Air conditioner control method, system, medium, equipment and product based on information fusion

Abstract

The application discloses an air conditioner control method and system based on information fusion, a medium, equipment and products, and belongs to the technical field of air conditioner control. The method comprises the following steps: acquiring personnel distribution information of each heat area in a room, temperature of each heat area, environment quality of each heat area, a thermal comfort index and air conditioning supply pipeline pressure; determining total air supply of the air conditioner according to the personnel distribution information, the temperature of each heat area, the environment quality and the thermal comfort index; determining air supply of each heat area according to the total air supply of the air conditioner, the personnel distribution information of each heat area, the temperature of each heat area, the environment quality of each heat area, the air conditioning supply pipeline pressure and the thermal comfort index; and controlling the air conditioner according to the air supply of each heat area of the air conditioner. The control of the air conditioner is more accurate. The technical problem that the air supply of each partition of the current air conditioner cannot be controlled individually according to personnel distribution, temperature and air quality and the like, so that the control of the air conditioner cannot be optimal is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of air conditioning system intelligence, and particularly relates to an air conditioning control method and system based on information fusion, a medium, equipment and products. BACKGROUND

[0002] The statements in this section merely provide background information related to the present application and do not necessarily constitute the prior art.

[0003] Air conditioning system energy consumption accounts for a large part of building energy consumption, in order to reduce air conditioning energy consumption, the temperature of the building is adjusted by using a heating ventilation air conditioning, the heating ventilation air conditioning (HVAC) system not only improves the energy efficiency of the building, but also pays special attention to the comfort of the occupants, the HVAC provides treated cold air or hot air to the indoor through the air supply system to ensure the indoor air quality and the comfort of the occupants.

[0004] When the current heating ventilation air conditioning adjusts the air supply amount, only the total air supply amount of the heating ventilation air conditioning is determined by the environmental temperature and air quality in the region, and then the total air supply amount is distributed to each subzone according to the set rules, and the air supply amount of each subzone cannot be individually and real-timely controlled according to the personnel distribution, temperature and air quality in each zone, resulting in that the control of the air conditioner cannot be optimized. SUMMARY

[0005] In order to solve the above problems, the present application provides an air conditioning control method and system based on information fusion, a medium, equipment and products, which realizes accurate control of the air conditioner.

[0006] To achieve the above object, the present application adopts the following technical scheme:

[0007] In a first aspect, an air conditioning control method based on information fusion is provided, comprising:

[0008] obtaining personnel distribution information of each hot zone in the room, temperature of each hot zone, environmental quality of each hot zone, thermal comfort index and heating ventilation air conditioning air supply pipeline pressure;

[0009] determining the total air supply amount of the heating ventilation air conditioning according to the personnel distribution information of each hot zone, the temperature of each hot zone, the environmental quality of each hot zone and the thermal comfort index;

[0010] determining the air supply amount of each hot zone according to the total air supply amount of the heating ventilation air conditioning, the personnel distribution information of each hot zone, the temperature of each hot zone, the environmental quality of each hot zone, the heating ventilation air conditioning air supply pipeline pressure, the thermal comfort index and the hot zone cold and heat regulation characteristic model; wherein the hot zone cold and heat regulation characteristic model is a correlation relationship model between the total air supply amount of the heating ventilation air conditioning, the personnel distribution information of each hot zone, the temperature of each hot zone, the environmental quality of each hot zone and the heating ventilation air conditioning air supply pipeline pressure, and the thermal comfort index and the air supply amount of each hot zone;

[0011] According to the air supply amount of each thermal zone of the heating ventilation air conditioner, the air conditioner is controlled.

[0012] Further, the indoor personnel image is acquired;

[0013] The personnel in the indoor personnel image are identified to obtain personnel distribution information of each thermal zone in the indoor.

[0014] Further, the personnel in the indoor personnel image are identified by a trained target recognition model, and the target recognition model is obtained by using YOLO.

[0015] Further, the thermal zone cold and heat regulation characteristic model takes the total air supply amount of the heating ventilation air conditioner, the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, and the heating ventilation air conditioner air supply pipeline pressure as inputs, and takes the thermal comfort index and the air supply amount of each thermal zone as outputs, and is obtained by using a Gaussian process regression model.

