Control method and device for range hood, range hood and computer readable storage medium

Abstract

The invention relates to the technical field of intelligent household appliances, and discloses a control method for a range hood, which comprises the following steps: after the range hood is started, obtaining user attributes and range hood operation parameters corresponding to the optimal smoke suction effect; and adjusting operation parameters of the range hood according to the user attributes. The method can consider the smoke suction effect of the range hood and the requirement of the user for the cooking environment. The invention further discloses a control device for the range hood, the range hood and a computer readable storage medium.

Description

Technical Field

[0001] This application relates to the field of smart home appliance technology, such as a control method and device for a range hood, a range hood, and a computer-readable storage medium. Background Technology

[0002] Currently, with the rapid development of science and technology, the functions of home appliances are becoming increasingly diversified, and the user experience is gradually improving. As an essential appliance in home cooking, the intelligent control technology for range hoods is becoming increasingly mature. To achieve intelligent control, range hoods are equipped with sensors to detect the fan speed and perform intelligent control based on the sensor's fan speed value. However, because different users have different sensitivities to cooking fumes or the cooking environment, sensor-based intelligent control methods for range hoods cannot meet the personalized needs of users.

[0003] To meet users' personalized needs, a method for adjusting the control strategy of a range hood is disclosed. The range hood operates in two modes: manual and automatic. In automatic mode, the range hood automatically controls the fan speed based on sensor parameters. The method includes: when the range hood is operating in automatic mode, acquiring the number of times the user manually adjusts the range hood's speed setting (both up and down); adjusting the control parameters of the range hood in automatic mode based on the number of speed adjustments, wherein the sensitive parameters of the sensor are adjusted based on the number of speed adjustments (both up and down), and the fan speed corresponding to the sensor parameters is adjusted accordingly.

[0004] In the process of implementing the embodiments of this disclosure, at least the following problems were found in the related art:

[0005] The relevant technology does not take into account the impact of users' cooking environment needs on the operation of the range hood. Relying solely on the number of times users manually adjust the range hood's speed settings cannot achieve precise control of the range hood, thus limiting the improvement of the accuracy of range hood control.

[0006] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0008] This disclosure provides a control method and apparatus for a range hood, a range hood, and a computer-readable storage medium, to balance the smoke extraction effect of the range hood with the user's needs for the cooking environment.

[0009] In some embodiments, the method includes: after the range hood is started, obtaining user attributes and range hood operating parameters corresponding to the optimal smoke extraction effect; and adjusting the range hood operating parameters according to the user attributes.

[0010] In some embodiments, user attributes include user sensitivity type, and range hood operating parameters include fan parameters. Adjusting the range hood operating parameters according to user attributes includes: reducing fan parameters when the user sensitivity type indicates noise sensitivity; and increasing fan parameters when the user sensitivity type indicates oil fume sensitivity.

[0011] In some embodiments, the user's sensitivity type is obtained as follows: obtaining the fan control command sent by the user during the historical operation phase of the range hood; wherein the fan control command is used to indicate the updating of historical fan parameters; if the fan control command indicates a decrease in historical fan parameters, the user is determined to be a noise-sensitive user; if the fan control command indicates an increase in historical fan parameters, the user is determined to be a fume-sensitive user.

[0012] In some embodiments, the user attributes also include the user's line-of-sight obstruction status. Adjusting the range hood operating parameters according to the user attributes further includes: after increasing the fan parameters, when the user's line-of-sight obstruction status indicates that the baffle plate constitutes a line-of-sight obstruction, obtaining the correspondence between the change in the rotation angle of the baffle plate and the change in the fan parameters; determining the target change in the fan parameters corresponding to the reduction in the baffle plate rotation angle based on the correspondence between the change in the baffle plate rotation angle and the change in the fan parameters; and performing airflow compensation on the adjusted fan parameters based on the target change in the fan parameters to enhance the smoke extraction intensity by increasing the fan parameters.

[0013] In some embodiments, user attributes include the user's line-of-sight obstruction state, and range hood operating parameters include fan parameters and baffle plate rotation angle. Adjusting the range hood operating parameters according to the user attributes includes: controlling the baffle plate rotation according to a target baffle plate rotation angle; wherein the target baffle plate rotation angle is determined by the correlation between the oil fume particulate matter capture efficiency and the baffle plate rotation angle; after the baffle plate rotation ends, obtaining the user's line-of-sight obstruction state; when the user's line-of-sight obstruction state indicates that the baffle plate constitutes a line-of-sight obstruction, controlling the baffle plate to reduce the target baffle plate rotation angle, and after reducing the target baffle plate rotation angle, compensating the fan parameters for airflow to enhance the oil fume extraction intensity by increasing the fan parameters.

[0014] In some embodiments, the target smoke baffle rotation angle is determined as follows: the correspondence between the oil fume particulate matter collection efficiency and the smoke baffle rotation angle is obtained; based on the correspondence between the oil fume particulate matter collection efficiency and the smoke baffle rotation angle, the target smoke baffle rotation angle corresponding to the optimal oil fume particulate matter collection efficiency is determined.

[0015] In some embodiments, the user's line-of-sight obstruction status is obtained in the following manner: receiving a smoke baffle update command sent by the user, and determining that the user's line-of-sight obstruction status is that the smoke baffle constitutes a line-of-sight obstruction when the smoke baffle update command indicates a reduction in the smoke baffle rotation angle; or, obtaining the initial smoke baffle rotation angle before the smoke baffle rotates and the smoke baffle control command sent by the user based on the initial smoke baffle rotation angle during the historical operation phase of the range hood, and determining that the user's line-of-sight obstruction status is that the smoke baffle constitutes a line-of-sight obstruction when the smoke baffle control command indicates a reduction in the initial smoke baffle rotation angle.

[0016] In some embodiments, the control device includes a processor and a memory storing program instructions, the processor being configured to execute the control method for a range hood as described above when the program instructions are executed.

[0017] In some embodiments, the range hood includes: a range hood body; and a control device for the range hood as described above, installed on the range hood body.

[0018] In some embodiments, the computer-readable storage medium stores program instructions that, when executed, cause a computer to perform the aforementioned method for designing a range hood baffle.

[0019] The control method and apparatus for a range hood, the range hood itself, and the computer-readable storage medium provided in this disclosure can achieve the following technical effects:

[0020] When the range hood is turned on, it obtains user attributes and operating parameters corresponding to the optimal smoke extraction effect, and adjusts these parameters accordingly. This embodiment of the disclosure can control the range hood by combining the user's needs for the cooking environment with the operating parameters corresponding to the optimal smoke extraction effect. Compared to simply relying on the number of times the user manually adjusts the range hood's settings, the control effect is improved, satisfying the user's needs for the cooking environment while maintaining effective smoke extraction.

