A method for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in heated non-combustible cigarettes.

Abstract

A method for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in heated non-combustible cigarettes is disclosed. First, a physical parameter S, namely the tobacco spatial distribution state index, is defined. The three-dimensional structure of the cigarette is digitized using industrial CT scanning. A two-dimensional image of the tobacco shred distribution inside the cigarette is obtained through filtered back-projection technology. Then, a three-dimensional reconstruction model of the cigarette is obtained through three-dimensional reconstruction and interpolation techniques. This model reflects the distribution state of the tobacco shreds inside the cigarette. Finally, the spatial distribution state of the tobacco shreds is quantitatively characterized using an image-based method. The advantages of this invention are: 1) The three-dimensional distribution state of tobacco shreds in cigarettes detected by CT scanning and reconstruction yields accurate and reliable results; 2) The spatial distribution state index defined by this method can effectively characterize the spatial distribution state of tobacco shreds in cigarettes; 3) This method can not only be used for quantitative analysis of the degree of spatial distribution state of tobacco shreds, but also provide guidance for the optimization and improvement of parameters in different tobacco processing and rolling processes.

Description

Technical Field

[0001] This invention relates to the field of cigarette processing, and in particular to a method for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in heated non-combustible cigarettes. Background Technology

[0002] Heated tobacco cigarettes are mostly made from reconstituted tobacco sheets cut into shreds, and have similar shapes and uniform quality. At the same time, the spatial distribution of tobacco shreds inside the cigarette is more regular and orderly than that of traditional cigarettes.

[0003] Heated cigarettes typically employ internal or surround electric heating methods. The spatial distribution of tobacco shreds, arranged in a specific order, helps maintain consistency in the quality of the generated smoke, ensuring stable draw resistance and smoke quality during the smoking process, as well as consistent sensory quality, highlighting the product's quality and style characteristics, thereby enhancing the consumer experience. With the global popularity of heated cigarettes and their rapid growth in domestic market share, the industry urgently needs methods for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in heated cigarettes. Currently, however, this field lacks such methods.

[0004] Chinese Patent (202210709131.1) discloses a method for detecting the orderliness of tobacco shreds in cigarettes based on CT scanning technology. This invention can obtain the overall structure of a cigarette based on CT scanning and three-dimensional reconstruction technology, and realize the automatic judgment and distribution law statistics of tobacco shreds inside the cigarette, thereby achieving rapid and non-destructive detection and determination of the orderliness of tobacco shreds. Compared with the method proposed in this application, the two mainly differ in the following aspects: First, in terms of technical means, although both adopt the CT scanning three-dimensional reconstruction method, Chinese Patent (202210709131.1) requires the prior establishment of a CT database of tobacco shreds, packaging paper, filter rod, and rolling paper materials to obtain CT grayscale images of the tobacco shreds, packaging paper, filter rod, and rolling paper areas of the cigarette to be tested. In contrast, this invention directly performs CT scanning on a single cigarette, and then uses filtering back projection technology and filtering preprocessing technology to obtain a two-dimensional CT image. The process is simpler and effectively reduces the complexity of CT scanning values, which is beneficial for subsequent three-dimensional reconstruction of the cigarette structure. Secondly, the two methods differ. Chinese patent (202210709131.1) projects tobacco shreds onto three mutually perpendicular planes, decomposing the projected image into several projected arcs. It then measures the acute angle between each arc and the straight line, obtaining several angle values. The percentage of the ratio of the mean of all angle values ​​to 90° is determined as the orderliness rate of a single tobacco shred. This invention establishes a three-dimensional rectangular coordinate system. Through an established three-dimensional reconstruction model, it obtains the feature line direction vector of the reconstructed thin-sheet tobacco shreds and calculates the spatial angle between this vector and the Z-axis direction vector. This value represents the spatial distribution state of a single tobacco shred. This invention more simply and directly represents the spatial characteristics of a single tobacco shred. Thirdly, this invention extracts tobacco shreds as feature lines with a width of 1 voxel, simplifying the spatial representation of tobacco shreds and facilitating subsequent detection of the spatial distribution state of the tobacco shreds.

