CN112963932A - Method and device for predicting set running state of household appliance and storage medium - Google Patents
Method and device for predicting set running state of household appliance and storage medium Download PDFInfo
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- CN112963932A CN112963932A CN202110220492.5A CN202110220492A CN112963932A CN 112963932 A CN112963932 A CN 112963932A CN 202110220492 A CN202110220492 A CN 202110220492A CN 112963932 A CN112963932 A CN 112963932A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/52—Indication arrangements, e.g. displays
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/56—Remote control
- F24F11/58—Remote control using Internet communication
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/61—Control or safety arrangements characterised by user interfaces or communication using timers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- General Engineering & Computer Science (AREA)
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Abstract
The invention belongs to the field of household appliances, and particularly relates to a method for predicting a set running state of a household appliance, which comprises the following steps: acquiring predicted operation data for predicting that the target household appliance reaches a set operation state; the predicted operation data comprises at least one of set operation parameters of the target household appliance, detection environment parameters of a deployed space and target set state parameters in the set operation state; uploading the predicted operation data to a cloud data center, and judging the predicted operation time of the target household appliance reaching the set operation state by the cloud data center based on the predicted operation data; the predicted runtime is received and presented to a user. The prediction method can accurately predict and feed back the time for reaching the temperature set by the user to the user, so that the user can know the running state of the household appliance more clearly, and the convenience and the comfortableness of the user in using the household appliance are improved.
Description
Technical Field
The invention belongs to the field of air conditioners, and particularly relates to a method and a device for predicting a set running state of a household appliance and a storage medium.
Background
The household air conditioner is the most common household appliance in our lives, along with the improvement of the life quality of people, people pay more attention to the intellectualization and comfort of the air conditioner, the traditional air conditioner can only preset the temperature, and the user can not know the time reaching the preset temperature clearly.
The present invention has been made in view of this situation.
Disclosure of Invention
The technical scheme of the invention can accurately predict and feed back the time reaching the temperature set by the user to the user.
In order to solve the above technical problem, a first object of the present invention is to provide a method for predicting a set operating state of a household appliance, comprising:
acquiring predicted operation data for predicting that the target household appliance reaches a set operation state; the predicted operation data comprises at least one of set operation parameters of the target household appliance, detection environment parameters of a deployed space and target set state parameters in the set operation state;
uploading the predicted operation data to a cloud data center, and judging the predicted operation time of the target household appliance reaching the set operation state by the cloud data center based on the predicted operation data;
the predicted runtime is received and presented to a user.
Further optionally, the uploading the predicted operation data to a cloud data center, and the determining, by the cloud data center based on the predicted operation data, the predicted operation time for the target household appliance to reach the set operation state includes:
establishing communication connection with the cloud data center through communication set in the target household appliance, and uploading the predicted operation data to the cloud data center based on the communication connection;
pre-establishing a prediction database for runtime prediction;
and the cloud data center carries out data comparison with the prediction database based on the prediction operation data, and obtains the prediction operation time when the target household appliance reaches the set operation state.
Further optionally, the pre-establishing a prediction database for runtime prediction comprises:
collecting multiple groups of reference operation data of multiple household appliances of the same type through the cloud data center; the reference operation data comprises at least one of operation parameters of the household appliance, reference environment parameters of a deployed space and set state parameters corresponding to a reference operation state; and the household appliance operates to the operating time of the reference state parameter according to the corresponding operating parameter;
recording the reference operation time when each household appliance reaches the reference operation state when operating with the corresponding operation parameters;
a prediction database for runtime prediction is established based on the reference run data and the reference run time.
Further optionally, the recording the reference operation time when each of the household appliances reaches the reference operation state includes:
starting a timing component arranged in the household appliance to start timing when the household appliance starts to operate;
and when the household appliance reaches the reference running state, controlling the timing assembly to stop timing, acquiring the timing time of the timing assembly as the reference running time, and resetting the timing assembly.
Further optionally, the method further comprises:
recording the actual running time of the target household appliance reaching the set running state;
and uploading the actual running time to the cloud data center, and updating and optimizing the prediction database by the cloud data center.