[0021] The above general description and the description below are exemplary and illustrative only and are not intended to limit this application. Attached Figure Description

[0022] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations and drawings do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are shown as similar elements. The drawings are not to be scaled. And wherein:

[0023] Figure 1 This is a schematic diagram of a method for analyzing the smoke extraction effect of a range hood, provided in an embodiment of this disclosure;

[0024] Figure 2 This is a schematic diagram of the temperature region on the inner surface of the cookware in the method provided in the embodiments of this disclosure;

[0025] Figure 3 This is a schematic diagram of another method for analyzing the smoke extraction effect of a range hood, provided in an embodiment of this disclosure;

[0026] Figure 4 This is a flowchart illustrating the process of inputting parameters into a target simulation model to simulate the smoking effect in the method provided in this embodiment of the disclosure;

[0027] Figure 5 This is a graph showing the relationship between the particle size distribution and mass fraction of oil fume particles provided in an embodiment of this disclosure;

[0028] Figure 6 This is a left view of a range hood provided in an embodiment of this disclosure;

[0029] Figure 7 This is a schematic diagram of a control method for a range hood provided in an embodiment of this disclosure;

[0030] Figure 8 This is a schematic diagram of another control method for a range hood provided in an embodiment of this disclosure;

[0031] Figure 9 This is a schematic diagram of another control method for a range hood provided in an embodiment of this disclosure;

[0032] Figure 10 This is a schematic diagram of a control device for a range hood provided in an embodiment of this disclosure;

[0033] Figure 11 This is a schematic diagram of a range hood provided in an embodiment of this disclosure.

[0034] Figure label:

[0035] 100: Range hood; 20: Range hood body; 201: Smoke baffle; 202: Oil filter;

[0036] 70: Control device for range hoods; 700: Processor;

[0037] 701: Memory; 702: Communication interface; 703: Bus. Detailed Implementation

[0038] To provide a more detailed understanding of the features and technical content of the embodiments of this disclosure, the implementation of the embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this disclosure. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.

[0039] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0040] Unless otherwise stated, the term "multiple" means two or more.

[0041] In this embodiment of the disclosure, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0042] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0043] The term "correspondence" can refer to an association or binding relationship. The correspondence between A and B means that there is an association or binding relationship between A and B.

[0044] In the experimental testing space, the generation and diffusion of cooking fumes under various cooking scenarios, as well as the changes in the flow field of cooking fumes under the action of a range hood, were simulated. The experimental equipment included a range hood, a heating source, and cookware; the heating source included a stove or other device capable of heating the cookware. Image acquisition devices were installed on both sides of the cookware to acquire the velocity parameters of the cooking fume particles. For example, one image acquisition device was installed on the front and one on the side of the cookware. A fume sampler was installed above the cookware to acquire the particle size parameters of the cooking fume particles.

[0045] Optionally, the image acquisition device includes a high-speed camera. When obtaining the velocity parameters of oil fume particles using particle image velocimetry, tracer particles are injected into the oil fume flow field and illuminated by a laser light source. The high-speed camera then acquires images, and the velocity parameters of the oil fume particles are obtained after image analysis and processing. Two high-speed cameras are calibrated to ensure that the frontal and side images are time-synchronized and spatially aligned.

[0046] The processor determines the mapping relationship between the initial velocity and particle size parameters of oil fume particles and the smoke source, including:

[0047] The processor acquires the initial velocity and particle size parameters of the oil fume particles in the target space.

[0048] The processor determines the smoke source in the target space based on the initial velocity and particle size parameters of the oil fume particles.

[0049] Thus, the target space mainly refers to the space where the oil fume is located during the oil fume experimental test, and the initial velocity of the oil fume particles refers to the generation velocity of the oil fume particles. Cooking scenarios include various cooking states such as stewing, stir-frying, and deep-frying, and the smoke source parameters generated in each scenario are also different. That is, the parameters of the oil fume particles are different (in this embodiment of the disclosure, the oil fume particle parameters include the initial velocity and particle size parameters of the oil fume particles). Therefore, the smoke source is determined by simulating the smoke generation of different cooking scenarios through experimental testing. Images and parameters of oil fume particles during the oil fume generation process are collected, and the initial velocity of the oil fume particles is obtained by processing and analyzing the images. The particle size parameters of the oil fume particles are obtained by analyzing the oil fume particle parameters. In this way, the initial velocity and particle size parameters of the oil fume particles for the corresponding cooking scenario are obtained. Simultaneously, based on the obtained initial velocity and particle size parameters of the oil fume particles, the smoke source is determined, thereby determining the cooking scenario. This allows us to determine the mapping relationship between the initial velocity and particle size parameters of the oil fume particles and the smoke source, which helps improve the accuracy of the analysis when analyzing the smoke exhaust effect of the range hood based on smoke source information.

[0050] It should be noted that the images of oil fume particles are acquired based on the plane containing the rim of the cookware as the initial surface, i.e., images of the location where the cookware emits smoke are collected. Analysis and processing of these images allows us to determine the initial velocity of the oil fume particles. Understandably, as the oil fume diffuses, its initial velocity changes. At this point, the velocity of the oil fume particles no longer accurately represents their initial velocity. Therefore, image acquisition primarily focuses on capturing images of oil fume particles along and near the rim of the cookware. Furthermore, to ensure the accuracy of the obtained particle size parameters, multiple oil fume samplers can be used to acquire these parameters.

[0051] Thus, by collecting particulate matter parameters of cooking fumes under specific cooking scenarios, the initial velocity and particle size parameters of the particulate matter are obtained. Based on the obtained initial velocity and particle size parameters, the smoke source is determined, and the cooking scenario is defined. This allows for the determination of the mapping relationship between the initial velocity and particle size parameters of the particulate matter and the smoke source. Consequently, the smoke extraction effect of the range hood under various cooking conditions can be accurately simulated based on the smoke source information.

[0052] Optionally, the processor acquires the initial velocity of the oil fume particles within the target space, including:

[0053] The processor uses particle image velocimetry to calculate the velocity field of oil fume particles within the target space, thereby obtaining the initial velocity of the oil fume particles within the target space. Alternatively,

[0054] The processor obtains the initial velocity of the oil fume particles in the target space, including:

[0055] The processor uses an image acquisition device to acquire images of oil fume particles generated in the target space; the oil fume images include multiple frames.

[0056] The processor processes the acquired oil fume images to obtain the grayscale peak distribution of the images; and calculates the time-averaged velocity field based on the grayscale peak distribution to obtain the initial velocity of oil fume particles in the target space.

