A method for detecting the coning and porosity of a burning cone

Abstract

The application provides a method for detecting a burning cone shape and porosity, comprising: obtaining a CT tomographic image of a cigarette sample after burning and performing three-dimensional reconstruction to obtain a three-dimensional reconstruction image; performing image segmentation processing on the three-dimensional reconstruction image to obtain a three-dimensional image and a point cloud data set of a cigarette burning cone part; calculating the height and maximum offset degree of the burning cone based on the point cloud data set of the cigarette burning cone part; and calculating the volume and porosity of the burning cone based on the three-dimensional image of the cigarette burning cone part.

Description

Technical Field

[0001] This invention relates to the field of cigarette product testing technology, specifically, to a method for detecting the combustion cone morphology and porosity. Background Technology

[0002] During cigarette combustion, the shape and porosity of the combustion cone are key factors affecting smoke release, combustion efficiency, and sensory quality. The shape of the combustion cone affects the uniformity of cigarette combustion. If the combustion cone shape is irregular, it may lead to uneven combustion, resulting in localized overheating or incomplete combustion. This will cause uneven distribution of smoke components, affecting the aroma and taste of the cigarette and reducing sensory quality. Combustion cone shape parameters include the height, volume, and maximum offset of the combustion cone. The height of the combustion cone refers to the length of the ash portion formed after the cigarette burns. When the combustion cone height is moderate, the combustion rate is stable, the smoke concentration is uniform, and the smoking experience is better. If the combustion cone height is too low, it indicates that the combustion rate is too fast, which may lead to smoke dilution, a weaker taste, and an increased rate of cigarette consumption, affecting satisfaction. An excessively high combustion cone usually means a slower combustion rate, possibly due to overly dense tobacco packing or low permeability. The volume of the combustion cone is determined by its height and cross-sectional area, primarily affecting the uniformity of combustion and ash stability. A reasonable combustion cone volume ensures stable combustion, moderate smoke concentration, smooth draw, and a harmonious flavor. When the combustion cone volume is small, the ash is loose and easily falls off, potentially leading to uneven combustion and affecting the drawing experience. If the combustion cone volume is too large, it may indicate incomplete combustion, excessive ash thickness, and hinder the supply of oxygen required for combustion. The maximum offset of the combustion cone refers to the maximum angle of deviation of the tobacco combustion zone (i.e., the combustion cone) relative to the cigarette axis during combustion. Generally, the smaller the offset, the more uniform the combustion process. A combustion cone with a large offset may lead to uneven tobacco combustion, affecting the drawing experience and quality of the cigarette.

[0003] The porosity of the combustion cone affects the combustion uniformity of cigarettes. Higher porosity facilitates airflow, resulting in more even combustion and reducing localized overheating or incomplete combustion. If the porosity is too low, poor airflow can lead to uneven combustion or even flameout. Furthermore, appropriate porosity allows for better release of aroma components in the smoke, improving the aroma quality of the cigarette; it also affects the smoke velocity and flow rate, thus influencing the sensory evaluation of the cigarette. Therefore, accurate detection of the combustion cone morphology is crucial for optimizing cigarette design and improving product quality.

[0004] Chinese Patent (CN118746263A) discloses a method for evaluating the tendency of the cigarette combustion cone to fall. This patent uses a robotic arm simulation device to simulate smoking cigarettes and measures the maximum deviation of the cigarette combustion cone. Then, it uses an angle summation and averaging method to sum the maximum deviations of the cigarette combustion cones measured from multiple cigarettes and calculate the average value. The tendency of the cigarette combustion cone to fall is then evaluated using this average value. Chinese Patent (CN114877844A) discloses a method for detecting the stability of the cigarette smoking process. This patent method simulates the process of human cigarette smoking, obtains images of the combustion cone with different numbers of puffs and measures the cone height. It uses a Peer model to fit the curve of the cone height change during each puff and evaluates the stability of the cone height during cigarette smoking based on the change in the combustion cone height during each puff.