[0016] Further, according to the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, the thermal comfort index, and the trained air supply amount prediction model, the total air supply amount of the heating ventilation air conditioner is determined, wherein the air supply amount prediction model includes a plurality of air supply amount prediction branches, and one air supply amount prediction branch corresponds to one comfort index, and each air supply amount prediction branch is obtained by using an adaptive neural fuzzy reasoning.

[0017] Further, the process of determining the total air supply amount of the heating ventilation air conditioner by the air supply amount prediction model includes:

[0018] Selecting an air supply amount prediction branch corresponding to the thermal comfort index;

[0019] Using the selected air supply amount prediction branch to fuzz the personnel distribution information of each thermal zone, the temperature of each thermal zone, and the environmental quality of each thermal zone, and determining the membership degrees of the personnel distribution information of each thermal zone, the temperature of each thermal zone, and the environmental quality of each thermal zone;

[0020] According to the membership degrees of the personnel distribution information of each thermal zone, the temperature of each thermal zone, and the environmental quality of each thermal zone, the output and the applicability of each fuzzy rule are determined;

[0021] The applicability of each rule is normalized to obtain the normalized applicability;

[0022] According to the normalized applicability, the outputs of the fuzzy rules are weighted and fused to obtain the total air supply amount of the heating ventilation air conditioner.

[0023] In a second aspect, an air conditioner control system based on information fusion is provided, which includes:

[0024] The acquisition module is configured to acquire the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, the thermal comfort index, and the pressure of the air supply pipeline of the HVAC;

[0025] The total air supply amount prediction unit is configured to determine the total air supply amount of the HVAC according to the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, and the thermal comfort index;

[0026] The thermal zone air supply amount prediction unit is configured to determine the air supply amount of each thermal zone according to the total air supply amount of the HVAC, the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, the pressure of the air supply pipeline of the HVAC, the thermal comfort index, and the thermal energy regulation and control characteristic model of each thermal zone, wherein the thermal energy regulation and control characteristic model is a correlation model between the total air supply amount of the HVAC, the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, and the pressure of the air supply pipeline of the HVAC and the thermal comfort index and the air supply amount of each thermal zone;

[0027] The air conditioner control unit is configured to control the air conditioner according to the air supply amount of each thermal zone of the HVAC.

[0028] In a third aspect, a computer device is provided, and the device comprises:

[0029] The processor is adapted to execute the computer program.

[0030] The computer readable storage medium has the computer program stored therein, and the computer program, when executed by the processor, implements the information fusion-based air conditioner control method of the first aspect.

[0031] In a fourth aspect, a computer readable storage medium is provided, and the computer readable storage medium has a computer program stored therein, the computer program being adapted to be loaded and executed by a processor to implement the information fusion-based air conditioner control method of the first aspect.

[0032] In a fifth aspect, a computer program product is provided, and the computer program product comprises a computer program, and the computer program, when executed by a processor, implements the information fusion-based air conditioner control method of the first aspect.

[0033] Compared with the prior art, the present application has the following beneficial effects:

[0034] The application provides an air conditioner control method and system based on information fusion, a medium, equipment and products.

[0035] Advantages of the additional aspects of the application will become apparent in the description that follows, some of which will be apparent to those skilled in the art from the description, or will be learned by practicing the application. BRIEF DESCRIPTION OF DRAWINGS

[0036] The accompanying drawings, which form a part of the specification, are included to provide a further understanding of the application and are incorporated herein in conjunction with the description of the application. The drawings are not to be considered restrictive in scope and are included for illustrative purposes only.

[0037] Figure 1 A flowchart of the air conditioner control method based on information fusion disclosed for the embodiment;

[0038] Figure 2 A flowchart of the indoor personnel position distribution identification disclosed for the embodiment;

[0039] Figure 3 A personnel position distribution fuzzy membership function disclosed for the embodiment;

[0040] Figure 4 A CO2 concentration fuzzy membership function disclosed for the embodiment;

[0041] Figure 5 A hot zone temperature fuzzy membership function disclosed for the embodiment;

[0042] Figure 6 A flowchart of the air conditioner control method based on information fusion disclosed for the embodiment;

[0043] Figure 7 A flowchart of the air conditioner control method based on information fusion disclosed for the embodiment;

[0044] Figure 8 A schematic diagram of the air conditioner control system based on information fusion disclosed for the embodiment. DETAILED DESCRIPTION

[0045] The application will be further described below in conjunction with the drawings and embodiments.

