Method and device for calculating regional oil fume escape volume based on PIV

Abstract

The present invention provides a method and device for calculating the amount of oil fume escape in different regions based on PIV, including: obtaining an original image of oil fume during its rising process; determining a target region based on the original image of oil fume; performing image preprocessing on the target region to obtain a denoised oil fume image; performing iterative window grid division on the denoised oil fume image to obtain the area of ​​the grid of each region at the current moment; applying an average velocity solution algorithm to the oil fume particles in each region to obtain the average displacement of the oil fume particles between the current moment and the next moment; calculating the average velocity based on the average displacement and a preset time step; obtaining the overall oil fume escape amount of the range hood based on the area, average velocity and depth of the grid of each region at the current moment; the method can describe the speed change and oil fume escape amount during the oil fume rising process, shorten the image processing cycle, and effectively evaluate the oil fume absorption effect of the range hood; and remove image noise through image preprocessing to make the calculation more accurate.

Description

Technical Field

[0001] The present invention relates to the field of intelligent home appliance control, and in particular to a method and device for calculating regional oil smoke escape volume based on PIV. Background Art

[0002] Cooking has always been a common daily activity in traditional households. The production of fumes during cooking necessitates the use of kitchen exhaust equipment to reduce exposure to these pollutants and maintain good air quality in the kitchen. A high-performance range hood can quickly direct cooking fumes and exhaust gases outdoors. Measuring the rising velocity of cooking fumes while the range hood is operating, tracking and calculating fume escape, and visualizing the overall smoke collection effect of the range hood are crucial for improving and optimizing range hood performance.

[0003] At present, the cooking fume suction and exhaust performance of range hoods in working state cannot be accurately measured, resulting in the inability to effectively evaluate the range hood's fume suction effect; the dynamic flow field data of cooking fume during the suction and exhaust process cannot be accurately obtained, affecting the further design and improvement of range hood performance. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a method and device for calculating the regional oil fume escape volume based on PIV, which can describe the speed change and oil fume escape volume of the oil fume rising process, and calculate the oil fume escape volume for the oil fume target through the iterative window grid division method and depth, thereby shortening the image processing cycle and effectively evaluating the oil fume absorption effect of the range hood; and removing image noise through image preprocessing, making the calculation more accurate, and having a certain reliable effect on the subsequent improvement and improvement of the range hood performance.

[0005] In a first aspect, an embodiment of the present invention provides a method for calculating regional fume escape based on PIV, the method comprising:

[0006] Obtaining the original image of the oil smoke during its rising process;

[0007] determining a target area according to the original image of the oil smoke;

[0008] Performing image preprocessing on the target area to obtain a denoised oil smoke image;

[0009] Performing iterative window grid division on the denoised oil smoke image to obtain the area of ​​each region at the current moment;

[0010] Applying an average velocity calculation algorithm to the oil smoke particles in each region to obtain an average displacement of the oil smoke particles between the current moment and the next moment;

[0011] Calculating an average velocity based on the average displacement and a preset time step;

[0012] The total amount of oil fume escaping from the range hood is obtained according to the area of ​​the grid of each region at the current moment, the average speed and the depth.

[0013] In a second aspect, an embodiment of the present invention provides a device for calculating regional oil smoke escape volume based on PIV, the device comprising:

[0014] An acquisition unit, used for acquiring an original image of the oil smoke during its rising process;

[0015] a determination unit, configured to determine a target area according to the original oil smoke image;

[0016] A preprocessing unit, configured to perform image preprocessing on the target area to obtain a denoised oil smoke image;

[0017] a division unit, configured to perform iterative window grid division on the denoised oil smoke image to obtain the area of ​​each grid region at a current moment;

[0018] an average displacement calculation unit, configured to apply an average velocity solution algorithm to the oil smoke particles in each area to obtain an average displacement of the oil smoke particles between the current moment and the next moment;

[0019] an average speed calculation unit, configured to calculate an average speed based on the average displacement and a preset time step;

[0020] The oil fume escape amount calculation unit is used to obtain the overall oil fume escape amount of the range hood according to the area of ​​the grid of each area at the current moment, the average speed and the depth.

[0021] In a third aspect, an embodiment of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and the processor implements the above-mentioned method when executing the computer program.

[0022] The embodiment of the present invention provides a method and device for calculating the amount of oil smoke escape in different regions based on PIV, including: obtaining an original image of oil smoke during the rising process; determining a target area based on the original image of oil smoke; performing image preprocessing on the target area to obtain a denoised oil smoke image; performing iterative window grid division on the denoised oil smoke image to obtain the area of ​​the grid of each region at the current moment; applying an average velocity solution algorithm to the oil smoke particles in each region to obtain the average displacement of the oil smoke particles between the current moment and the next moment; calculating the average velocity based on the average displacement and a preset time step; obtaining the overall oil smoke escape amount of the range hood based on the area, average velocity and depth of the grid of each region at the current moment; the speed change and oil smoke escape amount of the oil smoke rising process can be described, and the oil smoke escape amount is calculated for the oil smoke target through the iterative window grid division method and the depth, thereby shortening the image processing cycle and effectively evaluating the oil smoke absorption effect of the range hood; and removing image noise through image preprocessing makes the calculation more accurate, which has a certain reliable effect on the subsequent improvement and improvement of the range hood performance.