Further optionally, the target household appliance comprises a target air conditioner;
the set operation parameters comprise an operation mode and/or a windshield mode corresponding to the target air conditioner set based on a control instruction of a user;
the detection environment parameters comprise the environment temperature of a space where an air conditioner is deployed, the space size and/or the number of people in the space;
the target set state parameter includes a target set temperature of the target air conditioner set based on a control instruction of a user.
A second object of the present invention is to provide a device for predicting a set operating state of a household appliance, comprising:
the data acquisition module is used for acquiring predicted operation data for predicting that the target household appliance reaches a set operation state; the predicted operation data comprises at least one of set operation parameters of the target household appliance, detection environment parameters of a deployed space and target set state parameters in the set operation state;
the communication module is used for uploading the predicted operation data to a cloud data center, and the cloud data center judges the predicted operation time of the target household appliance reaching the set operation state based on the predicted operation data; receiving the predicted runtime;
a display module for presenting the predicted run time to a user.
Further optionally, the method further comprises:
the timing module is used for recording the actual running time of the target household appliance reaching the set running state;
and the communication module is used for uploading the actual running time to the cloud data center, and the cloud data center updates and optimizes the prediction database.
The third object of the invention also proposes a non-transitory computer-readable storage medium having stored thereon program instructions for implementing the above-mentioned prediction method when said program instructions are executed by one or more processors.
A fourth object of the invention is to propose a household appliance, the above prediction method thereof, or comprising the above apparatus, or having the above non-transitory computer-readable storage medium.
After adopting the technical scheme, compared with the prior art, the invention has the following beneficial effects:
according to the technical scheme, the time for reaching the temperature set by the user can be accurately predicted and fed back to the user, so that the user can know the running state of the household appliance more clearly, and the convenience and the comfort for the user to use the household appliance are improved.
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention, are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention without limiting the invention to the right. It is obvious that the drawings in the following description are only some embodiments, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. In the drawings:
FIG. 1: is a control logic diagram of an embodiment of the present invention;
FIG. 2: is a block diagram of an embodiment of the present invention.
It should be noted that the drawings and the description are not intended to limit the scope of the inventive concept in any way, but to illustrate it by a person skilled in the art with reference to specific embodiments.
Detailed Description
In the description of the present invention, it should be noted that the terms "inside", "outside", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, which are only for convenience in describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and operate, and thus, should not be construed as limiting the present invention.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," "contacting," and "communicating" are to be construed broadly, e.g., as meaning fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; may be directly connected or indirectly connected through an intermediate. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
The embodiment provides a method for predicting a set running state of a household appliance, which comprises the following steps: acquiring predicted operation data for predicting that the target household appliance reaches a set operation state; the predicted operation data comprises at least one of set operation parameters of the target household appliance, detection environment parameters of a deployed space and target set state parameters in the set operation state; uploading the predicted operation data to a cloud data center, and judging the predicted operation time of the target household appliance reaching the set operation state by the cloud data center based on the predicted operation data; the predicted runtime is received and presented to a user.
The prediction method in the embodiment is suitable for predicting the time of the air conditioner reaching the set temperature, predicting the time of the washing machine reaching the set washing temperature, predicting the time of the clothes dryer reaching the set drying temperature and the like. Taking the prediction of the time for the air conditioner to reach the set temperature as an example, as a control logic diagram shown in fig. 1, before the air conditioner is started, the air conditioner needs to be ensured to be in a power-on state, a user starts the air conditioner through a remote controller, a mobile terminal or an air conditioner operation panel, sets the operation parameters of the air conditioner, sets the environmental temperature required by the user, and simultaneously collects the environmental parameters of the environment where the air conditioner is located. The cloud data center returns the time corresponding to the data to the air conditioner after receiving the data, and the time obtained through the cloud data center in this embodiment is the predicted running time for the air conditioner to reach the temperature set by the user. In this embodiment, the predicted operating time may be displayed on a remote control, on an air conditioner operating panel, or on a user's mobile terminal.