[0057] Thus, there are two ways to obtain the initial velocity of oil fume particles. The first method, as described earlier, uses particle image velocimetry to calculate the velocity field of the oil fume particles in the target space to obtain their initial velocity. Specifically, tracer particles are injected into the oil fume flow field and illuminated by a laser light source. A high-speed camera then acquires images, which are analyzed to obtain the velocity field of the oil fume particles. The average velocity is then calculated based on this velocity field, thus yielding the initial velocity of the oil fume particles.

[0058] Method 2: Acquire multiple consecutive frames of oil fume images when particulate matter is generated. When the background of the oil fume experiment is black, the oil fume appears white. The acquired color oil fume images are converted to grayscale to obtain grayscale images. The shades of gray in the grayscale image represent different concentrations of oil fume. Therefore, based on the grayscale peak distribution of the images, the displacement of relevant peaks between adjacent frames can be calculated to obtain the instantaneous velocity field. Then, time averaging is performed on the instantaneous velocity field to obtain the time-averaged velocity field, thus obtaining the initial velocity of the oil fume particles in the target space. This method does not require the injection of tracer particles, making it more convenient, easier to use, and lower in cost compared to Method 1.

[0059] Optionally, the processor processes the acquired oil fume image to obtain the grayscale peak distribution of the image, including:

[0060] The processor converts the acquired oil fume images to grayscale before dividing them into grids.

[0061] The processor calculates the grayscale value of each grid cell, and the grayscale value of each grid cell is a grayscale sequence that changes over time.

[0062] The processor performs a Fourier transform on the grayscale values ​​to obtain the grayscale peak distribution of the image.

[0063] The acquired color oil fume images are processed in this way. Specifically, this includes: converting the color image (i.e., RGB image) to a grayscale image, such as using Python's OpenCV to convert an RGB image to grayscale. Discretizing the grayscale image, i.e., dividing the grayscale image into a grid. Calculating the grayscale value of each grid, such as by calculating the average value of each grid. Performing the above processing on each frame of the image, the grayscale values ​​corresponding to the same grid in consecutive frames change over time, yielding a grayscale sequence for each grid over time. Then, a Fourier transform is performed on the grayscale values, mapping them from the spatial domain to the frequency domain. The shift of the correlation peak is detected using a cross-correlation function; the distribution change of the image's grayscale peaks can be obtained through time variation. This completes the processing of the oil fume images for subsequent calculation of the initial velocity of oil fume particles.

[0064] Optionally, the processor calculates the time-averaged velocity field based on the grayscale peak distribution to obtain the initial velocity of the oil fume particles in the target space, including:

[0065] The processor obtains the instantaneous velocity field based on the displacement of the grayscale peaks of adjacent frames.

[0066] The processor calculates the average value of the instantaneous velocity field within a preset time period, obtains the time-averaged velocity field, and uses the time-averaged velocity field as the initial velocity of oil fume particles in the target space.

[0067] In this way, after obtaining the grayscale peak value of the oil fume image, the instantaneous velocity field is obtained based on the displacement of the grayscale peak values ​​of adjacent frames. Specifically, for two adjacent frames, if oil fume particles move within one or more grids, the cross-correlation function will show a peak at the point of movement (i.e., a correlation peak). The displacement of the coordinates can be determined through the correlation function, and the quotient of the displacement and the time interval is the instantaneous velocity field. The time interval is obtained based on the image frame rate. Repeating the above process for all grids yields the instantaneous velocity field for the entire image region. Then, the time-averaged velocity field is obtained by averaging the data from multiple frames within a preset time period. The preset time period should generally not be too long, and can be between 25s and 50s. Thus, by processing multiple frames within a preset time period, the time-averaged velocity field, i.e., the initial velocity of the oil fume particles, is calculated. This can counteract interference from external conditions or some image noise.

[0068] Additionally, it should be noted that for frontal and side images of cooking fumes, the instantaneous velocity field can be calculated separately. Then, the instantaneous velocity fields from the two perspectives can be combined to obtain a more accurate velocity field. Alternatively, the grayscale data from the frontal and side images of cooking fumes can be fused to generate a three-dimensional grayscale image, and the instantaneous velocity field of the three-dimensional field can be calculated.

[0069] Optionally, the processor calculates the grayscale value for each grid cell by including:

[0070] The processor maps the two-dimensional grids corresponding to the oil fume images from two perspectives at the same moment to the same three-dimensional grid.

[0071] The processor fuses gray values ​​at the same grid location in the 3D mesh to calculate the gray value of each grid.

[0072] The higher the gray value, the higher the concentration of oil fume particles.

[0073] As mentioned earlier, images of cooking fumes are captured from the front and sides of the cookware, i.e., from a first-person perspective and a second-person perspective, respectively. Both the first-person and second-person perspective images are two-dimensional images. Therefore, data from different perspectives at the same time need to be processed, i.e., the first-person and second-person perspective images are mapped onto the same three-dimensional grid. The grayscale value of each grid cell is calculated within the three-dimensional grid. The higher the concentration of cooking fumes, the larger the grayscale value. For example, in the grayscale image, 255 represents white, and 1–254 represents different shades of gray. Against a black background, cooking fumes appear white. Therefore, the higher the concentration of cooking fumes, the larger the grayscale value.

[0074] Furthermore, in some embodiments, when mapping a 2D mesh to a 3D mesh, grayscale values ​​can be fused based on viewpoint weights. As an example, the weight for the first viewpoint is 0.6, and the weight for the second viewpoint is 0.4. The weights can be set based on the reliability of the image corresponding to each viewpoint.

[0075] Optionally, the processor performs grayscale conversion on the acquired oil fume images, including:

[0076] The processor converts each pixel in the color image of cooking fumes into a grayscale value.

[0077] The processor removes non-smoke areas from the image based on a grayscale threshold to obtain the grayscale converted image.

[0078] This process converts a color image of cooking fumes into a grayscale image, where each grid cell is represented by a two-dimensional array. Each image then becomes a two-dimensional matrix. For example, if the coordinates of a grid cell in the image are (m, n), and the corresponding pixel value is f(m, n), the image can be represented as an M×N two-dimensional matrix, where M is the number of rows and N is the number of columns. After converting the image to grayscale, a grayscale threshold can be set to remove non-cooking fume areas from the image. If the grayscale value of a non-cooking fume area is small, a suitable grayscale threshold can be set to delete this area. This reduces computational load and improves processing speed.

[0079] Optionally, the processor acquires the particle size parameters of the oil fume particles in the target space, including:

[0080] The processor acquires the particle size distribution and particle size percentage of oil fume particles at multiple locations within the target space.

[0081] The processor calculates the average values ​​of particle size distribution and particle size percentage, and uses the average values ​​of particle size distribution and particle size percentage as the particle size parameters of oil fume particles.