[0046] It should be noted that the following detailed description is intended to provide further description of the present application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application pertains.

[0047] It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, steps, operations, elements, components, and / or groups thereof, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and / or groups thereof.

[0048] The embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0049] Embodiment 1

[0050] Air conditioning system energy consumption accounts for a large part of building energy consumption, in order to reduce air conditioning energy consumption, using heating ventilation air conditioning to adjust the temperature of the building, heating ventilation air conditioning (HVAC) system in improving the energy efficiency of the building also need to pay special attention to the comfort of the occupants, HVAC through the air supply system to the indoor air supply processed cold or hot air to ensure indoor air quality and the comfort of the occupants. At present, the air supply mode of heating ventilation air conditioning has constant air volume (CAV), variable air volume (VAV), demand control ventilation (DCV) three kinds.

[0051] Constant air volume (CAV) is to adjust the indoor temperature by supplying air to the indoor with constant air volume, but this air supply mode cannot guarantee the constant temperature of the indoor, and is suitable for occasions with small fluctuation of the number of people and ventilation demand and constant ventilation load, such as all-weather running warehouse, call center, data center and processing plant, etc.; also suitable for occasional use, air volume load predictable occasions, such as concert hall, conference venue or other activity place.

[0052] Variable air volume (VAV) is to adjust the air supply according to the heat load of the indoor, and to keep the indoor temperature in a constant state by constantly changing the air supply.

[0053] Demand control ventilation (DCV) is to automatically adjust the air supply according to the number of people or indoor pollution degree and other indicators to maintain indoor air quality, which can accurately control the air quality of each area in the indoor.

[0054] However, the above-mentioned air supply method only determines the total air supply volume of HVAC based on the ambient temperature and air quality in the area when adjusting the air supply volume. Then, the total air supply volume is distributed to each zone according to the set rules. The air supply volume of each zone cannot be individually controlled in real time based on the distribution of people, temperature and air quality in each zone, which means that the control of the air conditioning cannot achieve the optimal result.

[0055] To address the aforementioned technical problems, this embodiment discloses the following: Figure 1 The air conditioning control method based on information fusion shown includes:

[0056] S1: Obtain information on the distribution of people in each indoor hot zone, the temperature of each hot zone, the environmental quality of each hot zone, the thermal comfort index, and the pressure of the HVAC air supply duct.

[0057] In this embodiment, environmental quality can be characterized by the concentration of CO2 in the environment; thermal comfort index can be characterized by the PMV value.

[0058] By acquiring images of people indoors;

[0059] The system identifies individuals in indoor images to obtain information on the distribution of people in different indoor hot zones.

[0060] like Figure 8 As shown, the temperature of each hot zone is obtained through a temperature sensor; the CO2 concentration of each hot zone is obtained through a CO2 concentration sensor; the pressure of the HVAC air supply duct is obtained through a pressure sensor; and images of people indoors are obtained through a camera.

[0061] The trained target recognition model is used to identify people in indoor images. The target recognition model is constructed using YOLO.

[0062] Considering the diverse postures and common occlusions of people indoors, images of people indoors under different degrees of occlusion, postures, and illumination were collected in advance. Then, the people in the indoor images were manually labeled using a labeling tool. The labeled images were used as training images to form an indoor people image dataset, which was used to train the target recognition model.

[0063] like Figure 2 As shown, this embodiment employs a deep transfer learning strategy to train the constructed target recognition model. The training process includes:

[0064] First, the constructed target recognition model is pre-trained using public datasets for target detection to obtain the source model. Public datasets for target detection include the MS COCO dataset.

[0065] Then, a target recognition model is obtained by training the source model using a deep transfer learning strategy and an indoor personnel image special dataset, and the trained target recognition model can realize accurate detection of personnel distribution in an indoor environment.

[0066] The public dataset for target detection includes 66808 personnel images, and the indoor personnel image special dataset includes 2800 indoor personnel images with different degrees of occlusion, different postures, and different illuminations, and the resolution of the indoor personnel images is 608x608.

