A method and system for evaluating the smoke extraction effect of a range hood

Abstract

This invention provides a method and system for evaluating the smoke extraction effect of a range hood, relating to the technical field of equipment detection. The method includes: after the range hood starts operating, acquiring a target image set, wherein the target image set includes instantaneous images captured by a camera within a preset time period and under conditions free from stray light interference at a preset frequency; the instantaneous images are images captured when a parallel light source of preset thickness and wavelength illuminates the oil fume thermal plume generated by the smoke-generating device; converting the instantaneous images into grayscale images; processing the grayscale images using an image averaging algorithm and an image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume; and determining the smoke extraction effect of the range hood based on the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume, thus solving the technical problem of poor accuracy in existing range hood smoke extraction effect evaluation results.

Description

Technical Field

[0001] This invention relates to the technical field of equipment testing, and in particular to a method and system for evaluating the smoke extraction effect of a range hood. Background Technology

[0002] Existing range hood smoke extraction effectiveness testing devices primarily measure grease separation and odor reduction. These two indicators are commonly used to evaluate the smoke extraction effect of range hoods. Grease separation focuses on evaluating the range hood's grease filtering effect, while odor reduction focuses on evaluating its ventilation capacity. Neither of these indicators reflects the range hood's ability to capture and extract the hot plumes of cooking fumes from the stovetop during operation, thus failing to accurately analyze the smoke extraction effect. Furthermore, current methods for determining whether fumes have escaped rely mainly on visual inspection, which is subject to significant background interference and large errors.

[0003] No effective solutions have yet been proposed to address the above problems. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a method and system for evaluating the smoke extraction effect of a range hood, so as to alleviate the technical problem of poor accuracy of existing range hood smoke extraction effect evaluation results.

[0005] In a first aspect, embodiments of the present invention provide a method for evaluating the smoke extraction effect of a range hood, comprising: after the range hood starts working, acquiring a target image set, wherein the target image set includes instantaneous images captured by a camera device at a preset frequency within a preset time period and under conditions free from stray light interference, the instantaneous images being images captured when a parallel light source of preset thickness and preset wavelength illuminates the oil fume thermal plume generated by the smoke-generating device; converting the instantaneous images into grayscale images; processing the grayscale images using an image averaging algorithm and an image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution of the oil fume thermal plume and the oil fume boundary distribution map of the oil fume thermal plume; and determining the smoke extraction effect of the range hood based on the probability density map of the oil fume concentration distribution of the oil fume thermal plume and the oil fume boundary distribution map of the oil fume thermal plume.

[0006] Furthermore, based on the probability density map of the oil fume concentration distribution and the boundary distribution map of the oil fume thermal plume, the smoke extraction effect of the range hood is determined, including: based on the probability density map of the oil fume concentration distribution, determining the contour lines of the oil fume concentration distribution of the oil fume thermal plume, and determining a first distance between the contour lines and the smoke inlet of the range hood; and based on the boundary distribution map of the oil fume thermal plume, determining the oil fume pulsation boundary of the oil fume thermal plume, and determining a second distance between the oil fume pulsation boundary and the smoke inlet of the range hood; wherein, the smaller the first distance and the second distance, the better the smoke extraction effect of the range hood.

[0007] Further, the grayscale image is processed using an image averaging algorithm and an image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume. This includes: constructing a grayscale matrix based on the grayscale image; and processing the grayscale matrix using the image averaging algorithm and the image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume.

[0008] Further, the grayscale matrix is ​​processed using the image averaging algorithm and the image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume. This includes: determining the average image matrix corresponding to the target image set based on the image averaging algorithm and the grayscale matrix; determining the standard deviation image matrix corresponding to the target image set based on the image standard deviation algorithm and the average image matrix; determining the probability density map of the oil fume concentration distribution of the oil fume thermal plume based on the average image matrix; and determining the oil fume boundary distribution map of the oil fume thermal plume based on the standard deviation image matrix.

[0009] Secondly, embodiments of the present invention also provide a system for evaluating the smoke extraction effect of a range hood, comprising: a smoke generating device, a light source assembly, a camera device, and a processor, wherein the smoke generating device is disposed below the range hood, the light source assembly is disposed on the side of the smoke generating device, and the camera device is disposed in front of the smoke generating device; the smoke generating device is used to generate a hot plume of oil fumes; the light source assembly is used to generate a parallel light source of preset thickness and preset wavelength after the range hood starts working, and to irradiate the hot plume of oil fumes; the camera device is used to capture a target image set, wherein the target image set includes images captured by the camera device within a preset time period and without stray light interference. The processor captures instantaneous images at a preset frequency under a specific environment. These instantaneous images are taken when the oil fume plume is illuminated by a parallel light source of preset thickness and wavelength. The processor acquires a target image set and converts the instantaneous images into grayscale images. The processor processes the grayscale images using an image averaging algorithm and an image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume plume. Based on the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume plume, the processor determines the smoke extraction effect of the range hood.