[0082] To improve the accuracy of data collection, multiple oil fume samplers were set up within the target space to collect particulate matter size parameters from different locations. Specifically, particle size distribution data was collected, and the proportion of each particle size segment was calculated based on this data. This process was repeated for the data collected at each location, and then the average value of the particle size distribution and proportion from multiple locations was calculated. As an example, oil fume particles with a diameter range of 0.03–9.990 μm were collected and divided into several segments: 0.03–0.063, 0.063–0.109, 0.109–0.173, 0.173–0.267, 0.267–0.407, 0.407–0.655, 0.655–1.021, 1.021–1.655, 1.655–2.520, 2.250–4.085, 4.085–6.560, and 6.560–9.990. The proportion of particle size in each of these segments was statistically analyzed to obtain the particle size parameters of the oil fume particles.

[0083] Optionally, based on particle size distribution, the proportion of PM1.0 (particle size ≤ 1.0 μm) and PM2.5 (particle size ≤ 2.5 μm) particles can be statistically analyzed. The proportion of these two types of particles can characterize the smoke source.

[0084] Optionally, the processor determines the mapping relationship between the initial velocity and particle size parameters of the oil fume particles and the smoke source, including:

[0085] The processor acquires the initial velocity and particle size parameters of the oil fume particles in the target space.

[0086] When the initial velocity meets the first velocity condition and the particle size parameter meets the first particle size condition, the processor determines the smoke source in the target space as the first smoke source.

[0087] If the initial velocity meets the second velocity condition and the particle size parameter meets the second particle size condition, the processor determines the smoke source in the target space as the second smoke source.

[0088] Thus, based on initial velocity and particle size parameters, the corresponding smoke sources are determined. These sources primarily include two types: stir-frying and frying. Specifically, the particle size distribution in the stir-fry smoke source information is significantly higher than that in the frying smoke source, and the initial velocity of the stir-fry fumes is also significantly higher. Therefore, velocity and particle size conditions are set to distinguish between these two smoke sources. The velocity condition includes a velocity threshold, and the particle size condition includes particle size percentage thresholds for PM1.0 and PM2.5 particles. As an example, the first particle size condition includes a PM2.5 particle size percentage greater than or equal to 90% and a PM1.0 particle size percentage greater than or equal to 80%. The second particle size condition includes a PM2.5 particle size percentage greater than or equal to 85%, and a PM1.0 particle size percentage range of (68%, 80%). The first velocity condition is greater than or equal to 0.8 m / s, and the second velocity condition has a velocity range of (0.5 m / s, 0.8 m / s). In this way, the smoke source can be determined based on set conditions. Simultaneously, the corresponding smoke source information can be obtained. Therefore, based on accurate smoke source information, the smoke extraction effect of the range hood under various cooking conditions can be simulated, improving the accuracy of effect evaluation.

[0089] Furthermore, smoke sources can also include stewing and simmering types, where the initial velocity and particle size parameters of oil fume particles are much smaller than those in stir-frying and deep-frying scenarios. A third velocity condition and a third particle size condition can be set to determine the smoke source within the target space as a third smoke source.

[0090] Based on the previously established correspondence between the target smoke source and the particulate matter parameters of cooking fumes, combined with... Figure 1 As shown in the embodiments of this disclosure, a method for analyzing the smoke extraction effect of a range hood is provided, comprising:

[0091] S101, the processor determines the target smoke source to obtain the corresponding oil fume particulate matter parameters and cooking temperature parameters.

[0092] S102, the processor inputs the particulate matter parameters of the oil fume and the cooking temperature parameters into the target simulation model to simulate the smoke extraction effect and obtain the evaluation results of the smoke extraction effect of the range hood.

[0093] Here, analyzing the smoke extraction effect of a range hood requires first defining the cooking scenario to identify the target smoke source. The smoke sources generated under different cooking scenarios vary, affecting the accuracy of the parameter input for the target simulation model. Therefore, identifying the target smoke source allows us to obtain the corresponding particulate matter parameters and cooking temperature parameters. The correspondence between the target smoke source and the particulate matter parameters is detailed above. The correspondence between the target smoke source and the cooking temperature parameters is obtained experimentally. For example, under the target cooking scenario, the temperatures of the cookware and heat source are measured. The mapping relationship between the target smoke source and the cooking temperature parameters is saved and retrieved when needed.

[0094] This process involves obtaining the initial velocity and particle size parameters of the oil fume particles, as well as the temperatures of the cookware and stove, based on the target smoke source. For example, when the target smoke source is the primary smoke source, the initial velocity can be set to 1 m / s, and the cookware temperature can range from 20℃ to 350℃. This allows for the acquisition of accurate parameters that truly reflect the actual environment, resulting in accurate and reasonable data.

[0095] The parameters of oil fume particulate matter and cooking temperature are input into the target simulation model to obtain simulation results. The simulation results are then calculated and statistically analyzed to obtain the range hood's smoke extraction evaluation results. The evaluation of the range hood's smoke extraction effect is primarily based on its oil fume particulate matter capture efficiency. The target simulation model includes a fluid dynamics model and a discrete model, etc. The fluid dynamics model simulates the oil fume flow field, while the discrete model performs calculations. The parameters input into the target simulation model include not only oil fume particulate matter parameters and cooking temperature parameters, but also other factors affecting oil fume diffusion, such as airflow parameters and range hood parameters (e.g., range hood model, installation location, etc.), and operating parameters. This makes the simulation more closely resemble the actual scenario. It should be noted that the embodiments of this disclosure can analyze the smoke extraction effect of various range hoods under various operating parameters.

[0096] The method for analyzing the smoke extraction effect of a range hood, as provided in this disclosure, determines the corresponding particulate matter parameters based on the target smoke source, which helps improve the accuracy of these parameters under the target cooking scenario. Simultaneously, the cooking temperature parameter is introduced, as it affects the distribution of particulate matter, smoke generation rate, and thus the changes in the smoke flow field, consequently influencing the simulation results. This makes the input parameters closer to the actual cooking scenario, contributing to improved simulation accuracy. Consequently, a more accurate evaluation of the range hood's smoke extraction effect is obtained, which is helpful for optimizing range hood performance.

[0097] Optionally, in step S101, the parameters of oil fume particulate matter include the initial velocity, particle size distribution, and particle size ratio of the oil fume particulate matter.

[0098] Among them, the parameters of oil fume particulate matter and the target smoke source have a mapping relationship.

[0099] Here, there is a correspondence between the parameters of oil fume particulate matter and the target smoke source. The parameters of oil fume particulate matter include the initial velocity, particle size distribution, and particle size percentage of the oil fume particles. Specifically, the target smoke source is either a first smoke source or a second smoke source. The first smoke source is the smoke source corresponding to the stir-frying scenario, and the second smoke source is the smoke source corresponding to the stir-frying scenario. The initial velocity corresponding to the first smoke source is greater than the initial velocity corresponding to the second smoke source; and within the same particle size range, the particle size percentage of the first smoke source is greater than that of the second smoke source. The particle size range includes one or more particle size distributions. For example, the particle size range is the particle size range of PM2.5 particles.

