Method and device for correcting indoor temperature, electronic equipment and storage medium

Abstract

The invention provides a method and device for correcting the indoor temperature, electronic equipment and a storage medium, and the method comprises the steps that rotating speed data of an indoor fan of an air conditioner are obtained, and indoor temperature data measured by a temperature sensor of the air conditioner are collected; and inputting the rotating speed data and the indoor temperature data as input parameters into a temperature correction model to obtain temperature correction data so as to obtain corrected indoor temperature. The temperature data measured by the air conditioner are corrected according to the running state data, the real indoor temperature is determined, temperature test deviation caused by an air conditioner fan is avoided, the accuracy of correcting the indoor temperature is improved, the air conditioner can be controlled more accurately, and the user experience is improved.

Description

Technical Field

[0001] This application relates to the technical field of temperature testing, and particularly to a method, device, electronic device and storage medium for correcting indoor temperature. Background Art

[0002] In the operation control of air conditioners, temperature sensors play an important role. The temperature measured by the temperature sensor installed on the outer surface of the indoor unit can approximately represent the indoor ambient temperature. However, in fact, directly using the temperature sensor to represent the indoor temperature is inaccurate. The temperature measured by the temperature sensor is affected by the temperature of the indoor unit pipeline and the indoor fan. Especially after shutdown, the temperature measured by the temperature sensor changes rapidly, while the change of the indoor environment temperature has a delay. The inaccurate indoor loop temperature has a great impact on the operation control of the air conditioner. Summary of the Invention

[0003] This application aims to solve at least one of the technical problems in the related art to some extent.

[0004] To this end, this application proposes a method, device, electronic device and storage medium.

[0005] An embodiment of one aspect of this application proposes a method for correcting indoor temperature, including:

[0006] Obtain the rotation speed data of the indoor fan of the air conditioner, and collect the indoor temperature data measured by the temperature sensor of the air conditioner;

[0007] Use the rotation speed data and the indoor temperature data as input parameters, and input them into a temperature correction model to obtain temperature correction data, so as to obtain the corrected indoor temperature.

[0008] Optionally, the input parameters further include at least one of the following:

[0009] The on / off state of the air conditioner, and the duration of the on / off state of the air conditioner.

[0010] Optionally, the obtaining of the rotation speed data of the indoor fan of the air conditioner includes at least one of the following:

[0011] In response to the air conditioner being in the operating state, determine the rotation speed data according to the rotation speed of the indoor fan of the air conditioner in the operating state;

[0012] In response to the air conditioner being in the shutdown state, determine the rotation speed data according to the rotation speed of the indoor fan of the air conditioner at the previous moment before the air conditioner enters the shutdown state.

[0013] Optionally, the method further includes:

[0014] Determine the reference time points for the conversion of the air conditioner from the shutdown state to the startup state and from the startup state to the shutdown state;

[0015] Use the duration between the reference time point and the nearest time point when the temperature data is measured as the state duration.

[0016] Optionally, the temperature correction model includes a backpropagation neural network, and the backpropagation neural network includes six hidden layers.

[0017] Optionally, the method for obtaining the training data set used in the training of the temperature correction model includes:

[0018] Run the indoor fan of the air conditioner at different rotational speed data, and record the training temperature data measured by the temperature sensor of the air conditioner; arrange multiple temperature sensors indoors, record the temperature data within the same time, and take the average value as the actual temperature of the indoor environment;

[0019] Construct a training data set according to the training temperature data, rotational speed data, and actual temperature.

[0020] Another embodiment of this application proposes a device for correcting the indoor temperature, and the device for correcting the indoor temperature can implement any of the methods described in the foregoing aspect.

[0021] Optionally, the device for correcting the indoor temperature includes:

[0022] An acquisition module, configured to obtain the rotational speed data of the indoor fan of the air conditioner and acquire the indoor temperature data measured by the temperature sensor of the air conditioner;

[0023] A temperature correction module, configured to use the rotational speed data and the indoor temperature data as input parameters, input them into a temperature correction model to obtain temperature correction data, so as to obtain the corrected indoor temperature. Another embodiment of this application proposes an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the method described in the foregoing aspect is implemented.