[0023] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0024] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0026] Figure 1 Flowchart of the method for calculating regional oil smoke escape based on PIV provided in the first embodiment of the present invention;

[0027] Figure 2 A flow chart of the noise filtering algorithm provided in the first embodiment of the present invention;

[0028] Figure 3 A schematic diagram of a median filter operator provided in the first embodiment of the present invention;

[0029] Figure 4 A schematic diagram of a Gaussian filter operator provided in Example 1 of the present invention;

[0030] Figure 5 Schematic diagram of the average speed solution algorithm provided in Example 1 of the present invention;

[0031] Figure 6 Schematic diagram of iterative window grid division provided in the first embodiment of the present invention;

[0032] Figure 7 Schematic diagram of the device for calculating regional oil fume escape volume based on PIV provided in Example 1 of the present invention.

[0033] icon:

[0034] 1-range hood; 2-cooking fume simulating the rising process; 3-smoking pot; 11-acquisition unit; 12-determination unit; 13-preprocessing unit; 14-division unit; 15-average displacement calculation unit; 16-average speed calculation unit; 17-fume escape amount calculation unit. DETAILED DESCRIPTION

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0036] This application combines digital image processing technology to visualize the entire smoke collection situation of the range hood, measure the rising speed of the smoke, and perform iterative window grid division and setting in different areas to calculate the overall smoke escape volume of the range hood.

[0037] Among them, PIV technology (Particle Image Velocimetry) is a non-contact fluid dynamics velocity measurement method and is currently the most widely used full-field non-interference velocity measurement method. The basic principle of PIV technology is: first, a certain amount of tracer particles must be dispersed in the measured flow field area. The tracer particles must have good tracking properties. Then, a laser is emitted to form a thin sheet of light in the measured flow field area. The flow field area is photographed using a high-speed camera, so that the particle motion trajectory is clearly imaged as the subsequent PIV experimental image. Finally, the PIV image is analyzed and processed using mathematical methods to obtain the average velocity of the particles in each small area, and thus the flow information within the entire measured flow field range can be obtained.

[0038] CCD industrial camera: It consists of an optical lens, timing and synchronization signal generator, vertical driver, and analog / digital signal processing circuit. As a functional device, CCD has advantages over vacuum tubes, such as no burn-in, no lag, low voltage operation, and low power consumption.

[0039] Salt and pepper noise: also known as impulse noise, is a type of noise often seen in images. It is a random appearance of white or black dots, which may be black pixels in bright areas or white pixels in dark areas (or both).

[0040] Gaussian noise: refers to a type of noise whose probability density function follows a Gaussian distribution (i.e., normal distribution). The main source of Gaussian noise in digital images occurs during acquisition due to sensor noise caused by poor lighting and / or high temperature.

[0041] Target (enabled) area: Select the area where the oil smoke is located for subsequent image processing.

[0042] To facilitate understanding of this embodiment, the embodiment of the present invention is described in detail below.

[0043] Example 1:

[0044] Figure 1 This is a flow chart of the method for calculating regional oil fume escape based on PIV provided in Example 1 of the present invention.

[0045] Reference Figure 1 , the method comprises the following steps:

[0046] Step S101, obtaining an original image of the oil smoke during its rising process;

[0047] Step S102, determining the target area based on the original image of oil smoke;

[0048] Specifically, the frame rate of the CCD industrial camera is set to 250 frames per second, and the parameters such as the working air volume and suction force of the range hood to be tested are set at the same time. The CCD industrial camera is used to shoot the rising process of the oil smoke from the front and side, and then two sets of original oil smoke images corresponding to the two directions at each moment are obtained, and the image format is tiff. Assuming it is a point heat source, the oil smoke diffusion area is generally in the shape of an inverted cone (the actual calculation needs to consider the heat source diameter). Batch reading and loading are performed through the PIV algorithm, and the area where the oil smoke is located is selected and enabled, that is, the target area is selected according to the set range of the PIV algorithm, where the target area is the enabled area.

[0049] Step S103, performing image preprocessing on the target area to obtain a denoised oil smoke image;

[0050] Here, image preprocessing refers to adjusting the brightness of the target area loaded into the PIV algorithm program and filtering out noise in the image. The purpose is to highlight the area where the oil smoke is located and distinguish the background part, so that the subsequent processing and calculation of the oil smoke particles will be more accurate.