[0067] S2: determining the total air supply of the heating ventilation air conditioner according to the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, and the thermal comfort index. Specifically:

[0068] According to the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, the thermal comfort index, and the trained air supply prediction model, the total air supply of the heating ventilation air conditioner is determined, wherein the air supply prediction model includes multiple air supply prediction branches, one air supply prediction branch corresponds to one comfort index, and each air supply prediction branch is obtained by using adaptive neural fuzzy reasoning construction.

[0069] The process of determining the total air supply of the heating ventilation air conditioner by the air supply prediction model includes:

[0070] Selecting an air supply prediction branch corresponding to the thermal comfort index;

[0071] Fuzzy processing the personnel distribution information of each thermal zone, the temperature of each thermal zone, and the environmental quality of each thermal zone by using the selected air supply prediction branch to determine the membership degrees of the personnel distribution information of each thermal zone, the temperature of each thermal zone, and the environmental quality of each thermal zone;

[0072] Determining the output and applicability of each fuzzy rule according to the membership degrees of the personnel distribution information of each thermal zone, the temperature of each thermal zone, and the environmental quality of each thermal zone;

[0073] Normalizing the applicability of each rule to obtain the normalized applicability;

[0074] According to the normalized applicability, the outputs of the fuzzy rules are weighted and fused to obtain the total air supply of the heating ventilation air conditioner.

[0075] The fuzzy rules in the air supply prediction branch include the fuzzy rules between the personnel distribution information of each thermal zone and the total air supply of the heating ventilation air conditioner, the fuzzy rules between the temperature of each thermal zone and the total air supply of the heating ventilation air conditioner, and the fuzzy rules between the environmental quality of each thermal zone and the total air supply of the heating ventilation air conditioner. Each fuzzy rule is used to describe the non-linear relationship between the corresponding two parameters, and the fuzzy rules are determined by the personnel distribution information of each thermal zone, the temperature of each thermal zone, and the environmental quality of each thermal zone

[0076] These rules are expressed in the form of "If-Then", and through fuzzy sets and membership functions, precise input data is transformed into fuzzy logic judgments, thereby enabling the modeling of complex systems.

[0077] like Figure 6 As shown, the air supply volume prediction branch performs fuzzy processing on the personnel distribution information, temperature, and environmental quality of each hot zone at the input layer to determine the membership degree of personnel distribution to the total HVAC air supply volume, the membership degree of each hot zone temperature to the total HVAC air supply volume, and the membership degree of each hot zone environmental quality to the total HVAC air supply volume. Figure 3 - Figure 5 As shown; then, the rule operation layer matches the antecedent of the fuzzy rule and calculates the applicability of each rule; the normalization layer normalizes the applicability of each rule to obtain the normalized applicability; the output layer calculates the consequent of each rule based on the normalized applicability and outputs the total air volume of the HVAC system.

[0078] like Figure 3 , Figure 4 and Figure 5 As shown, in this embodiment, the linguistic description of personnel distribution membership is {rare, few, moderately few, moderately many, many, very many, extremely many}, while the linguistic descriptions of temperature membership and environmental quality membership are {very low, low, moderately low, moderately high, high, very high, extremely high}. The minimum membership optimization model is used to obtain the corresponding fuzzy membership functions. Then, based on the personnel distribution information and the fuzzy membership function of personnel distribution in each hot zone, the membership degree corresponding to personnel distribution is determined; based on the temperature of each hot zone and its fuzzy membership function, the membership degree corresponding to temperature is determined; and based on the environmental quality of each hot zone and its fuzzy membership function, the membership degree corresponding to environmental quality is determined.

[0079] The minimum membership optimization model refers to a mathematical optimization framework that transforms linguistic descriptions of population distribution, temperature, and environmental quality (such as the seven levels of population distribution, such as "very few" and "very many", and temperature, such as "very low" and "very high") into quantitative fuzzy membership functions. Its core is to use "minimum membership" as the optimization objective or constraint. By determining the parameters of the membership function (such as the inflection point and slope of triangular and trapezoidal functions), the function can accurately reflect the fuzziness of the linguistic description and balance the influence of different indicators in multi-dimensional evaluation with the minimum membership (such as the minimum value among the memberships of each dimension). Finally, based on measured data, the membership of each hot zone in the corresponding dimension is calculated, providing a scientific fuzzy quantitative basis for hot zone status analysis.