[0010] Further, the processor is configured to: determine the contour lines of the oil fume concentration distribution probability density of the oil fume thermal plume based on the oil fume concentration distribution probability density map of the oil fume thermal plume, and determine a first distance between the contour lines and the smoke inlet of the range hood; determine the oil fume pulsation boundary of the oil fume thermal plume based on the oil fume boundary distribution map of the oil fume thermal plume, and determine a second distance between the oil fume pulsation boundary and the smoke inlet of the range hood; wherein, the smaller the first distance and the second distance, the better the smoke extraction effect of the range hood.

[0011] Further, the processor is configured to: process the grayscale image using an image averaging algorithm and an image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution of the oil fume thermal plume and the oil fume boundary distribution map of the oil fume thermal plume, including: constructing a grayscale matrix based on the grayscale image; and processing the grayscale matrix using the image averaging algorithm and the image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution of the oil fume thermal plume and the oil fume boundary distribution map of the oil fume thermal plume.

[0012] Further, the processor is configured to: determine the average image matrix corresponding to the target image set based on the image averaging algorithm and the grayscale matrix; determine the standard deviation image matrix corresponding to the target image set based on the image standard deviation algorithm and the average image matrix; determine the probability density map of the oil fume concentration distribution of the oil fume thermal plume based on the average image matrix; and determine the oil fume boundary distribution map of the oil fume thermal plume based on the standard deviation image matrix.

[0013] Furthermore, the camera device is equipped with a filter, wherein the wavelength of the filter is the preset wavelength.

[0014] Thirdly, embodiments of the present invention also provide a computer-readable storage medium on which a computer program is stored.

[0015] In this embodiment of the invention, after the range hood starts working, a target image set is acquired. This target image set includes instantaneous images captured by a camera at a preset frequency within a preset time period under an environment free of stray light interference. The instantaneous images are captured when a parallel light source of preset thickness and wavelength illuminates the oil fume thermal plume generated by the smoke-generating device. The instantaneous images are converted into grayscale images. Image averaging and image standard deviation algorithms are used to process the grayscale images to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume. Based on these maps, the smoke extraction effect of the range hood is determined. This achieves a direct representation of the range hood's smoke collection ability, avoids errors caused by manual identification of the smoke extraction effect, and solves the technical problem of poor accuracy in existing range hood smoke extraction effect evaluation results. This improves the accuracy of the smoke extraction effect evaluation results.

[0016] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of a range hood smoke extraction effect evaluation system provided in an embodiment of the present invention;

[0020] Figure 2 This is a flowchart of a method for evaluating the smoke extraction effect of a range hood, provided as an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Example 1:

[0023] According to an embodiment of the present invention, an embodiment of a range hood smoke extraction effect evaluation system is provided. Figure 1 This is a schematic diagram of a range hood smoke extraction effect evaluation system according to an embodiment of the present invention, such as... Figure 1 As shown, the range hood smoke extraction effect evaluation system includes: a smoke generating device 10, a light source assembly 20, a camera device 30, and a processor. The smoke generating device is located below the range hood 40, the light source assembly is located on the side of the smoke generating device, and the camera device is located in front of the smoke generating device.

[0024] The smoke generating device is used to generate a hot plume of oily fumes;

[0025] The light source assembly is used to generate a parallel light source with a preset thickness and preset wavelength after the range hood starts working, and to irradiate the hot plume of oil fumes.

[0026] The camera device is used to capture a target image set, wherein the target image set includes instantaneous images captured by the camera device at a preset frequency within a preset time period under an environment free from stray light interference. The instantaneous images are images captured when the oil fume hot plume is irradiated by a parallel light source of preset thickness and preset wavelength.

[0027] The processor is used to acquire a target image set and convert the instantaneous image into a grayscale image;

[0028] The processor is used to process the grayscale image using an image averaging algorithm and an image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume.

[0029] The processor is used to determine the smoke extraction effect of the range hood based on the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume.

[0030] It should be noted that the aforementioned camera device is equipped with a filter, and the wavelength of the filter is a preset wavelength.