Further optionally, the uploading the predicted operation data to a cloud data center, and the determining, by the cloud data center based on the predicted operation data, the predicted operation time for the target household appliance to reach the set operation state includes: establishing communication connection with the cloud data center through communication set in the target household appliance, and uploading the predicted operation data to the cloud data center based on the communication connection; pre-establishing a prediction database for runtime prediction; and the cloud data center carries out data comparison with the prediction database based on the prediction operation data, and obtains the prediction operation time when the target household appliance reaches the set operation state.
Taking the predicted time for the air conditioner to reach the set temperature as an example, the cloud database receives the set air conditioner operation parameters sent by the air conditioner, when the environmental temperature required by the user is set, the data are matched with the data stored in the pre-established database, the time required for the air conditioner operation parameters and the environmental parameters to reach the set temperature of the user is found, and the matching result is returned to the air conditioner.
Further optionally, the pre-establishing a prediction database for runtime prediction comprises: collecting multiple groups of reference operation data of multiple household appliances of the same type through the cloud data center; the reference operation data comprises at least one of operation parameters of the household appliance, reference environment parameters of a deployed space and set state parameters corresponding to a reference operation state; and the household appliance operates to the operating time of the reference state parameter according to the corresponding operating parameter; recording the reference operation time when each household appliance reaches the reference operation state when operating with the corresponding operation parameters; a prediction database for runtime prediction is established based on the reference run data and the reference run time. And the method further comprises: recording the actual running time of the target household appliance reaching the set running state; and uploading the actual running time to the cloud data center, and updating and optimizing the prediction database by the cloud data center.
Taking the time for predicting the air conditioner to reach the set temperature as an example, the time, the air conditioner operation parameters and the environmental parameters which are required for the plurality of air conditioners which are in communication connection with the cloud data center to reach the set temperature of the user each time are sent to the cloud data center, the cloud data center stores the data information, a prediction database is built for a large amount of data, and the data information with deviation in the database is corrected and optimized.
Further optionally, the recording the reference operation time when each of the household appliances reaches the reference operation state includes: starting a timing component arranged in the household appliance to start timing when the household appliance starts to operate; and when the household appliance reaches the reference running state, controlling the timing assembly to stop timing, acquiring the timing time of the timing assembly as the reference running time, and resetting the timing assembly.
Still taking the example of predicting the time of the air conditioner reaching the set temperature as an example, the air conditioner comprises a data acquisition module, a communication module and a main control module. The data acquisition module is used for acquiring current operating parameters, environmental parameters and user set temperature of the air conditioner, and the timing module is used for recording the time when the current environmental temperature reaches the user set temperature; the communication module is used for uploading the data acquired by the data acquisition module and the time recorded by the timing module to the cloud data center and receiving the predicted running time returned by the cloud data center; the main control module is used for controlling the operation of the air conditioner and displaying the predicted operation time received by the communication module; the data acquisition module acquires the current environmental parameters of the air conditioner, the user set temperature and the air conditioner operation parameters, the timing module synchronously starts timing, and when the main control module detects that the environmental temperature reaches the user preset temperature T, the data acquisition module acquires the time recorded by the current timing module and resets the timing module. The communication module uploads the complaint data to the cloud data center, and the cloud data center establishes a corresponding prediction database by means of massive data acquisition, big data and the like and continuously corrects and optimizes database information in the follow-up process.
Further optionally, the target household appliance comprises a target air conditioner; the set operation parameters comprise an operation mode and/or a windshield mode corresponding to the target air conditioner set based on a control instruction of a user; the operation modes of the air conditioner in the embodiment include a heating mode and a cooling mode, and the time for reaching the temperature set by the user in different modes is different. The windshield modes comprise a low windshield, a middle and high windshield and a high windshield, and under the condition that the environment space of the air conditioner is certain, the time for reaching the temperature set by a user is longer in the low windshield operation mode than in the high windshield operation mode.
The detection environment parameters comprise the environment temperature of a space where an air conditioner is deployed, the space size and/or the number of people in the space; the target set state parameter includes a target set temperature of the target air conditioner set based on a control instruction of a user.
