Smoke suction and exhaust method, device, equipment and medium

Abstract

An embodiment of the present invention provides a smoke suction and exhaust method, device, equipment and medium, the method comprising: obtaining multimodal data of a preset space; determining smoke distribution prediction information of the preset space after a preset time based on the multimodal data; determining the suction capacity of at least one suction port of the preset space; determining at least one target suction port and controlling the suction equipment of the target suction port to perform suction based on the smoke distribution prediction information and the suction capacity of at least one suction port, thereby reducing the lag of the smoke suction and exhaust response and enabling the suction and exhaust control logic to cope with unevenly distributed smoke, avoiding excessive energy consumption but low exhaust efficiency, and thus improving the user experience.

Description

Technical Field

[0001] The present invention relates to the field of automation control technology, and in particular to a smoke suction and exhaust method, device, equipment and medium. Background Art

[0002] Traditional smoke extraction systems generally use a passive smoke extraction mode triggered by a fixed threshold, with the control triggering logic based solely on real-time smoke concentration data. This delayed response mechanism presents significant limitations when dealing with complex spatial environments: On the one hand, by the time the detection equipment detects excessive smoke levels, harmful gases have often already diffused and accumulated in a local area, significantly prolonging the smoke removal cycle by extracting and evacuating them. On the other hand, smoke may already be unevenly distributed when extracting and evacuating in areas with complex spatial structures. Existing technologies, when dealing with such uneven smoke distribution, suffer from insufficient smoke suction and excessive energy consumption due to excessive extraction and evacuation. Summary of the Invention

[0003] In view of the above problems, embodiments of the present invention are proposed to provide a smoke suction and exhaust method, device, equipment and medium that overcome the above-mentioned problems of insufficient smoke suction and excessive energy consumption due to excessive suction and exhaust when dealing with uneven distribution of smoke, or at least partially solve the above-mentioned problems.

[0004] In order to solve the above problems, an embodiment of the present invention discloses a smoke suction and exhaust method, which includes:

[0005] Obtain multimodal data of a preset space;

[0006] Determining smoke distribution prediction information of the preset space after a preset time based on the multimodal data;

[0007] determining the air suction capacity of at least one air suction port of the preset space;

[0008] At least one target air suction port is determined based on the smoke distribution prediction information and the air suction capacity of the at least one air suction port, and the air suction equipment of the target air suction port is controlled to perform air suction.

[0009] Optionally, the multimodal data includes at least one of smoke concentration data, airflow data, and image data, and determining, based on the multimodal data, the smoke distribution prediction information of the preset space after a preset time includes:

[0010] At least one of the smoke concentration data, the airflow data and the image data is input into a preset prediction model, so that the preset prediction model outputs smoke distribution prediction information of the preset space after a preset time.

[0011] Optionally, the suction capacity includes at least one of suction range and suction efficiency; the smoke distribution prediction information includes at least one of smoke concentration prediction information, smoke diffusion trend prediction information, and airflow prediction information.

[0012] Optionally, the suction capacity includes a suction range and a suction efficiency, and determining at least one target suction port and controlling a suction device of the target suction port to perform suction based on the smoke distribution prediction information and the suction capacity of the at least one suction port includes:

[0013] determining at least one target air suction port based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, the airflow prediction information, and the air suction range of the at least one air suction port;

[0014] determining a target control parameter of a suction device for the target air suction port based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information and the suction efficiency of the at least one target air suction port;

[0015] According to the target control parameters, the suction equipment corresponding to the target suction port is controlled to perform suction.

[0016] Optionally, determining at least one target air intake port according to at least one of smoke concentration prediction information, smoke diffusion trend prediction information, and airflow prediction information and the air intake range of the at least one air intake port includes:

[0017] Dividing the preset space into at least one candidate area;

[0018] determining a target area in the at least one candidate area according to at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information;

[0019] Determining the degree of overlap between the suction range of each suction port and the at least one target area;

[0020] A target air suction port is determined according to the degree of overlap of the air suction ports.

[0021] Optionally, determining a target control parameter of a suction device for the target air suction outlet based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information and the suction efficiency of the at least one target air suction outlet includes:

[0022] determining a working weight of the at least one target air intake port based on the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information; the working weight being used to indicate the importance of the at least one target air intake port in the current smoke intake and exhaust process;

[0023] At least one target control parameter is determined according to the suction efficiency of the at least one target air suction port and the working weight of the at least one target air suction port.

[0024] Optionally, determining a target control parameter of a suction device for the target air suction outlet based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information and the suction efficiency of the at least one target air suction outlet includes:

[0025] determining energy consumption data of the at least one target air intake;

[0026] At least one target control parameter is determined based on the energy consumption data of the at least one target air suction port, the smoke concentration prediction information, the smoke diffusion trend prediction information, the suction efficiency of the at least one target air suction port and a preset multi-objective optimization model.

[0027] Optionally, determining a target control parameter of a suction device for the target air suction outlet based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information and the suction efficiency of the at least one target air suction outlet includes:

[0028] Obtaining user preference information corresponding to the preset space;

[0029] At least one target control parameter is determined based on the user preference information corresponding to the preset space, the smoke concentration prediction information, the smoke diffusion trend prediction information, the suction efficiency of the at least one target air suction port and a preset multi-objective optimization model.