[0031] In this embodiment of the invention, after the range hood starts working, a target image set is acquired. This target image set includes instantaneous images captured by a camera at a preset frequency within a preset time period under an environment free of stray light interference. The instantaneous images are captured when a parallel light source of preset thickness and wavelength illuminates the oil fume thermal plume generated by the smoke-generating device. The instantaneous images are converted into grayscale images. Image averaging and image standard deviation algorithms are used to process the grayscale images to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume. Based on these maps, the smoke extraction effect of the range hood is determined. This achieves a direct representation of the range hood's smoke collection ability, avoids errors caused by manual identification of the smoke extraction effect, and solves the technical problem of poor accuracy in existing range hood smoke extraction effect evaluation results. This improves the accuracy of the smoke extraction effect evaluation results.

[0032] In this embodiment of the invention, the processor is configured to:

[0033] The grayscale image is processed using image averaging and image standard deviation algorithms to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume, including:

[0034] A grayscale matrix is ​​constructed based on the grayscale image, wherein the grayscale matrix is... Where X and Y represent the total number of rows and columns of the grayscale matrix corresponding to the nth grayscale image, respectively, and i and j represent the row and column numbers of the pixels in the grayscale image, respectively. n (i,j) represents the gray level of the pixel in the i-th row and j-th column of the n-th grayscale image;

[0035] The image averaging algorithm and the image standard deviation algorithm are used to process the grayscale matrix to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume.

[0036] The processor is used for:

[0037] The grayscale image is processed using image averaging and image standard deviation algorithms to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume, including:

[0038] A grayscale matrix is ​​constructed based on the grayscale image, wherein the grayscale matrix is ​​G(n) = Where X and Y represent the total number of rows and columns of the grayscale matrix corresponding to the nth grayscale image, respectively, and i and j represent the row and column numbers of the pixels in the grayscale image, respectively. n (i,j) represents the gray level of the pixel in the i-th row and j-th column of the n-th grayscale image;

[0039] The image averaging algorithm and the image standard deviation algorithm are used to process the grayscale matrix to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume.

[0040] The processor is used for:

[0041] The grayscale image is processed using image averaging and image standard deviation algorithms to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume, including:

[0042] A grayscale matrix is ​​constructed based on the grayscale image, wherein the grayscale matrix is... Where X and Y represent the total number of rows and columns of the grayscale matrix corresponding to the nth grayscale image, respectively, and i and j represent the row and column numbers of the pixels in the grayscale image, respectively. n (i,j) represents the gray level of the pixel in the i-th row and j-th column of the n-th grayscale image;

[0043] The image averaging algorithm and the image standard deviation algorithm are used to process the grayscale matrix to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume.

[0044] The following will combine Figure 1 The working process of the above-mentioned range hood smoke extraction effect evaluation system is explained.

[0045] In a kitchen environment, the smoke generator 10 can continuously generate a stable plume of hot oil fumes. When the range hood 40 is operating, most of the hot oil fumes quickly enter the range hood through its inlet and are absorbed and purified. A small amount of hot oil fumes escapes the range hood's outline and cannot be effectively absorbed. Under the action of a parallel light source with a certain thickness and wavelength generated by the light source assembly 20, oil fume particles (or droplets) undergo particle scattering. This scattered light is simultaneously captured by the camera device 30 on the front of the range hood, forming a momentary image. Because the camera device 30 is equipped with a filter of the same wavelength, stray light in the environment is filtered out. Therefore, the resulting momentary image only contains scattered light representing the oil fume concentration, and the background light intensity is zero. By acquiring momentary images of oil fume absorption over a certain period using the camera device, and calculating the distribution of oil fume particles and the distribution of oil fume pulsation boundaries under the parallel light plane during the experiment using image averaging and standard deviation algorithms, the results are obtained.

[0046] According to the principle of light scattering, the higher the concentration of cooking fumes, the stronger the scattered light. Therefore, the flow characteristics of cooking fumes can be analyzed using continuous instantaneous images captured by a camera. Based on the transient flow field images obtained from the camera, they are converted into a digital grayscale image matrix. The grayscale values ​​reflect the intensity of light scattered by the flow field particles and are closely related to the concentration of cooking fume particles. Therefore, the average distribution of the cooking fume thermal plume flow field can be obtained using an image averaging algorithm, and the fluctuation characteristics of the cooking fume flow field can be obtained using an image standard deviation algorithm. The calculation process is as follows:

[0047] The grayscale matrix of an image can be represented as:

[0048]

[0049] Where X and Y represent the total number of rows and columns of the grayscale matrix corresponding to the nth grayscale image, respectively, and i and j represent the row and column numbers of the pixels in the grayscale image, respectively. n (i,j) represents the gray level of the pixel in the i-th row and j-th column of the n-th grayscale image.

