Method and device for detecting indoor space temperature distribution and storage medium

Abstract

The invention relates to the technical field of temperature detection, and discloses a method for detecting indoor space temperature distribution, which comprises the following steps: dividing an indoor space where an intelligent air conditioner is located into a plurality of areas according to a preset division rule; a voice module of the intelligent air conditioner is controlled to send distance measuring ultrasonic waves to the obstacle reflecting surfaces in the multiple areas so as to obtain distance values between the obstacle reflecting surfaces in the multiple areas and the first microphone; respectively determining the average temperature value of each region according to the distance values between the barrier reflecting surfaces in the plurality of regions and the first microphone; and generating an area average temperature sequence table according to the average temperature value of each area. In this way, the feedback data, received by the voice module of the intelligent air conditioner, of all the areas are used for measuring and calculating the average temperature values of all the areas, and then the more accurate area average temperature sequence table is generated, so that a user can accurately know the distribution condition of indoor space temperature. The invention further discloses a device for detecting the indoor space temperature distribution and a storage medium.

Description

Technical Field

[0001] The present application relates to the field of temperature detection technology, for example, to a method, device and storage medium for detecting temperature distribution in an indoor space. Background Art

[0002] As people's living standards continue to improve, smart home appliances are gradually entering users' lives. At present, smart air conditioners can detect the temperature of the air conditioner's own space through their own temperature sensors, but they cannot detect the temperature distribution in the installation environment.

[0003] At present, users can arrange multiple temperature sensors or multiple IoT devices with temperature measurement functions at different locations in the smart air conditioner installation environment, so as to determine the temperature distribution in the smart air conditioner installation environment through the temperature conditions collected by different sensors or IoT devices in the case of networking. However, the cost of temperature distribution detection in this way is high. Once the arrangement position of the sensor or IoT device is unreasonable, it will be difficult to determine the temperature distribution of the indoor space more accurately. Therefore, how to accurately detect the temperature distribution of the indoor space where the smart air conditioner is located has become a technical problem that needs to be solved urgently.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present application, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical components or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0006] The embodiments of the present disclosure provide a method, device and storage medium for detecting the temperature distribution of an indoor space, which can more accurately detect the temperature distribution of the indoor space where the smart air conditioner is located.

[0007] In some embodiments, the method for detecting the temperature distribution of an indoor space includes: dividing the indoor space where the smart air conditioner is located into multiple areas according to a preset division rule; controlling the voice module of the smart air conditioner to send ranging ultrasonic waves to the obstacle reflection surfaces in the multiple areas respectively, so as to obtain the distance values ​​between the obstacle reflection surfaces and the first microphone in the multiple areas; determining the average temperature value of each area respectively according to the distance values ​​between the obstacle reflection surfaces and the first microphone in the multiple areas; and generating a regional average temperature sequence list according to the average temperature values ​​of each area.

[0008] In some embodiments, the device for detecting the temperature distribution of an indoor space includes: a division module, configured to divide the indoor space where the smart air conditioner is located into multiple areas according to a preset division rule; a control module, configured to control the voice module of the smart air conditioner to send ranging ultrasonic waves to the obstacle reflection surfaces in multiple areas respectively, so as to obtain the distance values ​​between the obstacle reflection surfaces and the first microphone in multiple areas; a determination module, configured to determine the average temperature value of each area according to the distance values ​​between the obstacle reflection surfaces and the first microphone in multiple areas; and a generation module, configured to generate a regional average temperature sequence list according to the average temperature value of each area.

[0009] In some embodiments, the device for detecting indoor space temperature distribution includes: a processor and a memory storing program instructions, and the processor is configured to execute the aforementioned method for detecting indoor space temperature distribution when running the program instructions.

[0010] In some embodiments, the storage medium stores program instructions, and when the program instructions are run, the aforementioned method for detecting the temperature distribution of an indoor space is executed.

[0011] The method, device and storage medium for detecting the temperature distribution of indoor space provided by the embodiment of the present disclosure can achieve the following technical effects: by dividing the indoor space where the smart air conditioner is located into multiple areas according to the preset division rule; and controlling the voice module of the smart air conditioner to send ranging ultrasonic waves to the obstacle reflection surfaces in the multiple areas respectively, so as to obtain the distance values ​​between the obstacle reflection surfaces and the first microphone in the multiple areas; thereby determining the average temperature value of each area respectively according to the distance values ​​between the obstacle reflection surfaces and the first microphone in the multiple areas; and then generating a regional average temperature sequence table according to the average temperature value of each area. In this way, after the indoor space where the smart air conditioner is located is divided into multiple areas, the voice module of the smart air conditioner can be used to send ranging ultrasonic waves to the obstacle reflection surfaces in different areas respectively, so as to calculate the average temperature value of each area through the feedback data of each area received by the voice module, and then generate a more accurate regional average temperature sequence table, so that the user can learn the distribution of the indoor space temperature by reading the regional average temperature sequence table. Compared with the existing indoor temperature detection method, it has lower cost and higher accuracy, and meets the user's demand for accurate detection of indoor space temperature distribution.

[0012] The above general description and the following description are exemplary and explanatory only and are not intended to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] One or more embodiments are exemplarily described by corresponding drawings, which do not limit the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements, and the drawings do not constitute a scale limitation, and wherein:

[0014] Figure 1-1 is a schematic diagram of area division for indoor space provided by an embodiment of the present disclosure;

[0015] Figure 1-2 is a schematic diagram of ultrasonic wave propagation sent by a voice module provided by an embodiment of the present disclosure;

[0016] Figure 1-3 is a regional schematic diagram of an indoor space in an embodiment of the present disclosure;

[0017] Figure 2 is a schematic diagram of a method for detecting temperature distribution in an indoor space provided by an embodiment of the present disclosure;

[0018] Figure 3 is a schematic diagram of a method for determining an average temperature value of a first area provided by an embodiment of the present disclosure;

[0019] Figure 4 is a schematic diagram of a method for determining a frequency correction strategy provided by an embodiment of the present disclosure;

[0020] Figure 5 is a schematic diagram of a device for detecting temperature distribution in an indoor space provided by an embodiment of the present disclosure;

[0021] Figure 6 It is a schematic diagram of another device for detecting temperature distribution in an indoor space provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0022] In order to be able to understand the features and technical contents of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The attached drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the convenience of explanation, a full understanding of the disclosed embodiments is provided through multiple details. However, one or more embodiments can still be implemented without these details. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.

[0023] The terms "first", "second", etc. in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged where appropriate, so that the embodiments of the embodiments of the present disclosure described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions.

[0024] Unless otherwise stated, the term "plurality" means two or more.

[0025] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B indicates: A or B.

[0026] The term "and / or" is a description of the association relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B.

[0027] The term "correspondence" may refer to an association relationship or a binding relationship. The correspondence between A and B means that there is an association relationship or a binding relationship between A and B.

[0028] Figure 1-1 is a schematic diagram of area division for indoor space provided by an embodiment of the present disclosure; Figure 1-2 is a schematic diagram of ultrasonic wave propagation sent by a voice module provided by an embodiment of the present disclosure; Figure 2 is a schematic diagram of a method for detecting indoor space temperature distribution provided by an embodiment of the present disclosure; Figure 1-1 to Figure 2 As shown, the embodiment of the present disclosure provides a method for detecting temperature distribution in an indoor space, comprising:

[0029] S21, the smart air conditioner divides the indoor space where the smart air conditioner is located into multiple areas according to a preset division rule.

[0030] S22, the smart air conditioner controls the voice module of the smart air conditioner to send ranging ultrasonic waves to the obstacle reflection surfaces in multiple areas respectively, so as to obtain the distance values ​​between the obstacle reflection surfaces in the multiple areas and the first microphone.