[0030] On the other hand, an embodiment of the present invention further provides a smoke suction and exhaust device, comprising:

[0031] A data acquisition module, used to acquire multimodal data of a preset space;

[0032] a data prediction module, configured to determine, based on the multimodal data, prediction information of smoke distribution in the preset space after a preset time;

[0033] a capacity determination module, configured to determine the air suction capacity of at least one air suction port of the preset space;

[0034] The suction execution module is used to determine at least one target suction port and control the suction equipment of the target suction port to perform suction based on the smoke distribution prediction information and the suction capacity of the at least one suction port.

[0035] Optionally, the multimodal data includes at least one of smoke concentration data, airflow data, and image data, and the data prediction module includes:

[0036] The model prediction submodule is used to input at least one of the smoke concentration data, the airflow data and the image data into a preset prediction model, so that the preset prediction model outputs the smoke distribution prediction information of the preset space after a preset time.

[0037] Optionally, the suction capacity includes at least one of suction range and suction efficiency; the smoke distribution prediction information includes at least one of smoke concentration prediction information, smoke diffusion trend prediction information, and airflow prediction information.

[0038] Optionally, the suction capacity includes a suction range and a suction efficiency, and the suction execution module includes:

[0039] an air intake port determination submodule, configured to determine at least one target air intake port based on at least one of smoke concentration prediction information, smoke diffusion trend prediction information, and airflow prediction information, and the air intake range of the at least one air intake port;

[0040] a parameter determination submodule, configured to determine a target control parameter of the air suction device for the target air suction port based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, the airflow prediction information, and the air suction efficiency of the at least one target air suction port;

[0041] The device control submodule is used to control the suction device corresponding to the target suction port to suction air according to the target control parameters.

[0042] Optionally, the air inlet determination submodule includes:

[0043] a space division unit, configured to divide the preset space into at least one candidate area;

[0044] a target area determination unit, configured to determine a target area in the at least one candidate area based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information;

[0045] an overlap degree determining unit, configured to determine an overlap degree between the air suction range of each air suction port and the at least one target area;

[0046] The target air intake port determining unit is configured to determine the target air intake port according to the degree of overlap of the respective air intake ports.

[0047] Optionally, the parameter determination submodule includes:

[0048] a weight determination unit, configured to determine a working weight of the at least one target air intake port based on the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information; the working weight being used to indicate a degree of importance of the at least one target air intake port in the current smoke intake and exhaust process;

[0049] A weight control unit is used to determine at least one target control parameter based on the suction efficiency of the at least one target air suction port and the working weight of the at least one target air suction port.

[0050] Optionally, the parameter determination submodule includes:

[0051] an energy consumption data determining unit, configured to determine energy consumption data of the at least one target air intake port;

[0052] The target optimization unit is used to determine at least one target control parameter based on the energy consumption data of the at least one target air intake port, the smoke concentration prediction information, the smoke diffusion trend prediction information, the suction efficiency of the at least one target air intake port and a preset multi-objective optimization model.

[0053] Optionally, the parameter determination submodule includes:

[0054] A user preference obtaining unit, configured to obtain user preference information corresponding to the preset space;

[0055] A preference parameter determination unit is used to determine at least one target control parameter based on the user preference information corresponding to the preset space, the smoke concentration prediction information, the smoke diffusion trend prediction information, the suction efficiency of the at least one target air intake port and a preset multi-objective optimization model.

[0056] Accordingly, an embodiment of the present invention discloses an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, the various steps of the above-mentioned embodiment of the smoke suction and exhaust method are implemented.

[0057] Accordingly, an embodiment of the present invention discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, each step of the above-mentioned embodiment of the smoke suction and exhaust method is implemented.

[0058] The embodiments of the present invention include the following advantages: by acquiring multimodal data of a preset space, and determining the smoke distribution prediction information of the preset space after a preset time based on the multimodal data, the smoke diffusion trend can be grasped in advance, and the lag of the smoke suction and exhaust response is reduced. Then, by determining the suction capacity of at least one suction port of the preset space, at least one target suction port is determined according to the smoke distribution prediction information and the suction capacity of the at least one suction port, and the suction equipment of the target suction port is controlled to perform suction. By determining the target suction port in the suction port and controlling the target suction port, the smoke suction and exhaust control logic can cope with unevenly distributed smoke, avoiding the situation where excessive energy consumption but low exhaust efficiency occurs, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 is a flow chart of steps of an embodiment of a smoke suction and exhaust method of the present invention;

[0060] Figure 2 This is a schematic diagram of the regional division of an embodiment of a smoke suction and exhaust method of the present invention;

[0061] Figure 3 It is a structural block diagram of an embodiment of a smoke suction and exhaust device of the present invention. DETAILED DESCRIPTION

[0062] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0063] Existing technologies, when smoke extraction is performed in areas with complex spatial structures, can lead to uneven smoke distribution. Specifically, existing treatment methods allow areas requiring smoke extraction to naturally accumulate more smoke due to air flow characteristics, while the system continues to operate according to static control logic. This static control logic can result in low-concentration areas receiving excessive exhaust, resulting in energy waste, while high-concentration areas cannot receive sufficient exhaust due to total air volume restrictions. This ultimately leads to excessive energy consumption and low exhaust efficiency.