[0005] However, the aforementioned patents all use the morphological characteristics of the combustion cone, such as deviation and height, as key quality indicators and employ two-dimensional image processing technology to achieve automated measurement. However, whether measuring deviation or height, they rely on two-dimensional projection images at a single or limited angle. This two-dimensional method cannot capture the complete three-dimensional morphology of the combustion cone; therefore, its measurement results are easily affected by factors such as the shooting angle, cigarette rotation, and the irregular shape of the combustion cone, resulting in a theoretical ceiling to measurement accuracy and robustness.

[0006] In order to solve the above problems, people have been seeking an ideal technological solution. Summary of the Invention

[0007] Based on this, it is necessary to provide a method for detecting the morphology and porosity of the combustion cone to address the above-mentioned technical problems. This method scans the cigarette combustion cone to obtain its three-dimensional spatial structure information, and then calculates the height, volume, maximum offset, and porosity of the combustion cone. This effectively solves the problem of angular influence involved in calculating the maximum offset of the combustion cone based on two-dimensional images, thereby significantly improving the accuracy of the calculation results.

[0008] To achieve the above objectives, the first aspect of the present invention provides a method for detecting the morphology and porosity of a combustion cone, comprising:

[0009] CT tomographic images of cigarette samples after combustion were acquired and three-dimensional reconstruction was performed to obtain three-dimensional reconstructed images;

[0010] The three-dimensional reconstructed image is processed by image segmentation to obtain a three-dimensional image and point cloud dataset of the cigarette combustion cone portion;

[0011] Calculate the height and maximum offset of the combustion cone based on the point cloud dataset of the cigarette combustion cone portion:

[0012] The formula for calculating height is: h=z n -z1

[0013] In the formula, z n z is the z-value at the apex of the combustion cone, and z1 is the z-value at the base of the combustion cone;

[0014] The formula for calculating the maximum offset is:

[0015]

[0016] In the formula, (a,b,z1) are the coordinates of the center point of the bottom surface of the combustion cone; (x n ,y n ,z n () represents the coordinates of the combustion cone's vertex;

[0017] The combustion cone volume and porosity were calculated based on a three-dimensional image of the cigarette combustion cone.

[0018] This technical solution employs CT scanning technology, utilizing the strong penetrating power of X-rays to non-destructively penetrate the outer packaging layer of cigarettes and obtain their internal three-dimensional spatial structure information. By performing image segmentation processing on the three-dimensional spatial structure information, a three-dimensional image and point cloud dataset of the cigarette's combustion cone are obtained. Then, based on the point cloud dataset, the height and maximum offset of the combustion cone are calculated, and based on the three-dimensional image of the combustion cone, the volume and porosity of the combustion cone are calculated. This fundamentally solves the problem of the difficulty in non-destructive testing of porosity and improves the detection results.

[0019] To achieve the above objectives, a second aspect of the present invention provides a combustion cone morphology and porosity detection device, comprising:

[0020] The acquisition module is configured to acquire CT tomographic images of cigarette samples after combustion and perform three-dimensional reconstruction to obtain three-dimensional reconstructed images;

[0021] The image segmentation module is configured to perform image segmentation processing on the three-dimensional reconstructed image to obtain a three-dimensional image and point cloud dataset of the cigarette combustion cone portion;

[0022] The shape recognition module is configured to calculate the height and maximum offset of the combustion cone based on the point cloud dataset of the cigarette combustion cone portion:

[0023] The formula for calculating height is: h=z n -z1

[0024] In the formula, z n z is the z-value at the apex of the combustion cone, and z1 is the z-value at the base of the combustion cone;

[0025] The formula for calculating the maximum offset is:

[0026]

[0027] In the formula, (a,b,z1) are the coordinates of the center point of the bottom surface of the combustion cone; (x n ,y n ,z n () represents the coordinates of the combustion cone's vertex;

[0028] The porosity detection module is configured to calculate the combustion cone volume and porosity based on a three-dimensional image of the cigarette combustion cone portion.

[0029] To achieve the above objectives, a third aspect of the present invention provides a computer device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus.

[0030] Memory, used to store computer programs;

[0031] The processor, when executing a program stored in memory, implements the combustion cone morphology and porosity detection method as described in the first aspect.