[0031] S23, the intelligent air conditioner determines the average temperature value of each area according to the distance values ​​between the obstacle reflective surface and the first microphone in the multiple areas.

[0032] S24, the intelligent air conditioner generates a regional average temperature sequence table according to the average temperature value of each area.

[0033] In this solution, the smart air conditioner is equipped with a voice module, which includes a speaker unit for emitting ultrasonic waves, a first microphone for receiving ultrasonic reflection signals, and a second microphone arranged adjacent to the first microphone. Specifically, the smart air conditioner can divide the indoor space where it is located into multiple areas according to a preset division rule. Here, the preset division rule includes dividing the indoor space where the smart air conditioner is located into multiple fan-shaped areas with preset angles with the first microphone as the center. As an example, Figure 1-1 As shown, the preset angle is 10°, then the indoor space where the smart air conditioner is located can be divided into 12 10° fan-shaped areas with the first microphone as the center according to the preset division rules, such as the first area S1, the second area S2, the third area S3, the fourth area S4, the fifth area S5, the sixth area S6, the seventh area S7, the eighth area S8, the ninth area S9, the tenth area S10, the eleventh area S11 and the twelfth area S12. In this way, the indoor space where the smart air conditioner is located can be accurately divided into areas in combination with the preset division rules. It should be noted that the radius of each area is determined by the dynamic scanning of ultrasonic ranging; and due to the emission angle of the speaker unit, there will be a 30° blind area on the left and right sides of the first microphone. Therefore, the blind areas on both sides are not divided into areas.

[0034] Furthermore, after the indoor space where the smart air conditioner is located is divided into multiple areas, the voice module controlling the smart air conditioner sends ranging ultrasonic waves to the obstacle reflection surfaces in the multiple areas respectively. The obstacle reflection surface in each area can be the wall on the opposite side of the air conditioner. Specifically, Figure 1-2 As shown, taking the first area S1 as an example, the air conditioner can control the voice module to send a ranging ultrasonic wave to the obstacle reflection surface A in the first area S1, and after the first microphone C1 receives the feedback signal of the ranging ultrasonic wave, the distance value d1 between the obstacle reflection surface A and the first microphone C1 is calculated by combining the sending time of the ranging ultrasonic wave, the receiving time of the feedback signal and the indoor sound wave speed. In this way, the distance value between the obstacle reflection surface and the first microphone in a single area can be accurately obtained.

[0035] As a preferred solution, the ranging ultrasonic wave can be sent directionally to each area in turn according to the preset sending order of the ranging ultrasonic wave. As an example, the preset sending order of the ranging ultrasonic wave can be a serial number order from small to large, that is, S1, S2, S3, S4, S5, etc. In this way, the ranging ultrasonic wave can be sent to each area in turn through the voice module in the preset order, so as to calculate the distance value between the obstacle reflecting surface and the first microphone in multiple areas in turn by the calculation method of the distance value between the obstacle reflecting surface and the first microphone in the aforementioned single area, so as to achieve accurate acquisition of the distance value between the obstacle reflecting surface and the first microphone in multiple areas.

[0036] Furthermore, after obtaining the distance values ​​between the obstacle reflection surface and the first microphone in multiple areas, the air conditioner can combine the distance values ​​between the obstacle reflection surface and the first microphone in multiple areas to determine the average temperature value of each area. In this way, the average temperature value of each area can be accurately obtained, providing an accurate data basis for the generation of the regional average temperature sequence table.

[0037] Furthermore, after determining the average temperature value of each region, a regional average temperature sequence table can be generated for a preset table type. As an example, Table 1 is a regional average temperature sequence table. As shown in Table 1:

[0038]

[0039] Table 1

[0040] It can be understood that the regional average temperature sequence table is not limited to the form of Table 1. In this embodiment, as long as the average temperature of each region can be clearly displayed, the specific form of the sequence table is not specifically limited.

[0041] By adopting the method for detecting the temperature distribution of an indoor space provided by the embodiment of the present disclosure, after the indoor space where the smart air conditioner is located is divided into multiple areas, the voice module of the smart air conditioner can be used to send ranging ultrasonic waves to the obstacle reflective surfaces in different areas respectively, so as to calculate the average temperature value of each area through the feedback data of each area received by the voice module, and then generate a more accurate regional average temperature sequence table, so that the user can obtain the distribution of the indoor space temperature by reading the regional average temperature sequence table. Compared with the existing indoor temperature detection method, the cost is lower and the accuracy is higher, which meets the user's demand for accurate detection of the indoor space temperature distribution.

[0042] Figure 3 is a schematic diagram of a method for determining an average temperature value of a first region provided by an embodiment of the present disclosure; Figure 3 As shown, optionally, the intelligent air conditioner determines the average temperature value of the first area according to the distance value between the obstacle reflection surface in the first area and the first microphone, including:

[0043] S31, the intelligent air conditioner calculates the wavelength interval width of the first area according to the distance value between the obstacle reflecting surface in the first area and the first microphone and the distance value between the obstacle reflecting surface in the first area and the second microphone.

[0044] S32, the intelligent air conditioner divides the first area according to the wavelength interval width and the first preset step size of the first area to obtain multiple groups of detection signal units.

[0045] S33, the intelligent air-conditioning control voice module sends detection ultrasonic waves to the multiple groups of detection signal units respectively, so that the voice module receives data fed back by different groups of detection signal units.

[0046] S34, the intelligent air conditioner determines the average temperature value of the first area according to the data fed back by the different groups of detection signal units.

[0047] In this solution, the smart air conditioner can determine the average temperature value of each area according to the distance value between the obstacle reflective surface and the first microphone in multiple areas. Here, the method for determining the average temperature value of each area is the same. Taking the first area as an example, the smart air conditioner can determine the average temperature value of the first area according to the distance value between the obstacle reflective surface and the first microphone in the first area. Specifically, the smart air conditioner can calculate the wavelength range width of the first area according to the distance value between the obstacle reflective surface and the first microphone in the first area and the distance value between the obstacle reflective surface and the second microphone in the first area. Here, if Figure 1-2 As shown, the distance value d1 between the obstacle reflection surface A and the first microphone C1 in the first area can be calculated by the transmission time of the ranging ultrasonic wave, the feedback signal reception time of the first microphone C1 and the indoor sound wave speed; the distance value between the obstacle reflection surface and the second microphone C2 in the first area can be calculated by the acquired angle α and the distance between the first microphone C1 and the second microphone C2 through the law of cosines. Generally, the distance between the first microphone C1 and the second microphone C2 is 35mm. Furthermore, after obtaining the error value of ultrasonic ranging, the intelligent air conditioner can calculate the path difference according to the distance value between the obstacle reflection surface and the first microphone in the first area, the distance value between the obstacle reflection surface and the second microphone in the first area and the error value of ultrasonic ranging; thereby taking the quotient of the path difference and the path coefficient corresponding to the first area as the wavelength interval width of the first area. In this way, the wavelength interval width of the first area can be accurately determined.

[0048] Furthermore, after determining the wavelength interval width of the first area, the smart air conditioner can divide the first area according to the wavelength interval width of the first area and the first preset step size to obtain multiple groups of detection signal units. As an example, the first preset step size is 0.01*I, where the value range of I is 1 to 5. In this way, the wavelength interval width of the first area can be divided into equal parts according to 0.01*I to obtain multiple groups of detection signal units. As a preferred solution, a single area can be divided into up to 5 equal parts. In this way, accurate division of multiple groups of detection signal units is achieved.