[0100] Optionally, in step S101, the cooking temperature parameters include the stove temperature and the pot temperature;

[0101] The cookware temperature includes the inner and outer surface temperatures of the cookware, and both the inner and outer surface temperatures include multiple annular temperature zones centered on the center of the cookware, with each annular temperature zone corresponding to a specific temperature.

[0102] Here, cooking temperature parameters include stove temperature and cookware temperature. Stove temperature refers to the combustion temperature of combustibles on the stove, while cookware temperature includes the inner and outer surface temperatures of the cookware. Cookware temperature comprises multiple annular temperature zones centered on the center of the cookware (see [link to relevant documentation]). Figure 2 The temperature of the annular temperature zone closer to the center is higher. Generally, the temperature of the outer surface of the cookware is slightly higher than that of the inner surface. Furthermore, the cookware temperature is related to the stove temperature. The more annular temperature zones there are, the more accurate the cookware temperature readings will be. Thus, by simulating the impact of combustion on the generation and diffusion of particulate matter during cooking using cookware and stove temperatures, the simulation more closely resembles the actual cooking process.

[0103] In addition, cookware temperature can be obtained through experimental testing. Specifically, the cookware is heated using a stove, and during the heating process, one or more thermocouples are used to measure the temperature at various locations on the inner and outer surfaces of the cookware. This allows for the acquisition of temperature distribution information on the inner and outer surfaces of the cookware. The annular temperature region may also include only one area.

[0104] Combination Figure 3 As shown in the embodiments of this disclosure, a method for analyzing the smoke extraction effect of a range hood is provided, comprising:

[0105] S101, the processor determines the target smoke source to obtain the particulate matter parameters and cooking temperature parameters of the target smoke source.

[0106] S203, the processor builds a kitchen model and imports the built kitchen model into the target simulation model to simulate the flow field of cooking fumes.

[0107] S204, the processor uses a static mesh to divide the oil fume flow field into a mesh.

[0108] S102, the processor inputs the parameters of oil fume particles and cooking temperature parameters into the target simulation model to simulate the smoke extraction effect and obtain the evaluation results of the smoke extraction effect of the range hood.

[0109] Here, a kitchen model is established and imported into the target simulation model to simulate the oil fume flow field. In existing technologies, the simulation of the oil fume flow field is based on the range hood area; however, the kitchen space has a certain influence on the oil fume flow field. To improve the accuracy of the oil fume flow field simulation, a kitchen model is established, including the size of the kitchen space, the placement of doors and windows, and the placement information of range hoods, stoves, etc. After importing the kitchen model into the target simulation model, the geometric boundaries of the fluid domain (air region) and solid domain (such as range hoods, stoves, etc.) in the oil fume flow field can be determined. Then, a static mesh can be used to mesh the oil fume flow field, that is, to discretize the continuous geometric space. Thus, after inputting parameters into the model, the flow field characteristics can be analyzed using the mesh elements. Optionally, the kitchen model is a standard kitchen model with dimensions of 3.5m * 2.5m * 2.5m. However, in this embodiment, the kitchen model size is not limited to this and can be set according to requirements.

[0110] In this embodiment of the disclosure, static meshing is preferably used for mesh generation, which can accurately capture the details of the oil fume flow field, simplify model setup, and avoid numerical dispersion problems. In some embodiments, dynamic meshing can also be used for mesh generation.

[0111] Optionally, in step S102, the processor inputs the particulate matter parameters and cooking temperature parameters into the target simulation model to simulate the smoke extraction effect and obtain the evaluation results of the range hood's smoke extraction effect, including:

[0112] S121, the processor inputs the particulate matter parameters of cooking fumes and the cooking temperature parameters into the discrete model.

[0113] S122, The processor sets and initializes the boundary conditions of the discrete model to calculate the simulated oil fume flow field.

[0114] S123, the processor calculates the collection efficiency of oil fume particles after the simulated oil fume flow field converges.

[0115] Here, the target simulation model includes a fluid dynamics model and a discrete model. Input parameters mainly refer to the input parameters of the discrete model, including parameters related to oil fume particles and cooking temperature. The oil fume particle parameters include not only the initial velocity, particle size distribution, and particle size distribution mentioned above, but also parameters such as the composition of oil fume particles. After inputting the parameters into the discrete model, boundary conditions are set and initialized to calculate the simulated oil fume flow field. After the oil fume flow field converges, the oil fume particle data is statistically analyzed to calculate the oil fume particle capture efficiency. This ensures data accuracy, obtains a stable flow field, and avoids errors in calculating the capture efficiency. Thus, by controlling the model parameters and boundary conditions, the reliability of the range hood effect simulation is ensured.

[0116] It should be noted that the input parameters of the discrete model also include the operating parameters of the range hood and other parameters. Furthermore, when calculating the simulated oil fume flow field, an appropriate calculation model or equation can be selected to improve computational efficiency and accuracy. For example, energy equations, thermal radiation models, and turbulence models can be used for calculation.

[0117] Optionally, in step S121, the processor inputs the particulate matter parameters of the oil fume into the discrete model, including:

[0118] The processor sets the composition of oil fume particles as heavy oil particles and the particle source as a surface jet source.

[0119] The processor fits the mass distribution of each quantity concentration corresponding to the particle size range of the oil fume particles to obtain the average particle size and distribution coefficient of the oil fume particles.

[0120] The processor inputs the average particle size and distribution coefficient of the oil fume particles into the discrete model.

[0121] Here, the particulate matter composition of cooking fumes consists of heavy oil particles, and the particle source is a surface jet source. Simultaneously, the number concentrations of each particle size range are calculated based on the particle size distribution and particle size distribution ratio. Specifically, the cooking fume particulate matter data is fitted to a Rosin-Rammler distribution, and the fitting calculations... Characteristic particle size for obtaining number concentration distribution And the distribution index n. Where Y(-) is the cumulative distribution function, and ds is the particle size. The total number of smoke-generating particles is a set value. After the total number of smoke-generating particles is determined, the mass fraction corresponding to each particle size can be calculated based on the data concentration corresponding to each particle size range. Then, based on the mass fraction and the median particle size (the median particle size is calculated based on the upper and lower limits of each particle size range), the mass-average particle size is calculated. For example, the mass-average particle size of oil fume particles is 2.83 μm, and the distribution index is 2.35. Figure 5The figure shows the relationship between the particle size distribution and mass fraction of oil fume particles. In the figure, ds represents the particle size and Y represents the mass fraction.