[0024] Another embodiment of this application proposes a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method described in the foregoing aspect is implemented.

[0025] Another embodiment of this application proposes a chip, and the chip includes a processing circuit configured to execute the method described in the foregoing aspect.

[0026] Another embodiment of this application proposes a computer program product, on which a computer program is stored. When the program is executed by a processor, the method described in the foregoing aspect is implemented.

[0027] The method, device, electronic device, chip, and storage medium for correcting the indoor temperature proposed in this application correct the temperature data measured by the air conditioner through the operating state data, realize the determination of the indoor temperature, avoid the deviation of temperature measurement caused by the air conditioner fan, improve the accuracy of measuring the indoor temperature, and improve the accuracy of air conditioner control, so that the air conditioner can be controlled more accurately and the user experience can be improved.

[0028] Some of the additional aspects and advantages of this application will be given in the following description, some will become obvious from the following description, or will be learned through the practice of this application. Brief Description of the Drawings

[0029] The above-mentioned and / or additional aspects and advantages of this application will become obvious and easy to understand from the following description of the embodiments in conjunction with the drawings, where:

[0030] Figure 1 is a schematic flowchart of a method for correcting the indoor temperature provided by an embodiment of this application;

[0031] Figure 2 is a schematic diagram of a model structure provided by an embodiment of this application;

[0032] Figure 3 is a schematic diagram of the effect of a temperature correction model provided by an embodiment of this application;

[0033] Figure 4 is a schematic structural diagram of a device for correcting the indoor temperature provided by an embodiment of this application;

[0034] Figure 5 is a schematic structural diagram of an electronic device provided by an embodiment of this application;

[0035] Figure 6 is a schematic structural diagram of a chip proposed by an embodiment of this application. Detailed Description of the Embodiments

[0036] The embodiments of this application will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are intended to explain this application and should not be construed as limiting this application.

[0037] In the operation control of an air conditioner, the temperature sensor plays an important role. The temperature measured by the temperature sensor installed on the outer surface of the indoor unit can approximately represent the indoor environmental temperature. However, in fact, directly using the temperature sensor to represent the indoor temperature is inaccurate. The temperature measured by the temperature sensor is affected by the temperature of the indoor unit pipeline and the indoor fan. Especially after shutdown, the temperature measured by the temperature sensor changes rapidly, while the change of the indoor environmental temperature has a delay. The inaccurate indoor loop temperature has a great impact on the operation control of the air conditioner.

[0038] The following describes the method, device, electronic device, chip, and storage medium for correcting the indoor temperature according to the embodiments of the present application with reference to the accompanying drawings.

[0039] Figure 1 It is a schematic flow chart of a method for correcting the indoor temperature provided by an embodiment of the present application.

[0040] As an implementation manner, the method for correcting the indoor temperature according to the embodiments of the present application can be configured in a device for correcting the indoor temperature. The device for correcting the indoor temperature can be applied to any electronic device, so that the electronic device can perform the function of correcting the indoor temperature.

[0041] Among them, the electronic device can be any device with computing capabilities. For example, it can be a mobile terminal, and the mobile terminal can be a hardware device such as a mobile phone, a tablet computer, a personal digital assistant, a wearable device, etc., which has various operating systems, touch screens, and / or display screens.

[0042] As another implementation manner, the method for correcting the indoor temperature according to the embodiments of the present application can also be executed by a chip with processing capabilities. The chip includes an Image Signal Processor (ISP), a Central Processing Unit (CPU), an Application-Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Field-Programmable Gate Array (FPGA), a System On A Chip (SOC), a Reduced Instruction Set Computer (RISC), etc., which will not be listed one by one here.

[0043] As Figure 1 shown, the method may include the following steps:

[0044] Step 101: Obtain the rotation speed data of the indoor fan of the air conditioner, and collect the indoor temperature data measured by the temperature sensor of the air conditioner.

[0045] Step 102: Use the rotation speed data and the indoor temperature data as input parameters, and input them into the temperature correction model to obtain temperature correction data, so as to obtain the corrected indoor temperature.