[0049] Furthermore, the smart air conditioner can control the voice module to send detection ultrasonic waves to multiple groups of detection signal units respectively. Here, the smart air conditioner can send detection ultrasonic waves to multiple groups of detection signal units in the first area in sequence according to a preset sending order, so that the first microphone and the second microphone can receive the data fed back by each group of detection signal units in sequence. Among them, the sampling time of the first microphone and the second microphone is aligned with the sending period of the speaker unit and the data sampling is performed synchronously. Optionally, the first microphone and the second microphone delay the data interception by 30ms from the starting sending time of each detection ultrasonic wave, and the interception width is 50 milliseconds. In this way, the integrity and stability of the sampling data of the voice module are ensured.

[0050] Furthermore, after receiving the data fed back by each group of detection signal units, the intelligent air conditioner can combine the data fed back by different groups of detection signal units to determine the average temperature value of the first area. In this way, after the first area is divided into multiple groups of detection signal units, the average temperature value of the first area can be accurately determined by combining the data fed back by different groups of detection signal units received by the voice module.

[0051] Optionally, S31, the intelligent air conditioner calculates the wavelength interval width of the first area according to the distance value between the obstacle reflection surface in the first area and the first microphone and the distance value between the obstacle reflection surface in the first area and the second microphone, including:

[0052] The smart air conditioner obtains the error value of ultrasonic ranging.

[0053] The intelligent air conditioner calculates the path difference according to the distance value between the obstacle reflecting surface in the first area and the first microphone, the distance value between the obstacle reflecting surface in the first area and the second microphone, and the error value of the ultrasonic ranging.

[0054] The intelligent air conditioner uses the quotient of the path difference and the path coefficient corresponding to the first area as the wavelength interval width of the first area.

[0055] It is understandable that there is a certain error in ultrasonic ranging. Therefore, the smart air conditioner can obtain the error value of ultrasonic ranging. Specifically, experiments have shown that the error value of ultrasonic ranging within a range of 6 meters indoors is ±300 mm. In this way, the smart air conditioner can determine that the error value of ultrasonic ranging is 300. In this way, the accurate determination of the error value of ultrasonic ranging can be achieved.

[0056] Furthermore, the intelligent air conditioner calculates the path difference according to the distance value between the obstacle reflection surface in the first area and the first microphone, the distance value between the obstacle reflection surface in the first area and the second microphone, and the error value of ultrasonic ranging, including: the intelligent air conditioner calculates the first path difference and the second path difference according to the distance value between the obstacle reflection surface in the first area and the first microphone, the distance value between the obstacle reflection surface in the first area and the second microphone, and the error value of ultrasonic ranging; the intelligent air conditioner uses the difference between the first path difference and the second path difference as the path difference. In this way, accurate calculation of the path difference can be achieved.

[0057] Specifically, the intelligent air conditioner calculates the first path difference according to the distance between the obstacle reflection surface in the first area and the first microphone, the distance between the obstacle reflection surface in the first area and the second microphone, and the error value of the ultrasonic ranging, including:

[0058] △d1=(d1+300-d2 max )

[0059] Among them, △d1 is the first wave path difference, d1 is the distance between the obstacle reflection surface in the first area and the first microphone, and d2 max is the distance between the obstacle reflective surface in the first area and the second microphone, d2 max It can be calculated by using the cosine theorem when the distance between the obstacle reflection surface in the first area and the first microphone is d1+300.

[0060] Specifically, the intelligent air conditioner calculates the second path difference according to the distance between the obstacle reflection surface in the first area and the first microphone, the distance between the obstacle reflection surface in the first area and the second microphone, and the error value of the ultrasonic ranging, including:

[0061] △d2=(d1-300-d2 min )

[0062] Among them, △d2 is the second path difference, d1 is the distance between the obstacle reflection surface in the first area and the first microphone, and d2 min is the distance between the obstacle reflective surface in the first area and the second microphone, d2 min It can be calculated by the cosine theorem when the distance value between the obstacle reflection surface in the first area and the first microphone is d1-300.

[0063] Specifically, the intelligent air conditioner uses the difference between the first path difference and the second path difference as the path difference, including:

[0064] △d=△d1-△d2

[0065] Among them, △d is the wave path difference, △d1 is the first wave path difference, and △d2 is the second wave path difference.

[0066] In this solution, the smart air conditioner can match the path coefficient m1 corresponding to the first area, so as to determine the wavelength interval width △λ1=△d / m1 of the first area. In this solution, the wavelength interval width of the first area can be accurately determined by combining the path difference and the path coefficient corresponding to the first area.

[0067] It can be understood that from the above discussion, it can be inferred that the wavelength interval width of different areas is the quotient of the path difference of the area and the path coefficient corresponding to the area. In this embodiment, the intelligent air conditioner can pre-store the path coefficients corresponding to different areas after testing. As an example, the path coefficients corresponding to the first area and the twelfth area are 6; the path coefficients corresponding to the second area, the third area, the tenth area, and the eleventh area are 4; the path coefficients corresponding to the fourth area, the fifth area, the eighth area, and the ninth area are 2; the path coefficients corresponding to the sixth area and the seventh area are 1. In this way, after determining the path coefficients of the corresponding areas, the wavelength interval widths of different areas can be calculated in combination with the above method, providing an accurate data basis for the division of the detection signal units in each area.

[0068] Optionally, the plurality of detection signal units include a first detection signal unit, and the intelligent air conditioner control voice module sends a detection ultrasonic wave to the first detection signal unit, including:

[0069] The intelligent air conditioning control voice module sends detection ultrasonic waves to the first detection signal unit multiple times at preset time intervals. The frequency of the detection ultrasonic waves sent by the voice module each time is determined by the frequency of the detection ultrasonic waves sent last time and the frequency correction strategy, and the frequency of the detection ultrasonic waves sent by the voice module to the first detection signal unit for the first time is the initial frequency.

[0070] In this solution, the intelligent air conditioner controls the voice module to send detection ultrasonic waves to multiple groups of detection signal units in sequence according to the sequence number of the detection signal units. Here, the intelligent air conditioner sends the detection ultrasonic waves to each group of detection signal units in the same way. Taking the first detection signal unit as an example, the intelligent air conditioner can control the voice module to send detection ultrasonic waves to the first detection signal unit multiple times at preset time intervals. Among them, the preset time interval can be 100ms, and the frequency at which the voice module first sends the detection ultrasonic wave to the first detection signal unit is the initial frequency. Specifically, the initial frequency is the quotient of the wavelength λ1 selected by the first detection signal unit and the target sound speed. Optionally, after obtaining the temperature of the environment where the intelligent air conditioner is located, the sound speed within the preset range where the intelligent air conditioner is located can be calculated and determined as the target sound speed. Among them, the preset range is a circumferential range with the intelligent air conditioner as the center and a radius of 1 meter. In this way, on the basis of accurately calculating the initial frequency, the voice module can be controlled to send the detection ultrasonic wave for the first time according to the initial frequency. It should be noted that when the voice module periodically sends out detection ultrasonic waves, the frequency of each detection ultrasonic wave sent out is different. The frequency of each detection ultrasonic wave sent out by the voice module is determined by the frequency of the detection ultrasonic wave sent out last time and the frequency correction strategy. In this way, the frequency of each detection ultrasonic wave sent out by the voice module can be accurately calculated.

[0071] Figure 4 is a schematic diagram of a method for determining a frequency correction strategy provided by an embodiment of the present disclosure; Figure 4 As shown, optionally, the frequency correction strategy is determined in the following manner:

[0072] S41, the smart air conditioner determines the current operation mode of the smart air conditioner.