[0122] Furthermore, inputting oil fume particulate matter parameters and cooking temperature parameters into the discrete model also includes inputting initial velocity values, particle size parameters, and cookware temperature. For example, when the target smoke source is the first smoke source, the initial velocity of the oil fume particles is 0.8 m / s, the proportion of PM2.5 particles is greater than or equal to 90%, and the proportion of PM1.0 particles is greater than or equal to 80%. The cookware temperature range is [100℃, 600℃]. When the target smoke source is the second smoke source, the initial velocity of the oil fume particles is 0.5 m / s, the proportion of PM2.5 particles is greater than or equal to 85%, and the proportion of PM1.0 particles is greater than or equal to 70%. The cookware temperature range is [100℃, 450℃]. Thus, determining the simulation input parameters based on the target smoke source can improve the accuracy of the model simulation.

[0123] Optionally, in S122, the processor sets the boundary conditions for the discrete model, including:

[0124] The processor sets the range hood outlet as the pressure outlet boundary, the door and window positions in the kitchen model as the pressure inlet boundary, the walls of the kitchen model as non-slip insulated walls, and the gas outlet interface as the velocity inlet boundary.

[0125] Here, the boundary conditions include pressure inlet / outlet, wall boundary, and velocity inlet boundary. Specifically, the range hood outlet is the pressure outlet boundary, which can simulate the distribution of oil fumes when the range hood is off. The kitchen door and window locations are pressure inlet boundaries, and the doors and windows are in the open state. The walls of the kitchen model and the stove are non-slip wall boundaries, where the walls of the kitchen model are non-slip adiabatic wall boundaries. The gas outlet interface is the velocity inlet interface; when a single burner is working, the gas outlet of that single burner is set as the velocity inlet boundary. Then, the above boundary conditions are initialized. For example, the gas outlet velocity range is [0m / s~1m / s], and the gas temperature range is [100℃~600℃], etc.

[0126] Optionally, in step S123, the processor calculates the collection efficiency of oil fume particles after the simulated oil fume flow field converges, including:

[0127] The processor counts the particulate matter from the primary and secondary capture of cooking fumes.

[0128] The processor calculates the primary capture efficiency and the secondary capture efficiency based on the primary capture and secondary capture of oil fume particles.

[0129] The processor uses the sum of the primary and secondary capture efficiencies as the capture efficiency of oil fume particles.

[0130] Here, primary and secondary capture of oil fume particles refer to the number of oil fume particles captured on the capture surface at different time intervals. Then, based on the total number of primary and secondary capture oil fume particles and the total number of smoke-generating particles, the primary capture rate and secondary capture efficiency can be calculated. The sum of the two capture rates is the oil fume particle capture efficiency. Specifically, by statistically analyzing the residence time x corresponding to the peak of the normal distribution of the number of particles on the capture surface, the minimum residence time s, and the maximum residence time m, particles within the residence time interval [s, 2x-s] are primary capture particles, and particles within the residence time interval [2x-s, m] are secondary capture particles. Thus, the oil fume particle capture efficiency is obtained to evaluate the smoke extraction effect of the range hood. Understandably, the higher the capture efficiency, the better the smoke extraction effect of the range hood. Furthermore, the capture surface of the range hood includes key areas or components that actively capture and intercept oil fumes during operation, such as the oil filter, centrifugal device, and baffle plate.

[0131] In addition, after calculating the collection efficiency of oil fume particles, the following is also included:

[0132] The processor stores the correspondence between the particulate matter collection efficiency and the range hood parameters and operating parameters. Preferably, when the range hood parameters are the same, it stores the correspondence between the highest particulate matter collection efficiency and the range hood operating parameters. In this way, during the application of the range hood, the operating parameters can be controlled based on the stored relationship to achieve better smoke extraction effect.

[0133] Combination Figure 6 As shown, the range hood includes a range hood body 20. An oil filter 202 is disposed below the range hood body 20. A smoke baffle 201 is disposed on the range hood body 20 near its outer edge. When the range hood 100 is closed, the smoke baffle 201 covers the lower surface of the oil filter 202. After the range hood is started, the smoke baffle 201 can rotate counterclockwise.

[0134] Based on the above-described structural configuration of the range hood and the above-described method for analyzing the smoke extraction effect of the range hood, combined with Figure 7 As shown, this disclosure provides a control method for a range hood, including:

[0135] S301: After the range hood is started, it obtains user attributes and the operating parameters of the range hood corresponding to the best smoke extraction effect.

[0136] In this step, user attributes include user sensitivity types. Range hood operating parameters include fan parameters or baffle rotation angle. Fan parameters include fan speed or fan airflow. Combined with... Figure 6As shown, the rotation angle of the smoke baffle represents the angle of the smoke baffle 201 relative to the reference plane when it rotates, with the plane where the oil mesh 202 is located as the reference plane.

[0137] S302, the range hood adjusts its operating parameters according to user attributes.

[0138] The control method for a range hood provided in this disclosure allows the range hood to obtain user attributes and operating parameters corresponding to the optimal smoke extraction effect after startup, and then adjust these parameters based on the user attributes. This disclosure combines the user's needs for the cooking environment with the operating parameters corresponding to the optimal smoke extraction effect to regulate the range hood. Compared to simply adjusting the range hood speed manually by the user, this method improves the control effect, satisfying the user's needs for the cooking environment while maintaining effective smoke extraction.

[0139] Optionally, the range hood adjusts its operating parameters based on user attributes, including:

[0140] When the user's sensitivity type indicates a noise-sensitive type, the range hood reduces its fan parameters.

[0141] When the user's sensitivity type indicates sensitivity to cooking fumes, the range hood's fan parameters are increased.

[0142] Thus, when the user's sensitivity type indicates noise sensitivity, it means the user is highly sensitive to fan noise. In this case, it is not advisable to output excessively high fan parameters to users with noise sensitivity. Therefore, when the user's sensitivity type is determined to be noise sensitivity, this embodiment of the disclosure lowers the fan parameters. When the user's sensitivity type indicates oil fume sensitivity, it means the user is highly sensitive to oil fumes, and the fan parameters need to be further increased based on the original fan parameters to quickly remove cooking fumes in a short time. In this way, in a cooking scenario, this embodiment of the disclosure can dynamically adjust the range hood fan parameters based on the user's own sensitivity to fan noise or oil fumes and the range hood operating parameters corresponding to the optimal smoke extraction effect. The range hood's adjustment effect is improved, meeting the user's needs for the cooking environment while taking into account the smoke extraction effect.

[0143] Optionally, the range hood obtains user-sensitive types in the following ways:

[0144] The range hood receives fan control commands sent by the user during its historical operation. These commands are used to instruct users to update historical fan parameters.

[0145] When the fan control command indicates a reduction in historical fan parameters, the range hood identifies the user as a noise-sensitive user.