[0064] One of the core concepts of the embodiments of the present invention is to solve the lag of smoke suction and exhaust by actively predicting smoke distribution information based on multimodal data, and dynamically open the air intake according to the prediction results, thereby meeting the problem of uneven distribution of smoke in complex spaces.

[0065] Reference Figure 1 , shows a flowchart of a smoke suction and exhaust method embodiment of the present invention, which may specifically include the following steps:

[0066] Step 101: Acquire multimodal data of a preset space.

[0067] In daily life, all kinds of production activities are faced with the existence of smoke. The essence of smoke is a dynamic aerosol system formed by the phase change of matter under heat. It generally has the characteristics of thermodynamic drive, irreversible diffusion and hazard carrier. The smoke suction and exhaust method proposed in the present invention focuses on the application scenarios where smoke suction and exhaust are required in closed or semi-closed spaces. Below, this solution will be explained with two typical application scenarios: kitchen scenario and industrial workshop scenario; this method can be carried on a central control device with central control capabilities. The central control device has different forms of expression depending on the scenario. For example, in the kitchen scenario, the central control device can be a central control screen, or a cloud server in a cloud collaboration scenario. In the industrial workshop scenario, it can be a central control device with decision-making capabilities such as a central control server.

[0068] Multimodal data is a data concept that was created to address the perceptual limitations and information blind spots faced by a single data type when solving practical problems. Specifically, it refers to a collection of multiple types of data collected through different technical means at the same time and in the same space. The data types containing at least two data types can be various types, such as numerical types, image types, and text types. All types of data must be marked with unified timestamps and spatial coordinates to ensure that the data association is valid. For the present invention, after obtaining multimodal data, data cleaning and data formatting are required to ensure that data noise is removed and the spatiotemporal characteristics of the multimodal data are unified.

[0069] For example, in the present invention, multimodal data acquired in a kitchen setting may include kitchen fume concentration values, thermal maps or thermal imaging data of heat sources such as stoves, air flow direction and speed within the kitchen, and visual data of the kitchen captured by a camera. Multimodal data acquired in an industrial workshop setting may include temperature values ​​of contaminants, such as welding point temperatures in a welding workshop, visual data captured by a camera, equipment log data, pipeline pressure values ​​in workshop pipelines, gas chromatography data, audio data collected by a microphone, and other multi-source data. The present invention is not limited to this.

[0070] The core of acquiring multimodal data is the sensor. The arrangement of sensors can affect the authenticity and effectiveness of data collection. The specific arrangement method, including location selection and sensor number selection, can be flexibly changed according to different application scenarios. For example, in a kitchen scenario, the arrangement of sensors can be as follows: select thermal imaging cameras, smoke concentration sensors, and airflow sensors. According to the size of the kitchen and the location of pollution sources such as stoves and ovens, the number of these sensors can be flexibly changed. For example, in a small kitchen, 2 to 3 of each type of sensor can be used. The installation location can be directly above the pollution source, on the side in front, in the corner, at the kitchen exit, and other key locations. The core strategy is to ensure that the entire preset space is covered, while giving priority to the corners of the space and sensitive areas in the scene where smoke may spread, such as near the pollution source, and ensuring that the sensors will not be damaged due to the characteristics of the application scenario. For industrial workshop scenarios, according to the characteristics of the scenario, based on the above core strategy, flexible settings can be made. The present invention does not limit this.

[0071] Step 102: Determine smoke distribution prediction information of the preset space after a preset time based on the multimodal data.

[0072] After unifying the spatiotemporal characteristics of multimodal data, these multimodal data can be used to predict smoke distribution. The essence of smoke distribution prediction information is actually the spatial concentration distribution state of smoke generated by pollution sources at a specific time in the future within a preset space. The preset time represents a specific time in the future. Different preset times can be set according to different business scenarios to predict the diffusion trend and concentration information of smoke at different time scales. For example, in a kitchen scenario, the preset time setting range can be based on the reaction time of ingredients. For example, in the context of stir-frying ingredients, the preset time setting can be set within the range of 10 to 60 seconds based on the reaction time of oil pyrolysis. In an industrial workshop scenario, the preset time setting can be set according to the specific production time to complete a single production task. The method of predicting through multimodal data can be based on fluid mechanics formula calculations or with the help of existing prediction models.

[0073] In one embodiment, the multimodal data includes at least one of smoke concentration data, airflow data, and image data. Step 102 may include the following sub-steps:

[0074] Sub-step S11 , inputting at least one of the smoke concentration data, the airflow data and the image data into a preset prediction model, so that the preset prediction model outputs smoke distribution prediction information of the preset space after a preset time.

[0075] As mentioned above, smoke distribution prediction information can be achieved through multimodal data through a prediction model. In actual application scenarios, the prediction model is generally divided into two main parts: the feature extraction part, which is used to extract the spatiotemporal feature data of the multimodal data, and the distribution prediction part, which is used to predict the smoke distribution based on the extracted spatiotemporal feature data.

[0076] For feature extraction, models based on the Vit (Vision Transformer) algorithm can be selected, such as a CNN (Convolutional Neural Network)-Vit hybrid model or a Vit-Adapter model. For distribution prediction, the model should be selected based on the smoke generation characteristics and properties of the smoke in different scenarios. For example, a CNN-LSTM (Long Short-Term Memory) hybrid model can be used for subsequent predictions in kitchen scenarios, while models such as DeepLabV3+ or UNet can be used for industrial workshop scenarios. After generating the prediction results, actual smoke distribution information after a preset time is continuously obtained to continuously optimize the accuracy of the preset prediction model. By combining the prediction model with multimodal data, the smoke distribution at the predicted time can be accurately predicted, providing reliable data support for subsequent smoke extraction and control.