[0073] S421, when the current operation mode of the intelligent air conditioner is the cooling mode, the intelligent air conditioner determines a frequency correction strategy to increase gradually according to a second preset step size.

[0074] S422: When the current operation mode of the intelligent air conditioner is the heating mode, the intelligent air conditioner determines a frequency correction strategy that is to decrease gradually according to a second preset step size.

[0075] In this solution, the smart air conditioner can determine the current operating mode of the smart air conditioner through its operating information. Here, the current operating mode of the smart air conditioner can be a cooling mode or a heating mode. In this way, the air conditioner operating mode can be accurately determined.

[0076] Furthermore, when the current operating mode of the smart air conditioner is the cooling mode, the smart air conditioner determines that the frequency correction strategy is to increase gradually according to the second preset step size. Here, the second preset step size is 20HZ. Specifically, the frequency of the detection ultrasonic wave sent for the second time = the initial frequency + 20, the frequency of the detection ultrasonic wave sent for the third time = the frequency of the detection ultrasonic wave sent for the second time + 20, the frequency of the detection ultrasonic wave sent for the fourth time = the frequency of the detection ultrasonic wave sent for the third time + 20, and so on. In this way, the frequency correction strategy can be accurately determined when the current operating mode of the smart air conditioner is the cooling mode.

[0077] Similarly, when the current operating mode of the smart air conditioner is the heating mode, the smart air conditioner determines the frequency correction strategy to decrease gradually according to the second preset step size. Here, the second preset step size is 20HZ. Specifically, the frequency of the detection ultrasonic wave sent for the second time = the initial frequency - 20, the frequency of the detection ultrasonic wave sent for the third time = the frequency of the detection ultrasonic wave sent for the second time - 20, the frequency of the detection ultrasonic wave sent for the fourth time = the frequency of the detection ultrasonic wave sent for the third time - 20, and so on. In this way, the frequency correction strategy can be accurately determined when the current operating mode of the smart air conditioner is the heating mode.

[0078] Optionally, S34, the intelligent air conditioner determines the average temperature value of the first area according to the data fed back by the different groups of detection signal units, including:

[0079] The intelligent air conditioner processes the data fed back by each group of detection signal units respectively to determine the target wavelength and target frequency of the first area.

[0080] The intelligent air conditioner uses the product of the target wavelength and the target frequency as the average sound speed of the first area.

[0081] The intelligent air conditioner calculates an average temperature value of the first area according to the average sound velocity of the first area.

[0082] In this embodiment, the intelligent air conditioner processes the data fed back by each group of detection signal units respectively to determine the target wavelength and target frequency of the first area, including:

[0083] The intelligent air conditioner processes the data fed back by each group of detection signal units in the first area in turn to obtain multiple groups of processed data;

[0084] The intelligent air conditioner calculates each group of processed data in turn to obtain the area of ​​the Lissajous figure of each group of data;

[0085] The intelligent air conditioner compares the areas of the Lissajous figures of each set of data to select the wavelength and frequency corresponding to the Lissajous figure with the smallest area;

[0086] The intelligent air conditioner uses the wavelength and frequency corresponding to the Lissajous figure with the smallest area as the target wavelength and target frequency of the area.

[0087] It can be understood that the smart air conditioner processes the data fed back by each group of detection signal units in the same way. Specifically, taking the first group of detection signal units as an example, the smart air conditioner processes the data fed back by the first group of detection signal units, including: the smart air conditioner normalizes the data fed back by the first group of detection signal units so that its amplitude is in [-1,1]; the smart air conditioner uses a bandpass filter in the range of [18K, 42k] to filter noise to reduce the noise interference of the environment where the smart air conditioner is located; the smart air conditioner intercepts the filtered data according to a width of 50ms to obtain the data processed by the first group of detection signal units. It should be noted that due to the limitation of the device, the detection frequency interval used in this embodiment is [20K, 40K]. The data fed back by the first group of detection signal units includes the sampling data of the first microphone and the second microphone in multiple frequency conversion cycles. As a preferred embodiment, the multiple frequency conversion cycles can be 10.

[0088] Furthermore, the intelligent air conditioner calculates the processed data to obtain the area of ​​the Lissajous figure of the intercepted width signal data. It should be emphasized that since the data fed back by the first group of detection signal units contains the sampling data of the voice module in multiple frequency conversion cycles, the area of ​​the Lissajous figure needs to be calculated for the data of each frequency conversion cycle respectively. Specifically, the particle motion trajectory equation of the Lissajous figure (amplitude normalized) is X2+Y2-2XYcos(Δφ)=sin2(Δφ), which can be converted into discrete form, and the calculation formula for determining the Lissajous area is S 李萨茹 =Σ(Yi+1+Yi)(Xi+1-Xi) / 2, where i represents any sampling point, starting from zero, the maximum value of i = sampling frequency*sampling width, the sampling frequency is 96KHz, the sampling width is 50 milliseconds, the X direction represents the sampling waveform of the first microphone, and the Y direction represents the sampling waveform of the second microphone. In this way, the area of ​​the Lissajous figure of each of the multiple frequency conversion cycle feedback data of the first group of detection signal units can be accurately obtained.

[0089] It can be understood that after the voice module sends a detection ultrasonic wave to a certain group of detection signal units, the detection ultrasonic wave will be reflected after encountering an obstacle. At this time, the reflected ultrasonic wave will be received and recorded by the first and second microphones; due to the principle of coherent waves, the same wave will be coherent at different distances due to different phases, and the area of ​​the figure formed when the phase difference between the two waveforms is Δφ=nΠ is the smallest, and the wavelength corresponding to the smallest area of ​​the Lissajous figure is the wavelength closest to the actual sound speed. Therefore, after the intelligent air conditioner calculates the area of ​​the Lissajous figure of each group of data in turn according to the aforementioned method, the area of ​​the Lissajous figure of each group of data is compared to screen out the wavelength and frequency corresponding to the Lissajous figure with the smallest area; thereby the wavelength and frequency corresponding to the Lissajous figure with the smallest area are used as the target wavelength and target frequency of the area. In this way, the target wavelength and target frequency can be accurately determined.

[0090] Furthermore, after determining the target wavelength and the target frequency, the intelligent air conditioner can use the product of the target wavelength and the target frequency as the average sound velocity of the first area. In this way, the average temperature value of the first area can be calculated based on the accurate calculation of the average sound velocity of the first area and the average sound velocity of the first area. In this way, the accurate determination of the average temperature value of the first area is achieved.

[0091] Optionally, the intelligent air conditioner calculates an average temperature value of the first area according to an average sound velocity of the first area, including:

[0092] T 平均 =(V 平均 -331.45) / 0.61

[0093] Among them, T 平均 is the average temperature of the first region, V 平均 is the average sound speed in the first region.

[0094] In this solution, after the intelligent air conditioner calculates the average sound velocity of each area, it can calculate the average temperature value of each area in combination with a specific algorithm. The average temperature value algorithm of each area is the same. Taking the first area as an example, T 平均 =(V 平均 -331.45) / 0.61; wherein Taverage is the average temperature value of the first region, and Vaverage is the average sound velocity of the first region. In this way, accurate calculation of the average temperature value is achieved.