[0005] In summary, the use of industrial CT scanning to digitize the three-dimensional structure of cigarettes, the obtaining of two-dimensional images of the distribution of tobacco shreds inside the cigarette through filtering back projection technology and noise filtering preprocessing technology, and the obtaining of a three-dimensional reconstruction model of the cigarette through three-dimensional reconstruction technology and interpolation technology, can reflect the distribution state of tobacco shreds inside heated non-combustible cigarettes. Finally, the quantitative characterization of the spatial distribution state of tobacco shreds using image method, and the quantitative characterization research is still in its infancy. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of existing technologies and provide a method for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in heated non-combustible cigarettes. This method defines a physical parameter S (spatial distribution index of tobacco shreds) and calculates the spatial distribution index using an image method. The calculation results show that the spatial distribution index can well reflect the spatial distribution of tobacco shreds in the cigarette.

[0007] The objective of this invention is achieved through the following technical solution:

[0008] A method for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in heated non-combustible cigarettes involves digitizing the three-dimensional structure of the cigarette through industrial CT scanning, obtaining a two-dimensional image of the tobacco shred distribution within the cigarette using filtered back projection technology, and then obtaining a three-dimensional reconstruction model of the cigarette using three-dimensional reconstruction and interpolation techniques. This model reflects the distribution of tobacco shreds within the cigarette. Finally, the spatial distribution of tobacco shreds is quantitatively characterized using image-based methods. The specific steps are as follows:

[0009] (1) Place the cigarette to be tested on the stage of the CT equipment, keep it vertical with a clamp and ensure that the tobacco part is within the CT scan range;

[0010] (2) Start the CT scanning device to scan the cigarette. The digital flat panel detector will transmit and save the received signal to the computer.

[0011] (3) The data processing system in the computer uses the Filtered Back Projection Algorithm (FDK algorithm) to process the acquired data and obtain a two-dimensional image of the distribution of tobacco inside the heated cigarette.

[0012] (4) The image processing system in the computer performs image matching, image smoothing, and image enhancement on the two-dimensional CT image sequence in order to perform edge extraction and image segmentation; interpolates images between adjacent two-dimensional CT images to improve the accuracy of the three-dimensional reconstruction model; finally, the image processing system reconstructs the three-dimensional structural model and extracts the image of the tobacco skeleton inside the cigarette.

[0013] (5) Select the central voxels of the two ends of the skeleton image respectively, connect the two central voxels into a line segment, and regard this line segment as the spatial distribution feature line of tobacco: the width is 1 voxel point, the length is n voxel points, and the length of the line is the length of tobacco L.

[0014] (6) Establish a three-dimensional spatial coordinate system (with the direction of the central axis of the tobacco as the z-axis) by taking the first voxel point near the lower end of the tobacco branch as the origin, and determine the standard direction vector of the feature line in this coordinate system.

[0015] (7) Calculate the spatial angle between this direction vector and the direction vector (0, 0, 1) of the central axis direction. The calculation formula is as follows:

[0016]

[0017] In the formula, k1 is the standard direction vector of the tobacco characteristic line, k2 is the direction vector of the central axis (0, 0, 1), and θ is the spatial angle.

[0018] (8) Perform 5-7 operation steps on each tobacco shred to obtain the spatial angle of all tobacco shreds. During this process, the three-dimensional spatial coordinate system is established, except that the origin changes to the midpoint voxel of the tobacco shred near the lower end of the cigarette stick. The other three axes remain unchanged.

[0019] (9) Compare the standard direction vectors of tobacco characteristic lines with the same spatial angle. Based on whether the standard direction vectors are the same, classify the tobacco characteristic lines and count their number n. j Then the correction coefficient for the spatial distribution of tobacco shreds is defined as follows: In the formula, n max For n j The maximum value in.