[0146] When the fan control command indicates an increase in historical fan parameters, the range hood identifies the user as someone sensitive to cooking fumes.

[0147] Thus, the embodiments of this disclosure can determine the user's sensitivity type based on the user's operating habits of the fan during the historical operation of the range hood, ensuring the accuracy of the user sensitivity type determination, thereby providing data support for the subsequent personalized fan control of the range hood.

[0148] Optionally, combined Figure 8 As shown, user attributes also include the user's line-of-sight obstruction status. Based on these user attributes, the range hood adjusts its operating parameters, including:

[0149] S401, when the user's sensitivity type indicates a noise-sensitive type, the range hood reduces the fan parameters.

[0150] S402, when the user's sensitivity type indicates that the range hood is sensitive to oil fumes, the range hood's fan parameters are increased.

[0151] S403, after increasing the fan parameters of the range hood, and assuming the user's line of sight is obstructed (i.e., the baffle plate obstructs the view), the correlation between the change in the rotation angle of the baffle plate and the change in the fan parameters is obtained. It should be noted that the correlation between the change in the rotation angle of the baffle plate and the change in the fan parameters can be obtained based on the method described above for analyzing the smoke extraction effect of the range hood.

[0152] S404, the range hood determines the target change in fan parameters corresponding to the decrease in the rotation angle of the smoke baffle based on the correspondence between the change in the rotation angle of the smoke baffle and the change in the fan parameters.

[0153] In this step, the relationship between the change in the rotation angle of the smoke baffle and the change in the fan parameters can be obtained using the method described above for analyzing the smoke extraction effect of a range hood. As an example, the change in the rotation angle of the smoke baffle is -1°, and the change in the fan parameters is xm. 3 / min (square meters per minute). The change in the smoke baffle's rotation angle is α. When α is greater than zero, it indicates that the smoke baffle's rotation angle increases by α. When α is less than zero, it indicates that the smoke baffle's rotation angle decreases by |α|. The unit of α is degrees, and the symbol is °.

[0154] S405, the range hood compensates for the airflow of the adjusted fan parameters based on the change in the target fan parameters, in order to enhance the smoke extraction intensity by increasing the fan parameters.

[0155] Thus, after the smoke baffle rotates, the adjusted fan parameters will weaken the range hood's smoke extraction effect before the baffle rotates. The sacrificed smoke extraction effect after the baffle rotates can be compensated for by increasing the fan parameters. However, increasing the fan parameters can also result in the rotated baffle obstructing the user's view. Therefore, this embodiment first determines whether the baffle obstructs the user's view after increasing the fan parameters. If it does, the correspondence between the change in the baffle rotation angle and the change in fan parameters is obtained. Then, based on this correspondence, the target fan parameter change corresponding to the reduction in the baffle rotation angle is determined, and the adjusted fan parameters are compensated for based on this target fan parameter change to enhance smoke extraction intensity. In this way, this embodiment can adjust the range hood fan parameters based on the real-time needs of smoke-sensitive users and the optimal smoke extraction parameters, improving the accuracy of range hood control while maintaining smoke extraction effectiveness.

[0156] It should be noted that adjusting the operating parameters of the range hood based on user attributes also includes: when the user's sensitivity type indicates noise sensitivity, the range hood reduces the fan parameters but maintains the adjusted fan parameters unchanged. Thus, based on the above method for analyzing the smoke extraction effect of the range hood, simulation tests show that for every 1-2 m³ / h increase in fan airflow... 3 The fan noise will increase by 1-2 dB or more per minute. To avoid discomfort for noise-sensitive users due to increased fan parameters, the adjusted fan parameters will be maintained and no airflow compensation will be performed when the user's sensitivity type is indicated as noise-sensitive.

[0157] Optionally, combined Figure 9 As shown, user attributes also include the user's line-of-sight obstruction status. Based on these user attributes, the range hood adjusts its operating parameters, including:

[0158] S501, the range hood controls the rotation of the baffle plate according to the target baffle plate rotation angle. The target baffle plate rotation angle is determined by the correlation between the oil fume particulate matter capture efficiency and the baffle plate rotation angle.

[0159] S502, the range hood achieves a state of obstruction of the user's view after the smoke baffle has finished rotating.

[0160] S503, when the user's line of sight is obstructed, indicating that the smoke baffle constitutes a line of sight obstruction, the range hood controls the smoke baffle to reduce the rotation angle of the target smoke baffle, and after reducing the rotation angle of the target smoke baffle, it compensates the fan parameters for airflow, so as to enhance the smoke extraction intensity by increasing the fan parameters.

[0161] In this way, since the reduced smoke extraction effect of the range hood after the smoke baffle rotates can be compensated for by increasing the fan parameters, and since the smoke baffle may obstruct the user's view after rotation, this embodiment of the disclosure obtains the user's view obstruction status after the smoke baffle finishes rotating. If the user's view obstruction status indicates that the smoke baffle is obstructing the view, the target smoke baffle rotation angle is reduced, and after reducing the target smoke baffle rotation angle, the fan parameters are adjusted to compensate for the airflow, thereby increasing the smoke extraction intensity. Thus, this embodiment of the disclosure can comprehensively adjust the range hood fan parameters by considering both the optimal smoke extraction effect corresponding to the smoke baffle rotation angle and the user's real-time needs for the cooking environment, optimizing the smoke extraction effect of the range hood during cooking while achieving personalized control of the range hood fan.

[0162] Optionally, the range hood determines the rotation angle of the target smoke baffle in the following ways:

[0163] The relationship between the efficiency of a range hood in capturing particulate matter from cooking fumes and the rotation angle of the baffle plate.

[0164] The range hood determines the target baffle rotation angle corresponding to the optimal particulate matter collection efficiency based on the correlation between the particulate matter collection efficiency and the baffle rotation angle. It should be noted that the correlation between the particulate matter collection efficiency and the baffle rotation angle can be obtained based on the method described above for analyzing the range hood's smoke extraction effect.

[0165] Thus, after obtaining the correspondence between the capture efficiency and the rotation angle of the smoke baffle in this embodiment of the present disclosure, the target rotation angle of the smoke baffle corresponding to the optimal oil fume particulate matter capture efficiency is determined according to the correspondence. After the range hood is started, the smoke baffle is controlled to rotate to the smoke baffle rotation angle that achieves the optimal oil fume particulate matter capture efficiency, thereby maximizing the smoke extraction effect of the range hood during cooking.

[0166] Optionally, the range hood obtains the user's line-of-sight obstruction status in the following manner:

[0167] The range hood receives a smoke baffle update command from the user, and if the command instructs the user to reduce the smoke baffle rotation angle, it determines that the smoke baffle is obstructing the user's view. Alternatively,

[0168] The range hood obtains the initial rotation angle of the baffle before it rotates and the baffle control command sent by the user during the historical operation of the range hood based on the initial baffle rotation angle. When the baffle control command indicates that the initial baffle rotation angle should be reduced, the range hood determines that the user's line of sight is obstructed by the baffle.