[0095] In practical applications, the smart air conditioner is provided with a voice module, which includes a speaker unit for emitting ultrasonic waves, a first microphone for receiving ultrasonic reflection signals, and a second microphone arranged adjacent to the first microphone. Specifically, the smart air conditioner can divide the indoor space where the smart air conditioner is located into 12 fan-shaped areas with the first microphone as the center, and the angle of each fan-shaped area is 10°, so that it can be determined that the smart air conditioner divides the indoor space where it is located into 12 areas, and then divides each area into multiple groups of detection signal units, so as to use the screening criteria of the smallest area of ​​the Lissajous figure formed by the related wave to determine the closest actual target wavelength and target frequency of each area, so as to calculate the average sound speed of the area in combination with the closest actual target wavelength and target frequency of each area, and then calculate the average temperature value of the area in combination with the pre-stored algorithm. Further, the average temperature value of each area can be calculated in sequence to generate a regional average temperature sequence table. In this way, it is convenient for users to obtain the distribution of indoor space temperature by reading the regional average temperature sequence table. Compared with the existing indoor temperature detection method, it has lower cost and higher accuracy, and meets the user's accuracy detection requirements for indoor space temperature distribution.

[0096] Optionally, after the smart air conditioner divides the indoor space where the smart air conditioner is located into a plurality of areas according to a preset division rule, the method further includes:

[0097] The intelligent air conditioner determines a target area among the multiple areas according to respective average temperature values ​​of the multiple areas.

[0098] The intelligent air conditioner determines the target air supply strategy for the target area according to the heat conduction energy of each of the multiple areas.

[0099] Intelligent air conditioning control Intelligent air conditioning supplies air to the target area according to the target air supply strategy.

[0100] In this embodiment, the smart air conditioner can determine the target area among the multiple areas by combining the average temperature values ​​of the multiple areas. In this way, the target area that needs special air supply to balance the indoor temperature can be inferred by combining the average temperature values ​​of each area, so that the target area determined in this way is more consistent with the temperature distribution of the indoor space where the smart air conditioner is located.

[0101] It can be understood that from the principle of thermal balance, if the cooling capacity of the smart air conditioner is equal to the heat conduction energy of each indoor area, the smart air conditioner can provide the required cooling capacity for the indoor space. In other words, the smart air conditioner will also achieve the best energy-saving state when operating according to the cooling capacity. In this way, in order to determine a more energy-saving target air supply strategy, the smart air conditioner can calculate the heat conduction energy of each of the multiple areas, and determine the target air supply strategy of the smart air conditioner for the target area by combining the heat conduction energy of each of the multiple areas. In this way, the target air supply strategy can be accurately determined. Furthermore, the smart air conditioner controls it to supply air to the target area according to the target air supply strategy.

[0102] With this solution, after the indoor space where the smart air conditioner is located is divided into multiple areas, the target area among the multiple areas can be accurately determined by combining the average temperature values ​​of the multiple areas, and the target air supply strategy of the smart air conditioner for the target area can be accurately determined by combining the heat conduction energy of the multiple areas. When the smart air conditioner is controlled to supply air to the target area according to the target air supply strategy, the environment of the target area can be more specifically and accurately controlled, which is convenient for quickly improving the uneven temperature distribution of the indoor environment, and providing users with a more energy-saving smart air conditioning control solution.

[0103] Optionally, the intelligent air conditioner determines a target area among the multiple areas according to respective average temperature values ​​of the multiple areas, including:

[0104] Smart air conditioner obtains the current operating mode of the smart air conditioner.

[0105] The intelligent air conditioner determines a target area among the multiple areas according to a current operation mode of the intelligent air conditioner and respective average temperature values ​​of the multiple areas.

[0106] In this embodiment, the smart air conditioner can determine the current operating mode of the smart air conditioner through its operating information. Here, the current operating mode of the smart air conditioner can be a cooling mode or a heating mode. In this way, the current operating mode of the smart air conditioner can be accurately determined. It can be understood that the smart air conditioner can determine that the indoor space where the smart air conditioner is located needs cooling when running in the cooling mode; the smart air conditioner can determine that the indoor space where the smart air conditioner is located needs heat when running in the heating mode. Therefore, after the smart air conditioner determines the current operating mode, the smart air conditioner can determine the target area in multiple areas in combination with the current operating mode and the average temperature values ​​of each of the multiple areas. In this way, the target area can be accurately determined in multiple areas in combination with the cooling and heating requirements of the indoor space under different operating modes.

[0107] Optionally, the intelligent air conditioner determines a target area among the multiple areas according to a current operation mode of the intelligent air conditioner and respective average temperature values ​​of the multiple areas, including:

[0108] The intelligent air conditioner sequentially obtains the comparison result of the average temperature value of each area and the average temperature value of its adjacent areas.

[0109] When the current operation mode of the intelligent air conditioner is the cooling mode and the comparison result indicates that the average temperature value of one or more areas is lower than the average temperature value of its adjacent areas, the intelligent air conditioner determines the one or more areas as the target areas among the multiple areas.

[0110] When the current operation mode of the intelligent air conditioner is the heating mode and the comparison result indicates that the average temperature value of one or more areas is higher than the average temperature value of its adjacent areas, the intelligent air conditioner determines the one or more areas as target areas among the multiple areas.

[0111] In this embodiment, the intelligent air conditioner can predetermine the adjacent areas of each area. Specifically, the adjacent areas of each area are the areas on both sides of the area. For example, the adjacent areas of the second area are the first area and the third area, the adjacent areas of the third area are the second area and the fourth area, the adjacent areas of the fourth area are the third area and the fifth area, and so on. It should be noted that since the first area and the twelfth area are boundary areas, the adjacent area of ​​the first area is set to the second area, and the adjacent area of ​​the twelfth area is set to the eleventh area. Furthermore, the intelligent air conditioner obtains the comparison results of the average temperature value of each area and the average temperature value of the area adjacent to it in turn. Here, the number of comparison results matches the number of areas. For example, if the average temperature value of the first area is 26.5°C, and the average temperature value of the second area adjacent to it is 26.3°C, then the comparison result of the average temperature value of the first area and the adjacent area is determined as the average temperature value of the first area> the average temperature value of the second area; if the average temperature value of the sixth area is 24.8°C, and the average temperature value of the fifth area adjacent to it is 25.3°C, and the average temperature value of the seventh area is 24.9°C, then the comparison result of the average temperature value of the sixth area and the adjacent area is determined as the average temperature value of the fifth area> the average temperature value of the seventh area> the average temperature value of the sixth area. In this way, the comparison results of each area and the adjacent area can be obtained in sequence, ensuring the accuracy of data acquisition.

[0112] Furthermore, if the current operating mode of the intelligent air conditioner is the cooling mode, it is determined that the indoor space where the air conditioner is located needs cooling capacity, and one or more regions whose average temperature value of the region is lower than the average temperature value of its adjacent regions are screened out in the comparison results, and one or more regions are determined as target regions. For example, if the average temperature value of the first region is screened out in the comparison results < the average temperature value of the second region, the average temperature value of the fourth region is < the average temperature value of the fifth region < the average temperature value of the third region, and the average temperature value of the twelfth region is < the average temperature value of the eleventh region, then the first region, the fourth region and the twelfth region can be used as target regions that need cooling capacity when the intelligent air conditioner is running in the cooling mode. With this solution, the target region can be accurately determined when the air conditioner is running in the cooling mode. Similarly, if the current operating mode of the intelligent air conditioner is the heating mode, it is determined that the indoor space where the air conditioner is located needs heat, and one or more regions whose average temperature value of the region is higher than the average temperature value of its adjacent regions are screened out in the comparison results, and one or more regions are determined as target regions. For example, if the average temperature value of the second area> the average temperature value of the first area> the average temperature value of the third area, the average temperature value of the seventh area> the average temperature value of the eighth area> the average temperature value of the sixth area, and the average temperature value of the twelfth area> the average temperature value of the eleventh area are screened out in the comparison results, then when the smart air conditioner is running in heating mode, the second area, the seventh area, and the twelfth area can be used as target areas that require heat. With this solution, the target area can be accurately determined when the air conditioner is running in heating mode.