[0050] The average image matrix is ​​then:

[0051] in,

[0052] The standard deviation image matrix is ​​then:

[0053] in,

[0054] In the probability density map of the oil fume concentration distribution in the oil fume thermal plume, the larger the average value, the greater the distribution probability of oil fume particles at this location, and the easier it is for the smoke to accumulate. By extracting the contour lines of the average probability density map, the effective smoke collection range of the oil fume on the plane of the light source can be obtained.

[0055] In the standard deviation algorithm for images, the core region of the oil fume flow exhibits greater light intensity and variation due to the larger reflected light intensity, resulting in a larger standard deviation. Conversely, in the boundary regions of fluctuating oil fume, even weak flow reflects light intensity, leading to a certain standard deviation. In areas without oil fume, the background grayscale is zero due to the sheet light source and remains largely unchanged over time, resulting in a near-zero standard deviation. This method can identify the core and fluctuating boundary regions of oil fume flow, thereby determining the effective smoke collection area and critical escape boundary of the range hood.

[0056] When the pulsating boundary of the oil fume in the oil fume boundary distribution map is closer to the range hood's inlet, it indicates a smaller range of oil fume escape, a higher negative pressure at the inlet, and a stronger absorption capacity of the range hood, resulting in better smoke extraction. Similarly, when the probability density contour line of the oil fume concentration distribution in the oil fume concentration distribution probability density map is closer to the range hood's inlet, it indicates a smaller range of oil fume escape, a higher negative pressure at the inlet, and a stronger absorption capacity of the range hood, resulting in better smoke extraction.

[0057] When the range hood is in operation, the cooking pot (i.e., the smoke generator) continuously produces a stable plume of hot oil fumes. The light source component is equipped with a sheet light source of a certain wavelength, which provides lateral illumination in the vertical direction. Oil fume particles or droplets will scatter as they pass through the light path. According to the principle of light scattering, there is a certain positive correlation between the intensity of scattered light and the concentration of particles. By using a camera device to collect the intensity of scattered light from the front of the incident light, the instantaneous distribution of oil fumes on the sheet light source plane can be obtained. By using the principle and algorithm of image grayscale matrix calculation, the change in the intensity of scattered light from oil fume particles on the sheet light source plane over a certain period of time can be calculated. This allows us to obtain the average distribution and pulsating boundary distribution of oil fumes on the sheet light source plane during cooking, and thus characterize the range hood's ability to collect and extract oil fumes.

[0058] Example 2:

[0059] This invention also provides a method for evaluating the smoke extraction effect of a range hood. The smoke extraction effect evaluation device for a range hood provided in the above-described embodiments of this invention is used to perform the smoke extraction effect evaluation method for a range hood. The following is a detailed description of the smoke extraction effect evaluation method for a range hood provided in this invention.

[0060] like Figure 2 As shown, Figure 2This is a flowchart of the above-mentioned method for evaluating the smoke extraction effect of a range hood. The method includes:

[0061] Step S102: After the range hood starts working, acquire a target image set, wherein the target image set includes instantaneous images captured by the camera device at a preset frequency within a preset time period in an environment without stray light interference. The instantaneous images are images captured when a parallel light source with a preset thickness and preset wavelength illuminates the oil fume hot plume generated by the smoke generating device.

[0062] Step S104: Convert the instantaneous image into a grayscale image;

[0063] Step S106: The grayscale image is processed using the image averaging algorithm and the image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume.

[0064] Step S108: Based on the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume, determine the smoke extraction effect of the range hood.

[0065] In this embodiment of the invention, after the range hood starts working, a target image set is acquired. This target image set includes instantaneous images captured by a camera at a preset frequency within a preset time period under an environment free of stray light interference. The instantaneous images are captured when a parallel light source of preset thickness and wavelength illuminates the oil fume thermal plume generated by the smoke-generating device. The instantaneous images are converted into grayscale images. Image averaging and image standard deviation algorithms are used to process the grayscale images to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume. Based on these maps, the smoke extraction effect of the range hood is determined. This achieves a direct representation of the range hood's smoke collection ability, avoids errors caused by manual identification of the smoke extraction effect, and solves the technical problem of poor accuracy in existing range hood smoke extraction effect evaluation results. This improves the accuracy of the smoke extraction effect evaluation results.