In this embodiment, the size of the environmental space where the air conditioner is located and the number of people may affect the cooling or heating effect of the air conditioner, for example, in the cooling mode, the larger the environmental space is, the more the number of people is, the longer the time for the whole room to reach the preset temperature is, relevant parameters affecting the cooling and heating effect of the whole room need to be considered by collecting the corresponding data and establishing the prediction database, and the size of the room space and the number of people need to be collected. Assuming that the specific heat of the room air is C coke/(kg x C.), the mass is 1kg of air, the temperature is increased (or decreased) by 1 ℃, and the energy of the C coke needs to be absorbed (or released)For a given air conditioner, under the condition of no change of mode, wind shield and environmental factors, the refrigerating capacity is fixed, namely the refrigerating capacity which can be produced in unit time is fixed, the refrigerating capacity of the air conditioner in unit time is set as W, the difference value between the current ambient temperature and the set temperature is set as delta T, and the mass of the air in unit volume is M kg/M3It is shown that, the room space size is S, the time function of the current ambient temperature reaching the preset temperature can be represented as T ═ C × S × M × Δ T)/W, and as can be seen from this expression, the larger S, the larger T, i.e. the larger the environmental space where the air conditioner is located, the longer the time to reach the preset temperature, and the larger the number of people, the larger the number of heat sources, the longer the human body, which is equivalent to one heat source, the more the number of people, the more the number of heat sources, the lower the cooling capacity W of the air conditioner per unit time, i.e. the more the number of people, the longer.
Further optionally, when the target household appliance is the target air conditioner, after the air conditioner is started, whether the intelligent prediction mode is started by the air conditioner is also judged, and if the intelligent prediction mode is judged to be started, the temperature regulation time of the air conditioner is predicted. If the user does not start the intelligent prediction mode, the air conditioner does not predict the set time. However, even if the intelligent prediction mode is not started, the current operating parameters, the environmental parameters and the time required for reaching the set temperature of the air conditioner are all required to be sent to the cloud data center and stored in the database. One specific implementation is as follows: the user can open the intelligent prediction mode through a remote controller, a mobile terminal or an air conditioner control panel, and after the intelligent prediction mode is opened, the communication module acquires the relevant parameters acquired by the data acquisition module: the method comprises the steps that the size of an environment space where an air conditioner is located, the number of people, the current environment temperature and the preset temperature of a user are obtained, the current set mode of the air conditioner is uploaded to a cloud data center, the data center automatically matches with the most approximate data in a database after obtaining related data, the predicted operation time corresponding to related parameters is returned, and a main control module controls a display module to display the predicted operation time.
The embodiment also proposes a device for predicting the set operating state of a household appliance, such as the frame diagram shown in fig. 2, which includes:
the data acquisition module is used for acquiring predicted operation data for predicting that the target household appliance reaches a set operation state; the predicted operation data comprises at least one of set operation parameters of the target household appliance, detection environment parameters of a deployed space and target set state parameters in the set operation state;
the communication module is used for uploading the predicted operation data to a cloud data center, and the cloud data center judges the predicted operation time of the target household appliance reaching the set operation state based on the predicted operation data; receiving the predicted runtime;
a display module for presenting the predicted run time to a user.
Further optionally, the method further comprises:
the timing module is used for recording the actual running time of the target household appliance reaching the set running state;
and the communication module is used for uploading the actual running time to the cloud data center, and the cloud data center updates and optimizes the prediction database.
Further optionally, the data collection module includes a millimeter wave radar or a camera for detecting a size of the space in which the air conditioner is located and a number of people. In this embodiment, the data acquisition module should have image recognition and processing capabilities. The size of the environment space where the air conditioner is located and the number of people can be detected, and the detection method and the detection device are not limited to millimeter wave radars, cameras and other devices.
The present embodiments also propose a non-transitory computer-readable storage medium having stored thereon program instructions which, when executed by one or more processors, are used to implement the above-described prediction method.