[0032] To achieve the above objectives, a fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the combustion cone morphology and porosity detection method as described in the first aspect.

[0033] To achieve the above objectives, the fifth aspect of the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the combustion cone morphology and porosity detection method steps as described in the first aspect.

[0034] The beneficial effects of this invention are as follows:

[0035] This invention utilizes industrial CT technology to precisely scan samples, enabling efficient acquisition of three-dimensional point cloud data and cross-sectional image data of cigarette combustion cones. Compared to traditional measurement techniques, this method significantly reduces errors caused by manual operation and equipment limitations, thereby ensuring high accuracy in geometric characteristic measurements.

[0036] Furthermore, based on the three-dimensional point cloud data and cross-sectional image data extracted from CT scan data, this invention can accurately calculate key parameters such as the height, volume, maximum offset, and porosity of the combustion cone. These parameters not only cover the geometric characteristics of the combustion cone but also involve its physical properties, making the overall evaluation of the combustion cone more comprehensive and detailed. Attached Figure Description

[0037] Figure 1 This is a schematic flowchart of the combustion cone morphology and porosity detection method described in Embodiment 1 of the present invention;

[0038] Figure 2This is a schematic diagram of CT scan operation.

[0039] Figure 3 This is a schematic diagram of a CT scan.

[0040] Figure 4 Image of a cigarette combustion cone cross-section;

[0041] Figure 5 A three-dimensional reconstruction model of the cigarette combustion cone.

[0042] In the figure, 1. X-ray source; 2. Platform; 3. Sample base; 4. Sample holder; 5. Flat panel detector; 6. Virtual flat panel detector. Detailed Implementation

[0043] To address the aforementioned issues, this invention proposes a method for detecting the morphology and porosity of a combustion cone. By scanning the cigarette combustion cone, its original morphology in three-dimensional space can be accurately reconstructed, providing a more precise quantitative basis for analyzing cigarette combustion characteristics. Based on the three-dimensional spatial structure, the height, volume, maximum offset, and porosity of the combustion cone are calculated, effectively solving the angular influence problem involved in calculating the maximum offset of the combustion cone based on two-dimensional images, thereby significantly improving the accuracy of the calculation results.

[0044] The technical solution of the present invention will be further described in detail below through specific embodiments.

[0045] Example 1

[0046] This embodiment provides a method for detecting the morphology and porosity of a combustion cone, such as... Figure 1 As shown, it includes the following steps:

[0047] S1. Sample preparation. Specifically:

[0048] The cigarette was placed in the smoking machine and the smoking operation was performed according to the national ISO standard. The smoking cycle was set to 60 seconds, the smoking volume to 35 ml, and the smoking duration to 2 seconds. After each smoking cycle, the cigarette was extinguished with nitrogen gas so that it could be used as a sample for CT detection.

[0049] S2, acquire CT tomographic images of the cigarette sample after combustion and perform three-dimensional reconstruction to obtain a three-dimensional reconstructed image.

[0050] Specifically, the detection structure of the CT equipment is as follows: Figure 2 As shown, the specific detection process includes:

[0051] S21, use the sample holder 4 to fix the cigarette sample, and adjust the position of the cigarette sample to ensure that the cigarette sample is perpendicular to the sample base 3.

[0052] S22, turn on the CT equipment, place the sample holder 4 into the slot of the platform 2 inside the CT equipment, and ensure that the sample holder 4 is fixed on the platform 2 to prevent the sample from falling off when the platform 2 rotates.

[0053] S23, set the X-ray source tube voltage to 150kV, X-ray source tube current to 90μA, scanning thickness to 0.004mm, scanning interval to 0.004mm, CT scanning mode to cone-beam scanning, and CT scanning mode to Normal scanning. Move the platform 2 on the stage to center the sample under test within the X-ray scanning range. Control the rotation of the platform 2 to ensure that the cigarette sample within a 360° range is in the X-ray scanning position.

[0054] S24, remove the sample holder 3, perform air calibration on the CT equipment, place the central axis calibration rod on the platform 2, and perform central axis calibration.