[0066] Preferably, the smoke extraction effect of the range hood is determined based on the probability density map of the oil fume concentration distribution and the boundary distribution map of the oil fume thermal plume, including: determining the contour lines of the oil fume concentration distribution probability density of the oil fume thermal plume based on the probability density map of the oil fume concentration distribution, and determining a first distance between the contour lines and the smoke inlet of the range hood; determining the oil fume pulsation boundary of the oil fume thermal plume based on the boundary distribution map of the oil fume thermal plume, and determining a second distance between the oil fume pulsation boundary and the smoke inlet of the range hood; wherein, the smaller the first distance and the second distance, the better the smoke extraction effect of the range hood.

[0067] Preferably, the grayscale image is processed using an image averaging algorithm and an image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume. This includes: constructing a grayscale matrix based on the grayscale image, wherein the grayscale matrix is... Where X and Y represent the total number of rows and columns of the grayscale matrix corresponding to the nth grayscale image, respectively, and i and j represent the row and column numbers of the pixels in the grayscale image, respectively. n (i,j) represents the gray level of the pixel in the i-th row and j-th column of the n-th grayscale image; the grayscale matrix is ​​processed using the image averaging algorithm and the image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume.

[0068] Preferably, the grayscale matrix is ​​processed using the image averaging algorithm and the image standard deviation algorithm to determine the probability density map of the oil fume concentration distribution and the oil fume boundary distribution map of the oil fume thermal plume. This includes: determining the average image matrix corresponding to the target image set based on the image averaging algorithm and the grayscale matrix, wherein the average image matrix is...

[0069] Based on the image standard deviation algorithm and the average image matrix, the standard deviation image matrix corresponding to the target image set is determined, wherein the standard deviation image matrix is:

[0070] Based on the average image matrix, the probability density map of the oil fume concentration distribution of the oil fume thermal plume is determined, and the oil fume boundary distribution map of the oil fume thermal plume is determined based on the standard deviation image matrix.

[0071] Example 3:

[0072] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the method described in Embodiment 1 above.

[0073] Furthermore, in the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0074] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0075] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0076] 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 can be selected to achieve the purpose of this embodiment according to actual needs.

[0077] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0078] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for evaluating the smoke suction effect of a range hood, characterized by, The method comprises the following steps: After the range hood starts to work, a target image set is acquired, wherein the target image set comprises instantaneous images taken by the camera device at a preset frequency within a preset time period and in a non-glare light interference environment, and the instantaneous images are images taken when a parallel light source with a preset thickness and a preset wavelength irradiates the oil fume hot plume generated by the oil fume generating device; The instantaneous images are converted into gray images; The gray images are processed by using an image average algorithm and an image standard deviation algorithm to determine an oil fume concentration distribution probability density graph of the oil fume hot plume and an oil fume boundary distribution graph of the oil fume hot plume; Based on the oil fume concentration distribution probability density graph of the oil fume hot plume and the oil fume boundary distribution graph of the oil fume hot plume, an effective smoke gathering area of the range hood and a smoke gas escape critical boundary are determined respectively; Based on the correlation between the effective smoke gathering area and the smoke gas escape critical boundary and the smoke suction effect, the smoke suction effect of the range hood is determined.

2. The method of claim 1, wherein, Based on the oil fume concentration distribution probability density graph of the oil fume hot plume and the oil fume boundary distribution graph of the oil fume hot plume, an effective smoke gathering area of the range hood and a smoke gas escape critical boundary are determined respectively; Based on the correlation between the effective smoke gathering area and the smoke gas escape critical boundary and the smoke suction effect, the smoke suction effect of the range hood is determined, comprising: Based on the oil fume concentration distribution probability density graph of the oil fume hot plume, an oil fume concentration distribution probability density contour line of the oil fume hot plume is determined; Based on the oil fume concentration distribution probability density contour line, the effective smoke gathering area is determined; and a first distance between the contour line and the smoke inlet of the range hood is determined; the first distance is also the distance between the boundary of the effective smoke gathering area and the smoke inlet; Based on the oil fume boundary distribution graph of the oil fume hot plume, an oil fume pulsation boundary of the oil fume hot plume is determined; Based on the oil fume pulsation boundary, the smoke gas escape critical boundary is determined, and a second distance between the oil fume pulsation boundary and the smoke inlet of the range hood is determined; the second distance is also the distance between the smoke gas escape critical boundary and the smoke inlet; Wherein, the smaller the first distance and the second distance are, the better the smoke suction effect of the range hood is.