[0051] Step S104, performing iterative window grid division on the denoised oil smoke image to obtain the area of ​​each region at the current moment;

[0052] Step S105: applying an average velocity calculation algorithm to the oil smoke particles in each area to obtain an average displacement of the oil smoke particles between the current moment and the next moment;

[0053] Step S106, calculating the average velocity based on the average displacement and the preset time step;

[0054] Step S107 , obtaining the total amount of oil fume escaping from the range hood according to the area, average speed, and depth of the grid of each region at the current moment.

[0055] In this embodiment, not only can the overall smoke collection effect of the range hood be qualitatively observed, but also the speed change of the smoke rising process and the overall smoke escape volume of the range hood can be quantitatively described. Specifically, for the smoke target, the depth value obtained by the slicing and layering method is used to calculate the overall smoke escape volume of the range hood through an iterative window grid division method, which can shorten the image processing cycle, and remove image noise through image preprocessing, making the calculation more accurate, and having a certain reliable effect on the subsequent improvement of the range hood performance.

[0056] Furthermore, step S104 includes the following steps:

[0057] Step S201, obtaining the overall height of the oil smoke and the diameter of the smoke pot;

[0058] Step S202, calculating the cross-sectional diameter of the oil smoke diffusion according to the overall height of the oil smoke and the diameter of the smoke pot;

[0059] Step S203, calculating the length of the oil smoke escaping portion according to the cross-sectional diameter of the oil smoke diffusion and the length of the range hood;

[0060] Step S204: when the cross-sectional diameter of the oil smoke diffusion is the length of the range hood, the oil smoke height is calculated according to the diameter of the smoke pot;

[0061] Step S205, calculating the length of the oil smoke escape area according to the oil smoke height and the overall oil smoke height;

[0062] Step S206, constructing an oil fume escape area according to the length of the oil fume escape portion and the length of the oil fume escape area;

[0063] Step S207, determining the oil smoke rising steadily area and the oil smoke sparse area according to the boundary angle coordinates of the oil smoke escape area and the target area;

[0064] Step S208: Perform iterative window grid division on the oil fume escape area, the oil fume rising smoothly area, and the oil fume scarce area, respectively, to obtain the area of ​​the grid of the oil fume escape area, the area of ​​the grid of the oil fume rising smoothly area, and the area of ​​the grid of the oil fume scarce area at the current moment;

[0065] Among them, the overall height of the oil smoke is the vertical height between the range hood and the smoke pot.

[0066] Specifically, the iterative window meshing method and parameter calibration involves setting a reasonable iterative window mesh size based on the target area size, inputting a time step (in seconds), and calibrating the vertical distance (in meters) between the range hood and the smoke pan. The time step is 4 milliseconds, and the vertical height h between the range hood and the smoke pan is 500 mm.

[0067] In general PIV algorithm calculations, the iterative window grid division is usually a grid of equal area, and the grid size can only be adjusted overall. The operation speed and the meticulousness of the recognition calculation cannot be balanced. However, this application proposes a regional grid division method for the oil smoke target based on the research on the diffusion characteristics of oil smoke. This method can accelerate the operation speed while ensuring processing accuracy. The specific implementation method is as follows:

[0068] Given the overall length of the range hood, the vertical height of the range hood from the smoke pot, and the diameter of the smoke pot (heat source), and through the study of the cooking fume heat plume diffusion model, the fume diffusion characteristic formula can be obtained as follows:

[0069] D=0.4915h+0.8537B (1)

[0070] Among them, D is the cross-sectional diameter of the oil smoke diffusion, h is the overall height of the oil smoke, and B is the diameter of the smoke pot.

[0071] α=12.77exp(-0.0398h)-79.04exp(-15.88h) (2)

[0072] Where α is the fume diffusion angle. Considering the symmetry between the range hood and the fume diffusion, we now describe the meshing of one side of the fume diffusion area, and use the same method for the other side.

[0073] Reference Figure 6When simulating the rising process of cooking fume 2, the method for dividing the fume escape area is as follows: let half the length of the range hood 1 be d1 and the length of the fume escape part be d2, then d2 = D / 2-d1. It is known that the diameter of the smoke pot 3 is B and the length of the range hood 1 is 2d1. Substituting them into formula (1), the fume height h1 when the fume cross-sectional diameter D is 2d1 can be obtained; then, based on the fume height h1 and the overall fume height h, the length d3 of the fume escape area is calculated. The area enclosed by d2 and d3 is the fume escape area A1.

[0074] Furthermore, step S207 includes the following steps:

[0075] Step S301, obtaining a remaining area according to the oil smoke escape area and the target area;

[0076] Step S302, obtaining a fume boundary fitting curve according to the set heat source boundary coordinates and the boundary angle coordinates of the fume escape area;

[0077] Step S303 : dividing the remaining area into a fume rising smoothly area and a fume sparse area according to the fume boundary fitting curve.