[0113] Optionally, the intelligent air conditioner determines a target air supply strategy for the target area according to the heat conduction energy of each of the multiple areas, including:

[0114] The intelligent air conditioner adds the heat conduction energy of the adjacent areas of the target area to obtain the heat conduction heat energy of the target area.

[0115] The smart air conditioner determines the target operating power of the smart air conditioner according to the thermal conduction heat energy of the target area.

[0116] The smart air conditioner will control the smart air conditioner to operate at the target operating power as the target air supply strategy of the smart air conditioner to the target area.

[0117] In this embodiment, the intelligent air conditioner adds the heat conduction energy of the adjacent areas of the target area to obtain the heat conduction energy of the target area, including: the intelligent air conditioner obtains the heat conduction energy of each area; the intelligent air conditioner adds the heat conduction energy of the adjacent areas of the target area to obtain the heat conduction energy of the target area. Specifically, the heat conduction energy of each area is obtained in the same way. Taking the second area as an example, optionally, the intelligent air conditioner obtains the heat conduction energy of the second area, including: the intelligent air conditioner obtains the temperature difference between the hot surface and the cold surface of the second area, the thermal conductivity, the area and cross-sectional thickness of the cold surface of the second area; the intelligent air conditioner calculates the heat conduction energy of the second area according to the temperature difference between the hot surface and the cold surface of the second area, the thermal conductivity, the area and cross-sectional thickness of the cold surface of the second area.

[0118] Optionally, the smart air conditioner obtains the temperature difference between the hot surface and the cold surface of the second area, including: the smart air conditioner obtains the temperature value of the hot surface and the temperature value of the cold surface of the second area; the smart air conditioner uses the difference between the temperature value of the hot surface and the temperature value of the cold surface of the second area as the temperature difference between the hot surface and the cold surface of the second area. It can be understood that, if Figure 1-3 As shown, the area is the second area, and the two sides of the second area include two area cross-sections, wherein the cross-section with a higher temperature is the hot surface, and the cross-section with a lower temperature is the cold surface, and the temperature values ​​of the hot surface and the cold surface can be determined by the temperature values ​​of their adjacent areas. For example, the side of the second area connected to the first area is the cold surface, and the side of the second area connected to the third area is the hot surface, then the temperature value of the cold surface of the second area is determined to be the temperature value of the first area, and the temperature value of the hot surface of the second area is the temperature value of the third area. In this way, the temperature value of the hot surface and the temperature value of the cold surface of the second area can be accurately determined, and a relatively accurate temperature difference value between the hot surface and the cold surface of the second area can be calculated.

[0119] Alternatively, thermal conductivity is generated by the continuous collision of molecules. Heat moves along the temperature gradient, from areas of high temperature and high molecular energy to areas of lower temperature and lower molecular energy. This transfer will continue until thermal equilibrium. Thermal conductivity is quantified using the International System of Units (SI units) W / m·K (watts per meter per degree Kelvin) and is the reciprocal of thermal resistivity, which is a measure of an object's ability to resist heat transfer.

[0120] Optionally, the intelligent air conditioner obtains the area of ​​the cold surface of the second region, including:

[0121] The intelligent air conditioner obtains the cold surface cross-sectional width and indoor house height;

[0122] The intelligent air conditioner determines the area of ​​the cold surface in the second zone according to the cross-sectional width of the cold surface and the indoor building height.

[0123] like Figure 1-3As shown, as an example, the voice module of the smart air conditioner can send a ranging ultrasonic wave to obtain the cross-sectional width Bc of the cold surface; the bedroom height value recommended in the national standard can be used as the indoor house height. In this way, after the smart air conditioner obtains the cross-sectional width of the cold surface and the indoor house height, the product of the cross-sectional width of the cold surface and the indoor house height can be used as the area of ​​the cold surface in the second area. That is, S 第二 =Bc*L; where S 第二 is the area of ​​the cold surface in the second zone, Bc is the cross-sectional width of the cold surface, and L is the indoor building height.

[0124] like Figure 1-3 As shown, it can be understood that the adjacent areas are all fan-shaped bodies formed by a fixed angle α. As an example, α is 10°. The arc length corresponding to the adjacent cross-section boundary is the maximum distance between the two cross-sections. In this way, the median arc length calculated by the cold surface cross-section radius can be used as the average distance between adjacent cross-sections, that is, the cross-section thickness H. Optionally, the cross-section thickness can be calculated in the following way:

[0125] H=2*π*Bc*α / 360

[0126] Where H is the cross-section thickness and Bc is the cold surface cross-section width. In this way, the cross-section thickness can be accurately determined.

[0127] Furthermore, after the intelligent air conditioner obtains the temperature difference between the hot surface and the cold surface of the second area, the thermal conductivity, the area and cross-sectional thickness of the cold surface of the second area, the heat conduction energy of the second area can be calculated according to the temperature difference between the hot surface and the cold surface of the second area, the thermal conductivity, the area and cross-sectional thickness of the cold surface of the second area. Specifically, the intelligent air conditioner calculates the heat conduction energy of the second area according to the temperature difference between the hot surface and the cold surface of the second area, the thermal conductivity, the area and cross-sectional thickness of the cold surface of the second area, including:

[0128] Q 第二 =△T*λ*S 第二 / H

[0129] Where Q is the heat conduction energy of the second region, △T is the temperature difference between the hot surface and the cold surface of the second region, λ is the thermal conductivity, S 第二 is the area of ​​the cold surface of the second region, and H is the cross-sectional thickness. In this way, the thermal conduction energy of the second region can be accurately calculated. It can be understood that the thermal conduction energy of each region is calculated in the same way. Therefore, in order to calculate the thermal conduction energy of different regions, it can be calculated by Q=△T·λ·S / H. Among them, Q is the thermal conduction energy of the region, △T is the temperature difference between the hot surface and the cold surface of the region, λ is the thermal conductivity, S is the area of ​​the cold surface of the region, and H is the cross-sectional thickness. In this way, the thermal conduction energy of each region can be obtained.

[0130] Furthermore, the intelligent air conditioner can add the heat conduction energy of the adjacent areas of the target area to obtain the heat conduction energy of the target area. For example, if the second area is the target area, the heat conduction energy of the first area and the heat conduction energy of the third area can be added to obtain the heat conduction energy of the target area. In this way, the heat conduction energy of the target area can be accurately calculated.

[0131] It can be understood that from the principle of thermal balance, if the cooling capacity / heating capacity of the smart air conditioner is equal to the heat conduction energy of each area in the room, the smart air conditioner can provide the required energy for the indoor space. In other words, the smart air conditioner will also achieve the best energy-saving state when operating according to the cooling capacity / heating capacity. Therefore, the smart air conditioner determines the target operating power of the smart air conditioner according to the heat conduction thermal energy of the target area, including: the smart air conditioner matches the operating power associated with the heat conduction thermal energy of the target area in the server end, and uses it as the target operating power. Among them, the operating power of the smart air conditioner corresponding to different heat conduction thermal energies is pre-stored in the server end, and the above correspondence is obtained by the R&D personnel through experiments. In this way, the accuracy of obtaining the target operating power is ensured, so that the target operating power determined in this way is more in line with the heat conduction law of the target area.

[0132] Furthermore, the smart air conditioner controls the smart air conditioner to operate at the target operating power as the target air supply strategy of the smart air conditioner to the target area. In this way, the air conditioner operating power can be set more energy-efficiently, meeting the user's energy-saving control needs for the smart air conditioner.

[0133] Optionally, the intelligent air conditioner determines a target air supply strategy for the target area according to the heat conduction energy of each of the multiple areas, including:

[0134] The intelligent air conditioner adds the heat conduction energy of the adjacent areas of the target area to obtain the heat conduction heat energy of the target area.