[0080] The embodiment obtains different thermal zone personnel distribution information, the temperature and air quality of each thermal zone, and the minimum actual total air supply volume of the heating ventilation air conditioner reaching the thermal comfort index as training data in advance; the training data is used to train the air supply volume prediction model, and the trained air volume prediction model is obtained after the training is completed.

[0081] S3: determining the air supply volume of each thermal zone according to the total air supply volume of the heating ventilation air conditioner, the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, the heating ventilation air conditioner air supply pipeline pressure, the thermal comfort index, and the thermal comfort index and the air supply volume of each thermal zone.

[0082] Specifically, the thermal comfort index and the air supply volume of each thermal zone are obtained by using the Gaussian process regression model based on the total air supply volume of the heating ventilation air conditioner, the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, and the heating ventilation air conditioner air supply pipeline pressure.

[0083] The embodiment uses a data-driven method to design a thermal comfort index and air supply volume of each thermal zone based on a Gaussian process regression model, and deeply mines the relationship between the total air supply volume of the heating ventilation air conditioner, the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, the heating ventilation air conditioner air supply pipeline pressure, and the thermal comfort index and the air supply volume of each thermal zone.

[0084] In the thermal comfort index and air supply volume of each thermal zone, the total air supply volume of the heating ventilation air conditioner, the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, and the heating ventilation air conditioner air supply pipeline pressure are input, and the thermal comfort index and the air supply volume of each thermal zone are output, and the time sequence dynamic correlation between the input and output parameters is captured through a kernel function; wherein the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, the total air supply volume of the heating ventilation air conditioner, and the heating ventilation air conditioner air supply pipeline pressure are real-time acquisition data, which are used for immediate control; and the air supply volume of each thermal zone is obtained by prediction, which assists in advance control; the algorithm trains the model through data driving, and realizes dynamic adaptation to the system characteristics by using a rolling update mechanism, so as to improve the system energy efficiency and thermal comfort.

[0085] The thermal comfort index and air supply volume of each thermal zone are:

[0086] .

[0087] wherein, xy is the input data, which includes the total air volume of HVAC, personnel distribution information in each hot zone, temperature in each hot zone, environmental quality in each hot zone, and HVAC air supply duct pressure; y is the output data, which includes thermal comfort index and air volume in each hot zone. m ( x ) is the mean function, It is the Kronecker function. It is the covariance matrix. It is the variance matrix. As can be seen from the formula, Gaussian process regression not only produces an estimate of the model, but also the variance of that estimate. This method takes into account the uncertainty of model predictions, and therefore has greater practical application value.

[0088] The hot zone heating and cooling regulation characteristic model and the air supply volume prediction model constitute the hot zone temperature collaborative adaptive air conditioning control model in this embodiment.

[0089] S4: Control the air conditioning according to the air supply volume of each hot zone of the HVAC system.

[0090] The air conditioning control method based on information fusion disclosed in this embodiment first comprehensively considers the personnel distribution information, temperature, environmental quality, and thermal comfort index of each hot zone to determine the total air supply volume of the HVAC system. Then, based on the total air supply volume, personnel distribution information, temperature, environmental quality, air supply duct pressure, thermal comfort index, and the heating and cooling characteristic model of each hot zone, the air supply volume of each hot zone is determined. This achieves comprehensive control of the air supply volume of each hot zone based on various indicators such as temperature, environmental quality, distribution information, and air supply duct pressure. Through model predictive control (MPC), the output commands such as the air supply volume of each hot zone are collaboratively optimized in the rolling time domain to achieve temperature tracking, air volume balance, and energy saving. In specific control, the algorithm achieves air volume balance through on-demand allocation and pressure closed-loop control, and adjusts the temperature using a combination of feedforward and feedback and a multi-zone collaborative strategy to ensure environmental comfort in the hot zones and efficient system operation.