[0055] S25, place the sample holder 4 on the platform 2, start the CT scan to scan the inside of the cigarette sample, collect two-dimensional projection data at different angles according to the rotation interval, and transmit the digital signal received by the flat panel detector 5 to the computer for storage.

[0056] Specifically, the schematic diagram of a CT scan is as follows: Figure 3 As shown.

[0057] S26, Preprocess the acquired CT tomographic images.

[0058] The two-dimensional projection data acquired at each angle during the aforementioned CT scan are weighted to correct the cone-beam distortion. The formula is as follows:

[0059]

[0060] In the formula, P W (β,a,b) is the weighted two-dimensional projection data; P(β,a,b) is the collected two-dimensional projection data. β is the weighting factor; β is the angle of X-ray emission; a, b are the horizontal and vertical coordinates of the pixel to be reconstructed mapped onto the virtual detector 6.

[0061] S27. The corrected and weighted projection data is then subjected to one-dimensional filtering along the projection of the flat panel detector 5, which is perpendicular to the CT equipment. The formula is as follows:

[0062]

[0063] In the formula, is the filtered data; H(a) is the convolution kernel.

[0064] S28, Reconstruct the image by backprojecting the above data.

[0065] One-dimensional filtered projection data along the X-ray direction The back projection calculation is performed using the following formula:

[0066]

[0067] In the formula, R is the distance from the ray source to the rotation center; U is similar to the weighting factor in the two-dimensional equidistant fan beam projection reconstruction algorithm, and its calculation method is: U(x,y,β)=R+xcosβ+ysinβ.

[0068] In the aforementioned back-projection reconstructed image, due to the large spacing along the Z-axis during sampling, interpolation calculations are required along the Z-axis. Bilinear interpolation is used here, and the specific process is as follows:

[0069] Select the four pixels closest to the pixel P(x,y) to be interpolated, and denote them as Q. 11 (x1,y1),Q 12 (x1,y2),Q 21 (x2,y1),Q 22 (x2, y2). First, interpolation is performed in the x-direction, with the following formula:

[0070]

[0071] Next, interpolation is performed in the y-direction, using the following formula:

[0072]

[0073] Thus, the final pixel value of the pixel P to be interpolated is obtained.

[0074] Through the above steps, a three-dimensional reconstruction model of the cigarette inside the cigarette sample can now be constructed, such as... Figure 4 As shown and Figure 5 As shown.

[0075] S3. Perform image segmentation processing on the reconstructed 3D image to obtain a 3D image and point cloud dataset of the cigarette combustion cone portion. Specifically, this includes:

[0076] S31, use image processing software such as threshold segmentation, edge detection or instance segmentation to segment the scanned cigarette sample image and extract the cigarette combustion cone part as a new region of interest.

[0077] S32, extract the newly extracted combustion cone portion image into a point cloud set D, which contains the three-dimensional coordinates (x, y, z) of each point in the combustion cone portion.

[0078] S4. Based on the combustion cone point cloud dataset D obtained in S3, calculate the height of the combustion cone portion. Specifically:

[0079] S41. Divide all points in the point cloud set D into n point cloud subsets D according to their z values. i .

[0080] Where the z-values ​​of all points in the D1 point cloud subset are the minimum z1 among all point clouds, D n The z-values ​​of all points in a subset of a point cloud are the maximum z-values ​​among all points in the point cloud. n .

[0081] S42, calculate the distance between the highest and lowest points of the cigarette's combustion cone, which is the actual height h of the combustion cone. The calculation formula is as follows:

[0082] h=z n -z1

[0083] S5. Based on the combustion cone point cloud dataset D obtained in S4, calculate the maximum offset of the combustion cone. Specifically:

[0084] S51, a subset D of the point cloud based on the vertices of the burning cone. n Calculate the coordinates of the center point of all points in the cloud subset. First, calculate the distance from each point in the set to all other points. Since the z-values ​​of all points in the cloud subset are equal, only the x and y coordinates are considered. The calculation formula is as follows:

[0085]

[0086] For each point, the distance to all other points is denoted as the distance set L. i Where L1 is the set of distances from the first point to all other points, L n That is, the set of distances from the nth point to all other points.