[0135] The smart air conditioner adds up the heat conduction energies of the multiple zones to obtain the total heat conduction energy.

[0136] The intelligent air conditioner determines the target swing air retention time of the intelligent air conditioner for the target area according to the ratio of the heat conduction heat energy of the target area to the total heat conduction energy.

[0137] The smart air conditioner will control the smart air conditioner to supply air to the target area according to the target swing wind retention time as the target air supply strategy of the smart air conditioner to the target area.

[0138] In this solution, the heat conduction energies of the adjacent areas of the target area can be added in the above-mentioned manner to obtain the heat conduction heat energy of the target area. Furthermore, the intelligent air conditioner can add the heat conduction energies of the multiple areas to obtain the total heat conduction energy. That is, the total heat conduction energy is the sum of the heat conduction energies of the first area to the twelfth area. In this way, the total heat conduction energy can be accurately determined.

[0139] Furthermore, after obtaining the thermal conduction energy and total thermal conduction energy of the target area, the smart air conditioner can calculate the ratio of the thermal conduction energy of the target area to the total thermal conduction energy. Among them, the ratio of the thermal conduction energy of the target area to the total thermal conduction energy = thermal conduction energy of the target area / total thermal conduction energy. Specifically, the smart air conditioner determines the target swing retention time of the smart air conditioner for the target area according to the ratio of the thermal conduction energy to the total thermal conduction energy of the target area, including: obtaining the total swing time of the smart air conditioner in each air supply cycle; the smart air conditioner uses the product of the total swing time and the ratio of the thermal conduction energy to the total thermal conduction energy of the target area as the target swing retention time of the smart air conditioner for the target area. That is, T 目标 =T 总 *k; where T 目标 is the target wind retention time of the smart air conditioner in the target area, T 总 is the total swing time, and k is the ratio of the heat conduction energy of the target area to the total heat conduction energy. In this embodiment, the total swing time of the intelligent air conditioner in one air supply cycle is the total time for the intelligent air conditioner to supply air once in the order of the regional serial numbers. The regional serial numbers are the first region, the second region, the third region, and so on. As an example, the total swing time of the intelligent air conditioner in each air supply cycle is 60 seconds. In this way, the target swing retention time of the intelligent air conditioner for the target area can be accurately determined in combination with a specific algorithm. Further, the intelligent air conditioner can control the intelligent air conditioner to supply air to the target area according to the target swing retention time as the target air supply strategy of the intelligent air conditioner for the target area. In this way, the target swing retention time of the intelligent air conditioner for the target area can be accurately determined in combination with the proportion of the heat conduction energy of the target area to the total heat conduction energy. In an optimized solution, when the intelligent air conditioner is controlled to supply air to the target area according to the target swing retention time, the intelligent air conditioner is controlled to swing the air to other areas at a uniform speed. Here, other areas are indoor areas other than the target area. In this way, air convection can be formed more quickly so that the indoor environment can quickly reach thermal equilibrium.

[0140] Optionally, after controlling the intelligent air conditioner to supply air to the target area according to the target air supply strategy, the method further includes:

[0141] The smart air conditioner obtains the indoor ambient temperature and the outdoor ambient temperature where the smart air conditioner is located; the smart air conditioner determines the secondary control strategy of the smart air conditioner according to the absolute value of the difference between the indoor ambient temperature and the outdoor ambient temperature; the smart air conditioner controls the smart air conditioner to execute the secondary control strategy.

[0142] In this embodiment, after controlling the smart air conditioner to supply air to the target area according to the target air supply strategy, the smart air conditioner can also obtain the indoor ambient temperature and outdoor ambient temperature of the smart air conditioner through the ambient temperature sensor. Furthermore, the smart air conditioner can also determine the secondary control strategy of the smart air conditioner in combination with the absolute value of the difference between the indoor ambient temperature and the outdoor ambient temperature. In this way, the secondary control strategy determined in this way can be more consistent with the indoor and outdoor ambient temperature conditions. In this way, when the smart air conditioner controls the smart air conditioner to execute the secondary control strategy, the indoor environment where the smart air conditioner is located can be accurately regulated, meeting the user's energy-saving control needs for the smart air conditioner.

[0143] Optionally, the intelligent air conditioner determines a secondary control strategy of the intelligent air conditioner according to an absolute value of a difference between the indoor ambient temperature and the outdoor ambient temperature, including:

[0144] When the absolute value of the difference between the indoor ambient temperature and the outdoor ambient temperature is greater than a set threshold, the smart air conditioner determines that the secondary control strategy of the smart air conditioner is to control the smart air conditioner according to the thermal comfort value output by the thermal comfort model; when the absolute value of the difference between the indoor ambient temperature and the outdoor ambient temperature is less than a set threshold, the smart air conditioner determines that the secondary control strategy of the smart air conditioner is to control the smart air conditioner to execute an energy-saving control strategy.

[0145] In this embodiment, when the absolute value of the difference between the indoor ambient temperature and the outdoor ambient temperature is greater than the set threshold, the intelligent air conditioner determines the secondary control strategy to control the intelligent air conditioner according to the thermal comfort value output by the thermal comfort model. As an example, the threshold is set to 3°C. With this scheme, when the indoor and outdoor temperature difference is large, the user's comfort feeling can be given priority, so that the control strategy determined in this way meets the user's control needs for the intelligent air conditioner. Similarly, when the absolute value of the difference between the indoor ambient temperature and the outdoor ambient temperature is less than the set threshold, the intelligent air conditioner determines the secondary control strategy to control the intelligent air conditioner to execute the energy-saving control strategy. Among them, the energy-saving control strategy includes controlling the intelligent air conditioner again to supply air to the target area according to the target air supply strategy. In this way, when the indoor and outdoor temperature difference is small, the energy consumption of the intelligent air conditioner operation process can be given priority, so that the control strategy determined in this way can avoid energy waste while adjusting the indoor environment, and meet the user's energy-saving control needs for the intelligent air conditioner.

[0146] Figure 5is a schematic diagram of a device for detecting temperature distribution in an indoor space provided by an embodiment of the present disclosure; Figure 5 As shown, the embodiment of the present disclosure provides a device for detecting the temperature distribution of an indoor space, including a division module 51, a control module 52, a determination module 53 and a generation module 54. The division module 51 is configured to divide the indoor space where the intelligent air conditioner is located into multiple areas according to a preset division rule; the control module 52 is configured to control the voice module of the intelligent air conditioner to send ranging ultrasonic waves to the obstacle reflection surfaces in the multiple areas respectively, so as to obtain the distance values ​​between the obstacle reflection surfaces and the first microphone in the multiple areas; the determination module 53 is configured to determine the average temperature value of each area respectively according to the distance values ​​between the obstacle reflection surfaces and the first microphone in the multiple areas; the generation module 54 is configured to generate a regional average temperature sequence list according to the average temperature value of each area.

[0147] By using the device for detecting the temperature distribution of an indoor space provided by the embodiment of the present disclosure, after the indoor space where the smart air conditioner is located is divided into multiple areas, the voice module of the smart air conditioner can be used to send ranging ultrasonic waves to the obstacle reflective surfaces in different areas respectively, so as to calculate the average temperature value of each area through the feedback data of each area received by the voice module, and then generate a more accurate regional average temperature sequence table, so that the user can obtain the distribution of the indoor space temperature by reading the regional average temperature sequence table. Compared with the existing indoor temperature detection method, the cost is lower and the accuracy is higher, which meets the user's demand for accurate detection of the indoor space temperature distribution.