[0078] Here, the heat source boundary coordinates are defined as a(B / 2,0), and the oil fume escape area boundary angular coordinates are defined as b(d1,h-d3). A oil fume boundary fitting curve can be determined by a and b. Based on this oil fume boundary fitting curve, the oil fume rising steadily area is marked as A2, and the oil fume sparse area is marked as A3, thus completing the overall oil fume area division.

[0079] Based on this regional division, the coordinates of each region's boundaries are determined. Different grid sizes are then set for each region, taking into account the subsequent calculation of the amount of oil smoke escaping. Specifically, the grid size for region A1 is denser, followed by region A2, and then sparser for region A3. This method of using different grid sizes for different regions ensures both accurate processing and faster computation. The grid setting divides the oil smoke image into small detection windows, within which oil smoke particles are scattered.

[0080] Furthermore, step S105 includes the following steps:

[0081] Step S401, obtaining a first oil smoke flow field image at a current moment and a second oil smoke flow field image at a next moment;

[0082] Step S402, performing Fourier transform on the first oil smoke flow field image to obtain the first oil smoke flow field image after Fourier transform;

[0083] Step S403, performing Fourier transform on the second oil smoke flow field image to obtain a second oil smoke flow field image after Fourier transform;

[0084] Step S404, conjugating the first oil smoke flow field image after Fourier transformation to obtain a conjugated first oil smoke flow field image;

[0085] Step S405, obtaining a frequency domain processing result based on the conjugated first oil smoke flow field image and the Fourier transformed second oil smoke flow field image;

[0086] Step S406, performing inverse Fourier transform on the result after frequency domain processing to obtain a function in the time domain;

[0087] Step S407: taking the maximum value of the function in the time domain as the average displacement of the oil smoke particles between the current moment and the next moment.

[0088] Specifically, the average velocity of the oil smoke particles in the iterative window grid is solved, referring to Figure 5 Assume that the initial time of the first frame of oil smoke particles is t1. After the time interval Δt, the displacement of the oil smoke particles in the x and y directions is (Δx, Δy). The oil smoke flow field image at time t1 is expressed as I1(x,y)=I(x,y)+n1(x,y). Considering that Δt is small enough, the oil smoke flow field image at time t2 can be expressed as I2(x,y)=I(x+Δx,y+Δy)+n2(x,y), where n1(x,y) and n2(x,y) are random noises in the system. The average displacement of the oil smoke particles in the detection window at each time can be determined by the following formula:

[0089] I F1 (u,v)=∫∫I1(x,y)e -j(ux+vy) dxdy (3)

[0090] Among them, I F1 (u, v) is the first oil smoke flow field image after Fourier transform.

[0091] I F2 (u,v)=∫∫I2(x,y)e -j(ux+vy) dxdy (4)

[0092] Among them, I F2 (u, v) is the second oil smoke flow field image after Fourier transform.

[0093] R F12 (u,v)=I * F1 (u,v)×I F2 (u,v) (5)

[0094] Among them, I * F1 (u,v) is I F2 The conjugate of (u,v), RF12 (u,v) is the result after frequency domain processing.

[0095]

[0096] According to r 12 =∫∫I1(x,y)I2(x+τ x ,y+τ y )dxdy=∫∫I(x,y)I(x+Δx+τ x ,y+Δy+τ y )dxdy

[0097] We can get r 12 (τ x ,τ y )=∫∫I(x,y)I(x+τ x ,y+τ y )dxdy (7)

[0098] Among them, r 12 (τ x ,τ y ) is a function in the time domain.

[0099] Convert formula (7) into r 12 (τ x ,τ y )=r(τ x +Δx,τ y +Δy), since the above function is an even function and reaches its maximum value at the origin, that is, r(τ x ,τ y )≤r(0,0), so that the following inequality holds:

[0100] r 12 (τ x ,τ y )≤r 12 (-Δx,-Δy) (8)

[0101] The time domain is reduced to r 12 (τ x ,τ y ) function corresponds to the relative displacement between the flow fields, which is determined as the average displacement of the oil smoke particles within the detection window between the current time t1 and the next time t2. The sampling interval Δt is the time step, and the average velocity is then calculated. Using this average velocity solution reduces computational effort, significantly accelerating the processing time of the oil smoke image PIV algorithm.