[0020] (10) The spatial distribution of tobacco shreds within a cigarette is a holistic concept. Therefore, evaluating the spatial distribution of tobacco shreds within the entire cigarette requires a comprehensive assessment of the spatial distribution index of all tobacco shreds to obtain the overall spatial distribution of tobacco shreds within the cigarette.

[0021] S, the spatial distribution state index of tobacco shreds;

[0022]

[0023] In the formula, S is the spatial distribution index of tobacco shreds in the cigarette. The correction factor is m, where m is the number of tobacco strands inside the cigarette, and cosθ is the number of tobacco strands inside the cigarette. i It is a spatial angle function for a single tobacco shred.

[0024] The cigarette imaging technology employs CT scanning imaging technology and three-dimensional reconstruction technology.

[0025] The advantages of this invention are: (1) the three-dimensional distribution state of tobacco shreds in cigarettes is detected by CT scanning three-dimensional reconstruction method, and the results are real and reliable; (2) the spatial distribution state index defined by this method can better characterize the spatial distribution state of tobacco shreds in cigarettes; (3) this method can not only be used for quantitative analysis of the degree of spatial distribution state of tobacco shreds, but also provide guidance for the optimization and improvement of parameters of different tobacco processing and rolling processes. Attached Figure Description

[0026] Figure 1 The flowchart shows the method for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in heated non-combustible cigarettes provided by the present invention.

[0027] Figure 2 A schematic diagram of the spatial distribution of tobacco shreds in heated non-combustible cigarettes;

[0028] Figure 3 A schematic diagram of the spatial distribution of a single tobacco shred.

[0029] Figure 4This is a diagram of the cone-beam scanning structure of a planar detector.

[0030] Figure 4 In the diagram: γ is the angle between the ray and the central ray, β is the angle formed by the central ray and the y-axis, called the projection angle, and κ is the cone angle in the Z-axis direction of the cone beam.

[0031] In the figure, the ab coordinate system is the coordinate system on the virtual detector. In this patent, a, b and a(x,y,β) and b(x,y,z,β) are the same, all representing the coordinate information on the virtual detector. Among them, x, y, z and β represent the expression factors of the ab coordinate system in the xyz coordinate system, that is, (a,b) can be converted to (x,y,z) and express the same spatial position information in different coordinate systems. Detailed Implementation

[0032] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0033] 1. Place the cigarette to be tested on the stage of the industrial CT equipment, keep it vertical with clamps and ensure that the tobacco part is within the CT scanning range; the cigarette sample to be tested needs to be placed in the equilibration chamber for temperature and humidity equilibration before the experiment. The specific values ​​are: temperature 22℃, relative humidity 65%, equilibration time of more than 24 hours.

[0034] 2. Start the CT scanning device to scan the cigarette. The digital flat panel detector transmits and saves the received signals to the computer. Before scanning the cigarette, the industrial CT equipment needs to be pre-set with the following parameters: image size of 2048x2048, X-ray source tube voltage of 100kV, X-ray source tube current of 70uA, scanning thickness of 0.004mm, scanning interval of 0.004mm, CT scanning method of cone-beam scanning, and CT scanning mode of Normal scanning.

[0035] 3. The data processing system in the computer uses the Filtered Back Projection (FDK) algorithm to process the acquired data, obtaining a two-dimensional image of the distribution of tobacco shreds inside the heated cigarette. The FDK algorithm mainly includes several steps: pre-weighting of the projection data, one-dimensional filtering, and back projection.

[0036] (1) First, the projection data is weighted using a function similar to cosine, and the distance and angle difference between the voxel and the source point are appropriately corrected.

[0037] (2) Then, perform one-dimensional filtering in the horizontal direction on the projection data of different projection angles;

[0038] (3) Perform a weighted back projection of the filtered data using a cone-beam scanner. The weight function in the back projection depends on the distance from the reconstructed point to the focal point. See the attached diagram for a cone-beam scanning structure with a planar detector. Figure 4 .