[0077] Step 103, determining the air suction capacity of at least one air suction port of the preset space;

[0078] In the field of smoke extraction, in addition to the important information of smoke distribution prediction, another important information is the suction capacity of the suction device within the preset space. Generally, when extracting smoke from an enclosed or closed space, it is necessary to rely on suction vents. The form of suction vents can be presented in various forms according to the needs of the scene, such as suction vents, vents, ventilation fans, or ventilation ducts. The suction capacity of the suction vents can be quantified by the performance of the suction equipment corresponding to the suction vents. For example, the performance of the suction equipment at different openings can be tested in a laboratory or simulation environment. Specifically, the effective negative pressure range created by the suction equipment at different openings can be tested and used as the suction range of the suction vent; or the amount of target smoke that can be sucked away per unit time at different openings of the suction equipment can be used as the suction efficiency. In addition to the test variables, the performance at different openings can also be comprehensively determined based on relevant indicators required by the business, such as the airway design of the suction vents, the pipe diameter, etc. Correspondingly, key indicators such as the installation location and number of the suction vents can be comprehensively determined based on the above test results and actual business needs, such as budget.

[0079] For example, possible air intakes include: top intakes installed directly above or slightly in front of the pollution source; side / rear intakes located to the side of the pollution source or on the wall near the pollution source; and covered intakes located on the ceiling, side walls, or corners of the pre-set space. The angle and distance between the intake and the pollution source should be maintained according to the specific application scenario to improve smoke capture efficiency.

[0080] After the installation of the air suction port has been completed, the air suction capacity of the air suction port can be determined by obtaining the working parameters of the current air suction port and combining them with the data in the test results to obtain the theoretical target value. The implementation method can be to set a mapping table of preset working parameters and related air suction capacity. The quantitative standard of the air suction capacity can be flexibly set according to the needs of the scene. For example, the air suction range weight and the air suction efficiency weight can be set according to the application scenario. The quantitative numerical representation of the air suction range and the air suction efficiency can be normalized according to the test data, and the sum of the products of the corresponding weighted data is used as the quantitative representation of the air suction capacity. The combination of the air suction port and the air suction device described in the present invention can dynamically select a variety of implementation methods according to different application scenarios. For example, in a kitchen scenario, the combination of the air suction port and the air suction device can be a variety of equipment such as a range hood, an air purification device, and an air conditioning device; in an industrial scenario, the combination of the air suction port and the air suction device can be a variety of implementation methods such as an industrial exhaust fan, an industrial ventilation duct, and an industrial dust removal system.

[0081] In one embodiment, the suction capacity includes at least one of the suction range and the suction efficiency; the smoke distribution prediction information includes at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information.

[0082] The smoke concentration prediction information is used to represent the smoke concentration in a preset space at a certain moment in the future. Its specific form of expression can be an image display: different colors in the image represent different concentrations. One way can be to use red to represent the highest concentration area, green to represent the lowest concentration area, and yellow and other transition colors to represent the intermediate concentration area. The color corresponding to the concentration in the image display can be freely set.

[0083] Smoke diffusion trend and airflow forecasts are used to represent smoke diffusion at a specific moment in the future. For example, they predict smoke concentration within a preset space over the next five minutes. This diffusion process can be reflected through color changes or the movement of concentration hotspots. For example, in a kitchen scenario, if smoke initially concentrates in the cooking area, over the next few minutes, the forecast map will show that smoke concentration gradually spreads to other parts of the kitchen, particularly toward open areas or areas with weak air flow.

[0084] In the present invention, by selecting at least one of the suction range and the suction efficiency as the representation of the suction capacity, selecting at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information as the representation of the smoke distribution prediction information, and performing subsequent predictions based on these data, the prediction accuracy and the smoke suction and exhaust efficiency can be improved.

[0085] Step 104: Determine at least one target air suction port based on the smoke distribution prediction information and the air suction capacity of the at least one air suction port and control the air suction equipment of the target air suction port to perform air suction.

[0086] After determining the smoke distribution prediction information and the suction capacity of at least one suction port, the target suction port can be determined based on these two indicators, and the suction equipment corresponding to the target suction port can be controlled to perform suction operations; the operation content includes the opening degree, opening time, etc. of the suction equipment corresponding to the suction port.

[0087] In one embodiment, the suction capacity includes suction range and suction efficiency, and step 104 may include the following sub-steps:

[0088] Sub-step S21, determining at least one target air intake port based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, the airflow prediction information, and the air intake range of the at least one air intake port;

[0089] One of the confirmation logics of the target air intake port is to roughly judge the distribution of smoke at a certain future moment through at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the air flow prediction information, and select the air intake port with sufficient suction range as the target air intake port based on the smoke distribution. For example, the air intake port whose suction range completely covers the area with the highest smoke concentration can be used as the target air intake port.