[0046] In this embodiment, a temperature sensor, called a temperature sensing bulb, is provided in the air conditioner. Since the temperature sensing bulb is installed in the air conditioner, the temperature it measures is greatly affected by the operating state of the air conditioner. For example, when the air conditioner is in operation, due to the continuous rotation of the fan, the temperature of the air conditioner will be lower than the actual indoor temperature. The difference between the temperature data measured by the temperature sensing bulb and the actual indoor temperature varies under different operating states of the air conditioner.

[0047] By obtaining the rotation speed data of the air conditioner and the indoor temperature data measured by the temperature sensor of the air conditioner, and using the rotation speed data to correct the indoor temperature data to obtain temperature correction data, and determining the corrected indoor temperature based on the temperature correction data, the corrected indoor temperature represents the actual indoor temperature. It can improve the accuracy of temperature measurement and avoid temperature measurement errors caused by changes in the operating state of the air conditioner (such as turning on and off, changes in fan speed, etc.).

[0048] Optionally, the input parameters further include at least one of the following:

[0049] The on / off state of the air conditioner, and the duration of the on / off state of the air conditioner.

[0050] In this embodiment, the on / off state of the air conditioner and the duration of the off state are also important factors affecting the difference between the indoor temperature data measured by the temperature sensor of the air conditioner and the actual indoor temperature data. When the air conditioner is in the on state, since the temperature sensor of the air conditioner is close to the fan, the indoor temperature it measures is greatly affected by the operation of the fan and changes quickly. However, due to the large indoor space, the actual indoor temperature is a slowly changing process. And as the on time increases, the indoor temperature data measured by the temperature sensor of the air conditioner and the actual indoor temperature data will gradually increase. By considering these two factors, the on / off state of the air conditioner and the duration of the on / off state, it provides a more comprehensive reference basis for temperature correction, can more accurately reflect the influence of the operating state of the air conditioner on temperature measurement, and thus further improve the accuracy of the corrected indoor temperature.

[0051] Optionally, the obtaining of the rotation speed data of the indoor fan of the air conditioner includes at least one of the following:

[0052] In response to the air conditioner being in the operating state, determine the rotation speed data according to the rotation speed of the indoor fan of the air conditioner in the operating state.

[0053] In response to the air conditioner being in the shutdown state, determine the rotation speed data according to the rotation speed of the indoor fan at the moment immediately before the air conditioner enters the shutdown state.

[0054] In this embodiment, when the air conditioner is in the shutdown state, the actual rotation speed of the indoor fan is 0. However, for the convenience of associating the rotation speed of the indoor fan with the actual indoor temperature, that is, the corrected temperature data, the rotation speed of the indoor fan of the air conditioner at shutdown is regarded as the rotation speed of the indoor fan when it has not been shut down.

[0055] In the shutdown state of the air conditioner, by obtaining the rotation speed of the indoor fan before shutdown as the measured rotation speed of the indoor fan, the problem that the rotation speed of the indoor fan cannot be directly obtained in the shutdown state is solved, the integrity of the operation state data is ensured, and the accuracy of temperature correction is further improved.

[0056] Optionally, the method further includes:

[0057] Determine the reference time points for the air conditioner to switch from the shutdown state to the startup state and from the startup state to the shutdown state;

[0058] Use the duration between the reference time point and the nearest time point when the temperature data is measured as the state duration.

[0059] In this embodiment, the duration of the air conditioner in the startup or shutdown state is related to the gap between the indoor temperature data measured by the temperature sensor and the actual corrected indoor temperature. The longer the air conditioner runs in the startup state, the greater the gap between the indoor temperature data measured by the temperature sensor of the air conditioner and the actual indoor temperature data. Therefore, the state duration is an important parameter for determining the corrected indoor temperature.

[0060] By determining the reference time point and calculating the state duration, the duration of the operation state of the air conditioner can be obtained more accurately, avoiding correction errors caused by inaccurate time calculation, thereby improving the reliability of temperature correction.