[0102] Furthermore, step S107 includes the following steps:

[0103] Step S501, obtaining the oil fume diffusion area on the first side and the oil fume diffusion area on the second side;

[0104] Step S502: Segment the oil smoke diffusion area on the first side to obtain n first equal-width sheet areas, wherein each first equal-width sheet area is a first depth of each grid;

[0105] Step S503, dividing the oil smoke diffusion area on the second side into m second equal-width sheet areas, wherein each second equal-width sheet area is a second depth of each grid;

[0106] Step S504, calculating the first oil fume escape volume of the oil fume diffusion area on the first side according to the area, average velocity and first depth of each grid in each area at the current moment;

[0107] Step S505, calculating the second oil fume escape amount of the oil fume diffusion area on the second side according to the area of ​​the grid at the current moment, the average speed and the second depth of each grid;

[0108] Step S506: Calculate the total oil fume escape amount of the range hood according to the first oil fume escape amount and the second oil fume escape amount.

[0109] Specifically, a slicing and layering method is used to calculate the amount of oil smoke escape in different regions. First, the oil smoke escape area is located, and then the algorithm is used to load the oil smoke side image to perform regional and layered cumulative calculation. The specific implementation method is as follows:

[0110] The average velocity is also called the escape velocity v of the soot particles i (m / s), the oil smoke diffusion characteristic formula is known, and the oil smoke diffusion area on the first side obtained by shooting can be divided into n first equal-width sheet areas, and the width of each sheet is recorded as l i , recorded as the first depth l of each grid at the current moment i , where i is the number of grids i = 1, 2, 3, ..., n. The first fume escape rate of the fume diffusion area on the first side can be determined by the following formula:

[0111]

[0112] Among them, Q t1 is the first oil smoke escape volume of the oil smoke diffusion area on the first side, s is the area of ​​the grid of each area at the current moment, l i The first depth of each grid, v i is the average speed.

[0113] The same analysis and calculation are performed on the other side of the range hood (the second side fume diffusion area) using the above method. The number of grid divisions in the fume escape area on the other side of the range hood is denoted as j, where j = 1, 2, 3, ..., n. The total fume escape volume of the range hood can be determined by the following formula:

[0114]

[0115] Among them, Q t is the total amount of oil smoke escaping from the range hood, l j The second depth of each grid, v j is the average speed.

[0116] Furthermore, step S103 includes the following steps:

[0117] Step S601, passing the target area through a noise filtering algorithm to obtain a filtered image;

[0118] Step S602 : performing median filtering and Gaussian filtering on the filtered oil smoke image using a median filter operator and a Gaussian filter operator respectively to obtain a denoised image.

[0119] Furthermore, step S601 includes the following steps:

[0120] Step S701, taking the logarithm of the target area to obtain the logarithmized target area;

[0121] Step S702, performing Fourier transform on the target area after taking the logarithm to obtain a Fourier transformed image;

[0122] Step S703, performing a scale transformation on the Fourier transformed image and the center-surround function in the frequency domain to obtain a scale-transformed function;

[0123] Step S704: Perform inverse Fourier transform on the scale-transformed function to obtain a filtered image.

[0124] Specifically, the present invention constructs a high-pass filter based on the Gaussian filtering principle, and converts the time domain image into the frequency domain for filtering calculation, and designs a noise filtering algorithm that can eliminate the problem of uneven lighting on the image. This method can enhance the image details in the dark area without losing the image details in the bright area, thus avoiding image distortion to a certain extent. The specific implementation process of the noise filtering algorithm is referred to Figure 2 :

[0125] f(x,y)=i(x,y)r(x,y) (11)

[0126] Among them, f(x,y) is the target area, i(x,y) is the illumination intensity component, and r(x,y) is the reflection intensity component.

[0127] lnf(x,y)=lni(x,y)+lnr(x,y) (12)

[0128] Wherein, lnf(x,y) is the logarithm of the target area, lni(x,y) is the logarithm of the illumination intensity component, and lnr(x,y) is the logarithm of the reflection intensity component.

[0129] G(u,v)=∫∫[lni(x,y)]e -j(ux+vy) dxdy+∫∫[lnr(x,y)]e -j(ux+vy) dxdy (13)

[0130] Among them, G(u,v) is the image after Fourier transform.

[0131] Set H(u,v) as the center surround function in the frequency domain, c and λ are Gaussian surround scales, and H(u,v) must be selected to satisfy: ∫∫H(x,y)dxdy=1

[0132] S(u,v)=G(u,v)H(u,v) (14)

[0133]

[0134] Among them, S(u,v) is the scale-transformed function, that is, the filtered image in the frequency domain.

[0135] h(x,y)=e g(x,y) (16)

[0136] Among them, h(x,y) is the filtered image.

[0137] In the process of image denoising, the median filter and Gaussian filter are combined to remove image noise; the median filter, whose filtering object is for the image of non-stationary signal, first sorts the grayscale values ​​of all pixels contained in the filter template window, finds the middle value to replace the grayscale value of the pixel on the image corresponding to the template center point, and mainly filters out salt and pepper noise in the image; Gaussian filter mainly filters out Gaussian noise in the image; refer to Figure 3 and Figure 4 , Figure 3 is a 5×5 median filter operator, Figure 4 The 5×5 Gaussian filter operator is used to perform median filtering on the filtered oil smoke image, and then the Gaussian filter operator is used to perform Gaussian filtering to finally obtain the denoised image.