[0090] In one embodiment, sub-step S21 may include the following sub-steps:

[0091] Sub-step S211, dividing the preset space into at least one candidate area;

[0092] To facilitate more specific quantification of the target air intake confirmation logic and achieve accurate smoke extraction and exhaust in the preset space, the preset space can be divided into at least one candidate area using a certain logic. The division logic can be determined based on the importance of the area. For example, in a kitchen scenario, pollution sources such as the stove can be set as important areas. When determining the target air intake, the air intakes within the important area or that can cover the important area will be opened first. In addition to the importance, the candidate areas can also be divided according to the location of the air intake.

[0093] For example, one way to divide the areas is to map the spatial grid to the coverage of the air intakes. Based on the size of the air intakes and areas, each air intake is responsible for a certain number of areas, or each area includes a certain number of air intakes. The areas can also be divided based on the air intake capacity of the air intakes.

[0094] Sub-step S212, determining a target area in the at least one candidate area based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information;

[0095] Through the smoke concentration prediction information, it is determined which areas in the candidate areas need to be treated with smoke suction and exhaust at a certain time in the future. Through the smoke diffusion trend prediction information, it can be determined which areas have the risk of smoke diffusion at a certain time in the future and need pre-start treatment. The candidate areas that need suction and exhaust treatment and the candidate areas that need pre-start suction and exhaust are regarded as target areas.

[0096] Sub-step S213, determining the degree of overlap between the suction range of each suction port and the at least one target area;

[0097] After knowing which areas are target areas, it is possible to determine which air intakes need to be opened, that is, determine which air intakes are target air intakes, based on the coverage of the target areas by the air intakes, that is, the degree of overlap.

[0098] Sub-step S214: determining a target air intake port according to the degree of overlap of the air intake ports.

[0099] For example, refer to Figure 2 , which shows a schematic diagram of the regional division of an embodiment of a smoke suction and exhaust method of the present invention:

[0100] In this example, the preset space can be evenly divided into 16 candidate areas, with an air intake 1 set between area 2 and area 3, an air intake 2 set between area 5 and area 12, an air intake 3 set in the middle of area 6, area 7, area 11, and area 10, an air intake 4 set between area 8 and area 9, and an air intake 5 set in the middle of area 14 and area 15; in addition to uniform division, the area division can also be based on whether the area contains pollution sources or according to the predetermined position of the air intake as mentioned above, or it can be divided in real time according to the smoke concentration, and the present invention does not limit this.

[0101] Because smoke generation and diffusion patterns vary in real-world scenarios, to prevent smoke from escaping, each time a target intake is identified, after determining the target area based on the current smoke concentration and diffusion trend forecasts, it is also necessary to determine the target intake corresponding to that area. One method for determining the target intake is to select intakes with a degree of overlap greater than a certain threshold as target intakes. By dividing the preset space into multiple candidate areas, the accuracy and efficiency of smoke extraction are improved.

[0102] Sub-step S22, determining a target control parameter of a suction device for the target air intake port based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, the airflow prediction information, and the suction efficiency of the at least one target air intake port;

[0103] After the target air intake port is determined, the target control parameters of the air suction device of the target air intake port can be determined so that the air suction device performs the air suction operation according to the target control parameters. For example, if it is determined based on the smoke diffusion trend prediction information and the airflow prediction information that the smoke may spread rapidly at this time, the air suction device corresponding to the target air intake port will be turned on with a higher power. Or, if it is determined based on the smoke concentration prediction information that the smoke covered by target air intake port A will have a higher concentration and the smoke concentration covered by target air intake port B will be relatively small, then the air suction device corresponding to target air intake port A will be turned on with a higher power, and the air suction device corresponding to target air intake port B will be turned on with a lower power. As for the mapping relationship between concentration and opening power or opening degree, it can be set according to actual needs, and the present invention does not limit this.

[0104] In actual application environments, the specific implementation of sub-step S22 can be flexibly adjusted according to business needs. Three exemplary embodiments are proposed below:

[0105] In a first exemplary embodiment, sub-step S22 may include the following steps:

[0106] determining a working weight of the at least one target air intake port based on the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information; the working weight being used to indicate the importance of the at least one target air intake port in the current smoke intake and exhaust process;

[0107] At least one target control parameter is determined according to the suction efficiency of the at least one target air suction port and the working weight of the at least one target air suction port.

[0108] For example, the working weight can be determined by setting C i 、T i and F i Three parameters, among which C iIt represents the smoke concentration within the coverage of the i-th target air inlet after a certain time; T i It indicates the smoke diffusion trend within the coverage of the i-th target air intake after a certain time. The smoke diffusion trend can be expressed by the rate of change of smoke concentration; F i : represents the airflow correction factor within the coverage area of ​​the i-th target air intake port after a certain moment. The setting logic of the correction factor can be that the weaker the airflow intensity, the larger the value, or the greater the influence of the airflow direction on the smoke diffusion trend, the larger the value. Each factor will be normalized, and the corresponding normalization processing method can be any one of the linear normalization (Min-Max) method, Z-Score normalization method, Maximum Abs method, or Decimal Scaling method. The present invention does not limit the normalization processing method.