[0039] The FDK reconstruction algorithm for flat panel detectors can be expressed by the following formula:

[0040]

[0041]

[0042] Where R represents the radius of rotation. b(x,y,z,β)) represents the filtered projection data, g(a) is the filtering function, and U(x,y,β)) represents the distance of the reconstructed pixel in the xy plane to the X-ray source. Here, a and b represent the coordinates on the virtual detector.

[0043]

[0044] a(x,y,β) represents the horizontal position of the corresponding ray on the virtual detector, and the corresponding vertical position can be represented as...

[0045]

[0046] The weighted function can be decomposed into the following expression:

[0047]

[0048] Z is the Z-axis coordinate of the point to be reconstructed. Similarly, we can obtain the length of U based on geometric relationships.

[0049] U(x,y,β)=R+xcosβ+ysinβ

[0050] The weighting factor U is similar to the weighting factor in the two-dimensional filtering back projection algorithm. Geometrically, it is related to the projection of the line connecting the ray source point and the reconstructed image onto the intermediate ray.

[0051] 4. The image processing system in the computer performs image matching, smoothing, and enhancement operations on the 2D CT image sequence to facilitate edge extraction and image segmentation; it also interpolates between adjacent 2D CT images to improve the accuracy of the 3D reconstruction model; finally, the image processing system reconstructs the 3D structural model. In CT scan images, the spacing in the X and Y directions is equal during sampling, with a larger difference only in the Z direction. Therefore, linear interpolation is performed in the Z direction. The calculation formula is:

[0052]

[0053] In the formula, P1 and P2 are the CT values ​​of corresponding points in adjacent CT images, a1 and a2 are the Z-axis distances of the two corresponding points from the interpolation point, and P is the CT value of the interpolation point.

[0054] Multifractal spectrum technology is used to extract the internal and contour features of each cigarette CT image. The images are then analyzed using their visual appeal. The range of spectral values ​​in the multifractal spectrum theory is set, and the edges of the cigarette CT images are detected and extracted. The contour of the three-dimensional image is drawn using the edge information extracted from each cigarette CT image. The original cigarette CT image and the contour image extracted by using linear interpolation are then integrated to form a three-dimensional reconstruction model.

[0055] 5. Select the middle voxels of the two short sides of the skeleton image, connect the two middle voxels into a line segment, and regard this line segment as the spatial distribution feature line of the tobacco: the width is 1 voxel point, the length is n voxel points, and the length of this line is the length L of the tobacco.

[0056] 6. Starting from the first voxel point at any end of the obtained characteristic line of the spatial distribution of tobacco shreds, establish a three-dimensional spatial coordinate system (with the direction of the central axis of the tobacco stick as the z-axis direction), and determine the standard direction vector of the characteristic line in this coordinate system; specifically, industrial CT scanning equipment can obtain the overall point cloud data of the tobacco stick, which includes three-dimensional coordinates X, Y, Z, etc. Using the point cloud data, the coordinates of any two points on the characteristic line can be accurately obtained, thereby obtaining the expression of the characteristic line and its direction vector.

[0057] 7. Calculate the spatial angle between this direction vector and the direction vector (0, 0, 1) of the central axis direction. The calculation formula is as follows:

[0058]

[0059] In the formula, k1 is the standard direction vector of the tobacco characteristic line, k2 is the direction vector of the central axis (0, 0, 1), and θ is the spatial angle.

[0060] In this method, the closer the cosθ value is to 1, that is, the closer the spatial angle θ is to 0°, the more parallel the tobacco shreds are to the central axis of the cigarette, and the more the spatial distribution of a single tobacco shred conforms to the desired state of cigarette rolling.

[0061] 8. Perform steps 5-7 on each tobacco shred to obtain the spatial angle of all tobacco shreds. During this process, the three-dimensional spatial coordinate system is established, except that the origin changes to the midpoint voxel of the width side of the measured tobacco shred, while the other three axes remain unchanged.