[0148] Figure 6 is another schematic diagram of a device for detecting temperature distribution in an indoor space provided by an embodiment of the present disclosure; Figure 6 As shown, an embodiment of the present disclosure provides a device for detecting indoor space temperature distribution, including a processor (processor) 100 and a memory (memory) 101. Optionally, the device may also include a communication interface (Communication Interface) 102 and a bus 103. Among them, the processor 100, the communication interface 102, and the memory 101 can communicate with each other through the bus 103. The communication interface 102 can be used for information transmission. The processor 100 can call the logic instructions in the memory 101 to execute the method for detecting indoor space temperature distribution of the above embodiment.

[0149] In addition, the logic instructions in the memory 101 described above may be implemented in the form of software functional units and when sold or used as independent products, may be stored in a computer-readable storage medium.

[0150] The memory 101 is a computer-readable storage medium that can be used to store software programs and computer executable programs, such as program instructions / modules corresponding to the method in the embodiment of the present disclosure. The processor 100 executes the function application and data processing by running the program instructions / modules stored in the memory 101, that is, the method for detecting the temperature distribution of the indoor space in the above embodiment is implemented.

[0151] The memory 101 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and an application required for at least one function; the data storage area may store data created according to the use of the terminal device, etc. In addition, the memory 101 may include a high-speed random access memory and may also include a non-volatile memory.

[0152] An embodiment of the present disclosure provides a smart air conditioner, comprising the above-mentioned device for detecting temperature distribution in an indoor space.

[0153] An embodiment of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to execute the above method for detecting temperature distribution in an indoor space.

[0154] An embodiment of the present disclosure provides a computer program product, which includes a computer program stored on a computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the above-mentioned method for detecting the temperature distribution of an indoor space.

[0155] The computer-readable storage medium mentioned above may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0156] The technical solution of the embodiment of the present disclosure can be embodied in the form of a software product, which is stored in a storage medium and includes one or more instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiment of the present disclosure. The aforementioned storage medium may be a non-transient storage medium, including: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes, or a transient storage medium.

[0157] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible changes. Unless explicitly required, separate components and functions are optional, and the order of operation may vary. The parts and features of some embodiments may be included in or replace the parts and features of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and the claims, unless the context clearly indicates, the singular forms of "a", "an" and "the" are intended to include plural forms as well. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of listings containing one or more associated ones. In addition, when used in the present application, the term "comprise" and its variants "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof. In the absence of further restrictions, the elements defined by the sentence "comprising a ..." do not exclude the presence of other identical elements in the process, method or device comprising the elements. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the various embodiments may refer to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can refer to the description of the method part.

[0158] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The technicians may use different methods for each specific application to implement the described functions, but such implementations should not be considered to exceed the scope of the embodiments of the present disclosure. The technicians may clearly understand that, for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above may refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0159] In the embodiments disclosed herein, the disclosed methods and products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units can be only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to implement this embodiment. In addition, each functional unit in the embodiment of the present disclosure may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit.

[0160] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A method for detecting temperature distribution in an indoor space, characterized in that: Applied to a smart air conditioner equipped with a voice module, the voice module is provided with a first microphone, and the method includes: Dividing the indoor space where the smart air conditioner is located into multiple areas according to a preset division rule; Controlling the voice module of the smart air conditioner to send ranging ultrasonic waves to obstacle reflection surfaces in multiple areas respectively, so as to obtain distance values ​​between the obstacle reflection surfaces in multiple areas and the first microphone; Determine the average temperature value of each area according to the distance between the obstacle reflection surface and the first microphone in the multiple areas; According to the average temperature value of each region, a regional average temperature sequence table is generated.

2. The method according to claim 1, characterized in that: The multiple areas include a first area, the voice module further includes a second microphone disposed adjacent to the first microphone, and determining an average temperature value of the first area according to a distance value between an obstacle reflection surface in the first area and the first microphone, including: Calculate the wavelength interval width of the first area according to the distance value between the obstacle reflection surface in the first area and the first microphone and the distance value between the obstacle reflection surface in the first area and the second microphone; Dividing the first area according to the wavelength interval width and the first preset step length of the first area to obtain multiple groups of detection signal units; Controlling the voice module to send detection ultrasonic waves to the multiple groups of detection signal units respectively, so that the voice module receives data fed back by different groups of detection signal units; An average temperature value of the first area is determined according to the data fed back by the different groups of detection signal units.

3. The method according to claim 2, characterized in that The step of calculating the wavelength interval width of the first region according to the distance value between the obstacle reflection surface in the first region and the first microphone and the distance value between the obstacle reflection surface in the first region and the second microphone comprises: Obtain the error value of ultrasonic ranging; Calculating the path difference according to the distance between the obstacle reflection surface in the first area and the first microphone, the distance between the obstacle reflection surface in the first area and the second microphone, and the error value of the ultrasonic ranging; The quotient of the path difference and the path coefficient corresponding to the first region is used as the wavelength interval width of the first region.

4. The method according to claim 2, characterized in that: The plurality of detection signal units include a first detection signal unit, and controlling the voice module to send a detection ultrasonic wave to the first detection signal unit includes: Control the voice module to send detection ultrasonic waves to the first detection signal unit multiple times at preset time intervals; The frequency of the detection ultrasonic wave sent by the voice module each time is determined by the frequency of the detection ultrasonic wave sent last time and the frequency correction strategy, and the frequency of the detection ultrasonic wave sent by the voice module to the first detection signal unit for the first time is the initial frequency.

5. The method according to claim 4, characterized in that The frequency correction strategy is determined by: Determine the current operation mode of the smart air conditioner; When the current operation mode of the intelligent air conditioner is the cooling mode, determining that the frequency correction strategy is to increase gradually according to a second preset step size; When the current operation mode of the intelligent air conditioner is the heating mode, the frequency correction strategy is determined to be gradually decreased according to the second preset step size.

6. The method according to claim 2, characterized in that Determining the average temperature value of the first area according to the data fed back by the different groups of detection signal units includes: Processing the data fed back by each group of detection signal units respectively to determine the target wavelength and target frequency of the first area; Taking the product of the target wavelength and the target frequency as the average sound velocity in the first area; An average temperature value of the first region is calculated according to the average sound velocity of the first region.

7. The method according to claim 6, characterized in that Calculating the average temperature value of the first area according to the average sound velocity of the first area includes: T 平均 =(V 平均 -331.45) / 0.61 Among them, T 平均 is the average temperature of the first region, V 平均 is the average sound speed in the first region.

8. A device for detecting temperature distribution in an indoor space, characterized in that: Applied to an intelligent air conditioner equipped with a voice module, the voice module is provided with a first microphone, and the device comprises: A division module is configured to divide the indoor space where the smart air conditioner is located into multiple areas according to a preset division rule; A control module configured to control the voice module of the smart air conditioner to send ranging ultrasonic waves to the obstacle reflection surfaces in the multiple areas respectively, so as to obtain the distance values ​​between the obstacle reflection surfaces in the multiple areas and the first microphone; A determination module is configured to determine the average temperature value of each area according to the distance values ​​between the obstacle reflection surface and the first microphone in the multiple areas; The generating module is configured to generate a regional average temperature sequence list according to the respective average temperature values ​​of each region.

9. A device for detecting temperature distribution in an indoor space, comprising a processor and a memory storing program instructions, characterized in that: The processor is configured to execute the method for detecting temperature distribution in an indoor space according to any one of claims 1 to 7 when running the program instructions.

10. A storage medium storing program instructions, characterized in that: When the program instructions are executed, the method for detecting the temperature distribution of an indoor space according to any one of claims 1 to 7 is executed.

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