[0109] Correspondingly, the influence coefficients α, β, and γ of the three parameters are set. Among them, α represents the influence coefficient of smoke concentration, which directly reflects the severity of pollution and is the core basis of the suction and exhaust strategy. That is, high-concentration smoke must be treated first, otherwise it will spread rapidly; β represents the influence coefficient of smoke diffusion trend, which can warn of potential pollution risks in the future and intervene in advance, which is of great significance for preventing diffusion and energy-saving scheduling; γ represents the influence coefficient of airflow factor, which can quantify the controllability of smoke. For example, if the airflow in a certain area is not smooth, even if the concentration is not high, it may form a dead corner for accumulation. The determination of relevant influence coefficients can be adjusted through simulation experiments. The corresponding evaluation indicators can be the suction and exhaust delay time, which represents how long it takes for the smoke concentration to drop to a safe concentration; the suction and exhaust energy consumption can be expressed as the total fan power per unit time; the smoke residual degree can be expressed as the ratio of the remaining smoke concentration after a certain period of smoke suction and exhaust to the concentration before the execution of smoke suction and exhaust.

[0110] Then the work weight W i The expression is: Wi = α* C i +β* T i +γ* F i .

[0111] Based on the smoke concentration prediction information, smoke diffusion trend prediction information and airflow prediction information, the work weight corresponding to each target air intake port can be obtained. When setting the control parameters of the target air intake port with a larger work weight, the suction and exhaust capacity will be given priority rather than other indicators. That is, the setting of the corresponding target control parameters will also increase accordingly. For example, the daily opening of a certain air intake port is up to 80% of the standard opening. When the work weight of the air intake port is greater than a certain threshold, the opening of the air intake port will be temporarily allowed to exceed 80% of the standard opening to facilitate faster response to smoke suction and exhaust.

[0112] In addition, when multiple target air suction ports perform suction and exhaust operations together, abnormal conditions such as air duct competition and negative pressure disturbance may occur. At this time, the main control air port and auxiliary air port can be set according to the work weight. The target air suction port with a larger work weight is the main control air port, and the target air suction port with a smaller work weight is the auxiliary air port with a lower priority. During the suction and exhaust process, the main control air port maintains normal suction operation; the auxiliary air port only operates as a supplement to avoid reverse suction interference;

[0113] Weight calculation is dynamic, adjusting the weight of each target intake inlet in real time as the smoke diffusion process evolves. Taking into account the smoke concentration, smoke diffusion trends, and airflow factors at each target intake, the weight of each target intake is determined. Target intakes with higher weights are opened wider, thereby securing more suction and exhaust resources. This improves the targetedness and efficiency of smoke extraction and avoids competition between multiple target intakes.

[0114] In a second exemplary embodiment, sub-step S22 may include the following steps:

[0115] determining energy consumption data of the at least one target air intake;

[0116] At least one target control parameter is determined based on the energy consumption data of the at least one target air suction port, the smoke concentration prediction information, the smoke diffusion trend prediction information, the suction efficiency of the at least one target air suction port and a preset multi-objective optimization model.

[0117] In actual scenarios, in addition to suction and exhaust efficiency, suction and exhaust energy consumption is also one of the key points that need to be considered. Smoke suction and exhaust should meet the unity of energy consumption and suction and exhaust efficiency. We cannot ignore the suction and exhaust efficiency because of the emphasis on energy consumption, nor can we ignore energy consumption because of the emphasis on suction and exhaust efficiency, which will cause unnecessary waste of resources.

[0118] Usually, the relationship between suction efficiency and energy consumption is not linear but complex nonlinear. Therefore, it is not possible to simply find the balance point between energy consumption and efficiency. At this time, multi-dimensional indicators such as energy consumption data, smoke concentration prediction information, smoke diffusion trend prediction information and the suction efficiency of at least one target suction port can be input into a preset multi-objective optimization model to find a balanced solution. The selection of the multi-objective optimization model can be a multi-objective reinforcement learning model or an evolutionary model, such as a multi-objective optimization model with a decomposition-based multi-objective evolutionary algorithm as the core. The present invention does not limit this. By combining the multi-objective optimization model, a balance between energy saving and suction and exhaust efficiency can be achieved, thereby improving user experience.

[0119] In a third exemplary embodiment, sub-step S22 may further include the following steps:

[0120] Obtaining user preference information corresponding to the preset space;

[0121] At least one target control parameter is determined based on the user preference information corresponding to the preset space, the smoke concentration prediction information, the smoke diffusion trend prediction information, the suction efficiency of the at least one target air suction port and a preset multi-objective optimization model.

[0122] In addition to the preset conditions, the target parameter settings can also be determined based on the user's usage preference information, such as the device operation model set by the user, the device operation parameters specified by the user, the operation status and other information, so that the smoke suction and exhaust process can better meet the user's needs.

[0123] For example, when the user sets the silent energy-saving model to take priority, unless the current situation is dangerous according to the predicted smoke concentration and smoke diffusion trend, even if the predicted smoke concentration and smoke diffusion trend show that the target air intake should turn on the corresponding suction device at high power, due to the preference data set by the user, the suction device at this time will also start at a lower power or silent mode, or during the suction and exhaust process, the user manually closes the target air intake that has been involved in the suction and exhaust work. At this time, the target air intake will be re-judged, and the target air intake manually closed by the user will no longer participate in the smoke suction and exhaust work within a certain period of time; taking user preference data as one of the target control parameters can significantly improve user satisfaction with the smoke suction and exhaust process.

[0124] Sub-step S23: controlling the suction device corresponding to the target suction port to perform suction according to the target control parameters.