[0138] Furthermore, the method further comprises the following steps:

[0139] Step S801, obtaining a velocity vector according to the average velocity;

[0140] Step S802, compare the velocity vector with the set velocity range; if it is less than, execute step S803; if it is greater, execute step S804;

[0141] Step S803, generating a velocity vector diagram according to the velocity vector, and generating a velocity change curve according to the velocity vector diagram;

[0142] Step S804: eliminating and interpolating the velocity vector using a two-dimensional bilinear interpolation algorithm.

[0143] Specifically, the average velocity includes both horizontal and vertical average velocities, and can display the overall rising velocity of the fume. After obtaining the average velocity, a velocity vector is derived based on the average velocity. This velocity vector may contain tracking errors for certain particles. By setting a velocity range and using a two-dimensional bilinear interpolation algorithm to remove and correct these errors, a velocity vector diagram of the rising fume particles can be drawn. The system can also optionally output a velocity curve for any frame, using a color scale to represent the velocity changes.

[0144] The present application can not only qualitatively observe the overall smoke collection effect of the range hood, visualize the overall rising situation of the oil smoke, and generate a velocity vector diagram without contact or interference in measuring the oil smoke, but also quantitatively describe the speed change of the oil smoke rising process and the overall oil smoke escape volume during the rising process. Specifically, for the oil smoke target, it is proposed to perform iterative window grid division and slice layering to calculate the overall oil smoke escape volume, and remove image noise through image preprocessing, thereby shortening the image processing cycle, accurately measuring, saving time and effort, and providing a reliable reference for the performance test of the range hood.

[0145] The embodiment of the present invention provides a method for calculating the amount of oil smoke escape in different regions based on PIV, including: obtaining an original image of oil smoke during the rising process; determining a target area based on the original image of oil smoke; performing image preprocessing on the target area to obtain a denoised oil smoke image; performing iterative window grid division on the denoised oil smoke image to obtain the area of ​​the grid of each region at the current moment; applying an average velocity solution algorithm to the oil smoke particles in each region to obtain the average displacement of the oil smoke particles between the current moment and the next moment; calculating the average velocity based on the average displacement and a preset time step; obtaining the overall oil smoke escape amount of the range hood based on the area, average velocity and depth of the grid of each region at the current moment; the speed change and oil smoke escape amount of the oil smoke rising process can be described, and the oil smoke escape amount is calculated for the oil smoke target through the iterative window grid division method and the depth, thereby shortening the image processing cycle and effectively evaluating the oil smoke absorption effect of the range hood; and removing image noise through image preprocessing makes the calculation more accurate, which has a certain reliable effect on the subsequent improvement and improvement of the range hood performance.

[0146] Example 2:

[0147] Figure 7 Schematic diagram of the device for calculating regional oil fume escape volume based on PIV provided in the second embodiment of the present invention.

[0148] Reference Figure 7 , the device comprises:

[0149] An acquisition unit 11 is used to acquire an original image of the oil smoke during its rising process;

[0150] A determination unit 12 is configured to determine a target area based on the original image of the oil smoke;

[0151] The preprocessing unit 13 is used to perform image preprocessing on the target area to obtain a denoised oil smoke image;

[0152] The division unit 14 is used to perform iterative window grid division on the denoised oil smoke image to obtain the area of ​​each grid at the current moment;

[0153] The average displacement calculation unit 15 is used to calculate the average displacement of the oil smoke particles between the current moment and the next moment by using an average velocity solution algorithm.

[0154] an average speed calculation unit 16, configured to calculate an average speed based on the average displacement and a preset time step;

[0155] The oil fume escape amount calculation unit 17 is used to obtain the total oil fume escape amount of the range hood according to the area, average speed and depth of each grid area at the current moment.

[0156] An embodiment of the present invention provides a regional oil fume escape calculation device based on PIV, comprising: obtaining an original oil fume image during the rising process of oil fume; determining a target area according to the original oil fume image; performing image preprocessing on the target area to obtain a denoised oil fume image; performing iterative window grid division on the denoised oil fume image to obtain the area of ​​the grid of each region at the current moment; applying an average velocity solution algorithm to the oil fume particles in each region to obtain the average displacement of the oil fume particles between the current moment and the next moment; calculating the average velocity according to the average displacement and a preset time step; obtaining the overall oil fume escape of the range hood according to the area, average velocity and depth of the grid of each region at the current moment; the speed change and oil fume escape during the rising process of oil fume can be described, and the oil fume escape is calculated for the oil fume target by using the iterative window grid division method and the depth, thereby shortening the image processing cycle and effectively evaluating the oil fume absorption effect of the range hood; and removing image noise by image preprocessing to make the calculation more accurate, which has a certain reliable effect on the subsequent improvement and improvement of the performance of the range hood.