[0061] In a possible embodiment, the temperature sensor in the air conditioner periodically measures the indoor temperature data. Optionally, the measurement period is 10 seconds.

[0062] In a possible embodiment, the temperature sensor in the air conditioner continuously measures the indoor temperature data. Table 1 shows the data used in the process of correcting the indoor temperature data in a possible embodiment. A backpropagation neural network (BPNN) is used to correct the indoor temperature data measured by the temperature sensor of the air conditioner. The inputs are the rotation speed data, the on / off state of the air conditioner, and the state duration of the on / off state of the air conditioner, and the output is the corrected temperature data.

[0063]

[0064] Table 1

[0065] By inputting the operating state data into the temperature correction model for feature extraction and generating the corrected indoor temperature, the automation and efficiency of temperature correction are achieved. At the same time, by utilizing the feature extraction ability of the model, the temperature data can be corrected more precisely, improving the accuracy of the corrected indoor temperature.

[0066] Optionally, the temperature correction model includes a backpropagation neural network, and the backpropagation neural network includes six hidden layers.

[0067] Figure 2 It is a schematic diagram of a model structure provided by an embodiment of the present application. As Figure 2 shown, in this embodiment, the input layer is i1 and i2, the hidden layers are h1 and h2, the output layer is o1, and b1 and b2 represent the biases of the input layer and the hidden layer respectively. Each line in the figure represents a weight, and the biases and weights are continuously changed in each iteration until the set number of iterations is reached or the required accuracy is achieved.

[0068] The input layer is used to receive the input training data; the hidden layer is used to perform feature extraction according to the training data; the output layer is used to obtain the corrected temperature according to the extracted features.

[0069] By designing the input layer, hidden layer, and output layer of the temperature correction model, the structure and function of the model are clarified, and the input data can be processed more efficiently and features can be extracted, thereby realizing a more accurate corrected temperature output and improving the overall performance and reliability of the model.

[0070] Optionally, the method for obtaining the training data set used in the training of the temperature correction model includes:

[0071] The air conditioner indoor fan is operated at different rotational speed data, and the training temperature data measured by the temperature sensor of the air conditioner is recorded; multiple temperature sensors are arranged indoors, and the temperature data within the same time is recorded and averaged as the actual temperature of the indoor environment;

[0072] A training data set is constructed according to the training temperature data, rotational speed data, and actual temperature.

[0073] In this embodiment, the training data is collected by experiment and a training data set is formed. A sample contains training temperature data, rotational speed data, the on / off state of the air conditioner, and the duration of the on / off state of the air conditioner. The label data corresponding to this sample is the actual temperature. The actual temperature corresponds to the corrected temperature data, which reflects the real temperature of the indoor space. Multiple samples are integrated into a set, and this set is the training data set.

[0074] In a possible embodiment, a random sampling method is used to divide the training data set into a training set and a test set, and the number of samples included is 80% and 20% of the samples in the training data set respectively. The hidden layer is set to 6 layers.

[0075] Figure 3 It is a schematic diagram of the effect of a temperature correction model provided by an embodiment of the present application. As Figure 3 shown, it includes the corrected indoor temperature predicted by the temperature correction model and the actual temperature of the indoor environment measured actually. The abscissa is the actual indoor temperature, and the ordinate is the corrected indoor temperature. The hollow circles represent samples, and the coordinates of the hollow circles include the corrected indoor temperature predicted by inputting the sample into the temperature correction model and the actual indoor temperature corresponding to the sample. The straight line in the figure is the regression line. The corrected indoor temperature and the actual indoor temperature corresponding to the coordinates on the straight line are equal. Therefore, the closer the hollow circle is to the regression line, the closer the corrected indoor temperature predicted according to the sample is to the actual indoor temperature, and the more accurate the model prediction is. According to multiple corrected indoor temperatures and actual temperatures, the determination coefficient R 2 value is 0.991. R 2 is one of the indicators for evaluating the performance of the model. It reflects the fitting degree of the model to the data, and the value range is from 0 to 1. The closer the R 2 value is to 1, the stronger the interpretation ability of the model to the data and the better the fitting effect. Therefore, through the correction of the temperature correction model, the obtained corrected indoor temperature is closer to the actual value of the indoor temperature than the indoor temperature data measured by the temperature sensor of the air conditioner.