[0125] According to the determined target control parameters, the suction equipment corresponding to the target suction port is controlled to perform suction and exhaust of smoke.

[0126] By using at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, the airflow prediction information and the suction efficiency and suction range of the at least one target air suction port, the target air suction port and the corresponding control parameters are determined respectively, and the determination of the target air suction port is decoupled from the control parameters of the target air suction port, thereby realizing dynamic smoke suction and exhaust, which can meet various application scenarios and improve the accuracy of smoke suction and exhaust.

[0127] By acquiring multimodal data of a preset space and determining the smoke distribution prediction information of the preset space after a preset time based on the multimodal data, the smoke diffusion trend can be grasped in advance and the lag of the smoke suction and exhaust response can be reduced. Then, by determining the suction capacity of at least one suction port of the preset space, at least one target suction port is determined according to the smoke distribution prediction information and the suction capacity of the at least one suction port, and the suction equipment of the target suction port is controlled to perform suction. By determining the target suction port in the suction port and controlling the target suction port, the smoke suction and exhaust control logic can cope with non-uniformly distributed smoke, avoiding the situation where excessive energy consumption but low exhaust efficiency occurs, thereby improving the user experience.

[0128] It should be noted that for the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0129] Reference Figure 3 , shows a structural block diagram of an embodiment of a smoke suction and exhaust device of the present invention, which may specifically include the following modules:

[0130] The data acquisition module 201 is used to acquire multimodal data of a preset space;

[0131] The data prediction module 202 is configured to determine smoke distribution prediction information of the preset space after a preset time based on the multimodal data;

[0132] A capacity determination module 203 is used to determine the air suction capacity of at least one air suction port in the preset space;

[0133] The suction execution module 204 is used to determine at least one target suction port and control the suction equipment of the target suction port to perform suction according to the smoke distribution prediction information and the suction capacity of the at least one suction port.

[0134] In one embodiment, the multimodal data includes at least one of smoke concentration data, airflow data, and image data, and the data prediction module includes:

[0135] The model prediction submodule is used to input at least one of the smoke concentration data, the airflow data and the image data into a preset prediction model, so that the preset prediction model outputs the smoke distribution prediction information of the preset space after a preset time.

[0136] In one embodiment, the suction capacity includes at least one of the suction range and the suction efficiency; the smoke distribution prediction information includes at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information.

[0137] In one embodiment, the suction capacity includes a suction range and a suction efficiency, and the suction execution module includes:

[0138] an air intake port determination submodule, configured to determine at least one target air intake port based on at least one of smoke concentration prediction information, smoke diffusion trend prediction information, and airflow prediction information, and the air intake range of the at least one air intake port;

[0139] a parameter determination submodule, configured to determine a target control parameter of the air suction device for the target air suction port based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, the airflow prediction information, and the air suction efficiency of the at least one target air suction port;

[0140] The device control submodule is used to control the suction device corresponding to the target suction port to suction air according to the target control parameters.

[0141] In one embodiment, the air inlet determination submodule includes:

[0142] a space division unit, configured to divide the preset space into at least one candidate area;

[0143] a target area determination unit, configured to determine a target area in the at least one candidate area based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information;

[0144] an overlap degree determining unit, configured to determine an overlap degree between the air suction range of each air suction port and the at least one target area;

[0145] The target air intake port determining unit is configured to determine the target air intake port according to the degree of overlap of the respective air intake ports.

[0146] In one embodiment, the parameter determination submodule includes:

[0147] a weight determination unit, configured to determine a working weight of the at least one target air intake port based on the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information; the working weight being used to indicate a degree of importance of the at least one target air intake port in the current smoke intake and exhaust process;

[0148] A weight control unit is used to determine at least one target control parameter based on the suction efficiency of the at least one target air suction port and the working weight of the at least one target air suction port.

[0149] In one embodiment, the parameter determination submodule includes:

[0150] an energy consumption data determining unit, configured to determine energy consumption data of the at least one target air intake port;

[0151] The target optimization unit is used to determine at least one target control parameter based on the energy consumption data of the at least one target air intake port, the smoke concentration prediction information, the smoke diffusion trend prediction information, the suction efficiency of the at least one target air intake port and a preset multi-objective optimization model.

[0152] In one embodiment, the parameter determination submodule includes:

[0153] A user preference obtaining unit, configured to obtain user preference information corresponding to the preset space;

[0154] A preference parameter determination unit is used to determine at least one target control parameter based on the user preference information corresponding to the preset space, the smoke concentration prediction information, the smoke diffusion trend prediction information, the suction efficiency of the at least one target air intake port and a preset multi-objective optimization model.

[0155] By acquiring multimodal data of a preset space and determining the smoke distribution prediction information of the preset space after a preset time based on the multimodal data, the smoke diffusion trend can be grasped in advance and the lag of the smoke suction and exhaust response can be reduced. Then, by determining the suction capacity of at least one suction port of the preset space, at least one target suction port is determined according to the smoke distribution prediction information and the suction capacity of the at least one suction port, and the suction equipment of the target suction port is controlled to perform suction. By determining the target suction port in the suction port and controlling the target suction port, the smoke suction and exhaust control logic can cope with non-uniformly distributed smoke, avoiding the situation where excessive energy consumption but low exhaust efficiency occurs, thereby improving the user experience.