The embodiment also proposes a household appliance that employs the above prediction method, or that comprises the above apparatus, or that has the above non-transitory computer-readable storage medium.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A method for predicting a set operating state of a household appliance, comprising:
acquiring predicted operation data for predicting that the target household appliance reaches a set operation state; the predicted operation data comprises at least one of set operation parameters of the target household appliance, detection environment parameters of a deployed space and target set state parameters in the set operation state;
uploading the predicted operation data to a cloud data center, and judging the predicted operation time of the target household appliance reaching the set operation state by the cloud data center based on the predicted operation data;
the predicted runtime is received and presented to a user.
2. The prediction method according to claim 1, wherein the uploading the predicted operation data to a cloud data center, and the determining, by the cloud data center, the predicted operation time for the target household appliance to reach the set operation state based on the predicted operation data comprises:
establishing communication connection with the cloud data center through communication set in the target household appliance, and uploading the predicted operation data to the cloud data center based on the communication connection;
pre-establishing a prediction database for runtime prediction;
and the cloud data center carries out data comparison with the prediction database based on the prediction operation data, and obtains the prediction operation time when the target household appliance reaches the set operation state.
3. The prediction method of claim 2, wherein pre-establishing a prediction database for run-time prediction comprises:
collecting multiple groups of reference operation data of multiple household appliances of the same type through the cloud data center; the reference operation data comprises at least one of operation parameters of the household appliance, reference environment parameters of a deployed space and set state parameters corresponding to a reference operation state; and the household appliance operates to the operating time of the reference state parameter according to the corresponding operating parameter;
recording the reference operation time when each household appliance reaches the reference operation state when operating with the corresponding operation parameters;
a prediction database for runtime prediction is established based on the reference run data and the reference run time.
4. The prediction method according to claim 3, wherein the recording of the reference operation time when each of the household appliances reaches the reference operation state comprises:
starting a timing component arranged in the household appliance to start timing when the household appliance starts to operate;
and when the household appliance reaches the reference running state, controlling the timing assembly to stop timing, acquiring the timing time of the timing assembly as the reference running time, and resetting the timing assembly.
5. The prediction method according to claim 2, characterized in that the method further comprises:
recording the actual running time of the target household appliance reaching the set running state;
and uploading the actual running time to the cloud data center, and updating and optimizing the prediction database by the cloud data center.
6. The prediction method according to any one of claims 1 to 5, wherein the target home appliance includes a target air conditioner;
the set operation parameters comprise an operation mode and/or a windshield mode corresponding to the target air conditioner set based on a control instruction of a user;
the detection environment parameters comprise the environment temperature of a space where an air conditioner is deployed, the space size and/or the number of people in the space;
the target set state parameter includes a target set temperature of the target air conditioner set based on a control instruction of a user.
7. A prediction device for setting an operation state of a home appliance, comprising:
the data acquisition module is used for acquiring predicted operation data for predicting that the target household appliance reaches a set operation state; the predicted operation data comprises at least one of set operation parameters of the target household appliance, detection environment parameters of a deployed space and target set state parameters in the set operation state;
the communication module is used for uploading the predicted operation data to a cloud data center, and the cloud data center judges the predicted operation time of the target household appliance reaching the set operation state based on the predicted operation data; receiving the predicted runtime;
a display module for presenting the predicted run time to a user.
8. The prediction apparatus according to claim 7, further comprising:
the timing module is used for recording the actual running time of the target household appliance reaching the set running state;
and the communication module is used for uploading the actual running time to the cloud data center, and the cloud data center updates and optimizes the prediction database.
9. A non-transitory computer-readable storage medium having stored thereon program instructions which, when executed by one or more processors, are to implement the method of any one of claims 1-6.
10. A domestic appliance employing the method of any one of claims 1-6, or comprising the apparatus of claim 7 or 8, or having the non-transitory computer-readable storage medium of claim 9.
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| CN102128481A (en) * | 2010-01-20 | 2011-07-20 | 珠海格力电器股份有限公司 | Air conditioner as well as control method and device thereof |
| JP2014231964A (en) * | 2013-05-29 | 2014-12-11 | ダイキン工業株式会社 | Air conditioning control system and air conditioning control program |
| CN104913441A (en) * | 2015-05-29 | 2015-09-16 | 广东美的制冷设备有限公司 | Temperature adjustment time prediction method of air conditioner, controller and air conditioner |
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