[0157] An embodiment of the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, the steps of the method for calculating the regional oil fume escape amount based on PIV provided in the above embodiment are implemented.

[0158] An embodiment of the present invention also provides a computer-readable medium having a non-volatile program code executable by a processor, wherein a computer program is stored on the computer-readable medium. When the computer program is run by the processor, the steps of the regional oil fume escape calculation method based on PIV of the above embodiment are executed.

[0159] The computer program product provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the previous method embodiments. For specific implementation, please refer to the method embodiments and will not be repeated here.

[0160] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems and devices can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0161] In addition, in the description of the embodiments of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0162] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0163] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present 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.

[0164] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. 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 above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for calculating regional fume escape based on PIV, characterized in that: The method comprises: Obtaining the original image of the oil smoke during its rising process; determining a target area according to the original image of the oil smoke; Performing image preprocessing on the target area to obtain a denoised oil smoke image; Performing iterative window grid division on the denoised oil smoke image to obtain the area of ​​each region at the current moment; Applying an average velocity calculation algorithm to the oil smoke particles in each region to obtain an average displacement of the oil smoke particles between the current moment and the next moment; Calculating an average velocity based on the average displacement and a preset time step; Obtaining the total amount of oil smoke escaping from the range hood according to the area of ​​the grid of each region at the current moment, the average speed, and the depth; The denoised oil smoke image is subjected to iterative window grid division to obtain the area of ​​each region of the grid at the current moment, including: Get the overall height of the oil smoke and the diameter of the smoke pot; Calculating the cross-sectional diameter of the oil smoke diffusion according to the overall height of the oil smoke and the diameter of the smoke pot; Calculate the length of the oil smoke escaping part based on the cross-sectional diameter of the oil smoke diffusion and the length of the range hood; When the cross-sectional diameter of the oil smoke diffusion is the length of the range hood, the oil smoke height is calculated according to the diameter of the smoke pot; Calculating the length of the oil fume escape area according to the oil fume height and the overall oil fume height; constructing the oil fume escape area according to the length of the oil fume escape portion and the length of the oil fume escape area; Determining a fume rising stable area and a fume-sparse area according to the boundary angle coordinates of the fume escape area and the target area; Performing iterative window grid division on the oil fume escape area, the oil fume rising smoothly area, and the oil fume scarce area, respectively, to obtain the area of ​​the grid of the oil fume escape area at the current moment, the area of ​​the grid of the oil fume rising smoothly area at the current moment, and the area of ​​the grid of the oil fume scarce area at the current moment; The overall height of the oil smoke is the vertical height between the range hood and the smoke pot; The method of applying an average velocity calculation algorithm to the oil smoke particles in each area to obtain an average displacement of the oil smoke particles between the current moment and the next moment includes: Acquire a first oil smoke flow field image at the current moment and a second oil smoke flow field image at the next moment; Performing Fourier transformation on the first oil smoke flow field image to obtain a first oil smoke flow field image after Fourier transformation; Performing Fourier transformation on the second oil smoke flow field image to obtain a second oil smoke flow field image after Fourier transformation; Taking conjugate of the first oil smoke flow field image after Fourier transformation to obtain a conjugate first oil smoke flow field image; Obtaining a frequency domain processing result according to the conjugated first oil smoke flow field image and the Fourier transformed second oil smoke flow field image; Performing inverse Fourier transform on the result after the frequency domain processing to obtain a function in the time domain; The maximum value of the function in the time domain is taken as the average displacement of the oil smoke particles between the current moment and the next moment.

2. The method for calculating regional fume escape based on PIV according to claim 1 is characterized in that: The step of determining the oil smoke rising smoothly area and the oil smoke scarce area according to the boundary angle coordinates of the oil smoke escape area and the target area includes: Obtaining a remaining area according to the oil smoke escape area and the target area; Obtaining a fume boundary fitting curve according to the set heat source boundary coordinates and the boundary angle coordinates of the fume escape area; The remaining area is divided into the oil smoke rising smoothly area and the oil smoke scarce area according to the oil smoke boundary fitting curve.