[0076] By obtaining the training temperature data, rotation speed data and actual temperature of the air conditioner to generate training data, and using the training data to train the temperature correction model, a temperature correction model based on actual data can be constructed, improving the generalization ability and correction accuracy of the model, and providing a reliable basis for subsequent temperature correction.

[0077] To implement the above embodiment, an embodiment of the present application also proposes a device for correcting the indoor temperature. The device for correcting the indoor temperature can implement the method as described above.

[0078] Figure 4 It is a schematic structural diagram of a device for correcting the indoor temperature provided by an embodiment of the present application.

[0079] As Figure 4 shown, the device may include:

[0080] A collection module 410, configured to obtain the rotation speed data of the indoor fan of the air conditioner and collect the indoor temperature data measured by the temperature sensor of the air conditioner;

[0081] A temperature correction module 420 is configured to use the rotational speed data and the indoor temperature data as input parameters and input them into a temperature correction model to obtain temperature correction data, thereby obtaining a corrected indoor temperature.

[0082] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and details are not described herein again.

[0083] To implement the above embodiments, the present application also provides a non-transitory computer-readable storage medium having stored thereon a computer program, which when executed by a processor, implements the method as described in the foregoing method embodiments.

[0084] To implement the above embodiments, the present application also provides a computer program product having stored thereon a computer program, which when executed by a processor, implements the method as described in the foregoing method embodiments.

[0085] To implement the above embodiments, the present application also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where when the processor executes the program, the method as described in the foregoing method embodiments is implemented.

[0086] Figure 5 FIG. is a schematic structural diagram of an electronic device provided by an embodiment of the present application. For example, the electronic device 800 may be an air conditioner, a temperature adjustment device, or the like.

[0087] Referring to Figure 5 , the electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0088] The processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communication, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0089] The memory 804 is configured to store various types of data to support the operation of the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, pictures, videos, and the like. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disk.

[0090] The power component 806 provides power to the various components of the electronic device 800. The power component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.

[0091] The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors can not only sense the boundaries of the touch or swipe actions but also detect the duration and pressure associated with the touch or swipe operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the electronic device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each of the front camera and the rear camera can be a fixed optical lens system or have a focal length and optical zoom capabilities.

[0092] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC) that is configured to receive external audio signals when the electronic device 800 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals can be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, the audio component 810 further includes a speaker for outputting audio signals.

[0093] The I / O interface 812 provides an interface between the processing component 802 and a peripheral interface module, which can be a keyboard, a click wheel, buttons, and the like. These buttons can include, but are not limited to: a home button, a volume button, a power-on button, and a lock button.

[0094] The sensor assembly 814 includes one or more sensors for providing an assessment of the status of the electronic device 800 in various aspects. For example, the sensor assembly 814 can detect the on / off state of the electronic device 800, the relative positioning of components, such as the display and keypad of the electronic device 800. The sensor assembly 814 can also detect a change in the position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, the orientation or acceleration / deceleration of the electronic device 800, and the temperature change of the electronic device 800. The sensor assembly 814 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 814 can also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 can also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0095] The communication component 816 is configured to facilitate communication between the electronic device 800 and other devices in a wired or wireless manner. The electronic device 800 can access a wireless network based on communication standards, such as WiFi, 4G, or 5G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0096] In an exemplary embodiment, the electronic device 800 can be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the above method.

[0097] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the above instructions can be executed by a processor 820 of the electronic device 800 to complete the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0098] To implement the above embodiments, the present application also provides a chip, including: The chip includes a processing circuit configured to execute the method provided in the foregoing embodiments.

[0099] Figure 6 FIG. 4 is a schematic structural diagram of a chip provided by an embodiment of the present application. Reference may be made to Figure 6 the schematic structural diagram of the chip 1100 shown in FIG. 5, but not limited thereto.

[0100] The chip 1100 includes a processing circuit 1101 configured to execute any of the above methods.