[0091] Example 2

[0092] In this embodiment, an air conditioning control system based on information fusion is disclosed, such as... Figure 8 As shown, it includes:

[0093] The acquisition module is used to acquire information on the distribution of people in each indoor hot zone, the temperature of each hot zone, the environmental quality of each hot zone, thermal comfort indexes, and the pressure of the HVAC air supply duct.

[0094] The total air supply volume prediction unit is used to determine the total air supply volume of the HVAC system based on the personnel distribution information of each hot zone, the temperature of each hot zone, the environmental quality and thermal comfort index of each hot zone.

[0095] Each hot area air supply amount prediction unit is configured to determine the air supply amount of each hot area according to the total air supply amount of the HVAC, the personnel distribution information of each hot area, the temperature of each hot area, the environmental quality of each hot area, the HVAC air supply pipeline pressure, the thermal comfort index, and a hot area cold and heat regulation characteristic model.

[0096] The air conditioner control unit is configured to control the air conditioner according to the air supply amount of each hot area of the HVAC.

[0097] The acquisition module includes a camera, a temperature sensor, a pressure sensor, and a CO2 sensor.

[0098] The air supply amount prediction module, the air speed prediction module, and the air conditioner control module constitute a cold / heat self-adaptive regulation device.

[0099] The application further discloses a computer device, which comprises:

[0100] The processor is adapted to execute the computer program.

[0101] The computer readable storage medium has a computer program stored therein, and the computer program is executed by the processor to realize the information fusion-based air conditioner control method disclosed in Embodiment 1.

[0102] The application further discloses a computer readable storage medium, which has a computer program stored therein, and the computer program is adapted to be loaded and executed by the processor to realize the information fusion-based air conditioner control method disclosed in Embodiment 1.

[0103] The application further discloses a computer program product, which comprises a computer program, and the computer program is executed by the processor to realize the information fusion-based air conditioner control method disclosed in Embodiment 1.

[0104] The method disclosed in Embodiment 1 can be directly embodied by a hardware processor or a combination of hardware and software modules in the processor. The software module can be located in a mature storage medium in the field, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, an electrically erasable programmable memory, a register, or the like. The storage medium is located in a memory, and the processor reads information in the memory and combines the hardware to complete the steps of the above method. To avoid repetition, no further description is given here.

[0105] Those skilled in the art can understand that the units and algorithm steps of each example described in combination with the present embodiment can be realized in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software manner depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0106] Although the specific embodiments of the present application are described above in combination with the drawings, it is not a limitation on the scope of protection of the present application. Those skilled in the art should understand that various modifications or variations made by those skilled in the art on the basis of the technical solutions of the present application without creative labor are still within the scope of protection of the present application.

Claims

1. An air conditioner control method based on information fusion, characterized by, The method comprises the following steps: obtaining indoor personnel distribution information of each thermal zone, temperature of each thermal zone, environment quality of each thermal zone, thermal comfort index and air supply pipeline pressure of the heating ventilation air conditioning; determining total air supply of the heating ventilation air conditioning according to the indoor personnel distribution information of each thermal zone, the temperature of each thermal zone, the environment quality of each thermal zone and the thermal comfort index; wherein, the air supply prediction model comprises a plurality of air supply prediction branches, one air supply prediction branch corresponds to one comfort index, and each air supply prediction branch is obtained by using self-adaptive neural fuzzy reasoning construction; the process of determining the total air supply of the heating ventilation air conditioning by the air supply prediction model comprises: selecting an air supply prediction branch corresponding to the thermal comfort index; fuzzy processing the indoor personnel distribution information of each thermal zone, the temperature of each thermal zone and the environment quality of each thermal zone by using the selected air supply prediction branch to determine the membership degrees of the indoor personnel distribution information of each thermal zone, the temperature of each thermal zone and the environment quality of each thermal zone; determining the output and applicability of each fuzzy rule according to the membership degrees of the indoor personnel distribution information of each thermal zone, the temperature of each thermal zone and the environment quality of each thermal zone; normalizing the applicability of each rule to obtain normalized applicability; and weighting and fusing the outputs of all fuzzy rules according to the normalized applicability to obtain the total air supply of the heating ventilation air conditioning; determining the air supply of each thermal zone according to the total air supply of the heating ventilation air conditioning, the indoor personnel distribution information of each thermal zone, the temperature of each thermal zone, the environment quality of each thermal zone, the air supply pipeline pressure of the heating ventilation air conditioning, the thermal comfort index and the thermal zone cold and heat regulation characteristic model; wherein, the thermal zone cold and heat regulation characteristic model is a correlation model between the total air supply of the heating ventilation air conditioning, the indoor personnel distribution information of each thermal zone, the temperature of each thermal zone, the environment quality of each thermal zone and the air supply pipeline pressure of the heating ventilation air conditioning and the thermal comfort index and the air supply of each thermal zone; controlling the air conditioner according to the air supply of each thermal zone of the heating ventilation air conditioner.