3. The method for calculating regional fume escape based on PIV according to claim 1, characterized in that: The total amount of oil fume escaped from the range hood is obtained based on the area of ​​the grid of each region at the current moment, the average speed, and the depth, including: Obtaining the oil fume diffusion area on the first side and the oil fume diffusion area on the second side; Divide the first side fume diffusion area to obtain n first equal-width sheet areas, wherein each first equal-width sheet area is a first depth of each grid; Divide the oil smoke diffusion area of ​​the second side surface to obtain m second sheet-like areas of equal width, wherein each second sheet-like area of ​​equal width is the second depth of each grid; Calculating a first oil fume escape amount of the oil fume diffusion area on the first side according to the area of ​​the grid of each area at the current moment, the average speed, and the first depth of each grid; Calculating a second oil fume escape amount of the oil fume diffusion area on the second side according to the area of ​​the grid of each area at the current moment, the average speed, and the second depth of each grid; The total oil fume escape amount of the range hood is calculated according to the first oil fume escape amount and the second oil fume escape amount.

4. The method for calculating regional fume escape based on PIV according to claim 1, characterized in that: The step of performing image preprocessing on the target area to obtain a denoised oil smoke image includes: Passing the target area through a noise filtering algorithm to obtain a filtered image; The filtered oil smoke image is subjected to median filtering and Gaussian filtering respectively by a median filtering operator and a Gaussian filtering operator to obtain the denoised image.

5. The method for calculating regional fume escape based on PIV according to claim 4 is characterized in that: The step of applying a noise filtering algorithm to the target area to obtain a filtered image includes: Taking the logarithm of the target area to obtain a logarithmized target area; Performing Fourier transform on the target area after taking the logarithm to obtain a Fourier transformed image; Performing a scale transformation on the Fourier transformed image and the center-surround function in the frequency domain to obtain a scale-transformed function; Performing inverse Fourier transform on the scale-transformed function to obtain the filtered image.

6. The method for calculating regional fume escape based on PIV according to claim 1, characterized in that: The method further comprises: According to the average velocity, a velocity vector is obtained; comparing the velocity vector with a set velocity range; If it is less than, generating a velocity vector diagram according to the velocity vector, and generating a velocity change curve according to the velocity vector diagram; If it is greater than, the velocity vector is eliminated and interpolated and corrected using a two-dimensional bilinear interpolation algorithm.

7. A device for calculating regional oil smoke escape based on PIV, characterized in that: The device comprises: An acquisition unit, used for acquiring an original image of the oil smoke during its rising process; a determination unit, configured to determine a target area according to the original oil smoke image; A preprocessing unit, configured to perform image preprocessing on the target area to obtain a denoised oil smoke image; a division unit, configured to perform iterative window grid division on the denoised oil smoke image to obtain the area of ​​each grid region at a current moment; an average displacement calculation unit, configured to apply an average velocity solution algorithm to the oil smoke particles in each area to obtain an average displacement of the oil smoke particles between the current moment and the next moment; an average speed calculation unit, configured to calculate an average speed based on the average displacement and a preset time step; an oil fume escape amount calculation unit, configured to obtain the total oil fume escape amount of the range hood according to the area of ​​the grid of each region at a current moment, the average speed, and the depth; The division unit is specifically used for: Get the overall height of the oil smoke and the diameter of the smoke pot; Calculating the cross-sectional diameter of the oil smoke diffusion according to the overall height of the oil smoke and the diameter of the smoke pot; Calculate the length of the oil smoke escaping part based on the cross-sectional diameter of the oil smoke diffusion and the length of the range hood; When the cross-sectional diameter of the oil smoke diffusion is the length of the range hood, the oil smoke height is calculated according to the diameter of the smoke pot; Calculating the length of the oil fume escape area according to the oil fume height and the overall oil fume height; constructing the oil fume escape area according to the length of the oil fume escape portion and the length of the oil fume escape area; Determining a fume rising stable area and a fume-sparse area according to the boundary angle coordinates of the fume escape area and the target area; Performing iterative window grid division on the oil fume escape area, the oil fume rising smoothly area, and the oil fume scarce area, respectively, to obtain the area of ​​the grid of the oil fume escape area at the current moment, the area of ​​the grid of the oil fume rising smoothly area at the current moment, and the area of ​​the grid of the oil fume scarce area at the current moment; The overall height of the oil smoke is the vertical height between the range hood and the smoke pot; The average displacement calculation unit is specifically used for: Acquire a first oil smoke flow field image at the current moment and a second oil smoke flow field image at the next moment; Performing Fourier transformation on the first oil smoke flow field image to obtain a first oil smoke flow field image after Fourier transformation; Performing Fourier transformation on the second oil smoke flow field image to obtain a second oil smoke flow field image after Fourier transformation; Taking conjugate of the first oil smoke flow field image after Fourier transformation to obtain a conjugate first oil smoke flow field image; Obtaining a frequency domain processing result according to the conjugated first oil smoke flow field image and the Fourier transformed second oil smoke flow field image; Performing inverse Fourier transform on the result after the frequency domain processing to obtain a function in the time domain; The maximum value of the function in the time domain is taken as the average displacement of the oil smoke particles between the current moment and the next moment.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

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