3. The method of claim 1, wherein, The gray images are processed by using an image average algorithm and an image standard deviation algorithm to determine an oil fume concentration distribution probability density graph of the oil fume hot plume and an oil fume boundary distribution graph of the oil fume hot plume, comprising: A gray matrix is constructed based on the gray images; The gray matrix is processed by using the image average algorithm and the image standard deviation algorithm to determine the oil fume concentration distribution probability density graph of the oil fume hot plume and the oil fume boundary distribution graph of the oil fume hot plume.

4. The method of claim 3, wherein, The gray matrix is processed by using the image average algorithm and the image standard deviation algorithm to determine the oil fume concentration distribution probability density graph of the oil fume hot plume and the oil fume boundary distribution graph of the oil fume hot plume, comprising: Based on the image average algorithm and the gray matrix, an average image matrix corresponding to the target image set is determined; Based on the image standard deviation algorithm and the average image matrix, a standard deviation image matrix corresponding to the target image set is determined; Determine the oil fume concentration distribution probability density map of the oil fume hot plume based on the average image matrix, and determine the oil fume boundary distribution map of the oil fume hot plume based on the standard deviation image matrix.

5. A system for evaluating the smoke suction performance of a range hood, characterized by Comprise: A smoking device, a light source assembly, a camera device and a processor, wherein the smoking device is arranged below the extractor hood, the light source assembly is arranged on the side of the smoking device, and the camera device is arranged on the front of the smoking device; The smoking device is used to generate an oil fume hot plume; The light source assembly is used to generate parallel light sources with a preset thickness and a preset wavelength after the extractor hood starts working, and irradiate the oil fume hot plume; The camera device is used to shoot a target image set, wherein the target image set comprises instantaneous images shot by the camera device at a preset frequency in a preset time period and in a non-dazzling light environment, and the instantaneous images are images shot when the parallel light sources with the preset thickness and the preset wavelength irradiate the oil fume hot plume; The processor is used to acquire the target image set, and convert the instantaneous images into gray images; The processor is used to process the gray images by using an image average algorithm and an image standard deviation algorithm, and determine the oil fume concentration distribution probability density map of the oil fume hot plume and the oil fume boundary distribution map of the oil fume hot plume; The processor is used to determine an effective smoke gathering area of the extractor hood and a smoke escape critical boundary based on the oil fume concentration distribution probability density map of the oil fume hot plume and the oil fume boundary distribution map of the oil fume hot plume; Determine the smoke suction effect of the extractor hood based on the correlation between the effective smoke gathering area, the smoke escape critical boundary and the smoke suction effect.

6. The system of claim 5, wherein, The processor is used to: Determine the oil fume concentration distribution probability density contour line of the oil fume hot plume based on the oil fume concentration distribution probability density map of the oil fume hot plume, and determine a first distance between the contour line and the smoke inlet of the extractor hood; Determine the oil fume pulsation boundary of the oil fume hot plume based on the oil fume boundary distribution map of the oil fume hot plume, and determine a second distance between the oil fume pulsation boundary and the smoke inlet of the extractor hood; Wherein, the smaller the first distance and the second distance are, the better the smoke suction effect of the extractor hood is.

7. The system of claim 5, wherein, The processor is used to: Process the gray images by using an image average algorithm and an image standard deviation algorithm, and determine the oil fume concentration distribution probability density map of the oil fume hot plume and the oil fume boundary distribution map of the oil fume hot plume, comprising: Construct a gray matrix based on the gray images; Process the gray matrix by using the image average algorithm and the image standard deviation algorithm, and determine the oil fume concentration distribution probability density map of the oil fume hot plume and the oil fume boundary distribution map of the oil fume hot plume.

8. The system of claim 7, wherein, The processor is used to: determining an average image matrix corresponding to the target image set based on the image average algorithm and the grayscale matrix; Determine a standard deviation image matrix corresponding to the target image set based on the image standard deviation algorithm and the average image matrix; Determine the oil fume concentration distribution probability density map of the oil fume hot plume based on the average image matrix, and determine the oil fume boundary distribution map of the oil fume hot plume based on the standard deviation image matrix.

9. The system of claim 7, wherein the camera is provided with a filter, and a wavelength of the filter is the preset wavelength. The camera is provided with a filter, and a wavelength of the filter is the preset wavelength.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that The computer program, when executed by a processor, performs the steps of the method of any one of claims 1 to 4.

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