[0169] In this way, the embodiments of this disclosure can determine whether the smoke baffle constitutes a visual obstruction based on the user's adjustment needs for the smoke baffle in actual cooking scenarios, or based on the user's adjustment habits of the smoke baffle angle in historical cooking scenarios, thereby knowing the user's needs for the cooking environment, so as to meet the user's needs for the cooking environment through the adjustment of the range hood.

[0170] Combination Figure 10 As shown, this disclosure provides a control device 70 for a range hood, including a processor 700 and a memory 701. Optionally, the device 70 may further include a communication interface 702 and a bus 703. The processor 700, communication interface 702, and memory 701 can communicate with each other via the bus 703. The communication interface 702 can be used for information transmission. The processor 700 can call logical instructions in the memory 701 to execute the control method for the range hood described in the above embodiment.

[0171] Furthermore, the logic instructions in the aforementioned memory 701 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium.

[0172] The memory 701, as a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as program instructions / modules corresponding to the methods in the embodiments of this disclosure. The processor 700 executes functional applications and data processing by running the program instructions / modules stored in the memory 701, thereby implementing the control method for the range hood described above.

[0173] The memory 701 may include a program storage area and a data storage area. The program storage area may store the operating system and application programs required for at least one function; the data storage area may store data created based on the use of the terminal device. Furthermore, the memory 701 may include high-speed random access memory and may also include non-volatile memory.

[0174] Combination Figure 11As shown, this disclosure provides a range hood 100, including a range hood body and the aforementioned control device 70 for the range hood. The control device 70 is installed on the range hood body. The installation relationship described herein is not limited to placement inside the range hood body, but also includes installation connections with other components of the range hood 100, including but not limited to physical connections, electrical connections, or signal transmission connections. Those skilled in the art will understand that the control device 70 for the range hood can be adapted to any feasible range hood body, thereby realizing other feasible embodiments.

[0175] This disclosure provides a computer-readable storage medium storing computer-executable instructions configured to perform the above-described control method for a range hood.

[0176] The technical solutions of this disclosure can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in this disclosure. The aforementioned storage medium can be a non-transitory storage medium, such as a USB flash drive, external hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, etc., and other media capable of storing program code.

[0177] The foregoing description and accompanying drawings fully illustrate embodiments of this disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or” as used in this application means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0178] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0179] The methods and products (including but not limited to devices and equipment) disclosed in the embodiments herein can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed units may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to implement this embodiment according to actual needs. Furthermore, the functional units in the embodiments of this disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

Claims

1. A control method for a range hood, characterized in that, include: After the range hood is started, user attributes and the range hood operating parameters corresponding to the best smoke extraction effect are obtained; Adjust the range hood's operating parameters based on user attributes.

2. The method according to claim 1, characterized in that, User attributes include user sensitivity types, and range hood operating parameters include fan parameters. Based on user attributes, the range hood operating parameters are adjusted, including: If the user's sensitivity type indicates noise sensitivity, reduce the fan parameters; If the user's sensitivity type indicates sensitivity to cooking fumes, increase the fan parameters.

3. The method according to claim 2, characterized in that, Obtain user sensitive types in the following ways: Receive fan control commands sent by the user during the historical operation phase of the range hood; among which, the fan control commands are used to instruct the updating of historical fan parameters; When the fan control command indicates a reduction in historical fan parameters, the user is identified as a noise-sensitive user. When the fan control command indicates an increase in historical fan parameters, the user is identified as a user sensitive to oil fumes.

4. The method according to claim 2, characterized in that, User attributes also include the user's line-of-sight obstruction status. Based on these user attributes, the range hood's operating parameters are adjusted. Other attributes include: After increasing the fan parameters, under the condition that the smoke baffle obstructs the user's view, the relationship between the change in the rotation angle of the smoke baffle and the change in the fan parameters is obtained. Based on the correspondence between the change in the rotation angle of the smoke baffle and the change in the fan parameters, determine the target change in fan parameters corresponding to the reduction in the rotation angle of the smoke baffle. Based on the change in the target fan parameters, the adjusted fan parameters are compensated for the air volume, so as to enhance the fume extraction intensity by increasing the fan parameters.

5. The method according to claim 1, characterized in that, User attributes include the user's line-of-sight obstruction status; range hood operating parameters include fan parameters and baffle rotation angle. Based on user attributes, the range hood operating parameters are adjusted, including: The rotation of the smoke baffle is controlled according to the target smoke baffle rotation angle; wherein, the target smoke baffle rotation angle is determined by the correspondence between the oil fume particulate matter capture efficiency and the smoke baffle rotation angle; After the smoke baffle finishes rotating, the user's line of sight is obstructed. When the user's line of sight is obstructed, indicating that the smoke baffle is obstructing the view, the smoke baffle is controlled to reduce the rotation angle of the target smoke baffle. After reducing the rotation angle of the target smoke baffle, the fan parameters are compensated for the air volume, so as to enhance the smoke extraction intensity by increasing the fan parameters.

6. The method according to claim 5, characterized in that, Determine the rotation angle of the target smoke baffle as follows: The relationship between the oil fume particulate matter capture efficiency and the rotation angle of the smoke baffle was obtained; Based on the correlation between the oil fume particulate matter collection efficiency and the rotation angle of the smoke baffle, the target rotation angle of the smoke baffle corresponding to the optimal oil fume particulate matter collection efficiency is determined.

7. The method according to claim 4 or 5, characterized in that, The user's line-of-sight occlusion status is obtained in the following ways: Upon receiving a smoke baffle update command from the user, and if the smoke baffle update command instructs the user to reduce the smoke baffle rotation angle, the system determines that the user's line of sight is obstructed by the smoke baffle; or... The system obtains the initial rotation angle of the smoke baffle before it rotates and the smoke baffle control command sent by the user during the historical operation of the range hood based on the initial rotation angle. When the smoke baffle control command indicates that the initial rotation angle of the smoke baffle should be reduced, the system determines that the user's line of sight is obstructed by the smoke baffle.

8. A control device for a range hood, comprising a processor and a memory storing program instructions, characterized in that, The processor is configured to execute the control method for a range hood as described in any one of claims 1 to 7 when running the program instructions.

9. A range hood, characterized in that, include: The range hood itself; The control device for a range hood as described in claim 8 is installed on the range hood body.

10. A computer-readable storage medium storing program instructions, characterized in that, When the program instructions are executed, they cause the computer to perform the control method for a range hood as described in any one of claims 1 to 7.

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