the node, and the environment adjusting device 140 corresponding to the control node needs to adjust the operation parameter based on the adjustment value, so that the environment data at the target time point can meet the preset condition.
In some embodiments, the output of the control node may be a numerical value or a vector, where the output is a numerical value if there is only one operating parameter, and a vector if there are multiple operating parameters, where each element in the vector represents an adjustment value for a certain operating parameter.
For example, controlThe control node M corresponds to a fan, and in the neural network 410, the control node M outputs a vector (P)1、P2). Wherein, P1Representing the power of the fan as P1，P2The wind quantity of the representative fan is P2。
As shown in FIG. 4, for example, the node characteristic of the test node 1 is a second characteristic vector (T)1，T2……Tn) The node characteristic of the control node 1 is a first characteristic vector (C)1，C2……Cn-1) The edge characteristics of the test node 1 and the control node 1 are in a spatial relationship or a positional relationship, the node characteristics of the test node 1, the node characteristics and the edge characteristics of the control node 1, and the like are configured into a graph and input to the graph neural network 410, and the control node outputs an adjustment value (P)1、P2....Pm) I.e. the adjusted values of the respective operating parameters.
In some embodiments, the graph neural network 410 may be trained based on training samples and labels. Specifically, the training samples with the labels are input into the neural network 410 model, and the parameters of the model are updated through training. The training sample is a sample graph formed based on sample environment data in the sample target environment 150, sample operating parameters of the sample environment adjusting device 140 for controlling the sample environment data, and spatial or distance relationships among the sample sensors 152, among the sample environment adjusting devices 140, and between the sample sensors 152 and the sample environment adjusting device 140, and is constructed in a manner similar to the aforementioned graph, and the sample graph includes sample testing nodes and sample control nodes. The label is the adjustment value of each sample environment adjustment device 140. More specifically, the label is an adjustment value of each sample control node in the constructed sample graph. Training samples may be obtained from historical test data.
In some embodiments of the present disclosure, a required adjustment value of the environmental data can be obtained by applying the scheme of the neural network 410 based on the complex intrinsic relationship and the target temperature and process data according to the environmental data and the intrinsic relationship thereof, so that the environmental data can be accurately adjusted and controlled, and energy can be reasonably saved. The features extracted by the graph neural network 410 integrate the environmental data of each target environment 150, the time nodes and the spatial location features among the devices, so that the target environment 150 can be adjusted more accurately and effectively, and the effect of reducing energy consumption is achieved.
FIG. 5 is an exemplary block diagram of a control system of an appliance test environment, shown in accordance with some embodiments of the present description.
As shown in fig. 5, in some embodiments, the module 500 may include a data collection module 510, a determination module 520, a regulation module 530, and a control module 540.
The data collection module 510 may be used to collect environmental data in the target environment 150, the target environment 150 being the environment of the test appliance. In some embodiments, the data collection module 510 may be further configured to collect the adjusted environmental data in the target environment 150 after the adjustment value controls the operation of the environmental adjustment device 140.
The determining module 520 may be configured to determine whether the environmental data satisfies a preset condition. In some embodiments, the determining module 520 may be further configured to determine whether the adjusted environmental data in the target environment 150 satisfies a preset condition.
The adjustment module 530 may be configured to determine an adjustment value based on the environmental data in response to the predetermined condition not being satisfied. In some embodiments, the adjusting module 530 may be further configured to generate an adjustment value corresponding to the adjusted environment data in response to the adjusted environment data not meeting the preset condition.
The control module 540 may be configured to control the operation of the environment adjusting apparatus 140 based on the adjustment value, so that the environmental data in the adjusted target environment 150 satisfies the preset condition. In some embodiments, the control module 540 may be further configured to operate under a condition that keeps the environmental data stable in response to the adjusted environmental data satisfying a preset condition.
In some embodiments, module 500 may also include an alert prompt module 550.
In some embodiments, the alarm prompt module 550 may be configured to issue an alarm prompt in response to the adjusted environmental data not meeting the preset condition and the variation value not being within the preset range.
It should be noted that the above description of the control system and its modules in the electrical testing environment is for convenience of description only, and the description is not limited to the scope of the embodiments. It will be appreciated by those skilled in the art that, given the teachings of the present system, any combination of modules or sub-system configurations may be used to connect to other modules without departing from such teachings. In some embodiments, the data collection module, the determination module, the control module, and the adjustment module disclosed in fig. 5 may be different modules in a system, or may be a module that implements the functions of two or more modules described above. For example, each module may share one memory module, and each module may have its own memory module. Such variations are within the scope of the present disclosure.
Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be regarded as illustrative only and not as limiting the present specification. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present specification and thus fall within the spirit and scope of the exemplary embodiments of the present specification.
Also, the description uses specific words to describe embodiments of the description. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the specification is included. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.
Additionally, the order in which the elements and sequences of the process are recited in the specification, the use of alphanumeric characters, or other designations, is not intended to limit the order in which the processes and methods of the specification occur, unless otherwise specified in the claims. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.
Similarly, it should be noted that in the preceding description of embodiments of the present specification, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to imply that more features than are expressly recited in a claim. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.
Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the number allows a variation of ± 20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.
For each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., cited in this specification, the entire contents of each are hereby incorporated by reference into this specification. Except where the application history document does not conform to or conflict with the contents of the present specification, it is to be understood that the application history document, as used herein in the present specification or appended claims, is intended to define the broadest scope of the present specification (whether presently or later in the specification) rather than the broadest scope of the present specification. It is to be understood that the descriptions, definitions and/or uses of terms in the accompanying materials of this specification shall control if they are inconsistent or contrary to the descriptions and/or uses of terms in this specification.
Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present disclosure. Other variations are also possible within the scope of the present description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.