2. The information fusion-based air conditioning control method according to claim 1, wherein, obtaining indoor personnel images; recognizing the personnel in the indoor personnel images to obtain indoor personnel distribution information of each thermal zone.

3. The information fusion-based air conditioning control method according to claim 2, wherein The personnel in the indoor personnel images are recognized by using a trained target recognition model, and the target recognition model is obtained by using YOLO.

4. The information fusion-based air conditioning control method according to claim 1, wherein The thermal zone cold and heat regulation characteristic model takes the total air supply of the heating ventilation air conditioner, the indoor personnel distribution information of each thermal zone, the temperature of each thermal zone, the environment quality of each thermal zone and the air supply pipeline pressure of the heating ventilation air conditioner as input, takes the thermal comfort index and the air supply of each thermal zone as output, and is obtained by using a Gaussian process regression model.

5. An information fusion-based air conditioning control system, characterized by, The method comprises the following steps: an acquisition module is configured to obtain indoor personnel distribution information of each thermal zone, temperature of each thermal zone, environment quality of each thermal zone, thermal comfort index and air supply pipeline pressure of the heating ventilation air conditioning; The total air supply amount prediction unit is configured to determine the total air supply amount of the HVAC according to the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, and the thermal comfort index. The air supply amount prediction model includes a plurality of air supply amount prediction branches, one air supply amount prediction branch corresponding to one comfort index, and each air supply amount prediction branch being obtained by using adaptive neuro-fuzzy reasoning. The process of determining the total air supply amount of the HVAC by the air supply amount prediction model includes: selecting an air supply amount prediction branch corresponding to the thermal comfort index; performing fuzzy processing on the personnel distribution information of each thermal zone, the temperature of each thermal zone, and the environmental quality of each thermal zone by using the selected air supply amount prediction branch to determine the membership degrees of the personnel distribution information of each thermal zone, the temperature of each thermal zone, and the environmental quality of each thermal zone; determining the output and the applicability of each fuzzy rule according to the membership degrees of the personnel distribution information of each thermal zone, the temperature of each thermal zone, and the environmental quality of each thermal zone; performing normalization processing on the applicability of each rule to obtain the normalized applicability; and performing weighted fusion on the outputs of the fuzzy rules according to the normalized applicability to obtain the total air supply amount of the HVAC. The air supply amount prediction unit of each thermal zone is configured to determine the air supply amount of each thermal zone according to the total air supply amount of the HVAC, the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, the air supply pipeline pressure of the HVAC, the thermal comfort index, and the thermal energy regulation and control characteristic model of each thermal zone. The thermal energy regulation and control characteristic model is a correlation model between the total air supply amount of the HVAC, the personnel distribution information of each thermal zone, the temperature of each thermal zone, the environmental quality of each thermal zone, and the air supply pipeline pressure of the HVAC and the thermal comfort index and the air supply amount of each thermal zone. The air conditioner control unit is configured to control the air conditioner according to the air supply amount of each thermal zone of the HVAC.

6. An electronic device, comprising: The device comprises: a processor adapted to execute a computer program; a computer readable storage medium having a computer program stored therein, the computer program being executed by the processor to implement the information fusion-based air conditioner control method of any one of claims 1-4.

7. A computer readable storage medium characterized in that, The computer readable storage medium stores a computer program, and the computer program is adapted to be loaded and executed by the processor to implement the information fusion-based air conditioner control method of any one of claims 1-4.

8. A computer program product, characterised in that, The computer program product comprises a computer program, and the computer program is executed by the processor to implement the information fusion-based air conditioner control method of any one of claims 1-4.

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