[0156] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0157] An embodiment of the present invention further provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and capable of running on the processor. When the computer program is executed by the processor, the various processes of the above-mentioned embodiment of the smoke suction and exhaust method are implemented, and the same technical effects are achieved. To avoid repetition, they are not described here. In a kitchen scenario, the electronic device can be a range hood, an air purification device, an air conditioning device, and other equipment; in an industrial scenario, the electronic device can be an industrial exhaust fan, an industrial ventilation duct, an industrial dust removal system, and other equipment.

[0158] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the above-mentioned smoke suction and exhaust method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0159] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0160] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, apparatuses, or computer program products. Thus, embodiments of the present invention may take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0161] The embodiments of the present invention are described with reference to flowcharts and / or block diagrams of methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0162] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0163] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0164] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they become aware of the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0165] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

[0166] The above is a detailed introduction to the smoke suction and exhaust method, device, equipment and medium provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A smoke suction and exhaust method, characterized in that: The method comprises: Acquiring multimodal data of a preset space; the multimodal data including at least one of smoke concentration data, airflow data, and image data; inputting at least one of the smoke concentration data, the airflow data, and the image data into a preset prediction model, so that the preset prediction model outputs smoke distribution prediction information of the preset space after a preset time; the smoke distribution prediction information includes at least one of smoke concentration prediction information, smoke diffusion trend prediction information, and airflow prediction information; Determining the suction capacity of at least one suction port of the preset space; the suction capacity includes a suction range; determining at least one target air suction port and controlling the air suction device of the target air suction port to perform air suction based on the smoke distribution prediction information and the air suction capacity of the at least one air suction port; The step of determining at least one target air suction port and controlling the air suction device of the target air suction port to perform air suction based on the smoke distribution prediction information and the air suction capacity of the at least one air suction port comprises: Dividing the preset space into at least one candidate area; determining a target area in the at least one candidate area according to at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information; Determining the degree of overlap between the suction range of each suction port and the at least one target area; A target air suction port is determined according to the degree of overlap of the air suction ports.

2. A smoke suction and exhaust method according to claim 1, characterized in that: The suction capacity includes suction efficiency. Determining at least one target suction port and controlling the suction device of the target suction port to perform suction based on the smoke distribution prediction information and the suction capacity of the at least one suction port includes: determining a target control parameter of a suction device for the target air suction port based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information and the suction efficiency of the at least one target air suction port; According to the target control parameters, the suction equipment corresponding to the target suction port is controlled to perform suction.

3. A smoke suction and exhaust method according to claim 2, characterized in that: The determining, based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information and the suction efficiency of the at least one target air suction port, a target control parameter of the air suction device for the target air suction port comprises: determining a working weight of the at least one target air intake port based on the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information; the working weight being used to indicate the importance of the at least one target air intake port in the current smoke intake and exhaust process; At least one target control parameter is determined according to the suction efficiency of the at least one target air suction port and the working weight of the at least one target air suction port.

4. A smoke suction and exhaust method according to claim 2, characterized in that: The determining, based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information and the suction efficiency of the at least one target air suction port, a target control parameter of the air suction device for the target air suction port comprises: determining energy consumption data of the at least one target air intake; At least one target control parameter is determined based on the energy consumption data of the at least one target air suction port, the smoke concentration prediction information, the smoke diffusion trend prediction information, the suction efficiency of the at least one target air suction port and a preset multi-objective optimization model.

5. The smoke suction and exhaust method according to claim 2, characterized in that: The determining, based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information and the suction efficiency of the at least one target air suction port, a target control parameter of the air suction device for the target air suction port comprises: Obtaining user preference information corresponding to the preset space; At least one target control parameter is determined based on the user preference information corresponding to the preset space, the smoke concentration prediction information, the smoke diffusion trend prediction information, the suction efficiency of the at least one target air suction port and a preset multi-objective optimization model.

6. A smoke suction and exhaust device, characterized in that: The device comprises: A data acquisition module, configured to acquire multimodal data of a preset space; the multimodal data including at least one of smoke concentration data, airflow data, and image data; a data prediction module, configured to input at least one of the smoke concentration data, the airflow data, and the image data into a preset prediction model, so that the preset prediction model outputs smoke distribution prediction information for the preset space after a preset time; the smoke distribution prediction information includes at least one of smoke concentration prediction information, smoke diffusion trend prediction information, and airflow prediction information; A capacity determination module, configured to determine the air suction capacity of at least one air suction port in the preset space; the air suction capacity includes an air suction range; an air suction execution module, configured to determine at least one target air suction outlet and control the air suction equipment of the target air suction outlet to perform air suction based on the smoke distribution prediction information and the air suction capacity of the at least one air suction outlet; The air suction execution module includes: a space division unit, configured to divide the preset space into at least one candidate area; a target area determination unit, configured to determine a target area in the at least one candidate area based on at least one of the smoke concentration prediction information, the smoke diffusion trend prediction information, and the airflow prediction information; an overlap degree determining unit, configured to determine an overlap degree between the air suction range of each air suction port and the at least one target area; The target air intake port determining unit is configured to determine the target air intake port according to the degree of overlap of the respective air intake ports.

7. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the steps of a smoke suction and exhaust method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the smoke suction and exhaust method according to any one of claims 1 to 5 are implemented.

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