Claims (10)

1. A method of controlling an appliance test environment, the method comprising:
acquiring environmental data in a target environment, wherein the target environment is the environment of a test electric appliance;
judging whether the environmental data meet preset conditions or not;
in response to the preset condition not being satisfied, determining an adjustment value based on the environmental data;
controlling the operation of an environment adjusting device based on the adjustment value so that the adjusted environment data in the target environment satisfies the preset condition.
2. The control method of an appliance test environment of claim 1, the method further comprising:
after the operation of controlling an environment adjusting device based on the adjusting value is finished, acquiring the adjusted environment data in the target environment;
judging whether the adjusted environment data in the target environment meet preset conditions or not;
responding to the adjusted environmental data meeting the preset condition, and keeping the environmental data to operate under a stable condition;
in response to the adjusted environmental data not meeting the preset condition, generating the adjustment value corresponding to the adjusted environmental data, and controlling further operation of the environmental adjustment device based on the adjustment value corresponding to the adjusted environmental data;
and sending out an alarm prompt in response to the adjusted environment data not meeting the preset condition and the variation value not being in the preset range.
3. The method of controlling an appliance testing environment of claim 2, the operation of the environment conditioning device comprising one or more of temperature control, humidity control, and wind control.
4. The control method of an appliance test environment of claim 1, said determining an adjustment value based on said environment data comprising:
processing the environmental data through a neural network model to determine the adjustment value.
5. A control system of an electric appliance testing environment comprises a data acquisition module, a judgment module, an adjustment module and a control module;
the data acquisition module is used for acquiring environmental data in a target environment, and the target environment is the environment of the test electric appliance;
the judging module is used for judging whether the environmental data meet preset conditions or not;
the adjusting module is used for responding to the condition that the preset condition is not met and determining an adjusting value based on the environment data;
the control module is used for controlling the operation of an environment adjusting device based on the adjusting value, so that the adjusted environment data in the target environment meets the preset condition.
6. The control system of an appliance testing environment of claim 5, the system further comprising an alert prompt module:
the data acquisition module is further used for acquiring the adjusted environmental data in the target environment after the operation of controlling the environmental adjustment device based on the adjustment value is finished;
the judging module is further used for judging whether the adjusted environment data in the target environment meet preset conditions or not;
the control module is further used for responding that the adjusted environmental data meet the preset condition and keeping the environmental data to operate under the stable condition;
the adjusting module is further used for responding to the condition that the adjusted environment data does not meet the preset condition, generating the adjusting value corresponding to the adjusted environment data, and controlling the further operation of the environment adjusting device based on the adjusting value corresponding to the adjusted environment data;
the alarm prompt module is used for responding to the adjusted environment data that the environment data do not meet the preset conditions and the change value is not in the preset range, and sending out an alarm prompt.
7. The control system of an appliance testing environment of claim 6, the operation of the environmental conditioning device comprising one or more of temperature control, humidity control, and wind control.
8. The control system of an appliance testing environment of claim 5, the adjustment module further to:
processing the environmental data through a neural network model to determine the adjustment value.
9. A control device of an electric appliance test environment, comprising a processor, wherein the processor is used for executing the control method of the electric appliance test environment of any one of claims 1-4.
10. A computer-readable storage medium storing computer instructions, wherein when the computer instructions in the storage medium are read by a computer, the computer executes the control method of the electrical appliance test environment according to any one of claims 1 to 4.
CN202111505252.6A 2021-12-10 2021-12-10 Control method and system for electric appliance test environment Active CN114253159B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111505252.6A CN114253159B (en) 2021-12-10 2021-12-10 Control method and system for electric appliance test environment

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111505252.6A CN114253159B (en) 2021-12-10 2021-12-10 Control method and system for electric appliance test environment

Publications (2)

Publication Number Publication Date
CN114253159A true CN114253159A (en) 2022-03-29
CN114253159B CN114253159B (en) 2022-10-04

Family

ID=80794577

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111505252.6A Active CN114253159B (en) 2021-12-10 2021-12-10 Control method and system for electric appliance test environment