[0062] 9. Compare the standard direction vectors of tobacco characteristic lines with the same spatial angle. Based on whether the standard direction vectors are the same, classify the tobacco characteristic lines and count their number n.j Then the correction coefficient for the spatial distribution of tobacco shreds is defined as follows: In the formula, n max For n j The maximum value in the equation. As can be seen from the three-dimensional geometry of a cone, any generatrix on the cone makes the same spatial angle with the central axis. However, it can be observed that generatrixes with the same spatial angle have different spatial distributions. Therefore, after classifying different tobacco shreds using spatial angles, the shreds with the same spatial angle need to be further subdivided to obtain a precise value for the spatial distribution of the tobacco shreds.

[0063] 10. The spatial distribution of tobacco shreds within a cigarette is a holistic concept. Therefore, to evaluate the spatial distribution of tobacco shreds within the entire cigarette, it is necessary to comprehensively consider the spatial distribution indices of all tobacco shreds to obtain the spatial distribution index S of tobacco shreds within the cigarette.

[0064]

[0065] In the formula, S is the spatial distribution index of tobacco shreds in the cigarette. The correction factor is m, where m is the number of tobacco strands inside the cigarette, and cosθ is the number of tobacco strands inside the cigarette. i It is a spatial angle function for a single tobacco shred.

[0066] The evaluation criteria for S are consistent with those for cosθ of a single tobacco shred. The closer the S value is to 1, the more the spatial distribution of tobacco shreds inside the entire cigarette conforms to the expectations of cigarette rolling.

Claims

1. A method for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in a heated non-combustible cigarette, characterized in that: First, a physical parameter S is defined as the spatial distribution state index of tobacco shreds. Industrial CT scanning is used to digitize the three-dimensional structure of the cigarette. A two-dimensional image of the tobacco shred distribution inside the cigarette is obtained through filtered back projection technology. Then, a three-dimensional reconstruction model of the cigarette is obtained through three-dimensional reconstruction and interpolation techniques. This model reflects the distribution state of the tobacco shreds inside the cigarette. Finally, the spatial distribution state of the tobacco shreds is quantitatively characterized using image methods. The specific steps are as follows: (1) Place the cigarette to be tested on the stage of the CT equipment, keep it vertical with clamps and ensure that the tobacco part is within the CT scan range; (2) Start the CT scanning device to scan the cigarette. The digital flat panel detector will transmit and save the received signal to the computer. (3) The data processing system in the computer uses a filtering back projection algorithm to process the acquired data and obtain a two-dimensional image of the distribution of tobacco inside the heated cigarette. (4) The image processing system in the computer performs image matching, image smoothing and image enhancement operations on the two-dimensional CT image sequence in order to perform edge extraction and image segmentation; interpolation is performed between adjacent two-dimensional CT images to improve the accuracy of the three-dimensional reconstruction model; finally, the three-dimensional structural model is reconstructed by the image processing system and the image of the tobacco skeleton inside the cigarette is extracted. (5) Select the central voxels of the two ends of the skeleton image respectively, connect the two central voxels into a line segment, and regard this line segment as the spatial distribution feature line of tobacco: the width is 1 voxel point and the length is n voxel points. The length of this line is the length L of tobacco. (6) Establish a three-dimensional spatial coordinate system with the first voxel point near the lower end of the tobacco branch as the origin, where the direction of the central axis of the tobacco branch is the z-axis direction, and determine the standard direction vector of the feature line in this coordinate system. (7) Calculate the spatial angle between this direction vector and the direction vector (0, 0, 1) of the central axis direction. The calculation formula is as follows: ； In the formula, k1 is the standard direction vector of the tobacco characteristic line, k2 is the direction vector of the central axis (0, 0, 1), and θ is the spatial angle. (8) Perform 5-7 operation steps on each tobacco shred to obtain the spatial angle of all tobacco shreds. During this process, the three-dimensional spatial coordinate system is established, except that the origin changes to the midpoint voxel of the measured tobacco shred near the lower end of the tobacco stick, and the other three axes remain unchanged. (9) Compare the standard direction vectors of tobacco characteristic lines with the same spatial angle. Based on whether the standard direction vectors are the same, classify the tobacco characteristic lines and count their number n respectively. j Then the correction coefficient for the spatial distribution of tobacco shreds is defined as follows: , In the formula, n max For n j The maximum value in; (10) The spatial distribution of tobacco shreds inside a cigarette is a holistic concept. Therefore, to evaluate the spatial distribution of tobacco shreds inside a cigarette, it is necessary to comprehensively consider the spatial distribution index of all tobacco shreds to obtain the spatial distribution index S of tobacco shreds in the cigarette. ； In the formula, S is the spatial distribution index of tobacco shreds in the cigarette. The correction factor is m, where m is the number of tobacco strands inside the cigarette, and cosθ is the number of tobacco strands inside the cigarette. i It is a spatial angle function for a single tobacco shred.