[0087] Based on the distance sets obtained above, calculate the variance of each distance set. The point with the smallest variance indicates that the distances from that point to other points are most uniform, and it can be identified as the center point of the planar point cloud. Record its coordinates (x, y). n ,y n ).

[0088] S52, based on the point cloud subset D1 of the combustion cone's base, calculate the coordinates of the center points of all points in this subset. First, fit a circle to the point cloud subset, assuming the circle's equation is:

[0089] .

[0090] In the formula, (a,b) are the coordinates of the center of the circle, and r is the radius of the circle.

[0091] For all points in the point cloud subset D1, calculate the distance from each point to the nearest point on the circle using the following formula:

[0092]

[0093] The formula for calculating the sum of the squared distances from all points to the nearest point on the circle is:

[0094]

[0095] By minimizing the above objective function, the optimal model for fitting the circle is finally obtained.

[0096] S53. Based on the calculation results of S51 and S52, calculate the equation of the straight line L1 perpendicular to the bottom surface of the combustion cone and the equation of the straight line L2 from the top of the combustion cone to the center point of the bottom surface of the combustion cone.

[0097] Given that the coordinates of the center point of the combustion cone's base are (a, b, z1) and the equation of the normal is (0, 0, 1), then the equation of line L1 is:

[0098]

[0099] Given that the coordinates of the center point of the base of the combustion cone are (a, b, z1) and the coordinates of the vertex of the combustion cone are (x, b, z1)... n ,y n ,z n If ), then the equation of line L2 is:

[0100]

[0101] The angle between L1 and L2 is the maximum offset of the combustion cone, and its calculation formula is as follows:

[0102]

[0103] S6. Calculate the volume of the combustion cone based on the 3D image of the cigarette's combustion cone. Specifically:

[0104] S61 identifies the boundary of the combustion cone in the cross-sectional image and segments it from the surrounding air region, aiming to accurately distinguish the boundary between the combustion cone region and the surrounding environment.

[0105] S62, Based on the segmentation results, count the pixels in the region to obtain the number of pixels n inside the combustion cone. i .

[0106] S63, calculate the number of pixels between adjacent sections, the formula is:

[0107]

[0108] S64, sum up the number of pixels between all adjacent sections, and the resulting number of pixels is the total number of elements contained in the combustion cone.

[0109] The volume of the combustion cone can be obtained by converting the voxel size to the actual size based on the resolution set during CT imaging.

[0110] S7. Based on the three-dimensional image of the cigarette combustion cone, calculate the porosity of the combustion cone. Specifically:

[0111] S71, based on the combustion cone boundary identified in S61, divides the combustion cone portion from the surrounding air portion, thereby obtaining the combustion cone region that excludes the surrounding air.

[0112] S72, based on the different grayscale values ​​of the tobacco shreds and pores in the combustion cone, a certain threshold is set to divide them, and the number of pixels in the divided tobacco shreds portion is recorded as k. i The total number of pixels is n. i .

[0113] S73, calculate the porosity in each cross-section using the following formula:

[0114]

[0115] S74, calculate the average porosity of all cross-sections, which is the overall porosity of the combustion cone section. The calculation formula is as follows:

[0116]

[0117] This invention utilizes industrial CT technology to precisely scan samples, enabling efficient acquisition of three-dimensional point cloud data and cross-sectional image data of cigarette combustion cones. Compared to traditional measurement techniques, this method significantly reduces errors caused by manual operation and equipment limitations, thereby ensuring high accuracy in geometric characteristic measurements.

[0118] It is understandable that the order of steps S5-S7 is not strictly limited during the actual calculation, and in some embodiments, S5-S7 can be performed simultaneously.

[0119] Furthermore, based on the three-dimensional point cloud data and cross-sectional image data extracted from CT scan data, this invention can accurately calculate key parameters such as the height, volume, maximum offset, and porosity of the combustion cone. These parameters not only cover the geometric characteristics of the combustion cone but also involve its physical properties, making the overall evaluation of the combustion cone more comprehensive and detailed.

[0120] It should be understood that although the steps in the flowcharts involved in the above embodiments are sequentially shown according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0121] Embodiment 2

[0122] Based on the same inventive concept, an embodiment of the present application further provides a combustion cone morphology and porosity detection device for implementing the combustion cone morphology and porosity detection method described above. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the combustion cone morphology and porosity detection device provided below can refer to the limitations on the combustion cone morphology and porosity detection method in the above text, and will not be elaborated here.

[0123] The combustion cone morphology and porosity detection device includes:

[0124] An acquisition module, configured to acquire a CT tomographic image of a whole pack of cigarette samples and perform three-dimensional reconstruction to obtain a three-dimensional reconstruction image of the whole pack (strip) of cigarette samples;

[0125] An image segmentation module, configured to perform image segmentation processing on the three-dimensional reconstruction image to obtain a three-dimensional image of the tobacco filling section of a single cigarette;

[0126] A stem identification module, configured to perform image segmentation on the stems and tobacco in the three-dimensional image of the tobacco filling section of a single cigarette based on a density threshold, and perform a quantitative statistical analysis on the stem part in a single cigarette through clustering analysis to obtain the stem content of a single cigarette; calculate the total stem content and the standard deviation of the stem content in the whole pack (strip) of cigarettes based on the stem content of a single cigarette;

[0127] Among them, the calculation formula for the total stem content is:

[0128] The calculation formula for the standard deviation of the stem content is , , is the number of stems contained in the i-th cigarette.

[0129] Embodiment 3

[0130] This embodiment provides a computer device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0131] Memory, used to store computer programs;

[0132] The processor, when executing the program stored in the memory, implements the combustion cone morphology and porosity detection method as described in Example 1.

[0133] Example 4

[0134] Based on the above embodiments, this embodiment provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the combustion cone morphology and porosity detection method described in Embodiment 1.

[0135] Example 5

[0136] Based on the above embodiments, this embodiment provides a computer program product, including a computer program that, when executed by a processor, implements the combustion cone morphology and porosity detection method described in Embodiment 1.

[0137] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them; although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications can still be made to the specific implementation of the present invention or equivalent substitutions can be made to some technical features without departing from the spirit of the technical solutions of the present invention, and all such modifications and substitutions should be covered within the scope of the technical solutions claimed in the present invention.

Claims

1. A method for detecting the morphology and porosity of a combustion cone, characterized in that, include: CT tomographic images of cigarette samples after combustion were acquired and three-dimensional reconstruction was performed to obtain three-dimensional reconstructed images; The three-dimensional reconstructed image is processed by image segmentation to obtain a three-dimensional image and point cloud dataset of the cigarette combustion cone portion; Calculate the height and maximum offset of the combustion cone based on the point cloud dataset of the cigarette combustion cone portion: The formula for calculating height is: h=z n -z1 In the formula, z n z is the z-value at the apex of the combustion cone, and z1 is the z-value at the base of the combustion cone; The formula for calculating the maximum offset is: In the formula, (a,b,z1) are the coordinates of the center point of the bottom surface of the combustion cone; (x n ,y n ,z n () represents the coordinates of the combustion cone's vertex; The combustion cone volume and porosity were calculated based on a three-dimensional image of the cigarette combustion cone.

2. The method for detecting the morphology and porosity of a combustion cone according to claim 1, characterized in that, The steps for obtaining cigarette samples after combustion include: The cigarette sample was placed in the smoking machine and the smoking operation was performed according to the national ISO standard. The smoking cycle was set to 60 seconds, the smoking volume to 35 ml, and the smoking duration to 2 seconds. After each smoking cycle, the cigarette was extinguished with nitrogen gas so that it could be used as a sample for CT detection.

3. The method for detecting the morphology and porosity of a combustion cone according to claim 1 or 2, characterized in that, Calculating the combustion cone volume based on a 3D image of the cigarette combustion cone portion, including: Image segmentation is performed on the three-dimensional image of the cigarette combustion cone, and the combustion cone region is extracted as the region of interest; The region of interest is segmented, and two-dimensional cross-sectional images are extracted at each continuous height along the Z-axis; Count the number of pixels n in each two-dimensional cross-sectional image. i And calculate the number of pixels between adjacent sections, the formula is: In the formula, n i+1 The number of pixels in the (i+1)th section; The total number of pixels between all adjacent sections is summed to determine the total number of elements contained in the combustion cone. The volume of the combustion cone is obtained by converting the voxel size to the actual size based on the resolution set during CT imaging.

4. The method for detecting the morphology and porosity of a combustion cone according to claim 3, characterized in that, The porosity of the combustion cone is calculated based on a three-dimensional image of the cigarette combustion cone, including: After extracting each two-dimensional cross-sectional image, the tobacco shreds and gaps in the two-dimensional cross-sectional image are segmented based on the threshold segmentation method, and the number of pixels in the tobacco shred part and the total number of pixels are counted. The porosity of each cross section is calculated based on the number of pixels in the tobacco shreds and the total number of pixels. Calculate the average porosity of all cross sections as the overall porosity of the combustion cone section.

5. The method for detecting the morphology and porosity of a combustion cone according to claim 4, characterized in that, Obtain CT tomographic images of the burned cigarette sample, including: Use a sample holder to fix the cigarette sample, and adjust the position of the cigarette sample to ensure that the cigarette sample is perpendicular to the sample base. Turn on the CT equipment and place the sample holder into the mounting platform slot inside the CT equipment, ensuring that the sample holder is fixed on the mounting platform; The X-ray source tube voltage is set to 100kV, the X-ray source tube current to 70μA, the scanning thickness to 0.004mm, the scanning interval to 0.004mm, the CT scanning mode to cone-beam scanning, and the CT scanning mode to Normal scanning. The worktable is moved to position the cigarette sample in the center of the X-ray scanning range; the rotation of the worktable is controlled to ensure that the cigarette sample is in the X-ray scanning position within a 360° range. Remove the sample holder, perform air calibration on the CT equipment, and place the central axis calibration rod on the platform to perform central axis calibration. Place the sample holder on the platform and start the CT scan to scan the inside of the cigarette sample. Collect two-dimensional projection data at different angles according to the rotation interval.

6. The method for detecting the morphology and porosity of a combustion cone according to claim 5, characterized in that, The steps to obtain a 3D reconstructed image include: The two-dimensional projection data collected at each angle are weighted. The weighted projection data is filtered in one dimension along the projection of the flat panel detector perpendicular to the CT equipment. Back projection calculations were performed on the one-dimensional filtered projection data along the X-ray direction to obtain a three-dimensional reconstruction model of the cigarette inside the filter rod sample. In the back projection calculation process, bilinear interpolation is used to perform interpolation calculations in the Z-axis direction.

7. A device for detecting the morphology and porosity of a combustion cone, characterized in that, include: The acquisition module is configured to acquire CT tomographic images of cigarette samples after combustion and perform three-dimensional reconstruction to obtain three-dimensional reconstructed images; The image segmentation module is configured to perform image segmentation processing on the three-dimensional reconstructed image to obtain a three-dimensional image and point cloud dataset of the cigarette combustion cone portion; The shape recognition module is configured to calculate the height and maximum offset of the combustion cone based on the point cloud dataset of the cigarette combustion cone portion: The formula for calculating height is: h=z n -z1 In the formula, z n z is the z-value at the apex of the combustion cone, and z1 is the z-value at the base of the combustion cone; The formula for calculating the maximum offset is: In the formula, (a,b,z1) are the coordinates of the center point of the bottom surface of the combustion cone; (x n ,y n ,z n () represents the coordinates of the combustion cone's vertex; The porosity detection module is configured to calculate the combustion cone volume and porosity based on a three-dimensional image of the cigarette combustion cone portion.

8. A computer device, characterized in that: It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; The processor, when executing a program stored in memory, implements the combustion cone morphology and porosity detection method as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the combustion cone morphology and porosity detection method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the combustion cone morphology and porosity detection method according to any one of claims 1 to 6.

Images