[0101] In some embodiments, the chip 1100 further includes one or more interface circuits 1102. Optionally, the interface circuit 1102 is connected to the memory 1103. The interface circuit 1102 can be used to receive signals from the memory 1103 or other devices, and the interface circuit 1102 can be used to send signals to the memory 1103 or other devices. For example, the interface circuit 1102 can read the instructions stored in the memory 1103 and send the instructions to the processing circuit 1101.

[0102] In some embodiments, the interface circuit 1102 executes at least one of the communication steps such as sending and / or receiving in the above method, and the processing circuit 1101 executes other steps.

[0103] In some embodiments, terms such as interface circuit, interface, transceiver pin, transceiver, etc. can be used interchangeably.

[0104] In some embodiments, the chip 1100 further includes one or more memories 1103 for storing instructions. Optionally, all or part of the memories 1103 can be outside the chip 1100.

[0105] In the description of this specification, the descriptions with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0106] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In the description of this application, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically and clearly defined.

[0107] Any process or method description represented in a flowchart or described otherwise herein can be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a customized logical function or process. The scope of the preferred embodiments of this application includes additional implementations, where functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed. This should be understood by those skilled in the technical field to which the embodiments of this application pertain.

[0108] The logic and / or steps represented in a flowchart or described otherwise herein, for example, can be considered as an ordered list of executable instructions for implementing a logical function, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in conjunction with such instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other appropriate processing as necessary, and then stored in a computer memory.

[0109] It should be understood that each part of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits with logic gate circuits for implementing logic functions on data signals, application specific integrated circuits with appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0110] Those of ordinary skill in the art can understand that all or part of the steps carried by the method of the above embodiments can be completed by instructing relevant hardware through a program. The said program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0111] In addition, in each embodiment of the present application, each functional unit can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module. When the above integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0112] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A method for correcting indoor temperature, characterized in that, Including: Obtain the rotation speed data of the indoor fan of the air conditioner, and collect the indoor temperature data measured by the temperature sensor of the air conditioner; Use the rotation speed data and the indoor temperature data as input parameters, and input them into a temperature correction model to obtain temperature correction data, so as to obtain a corrected indoor temperature.

2. The method according to claim 1, wherein The input parameters further include at least one of the following: The on / off state of the air conditioner, and the duration of the on / off state of the air conditioner.

3. The method according to claim 1, characterized in that, The obtaining of the rotation speed data of the indoor fan of the air conditioner includes at least one of the following: In response to the air conditioner being in an operating state, determine the rotation speed data according to the rotation speed of the indoor fan of the air conditioner in the operating state; In response to the air conditioner being in a shutdown state, determine the rotation speed data according to the rotation speed of the indoor fan of the air conditioner at the moment before the air conditioner enters the shutdown state.

4. The method according to claim 3, characterized in that, The method further includes: Determine the reference time points for the air conditioner to switch from shutdown to startup and from startup to shutdown; Use the time duration between the reference time point and the nearest time point for measuring the temperature data as the duration of the state.

5. The method according to claim 1, wherein The temperature correction model includes a backpropagation neural network, and the backpropagation neural network includes six hidden layers.

6. The method according to claim 1, wherein The method for obtaining the training data set used in the training of the temperature correction model includes: Run the indoor fan of the air conditioner at different rotation speed data, and record the training temperature data measured by the temperature sensor of the air conditioner; arrange multiple temperature sensors indoors, record the temperature data within the same time and take the average value as the actual temperature of the indoor environment; Construct a training data set according to the training temperature data, rotation speed data and actual temperature.

7. A device for correcting indoor temperature, characterized in that, The device for correcting the indoor temperature can implement the method described in any one of the foregoing claims.

8. An electronic device, characterized in that, Including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the method described in any one of the foregoing claims.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method described in any one of the foregoing claims.

10. A chip, characterized in that, The chip includes a processing circuit, and the processing circuit is configured to execute the method described in any one of the foregoing claims.

11. A computer program product, characterized in that, Including a computer program, when the computer program is executed by the processor, it implements the method described in any one of the foregoing.

Images