2. The method for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in a heated non-combustible cigarette according to claim 1, characterized in that: In step (3), the filtering back projection algorithm mainly includes several steps: pre-weighting of the projection data, one-dimensional filtering, and back projection. (1) First, the projection data is weighted using a function similar to cosine, and the distance and angle difference between the voxels and the source point are appropriately corrected; (2) Then, one-dimensional filtering is performed on the projection data at different projection angles in the horizontal direction; (3) Perform a weighted back projection of the filtered data using a cone beam. The weight function in the back projection depends on the distance from the reconstructed point to the focal point. The FDK reconstruction algorithm for flat panel detectors can be expressed by the following formula: ； ； Where R represents the radius of rotation. This represents the filtered projection data, where g(a) is the filtering function. () represents the distance of the reconstructed pixel in the xy plane to the X-ray source; ； This represents the horizontal position of the corresponding ray on the virtual detector, and the corresponding vertical position can be represented as... ； The weighted function can be decomposed into the following expression: ； Z is the Z-axis coordinate of the point to be reconstructed. Similarly, we can obtain the length of U based on geometric relationships. ； The weighting factor U is similar to the weighting factor in the two-dimensional filtering back projection algorithm. Geometrically, it is related to the projection of the line connecting the ray source point and the reconstructed image onto the intermediate ray.

3. The method for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in a heated non-combustible cigarette according to claim 1, characterized in that: In step (1), the cigarette sample to be tested needs to be placed in a equilibration chamber for temperature and humidity equilibration before the experiment. The specific values ​​are: temperature 22℃, relative humidity 65%, and equilibration time of more than 24 hours.

4. The method for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in a heated non-combustible cigarette according to claim 1, characterized in that: In step (2), the CT equipment is set with the following parameters: image size of 2048x2048 for the purpose of scanning the cigarette structure, X-ray source tube voltage of 100 kV, X-ray source tube current of 70 uA, scanning thickness of 0.004 mm, scanning interval of 0.004 mm, CT scanning mode of cone-beam scanning, and CT scanning mode of Normal scanning.

5. The method for detecting and quantitatively characterizing the spatial distribution of tobacco shreds in a heated non-combustible cigarette according to claim 1, characterized in that: The specific process of step (4) is as follows: In the CT scan image, the spacing in the X and Y directions is equal during the sampling process, and the spacing in the Z direction has a large difference. Therefore, a linear interpolation is performed in the Z direction, and the calculation formula is: ； In the formula, P1 and P2 are the CT values ​​of corresponding points in adjacent CT images, a1 and a2 are the Z-axis distances between the two corresponding points and the interpolation point, and P is the CT value of the interpolation point. Multifractal spectrum technology is used to extract the internal and contour features of each cigarette CT image. The images are then analyzed using their visual appeal. The range of spectral values ​​in the multifractal spectrum theory is set, and the edges of the cigarette CT images are detected and extracted. The contour of the three-dimensional image is drawn using the edge information extracted from each cigarette CT image. The original cigarette CT image and the contour image extracted by using linear interpolation are then integrated to form a three-dimensional reconstruction model.

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