Country Status (1)

Country Link
CN (1) CN114253159B (en)

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130111479A1 (en) * 2011-10-31 2013-05-02 International Business Machines Corporation Performance of Scheduled Tasks via Behavior Analysis and Dynamic Optimization
CN109324240A (en) * 2017-07-31 2019-02-12 广东美的制冷设备有限公司 The detection method and device of the power consumption of air conditioner under refrigeration mode
CN111537252A (en) * 2020-04-28 2020-08-14 宁波奥克斯电气股份有限公司 Air conditioner testing method and device, computer equipment and storage medium
CN211826260U (en) * 2019-09-25 2020-10-30 中国标准化研究院 Automatic safety detector for electric appliance
CN111928420A (en) * 2020-07-17 2020-11-13 珠海格力电器股份有限公司 Air conditioner control method and device, electronic equipment and storage medium
CN111955382A (en) * 2020-09-16 2020-11-20 珠海格力电器股份有限公司 Air conditioning system, control method, controller and air conditioning unit
CN112665303A (en) * 2020-12-28 2021-04-16 Tcl家用电器（合肥）有限公司 Refrigerator control method and device, refrigerator and computer readable storage medium
CN112911283A (en) * 2021-02-05 2021-06-04 湖南快乐阳光互动娱乐传媒有限公司 Smart television testing method and device
CN113225994A (en) * 2021-05-08 2021-08-06 广州远正智能科技股份有限公司 Intelligent air conditioner control method facing data center

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130111479A1 (en) * 2011-10-31 2013-05-02 International Business Machines Corporation Performance of Scheduled Tasks via Behavior Analysis and Dynamic Optimization
CN109324240A (en) * 2017-07-31 2019-02-12 广东美的制冷设备有限公司 The detection method and device of the power consumption of air conditioner under refrigeration mode
CN211826260U (en) * 2019-09-25 2020-10-30 中国标准化研究院 Automatic safety detector for electric appliance
CN111537252A (en) * 2020-04-28 2020-08-14 宁波奥克斯电气股份有限公司 Air conditioner testing method and device, computer equipment and storage medium
CN111928420A (en) * 2020-07-17 2020-11-13 珠海格力电器股份有限公司 Air conditioner control method and device, electronic equipment and storage medium
CN111955382A (en) * 2020-09-16 2020-11-20 珠海格力电器股份有限公司 Air conditioning system, control method, controller and air conditioning unit
CN112665303A (en) * 2020-12-28 2021-04-16 Tcl家用电器（合肥）有限公司 Refrigerator control method and device, refrigerator and computer readable storage medium
CN112911283A (en) * 2021-02-05 2021-06-04 湖南快乐阳光互动娱乐传媒有限公司 Smart television testing method and device
CN113225994A (en) * 2021-05-08 2021-08-06 广州远正智能科技股份有限公司 Intelligent air conditioner control method facing data center

Also Published As

Publication number Publication date
CN114253159B (en) 2022-10-04

Similar Documents

Publication Publication Date Title
CN112577161B (en) Air conditioner energy consumption model training method and air conditioner system control method
CN111096094B (en) Cooling unit energy optimization via intelligent supply air temperature setpoint control
US11385607B2 (en) Variable air volume modeling for an hvac system
US11783203B2 (en) Building energy system with energy data simulation for pre-training predictive building models
Belic et al. HVAC control methods-a review
CN110726218B (en) Air conditioner, control method and device thereof, storage medium and processor
CN109827299A (en) Based on Internet of Things air-treatment unit adjusting method, device, system and medium
CN105650811A (en) Method and device for controlling indoor unit of air conditioner
CN109323414B (en) Air conditioner, control method and control device thereof and electronic equipment
CN103282841A (en) Building automation system
CN111955382A (en) Air conditioning system, control method, controller and air conditioning unit
CN109140660A (en) For the Intelligent temperature controller method and device of air-conditioning, air-conditioning, storage medium
JP2021103083A5 (en)
CN114253159B (en) Control method and system for electric appliance test environment
Deng et al. Self-tuning PID-type fuzzy adaptive control for CRAC in datacenters
CN110726216B (en) Air conditioner, control method, device and system thereof, storage medium and processor
CN109445494B (en) Enthalpy difference laboratory dry-bulb working condition automatic control method
US11474869B2 (en) Central plant control system with subplant rank generator
US10962938B2 (en) Building management system with self-optimizing control, performance monitoring, and fault detection
CN107247406B (en) Control method and system for test station
CN112013518A (en) Air conditioning equipment, automatic control method thereof and terminal control equipment
CN205536381U (en) Controlling means of air conditioner
CN115696871B (en) Data center water cooling system regulation and control method and device based on machine learning
CN114754477B (en) Air conditioner control system, method, central air conditioner system, device and storage medium
KR20190075717A (en) Centralized HVAC System Using Genetic Algorithm and Method Using The Same

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant