Tobacco shred arrangement order prediction method and device and electronic equipment

Abstract

The invention provides a tobacco shred arrangement order prediction method and device and electronic equipment. The method can be applied to the technical field of tobacco processing, and comprises the following steps: acquiring characteristic parameters of a to-be-detected cigarette, including at least one of the following parameters: porosity, actual permeability, specific surface area and pore radius; based on the preset ideal porosity and the ideal pore radius of the ideal cigarette, the maximum permeability and the minimum permeability of the ideal cigarette are obtained through calculation. And according to the maximum permeability, the minimum permeability and the actual permeability, determining a tobacco shred arrangement orderliness result of the to-be-detected cigarette.

Description

Technical Field

[0001] This disclosure relates to the field of tobacco processing technology, specifically to a method, apparatus, and electronic device for predicting the orderly arrangement of tobacco shreds. Background Technology

[0002] With the development of functional and refined processing of tobacco products, the orderliness of the tobacco filling structure inside cigarettes has increasingly become one of the important factors affecting the consistency of product performance and quality. Traditional methods for predicting the orderliness of tobacco shreds mainly rely on manual judgment, two-dimensional slicing analysis, and density detection. These methods have limitations such as large prediction errors and high sample destructiveness, making them difficult to apply in actual production. In other words, the tobacco industry currently lacks a quantitative characterization method for the orderliness of tobacco shred structure.

[0003] In summary, there is an urgent need for a predictive method that can be used to quantify the structural orderliness of tobacco shreds, so as to provide quantitative data support for the tobacco industry to optimize tobacco shred filling processes. Summary of the Invention

[0004] In view of the above problems, this disclosure provides a method, apparatus and electronic device for predicting the orderliness of tobacco shred arrangement.

[0005] According to a first aspect of this disclosure, a method for predicting the orderliness of tobacco shred arrangement is provided, comprising: obtaining characteristic parameters of a cigarette to be tested, the characteristic parameters including at least one of the following: porosity, actual permeability, specific surface area, and pore radius; calculating the maximum permeability and minimum permeability of an ideal cigarette based on the predetermined ideal porosity and ideal pore radius; and determining the result of the orderliness of tobacco shred arrangement of the cigarette to be tested based on the maximum permeability, minimum permeability, and actual permeability.

[0006] According to embodiments of this disclosure, determining the orderliness of the tobacco arrangement of the cigarette under test based on the maximum penetration rate, minimum penetration rate, and actual penetration rate includes: calculating a first difference based on the difference between the actual penetration rate and the minimum penetration rate; calculating a second difference based on the difference between the maximum penetration rate and the minimum penetration rate; and determining the orderliness of the tobacco arrangement of the cigarette under test based on the ratio between the first difference and the second difference.

[0007] According to an embodiment of this disclosure, a method for predicting the orderliness of tobacco shred arrangement further includes: the value of the tobacco shred arrangement orderliness result of the cigarette to be tested is between 0 and 1, the larger the value of the tobacco shred arrangement orderliness result indicates the higher the tobacco shred arrangement orderliness, and the smaller the value of the tobacco shred arrangement orderliness result indicates the lower the tobacco shred arrangement orderliness.

[0008] According to embodiments of this disclosure, based on the predetermined ideal porosity and ideal pore radius of an ideal cigarette, the maximum and minimum permeability of the ideal cigarette are calculated, including the maximum permeability calculated using the following algorithm:

[0009]

[0010] The minimum penetration rate is calculated using the following algorithm:

[0011]

[0012] Where K0 is the Kozeny constant, ɛ max r max These represent the maximum ideal porosity and the maximum ideal pore radius of a predetermined ideal cigarette; ɛ min r min These are the minimum ideal porosity and minimum ideal pore radius of a predetermined ideal cigarette, respectively.

[0013] According to embodiments of this disclosure, the tobacco shreds of an ideal cigarette are all arranged parallel to the central axis of the ideal cigarette.

[0014] According to embodiments of this disclosure, obtaining characteristic parameters of a cigarette to be tested includes: acquiring a projection data image of the cigarette to be tested using a scanning device; processing the projection data image using a reconstruction algorithm to obtain a tomographic image of the cigarette to be tested; performing image segmentation and preprocessing on the tomographic image of the cigarette to be tested to extract pore structure feature information, including the size and shape of pores and tobacco shreds, pore volume, tobacco shred filling rate, and pore size distribution; establishing an effective pore network structure topology model and a pore throat ball-and-stick geometric model based on the pore structure feature information; and obtaining characteristic parameters of the cigarette to be tested from the effective pore network structure topology model and the pore throat ball-and-stick geometric model.

[0015] A second aspect of this disclosure provides a device for predicting the orderliness of tobacco shred arrangement, comprising a parameter acquisition module for acquiring characteristic parameters of a cigarette to be tested, including at least one of the following: porosity, actual permeability, specific surface area, and pore radius. A first calculation module is used to calculate the maximum and minimum permeability of an ideal cigarette based on the predetermined ideal porosity and ideal pore radius. A second calculation module is used to determine the orderliness result of the tobacco shred arrangement of the cigarette to be tested based on the maximum, minimum, and actual permeability.

[0016] A third aspect of this disclosure provides an electronic device comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method described above.

[0017] A fourth aspect of this disclosure also provides a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed by a processor, implement the steps of the above-described method.

[0018] The fifth aspect of this disclosure also provides a computer program product, including a computer program or instructions that, when executed by a processor, implement the steps of the above-described method.

[0019] According to embodiments of this disclosure, a pore network model of the cigarette structure is constructed to obtain cigarette characteristic parameters, and a quantitative characterization of the ordered structure of the tobacco shreds to be tested is achieved based on the ideal cigarette structure. Considering the porous fiber media characteristics of cigarettes, the degree of tobacco shred order is closely related to the permeability parameter. Based on the ideal structure of an ideal cigarette, the maximum and minimum permeability of the ideal cigarette are simulated and calculated, establishing a quantitative evaluation standard for tobacco shred order. Based on the actual permeability of the cigarette to be tested and the maximum and minimum permeability of the ideal cigarette, the predicted result of the ordered arrangement of the tobacco shreds in the cigarette to be tested is calculated. This method has the advantages of standardization and quantification, improving the accuracy of tobacco shred order prediction in the tobacco field. It is beneficial for further quantitative analysis to establish the correlation between the degree of tobacco structure order and the heat and mass transfer performance during the heating process. Furthermore, it has high detection efficiency and can be integrated into the production line for real-time quality monitoring. It can serve as a key evaluation indicator in tobacco product quality control, process evaluation, and new product development. Attached Figure Description

[0020] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0021] Figure 1 This diagram illustrates application scenarios for the method, apparatus, device, medium, and program products for predicting the orderliness of tobacco arrangement according to embodiments of this disclosure.

[0022] Figure 2 This is a flowchart of a method for predicting the orderliness of tobacco shred arrangement according to an embodiment of the present disclosure;

[0023] Figure 3 This is a longitudinal cross-sectional view showing the orderly arrangement of tobacco shreds in an embodiment of this disclosure;

[0024] Figure 4 This is a semi-ordered longitudinal section view of the tobacco shreds in an embodiment of this disclosure;

[0025] Figure 5 This is a longitudinal cross-sectional view of the disordered arrangement of tobacco shreds in an embodiment of this disclosure;

[0026] Figure 6 This is an axial three-dimensional schematic diagram of the ordered cigarette pore network topology model in the embodiments of this disclosure;

[0027] Figure 7AThis is an axial three-dimensional schematic diagram of the geometric model of the ordered cigarette stick throat ball in the embodiments of this disclosure;

[0028] Figure 7B This is a radial three-dimensional schematic diagram of the geometric model of the ordered cigarette butt throat ballstick in the embodiments of this disclosure;

[0029] Figure 8 This is a structural block diagram of a tobacco shred arrangement order prediction device according to an embodiment of the present disclosure;

[0030] Figure 9 This is a block diagram of an electronic device suitable for implementing a method for predicting the orderliness of tobacco arrangement according to an embodiment of the present disclosure. Detailed Implementation

[0031] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0032] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0033] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0034] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0035] Heated cigarettes are a new type of tobacco product. Currently, the tobacco shreds filling the core section come in two forms: ordered and disordered. In ordered structures, the tobacco shreds are arranged axially along the direction of smoke flow, exhibiting a longitudinally ordered and regular arrangement. In disordered structures, similar to traditional cigarettes, the tobacco shreds are arranged randomly and irregularly within the core section. Heated cigarettes release aerosols by heating the core at a low temperature. The orderliness of the tobacco shred arrangement directly affects heat transfer uniformity, aerosol release stability, and sensory quality. Disordered structures suffer from uneven axial arrangement, which can cause jamming when the heating element (usually a needle or plate) is inserted, preventing it from reaching its intended position and thus affecting heat conduction and transfer, potentially resulting in no smoke or failure to achieve the expected sensory quality. Therefore, the filling state of the tobacco shreds within the cigarette directly affects smoke flow resistance, combustion uniformity, and draw resistance stability. If the tobacco shreds are randomly distributed or arranged internally in a disorderly manner, forming an asymmetrical structure, it may cause fluctuations in the cigarette's smoking performance, thereby affecting the consumer experience. The orderliness of tobacco shreds reflects the three-dimensional spatial arrangement of tobacco fibers in a cigarette, directly determining the cigarette's draw resistance, air permeability, combustion uniformity, flavor base permeation efficiency, and smoke release consistency. It is a crucial structural indicator for cigarettes. In summary, the orderliness of tobacco shreds in heated cigarette products is a key indicator of quality control and a focus of the tobacco industry. Currently, the industry lacks a method for quantitatively evaluating the orderliness of tobacco shred filling within cigarettes.

[0036] In realizing the concept disclosed herein, the inventors discovered at least the following problems in the related technologies: In the tobacco industry, there are currently various methods for characterizing the structural orderliness of tobacco shreds, but there is a lack of effective methods for quantifying the degree of orderliness. Traditional manual visual inspection methods rely mainly on experience, which is highly subjective and cannot be used to establish fixed prediction standards in actual production, nor can they quantify the three-dimensional structural defects of cigarettes. Two-dimensional slicing analysis is the mainstream low-cost method for tobacco companies to predict the orderliness of cigarette shreds. It involves cutting cigarettes horizontally or vertically to obtain two-dimensional thin slices of tobacco shreds. The arrangement direction and packing density of the tobacco shreds on the slices are observed using optical microscopes, two-dimensional DR imaging, and scanning electron microscopes. However, this method suffers from defects such as two-dimensional projection distortion, local sampling errors, and sample damage, and cannot meet the needs of tobacco shred structure characterization. Density detection is also one of the prediction methods used in the industry, but this method can only reflect overall density differences and cannot resolve key parameters such as pore structure and anisotropy.

[0037] In view of this, embodiments of the present disclosure provide a method for predicting the orderliness of tobacco shred arrangement, comprising: obtaining characteristic parameters of a cigarette to be tested, the characteristic parameters including at least one of the following: porosity, actual permeability, specific surface area, and pore radius; calculating the maximum permeability and minimum permeability of the ideal cigarette based on the predetermined ideal porosity and ideal pore radius; and determining the orderliness result of the tobacco shred arrangement of the cigarette to be tested based on the maximum permeability, the minimum permeability, and the actual permeability.

[0038] According to embodiments of this disclosure, the tobacco shreds of an ideal cigarette are all arranged parallel to the central axis of the ideal cigarette.

[0039] Figure 1 This diagram illustrates application scenarios for the method, apparatus, device, medium, and program products for predicting the orderliness of tobacco arrangement according to embodiments of this disclosure.

[0040] like Figure 1 As shown, application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0041] In the application scenarios of this disclosure embodiment, users can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 via the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only examples).

[0042] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0043] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0044] It should be noted that the tobacco shred arrangement order prediction method provided in this disclosure can be executed by the first terminal device 101, the second terminal device 102, or the third terminal device 103, or by other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103. Correspondingly, the tobacco shred arrangement order prediction device provided in this disclosure can also be located in the first terminal device 101, the second terminal device 102, or the third terminal device 103, or in other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103. Alternatively, the tobacco shred arrangement order prediction method provided in this disclosure can also be executed by the server 105. Correspondingly, the tobacco shred arrangement order prediction device provided in this disclosure can also be located in the server 105. The tobacco shred arrangement order prediction method provided in this disclosure can also be executed by a server or server cluster that is different from the server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or the server 105. Accordingly, the tobacco arrangement order prediction device provided in this disclosure can also be set in a server or server cluster that is different from server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or server 105.

[0045] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0046] The following will be based on Figure 1 The described scene, through Figure 2 The method for predicting the orderliness of tobacco arrangement according to embodiments of this disclosure will be described in detail.

[0047] Figure 2 The diagram shows a flowchart of a method for predicting the orderliness of tobacco shred arrangement according to an embodiment of the present disclosure. Figure 2 As shown, the method for predicting the orderliness of tobacco arrangement in this embodiment includes operations S201 to S203.

[0048] In operation S201, the characteristic parameters of the cigarette to be tested are obtained. The characteristic parameters include at least one of the following: porosity, actual permeability, specific surface area, and pore radius.

[0049] According to embodiments of this disclosure, obtaining characteristic parameters of a cigarette to be tested includes: acquiring a projection data image of the cigarette to be tested using a scanning device; processing the projection data image using a reconstruction algorithm to obtain a tomographic image of the cigarette to be tested; performing image segmentation and preprocessing on the tomographic image of the cigarette to be tested to extract pore structure feature information, including the size and shape of pores and tobacco shreds, pore volume, tobacco shred filling rate, and pore size distribution; establishing an effective pore network structure topology model and a pore throat ball-and-stick geometric model based on the pore structure feature information; and obtaining characteristic parameters of the cigarette to be tested from the effective pore network structure topology model and the pore throat ball-and-stick geometric model.

[0050] According to embodiments of this disclosure, the microstructural features of cigarettes can be extracted using Avizo software, including porosity and permeability (in millidarcy mD) parameters extracted from the pore network topology model, and pore radius parameters calculated based on the pore throat ball-and-stick geometric model. The extracted structural parameters of cigarette samples 1-12 are shown in Table 1. Samples 1-6 are ordered cigarettes, samples 7-9 are semi-ordered cigarettes, and samples 10-12 are disordered cigarettes.

[0051] Table 1

[0052]

[0053] In operation S202, the maximum and minimum permeability of the ideal cigarette are calculated based on the predetermined ideal porosity and ideal pore radius of the ideal cigarette.

[0054] Cigarettes are a typical cylindrical porous medium with random fibrous structure, composed of a large number of irregularly arranged tobacco fibers, forming a complex network of pore channels. The relationship between permeability and pore structure parameters in the cigarette structure is described by the Kozeny-Carman equation, as shown in formula (1):

[0055] (1);

[0056] Where k is the permeability of the cigarette; ε is the porosity; S is the specific surface area; K0 is the Kozeny constant, usually between 4 and 5, which can be adjusted according to the different structural shapes of the research object. For random fiber media, K0 is usually taken as 5. In order to simplify the analysis, the tobacco structure can be equivalent to an ideal system composed of several parallel or approximately parallel tubular channels. In this simplified model, if the average radius of the pores is r, the specific surface area S can be approximately expressed as S≈2 / r. This relationship has good applicability in the tobacco structure and can be equivalently replaced. Substituting the equivalent relationship S≈2 / r into formula (1), we get formula (2) as follows:

[0057] (2);

[0058] According to embodiments of this disclosure, based on the predetermined ideal porosity and ideal pore radius of an ideal cigarette, the maximum permeability and minimum permeability of the ideal cigarette are calculated, including the maximum permeability calculated using formula (3):

[0059] (3);

[0060] Among them, ɛ max r represents the maximum ideal porosity of a predetermined ideal cigarette. max This represents the maximum ideal pore radius of a predetermined ideal cigarette.

[0061] According to embodiments of this disclosure, k max The goal is to characterize the theoretical upper limit of permeability under the ideal ordered tobacco filling state. Based on the Kozeny-Carman equation, a method for estimating the maximum permeability under the "most ordered cigarette" state with physical feasibility and structural rationality can be constructed.

[0062] For example, the CT measurement results of the six ordered cigarette samples in Table 1 show that the porosity of the ordered cigarette samples is concentrated in the range of approximately 0.52 to 0.56. To describe the upper limit of ideal ordered filling, the value ε can be taken as... max = 0.6, slightly higher than the measured maximum value.

[0063] According to embodiments of this disclosure, in the measured samples in Table 1, the pore radius ranged from 13 to 14 μm based on the ball-and-stick model. Under ideal ordered conditions, the tobacco shreds are axially parallel, the tortuosity of the pores is reduced, and the equivalent channel size will significantly increase. Therefore, the pore radius is taken as r... max =20μm, which is an upper limit of ordering based on actual measurement results, used to characterize the most ordered and smoothest theoretical structure.

[0064] ε max = 0.6, r maxSubstituting 20μm into the maximum permeability calculation formula (3), we get:

[0065]

[0066] Unit conversion: 1 mD = 9.869233 × 10−16 m 2 , get k max =27357.75mD.

[0067] According to embodiments of this disclosure, the minimum penetration rate is calculated using formula (4):

[0068] (4);

[0069] Among them, ɛ min r represents the minimum ideal porosity of a predetermined ideal cigarette. min This is the minimum ideal pore radius of a predetermined ideal cigarette.

[0070] According to embodiments of this disclosure, when the tobacco shreds are arranged in an extremely disordered manner, the pore channels are severely blocked, or there is no effective communication path, the porosity and pore radius are approximately 0, and the equivalent permeability, reflecting the fluid flow capacity in the porous medium, also approaches 0 under the theoretical limit. Therefore, corresponding to the completely failed flow limit state, k min The value is 0.

[0071] In operation S203, the orderliness of the tobacco arrangement of the cigarette shreds in the test cigarette is determined based on the maximum penetration rate, minimum penetration rate, and actual penetration rate.

[0072] According to embodiments of this disclosure, determining the orderliness of the tobacco arrangement of the cigarette under test based on the maximum penetration rate, minimum penetration rate, and actual penetration rate includes: calculating a first difference based on the difference between the actual penetration rate and the minimum penetration rate; calculating a second difference based on the difference between the maximum penetration rate and the minimum penetration rate; and determining the orderliness of the tobacco arrangement of the cigarette under test based on the ratio between the first difference and the second difference.

[0073] For example, k max k represents the theoretical maximum penetration rate. min k represents the theoretical minimum penetration rate. sample Let k be the actual penetration rate of the cigarette to be tested. sample -k min The second difference is k max -k min The result of calculating the orderliness of the tobacco arrangement of the cigarette to be tested is shown in formula (5):

[0074] (5);

[0075] Wherein, D represents the result of the orderly arrangement of tobacco shreds in the cigarette to be tested, and its physical meaning is the deviation characteristic parameter of the actual sample tobacco shreds from the ideal tobacco shred structure. The closer D is to 0, the more disordered the tobacco shreds are; the closer it is to 1, the more ordered the tobacco shreds are. Among these, the maximum penetration rate k... max Taking the theoretical ordered limit value of 27357.75 mD, the minimum permeability k min Take 0mD. The actual penetration rate k for each cigarette sample in Table 1. sample Substituting the values ​​into the deviation calculation formula, the deviation characteristic parameters of the cigarettes to be tested can be obtained, as shown in Table 2.

[0076] Table 2

[0077]

[0078] According to an embodiment of this disclosure, a method for predicting the orderliness of tobacco shred arrangement further includes: the value of the tobacco shred arrangement orderliness result of the cigarette to be tested is between 0 and 1, the larger the value of the tobacco shred arrangement orderliness result indicates the higher the tobacco shred arrangement orderliness, and the smaller the value of the tobacco shred arrangement orderliness result indicates the lower the tobacco shred arrangement orderliness.

[0079] It should be noted that the result D of the tobacco shred arrangement order of the tested cigarette is a continuous quantitative index used to describe the degree of deviation of the sample from the "theoretically most ordered state". In this invention: D approaching 1 indicates that it is close to the theoretically most ordered limit state, and D approaching 0 indicates that it is close to the completely disordered limit state. It should be noted that the "theoretically most ordered state" is an upper limit reference structure constructed by extrapolating ideal parameters, and is not equivalent to the structural state that can be stably realized in actual production.

[0080] According to embodiments of this disclosure, by constructing the most disordered and most ordered structures of an ideal cigarette, the permeability parameters under the limiting state of the ideal cigarette are simulated and calculated. A complete reference scale from most disordered to most ordered is established through normalization mapping, providing an ideal quantitative standard for predicting the orderliness of cigarette tobacco shreds. Specifically, within a certain numerical range, a larger numerical value for the tobacco shred arrangement orderliness indicates higher orderliness. As shown in Table 2, the maximum deviation in the test samples is approximately 0.29, indicating that even the actual "ordered cigarette" under current process conditions has a structural state significantly lower than the theoretical optimal limit. This precisely reflects the sensitivity of this indicator to the process optimization space, rather than negating the ordered properties of the sample. Therefore, a deviation value not close to 1 does not mean that the sample cannot be judged as ordered, but rather indicates that the sample still has room for improvement relative to the theoretical optimal ordered state. The result distribution shows that the deviation of ordered samples is generally higher than that of semi-ordered and disordered samples, meaning that this indicator can effectively distinguish different filling structure states and has good predictive ability for the tobacco shred arrangement orderliness of the tested cigarette, and can be used to characterize the differences in the degree of order between different tobacco filling structures. Ordered, semi-ordered, and disordered tobacco shreds are all relative concepts under a unified evaluation standard. The greater the deviation value, the closer the tobacco shred arrangement structure is to the ideal ordered state, and the higher the overall orderliness.

[0081] According to an embodiment of this disclosure, in operation S201, the characteristic parameters of the cigarette to be tested can be obtained through operations S2011 to S2015.

[0082] Operation S2011: Obtaining the characteristic parameters of the cigarette to be tested includes: acquiring the projected data image of the cigarette to be tested through a scanning device.

[0083] According to embodiments of this disclosure, the scanning device can be an X-ray 3D-μCT tomographic imaging system, including a microfocus X-ray source, a high-resolution area array detector, a multi-degree-of-freedom motion platform, and DR image (Digital Radiography Image) acquisition and three-dimensional reconstruction software. It uses the method of "synchronous rotation + lifting" of the sample to achieve spiral trajectory scanning, complete coverage of the entire height of the cigarette, and obtain a complete projection data image in one scan, realizing high-resolution three-dimensional tomographic detection of the internal structure and quality status of the cigarette sample. For example, using WorX's XWT-225CT X-ray source and Varex Imaging's XRpad2 4336 HWC (High-Definition Wireless Cassette) detector, the imaging parameters were set as follows: tube voltage 70 kV, tube current 100 μA, gain 2 pF, integration time 1000 ms, scanning angle 360°, FDD (Focus-to-Detector Distance) 753.64 mm, FOD (Focus-to-Object Distance) 22.36 mm, and 720 images were projected.

[0084] Operation S2012: The projected data image is processed by the reconstruction algorithm to obtain the tomographic image of the cigarette to be tested.

[0085] According to embodiments of this disclosure, the FDK (Feldkamp-Davis-Kress Algorithm) reconstruction algorithm can be used to process the projection data, reconstruct a tomographic image of the cigarette, and obtain its longitudinal section, as shown below. Figures 3-5 As shown.

[0086] Figure 3 This is a longitudinal cross-sectional view showing the orderly arrangement of tobacco shreds in an embodiment of this disclosure.

[0087] Figure 4 This is a longitudinal cross-sectional view of the semi-ordered arrangement of tobacco shreds in an embodiment of this disclosure.

[0088] Figure 5 This is a longitudinal cross-sectional view of the disordered arrangement of tobacco shreds in an embodiment of this disclosure.

[0089] As shown in the figure, compared with semi-ordered and disordered cigarettes, the tobacco shreds in the longitudinal section of ordered cigarettes are arranged more regularly, and the overall direction is more parallel to the central axis of the cigarette.

[0090] Tomographic images, also known as tomographic or volumetric images, are two-dimensional or three-dimensional visual representations of a specific thin cross-section within an object, obtained through tomographic imaging technology. The core of this technology involves multi-angle data acquisition and computer reconstruction to eliminate interference from overlapping structures, achieving precise layered display of the internal structure. Unlike traditional projection images, tomographic images focus on a single thin layer (volume layer), clearly revealing the spatial relationships and density signal differences of the tissues and structures within that layer. The data essence of tomographic images is the quantification of material properties, spatial location, and structural relationships. The essence of the FDK algorithm for reconstructing cigarette tomographic images is to first perform geometric compensation and filtering on the multi-angle acquired cigarette projection data, and then, according to the spatial geometry of cone-beam scanning, "back-map" the projection information from each angle to pixels in the tomographic space. Through angle-by-angle and pixel-by-pixel accumulation, tomographic data reflecting the internal density distribution of the cigarette is finally formed, and then converted into a visual image.

[0091] Operation S2013: Perform image segmentation and preprocessing on the tomographic image of the cigarette to be tested, and extract pore structure feature information, including the size and shape of pores and tobacco shreds, pore volume, tobacco shred filling rate, and pore size distribution.

[0092] Image segmentation and preprocessing of the reconstructed image can eliminate image noise, clarify structural boundaries, and accurately separate the three types of regions—tobacco shreds, pores, and impurities—in the tomographic image of the cigarette. First, the tomographic image is preprocessed, which may include noise reduction and contrast enhancement. Noise reduction removes artifacts and noise points generated during scanning or reconstruction, while contrast enhancement makes the grayscale differences between tobacco shreds and pores more apparent, avoiding interference with subsequent segmentation. Subsequently, image segmentation is performed using algorithms such as thresholding and edge detection to clearly distinguish the tobacco shred regions (high density, bright grayscale) and the pore regions (low density, dark grayscale) in the image.

[0093] The original image data includes pixel or voxel grayscale values. The grayscale value of each pixel (2D tomography) or voxel (3D tomography) directly corresponds to the degree of X-ray attenuation of the material inside the cigarette. The higher the grayscale value, the greater the material density (e.g., dense tobacco areas), and the lower the grayscale value, the smaller the density (e.g., pores). The X-ray attenuation coefficient can quantitatively reflect the material's ability to absorb X-rays, directly distinguishing different components such as tobacco, filter, pores, and impurities. It is directly obtained from grayscale values ​​and physical property data, such as the equivalent air permeability coefficient of tobacco pores, can be derived based on the X-ray attenuation coefficient. It can also include spatial coordinate data, i.e., the two-dimensional (X, Y) or three-dimensional (X, Y, Z) coordinates of each pixel or voxel, specifying its exact location in the cigarette tomography (e.g., radial distance from the cigarette center, axial length). From the segmented pore region, pore structure feature information reflecting the tobacco filling state is extracted. For example, it may include: (1) the location and size of pores or tobacco shreds, including area, volume, sphericity, irregularity and pore size distribution information; (2) porosity: the proportion of the total volume of pores to the tobacco branch, the uniformity of pore distribution in the tobacco branch, the connectivity between pores, the width or length of the connecting channel, the connectivity rate, etc.; (3) adjacency relationship data: the topological relationship between different regions, such as the contact area between tobacco shreds and pores, the adjacent position of impurities and tobacco shreds, used to analyze the mutual influence between structures and to judge the blocking effect of impurities on pore connectivity; (4) distribution characteristic data: spatial distribution uniformity indicators of pores and tobacco shreds, such as porosity standard deviation and local density variation coefficient, which can reflect the uniformity of tobacco shred filling.

[0094] Operation S2014: Establish an effective pore network structure topology model and pore throat ball-and-stick geometric model based on pore structure feature information.

[0095] Pore ​​network structures, as an effective way to describe the internal spatial structure of porous media, are widely used in fields such as geotechnical engineering, materials science, and filtration. Their core value lies in establishing a connection between the internal structure and external properties of tobacco, transforming the invisible pore morphology within cigarettes into quantifiable, simulable, and controllable data. This provides a scientific tool for process optimization, performance prediction, and quality control in tobacco research, driving the industry's transformation from experience-based judgment to precision design.

[0096] According to embodiments of this disclosure, a pore network model and a pore throat ball-and-stick model can be established using the 3D reconstruction software Avizo. The obtained discrete pore features are integrated into a calculable and simulable digital network model, which intuitively reflects the functional characteristics of the pores.

[0097] Figure 6 This is an axial three-dimensional schematic diagram of the pore network model obtained through three-dimensional reconstruction.

[0098] Figure 7AThis is an axial three-dimensional schematic diagram of the geometric model of the ordered tobacco branch throat ballstick in the embodiments of this disclosure.

[0099] Figure 7B This is a radial three-dimensional schematic diagram of the geometric model of the ordered tobacco stem throat ballstick in the embodiments of this disclosure.

[0100] The Pore Network Model (PNM) is an abstract topological model without specific geometric shapes. For tobacco shreds, it doesn't concern itself with whether the pores are spherical or cylindrical, or whether the throats are cylindrical or slits. Instead, it abstracts tobacco pores as nodes (pores) and throats as connecting edges, assigning quantitative parameters to nodes and edges. Nodes correspond to the size and location of the pores, while edges correspond to the width and length of the connected channels. It can extract the topological structure parameters and macroscopic equivalent seepage parameters of tobacco pores, serving as the universal fundamental parameters for all pore network subclasses (including ball-and-stick models). Without geometric dimensions, it is the core for characterizing the connection rules of tobacco pores and the overall seepage capacity. All parameters can be determined using CT / Micro-CT (Computed Tomography / Microcomputed Tomography) or mercury intrusion porosimetry. Simultaneously, it eliminates invalid isolated pores that do not participate in gas or heat transfer, retaining only the connected pores that affect cigarette combustion and air permeability, ensuring the model's practicality.

[0101] The Pore-Throat Ball-Stick Model is a visual representation of a pore network model. It abstracts pores as spheres and throats as cylinders or sticks, giving the abstract pore network a clear geometric shape for easier visualization and numerical computation. The Maximum Ball Algorithm is typically used, placing the largest inscribed sphere in the pore space to represent the pore, with narrow channels between the spheres connected by sticks. The Pore-Throat Ball-Stick Model can visually represent the microscopic pore distribution of tobacco shreds through its ball-stick structure, allowing for the calculation of parameters such as the pore-throat ratio and pore radius.

[0102] Operation S2015: Obtain the characteristic parameters of the cigarette under test from the effective pore network structure topology model and the pore throat ball-and-stick geometric model.

[0103] In porous materials, structural properties can be quantitatively characterized through specific structural characteristic parameters. For example, porosity can characterize the ratio of the total volume of tiny pores in a tobacco shred structure to the total volume of the porous medium; permeability refers to the flow rate of fluid in a porous medium, which can be statistically analyzed using the Absolute Permeability Tensor Calculation function in Avizo software; furthermore, fractal dimension is an important fractal parameter used to quantitatively describe the complex structure and spatial characteristics of a material, which can be statistically analyzed using the Fractal Dimension function in Avizo software.

[0104] The above are merely preferred embodiments of this disclosure. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this disclosure. For example, the selection of the predetermined language model can be changed or upgraded according to actual circumstances, and the content of the first and second prompt messages can also be adjusted for different types of text. These improvements should also be considered within the scope of protection of this disclosure.

[0105] Furthermore, based on the above-mentioned method for predicting the orderliness of tobacco shred arrangement, this disclosure also provides a device for predicting the orderliness of tobacco shred arrangement. The following will be combined with... Figure 8 The device is described in detail.

[0106] Figure 8 This is a structural block diagram of a tobacco shred arrangement order prediction device according to an embodiment of the present disclosure.

[0107] like Figure 8 As shown, the tobacco shred arrangement order prediction device 800 of this embodiment includes a parameter acquisition module 801, a first calculation module 802, and a second calculation module 803.

[0108] The parameter acquisition module 801 is used to acquire characteristic parameters of the cigarette to be tested, including at least one of the following: porosity, actual permeability, specific surface area, and pore radius. In one embodiment, the parameter acquisition module 801 can be used to perform the operation S201 described above, which will not be repeated here.

[0109] The first calculation module 802 is used to calculate the maximum and minimum permeability of an ideal cigarette based on the predetermined ideal porosity and ideal pore radius of the ideal cigarette. In one embodiment, the first calculation module 802 can be used to perform the operation S202 described above, which will not be repeated here.

[0110] The second calculation module 803 is used to determine the orderliness of the tobacco arrangement of the cigarette shreds in the test cigarette based on the maximum penetration rate, minimum penetration rate, and actual penetration rate. In one embodiment, the second calculation module 803 can be used to perform the operation S203 described above, which will not be repeated here.

[0111] According to embodiments of this disclosure, the second calculation module 803 includes: a first calculation submodule, a second calculation submodule, and a determination submodule. The first calculation submodule is used to calculate a first difference based on the difference between the actual penetration rate and the minimum penetration rate; the second calculation submodule is used to calculate a second difference based on the difference between the maximum penetration rate and the minimum penetration rate; and the determination submodule is used to determine the orderliness result of the tobacco arrangement of the cigarette to be tested based on the ratio between the first difference and the second difference.

[0112] According to an embodiment of this disclosure, the determining module further includes a value between 0 and 1 for the tobacco shred arrangement order result of the cigarette to be tested. A larger value indicates a higher degree of tobacco shred arrangement order, and a smaller value indicates a lower degree of tobacco shred arrangement order.

[0113] According to embodiments of this disclosure, the first computing module 802 includes a third computing submodule and a fourth computing submodule.

[0114] The third calculation submodule is used to calculate the maximum penetration rate of an ideal cigarette using the following algorithm:

[0115]

[0116] Where, k max K0 is the maximum penetration rate of an ideal cigarette, where K is the Kozeny constant and ɛ is the maximum penetration rate of the cigarette. max r represents the maximum ideal porosity of a predetermined ideal cigarette. max This represents the maximum ideal pore radius of a predetermined ideal cigarette.

[0117] The fourth calculation submodule is used to calculate the minimum penetration rate of an ideal cigarette using the following algorithm:

[0118]

[0119] Where, k min K0 is the minimum permeability of an ideal cigarette, where K is the Kozeny constant and ɛ is the octane rating. min r represents the minimum ideal porosity of a predetermined ideal cigarette. min This is the minimum ideal pore radius of a predetermined ideal cigarette.

[0120] According to an embodiment of this disclosure, the first calculation module 802 further includes that the tobacco shreds of the ideal cigarette are all arranged parallel to each other along the central axis of the ideal cigarette.

[0121] According to embodiments of this disclosure, the parameter acquisition module 801 includes a first image acquisition module, a second image acquisition module, a first extraction module, a model building module, and a second extraction module. The first image acquisition module is used to acquire a projection data image of the cigarette to be tested using a scanning device; the second image acquisition module is used to process the projection data image using a reconstruction algorithm to obtain a tomographic image of the cigarette to be tested; the first extraction module is used to perform image segmentation and preprocessing on the tomographic image of the cigarette to be tested, extracting pore structure feature information, which includes at least one of the following: pore and tobacco region size, shape, pore volume, tobacco filling rate, and pore size distribution; the model building module is used to establish an effective pore network structure topology model and a pore throat ball-and-stick geometric model based on the pore structure feature information; the second extraction module is used to acquire characteristic parameters of the cigarette to be tested based on the effective pore network structure topology model and the pore throat ball-and-stick geometric model.

[0122] According to embodiments of this disclosure, any plurality of modules among parameter acquisition module 801, first calculation module 802, and second calculation module 803 can be combined into one module, or any one of these modules can be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules can be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of this application, at least one of parameter acquisition module 801, first calculation module 802, and second calculation module 803 can be at least partially implemented as hardware circuitry, such as field-programmable gate array (FPGA), programmable logic array (PLA), system-on-a-chip, system-on-a-substrate, system-on-package, application-specific integrated circuit (ASIC), or implemented by any other reasonable means of integrating or packaging circuitry, or implemented in any one of software, hardware, and firmware methods, or in a suitable combination of any of these. Alternatively, at least one of parameter acquisition module 801, first calculation module 802, and second calculation module 803 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0123] Figure 9 A block diagram schematically illustrates an electronic device suitable for implementing a method for predicting the orderliness of tobacco arrangement according to an embodiment of the present disclosure.

[0124] like Figure 9As shown, an electronic device 900 according to an embodiment of the present disclosure includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage portion 908 into a random access memory (RAM) 903. The processor 901 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 901 may also include onboard memory for caching purposes. The processor 901 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0125] RAM 903 stores various programs and data required for the operation of electronic device 900. Processor 901, ROM 902, and RAM 903 are interconnected via bus 904. Processor 901 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 902 and / or RAM 903. It should be noted that programs may also be stored in one or more memories other than ROM 902 and RAM 903. Processor 901 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in one or more memories.

[0126] According to embodiments of this disclosure, the electronic device 900 may further include an input / output (I / O) interface 905, which is also connected to a bus 904. The electronic device 900 may also include one or more of the following components connected to the input / output (I / O) interface 905: an input section 906 including a keyboard, mouse, etc.; an output section 907 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the input / output (I / O) interface 905 as needed. A removable medium 911, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 910 as needed so that computer programs read from it can be installed into the storage section 908 as needed.

[0127] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0128] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 902 and / or RAM 903 and / or one or more memories other than ROM 902 and RAM 903 described above.

[0129] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to enable the computer system to implement the tobacco shred arrangement order prediction method provided in the embodiments of this disclosure.

[0130] When the computer program is executed by the processor 901, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0131] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via the communication section 909, and / or installed from a removable medium 911. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0132] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 909, and / or installed from the removable medium 911. When the computer program is executed by the processor 901, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0133] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on a user's computing device, partially on a user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0134] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0135] Those skilled in the art will understand that the features described in the various embodiments of this disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments of this disclosure can be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0136] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A method for predicting the ordered arrangement of tobacco shreds, characterized in that, The method includes: Obtain the characteristic parameters of the cigarette to be tested, wherein the characteristic parameters include at least one of the following: porosity, actual permeability, specific surface area, and pore radius; Based on the predetermined ideal porosity and ideal pore radius of the ideal cigarette, the maximum and minimum permeability of the ideal cigarette are calculated. Based on the maximum penetration rate, the minimum penetration rate, and the characteristic parameters of the cigarette to be tested, a prediction result of the ordered arrangement of tobacco shreds in the cigarette to be tested is generated.

2. The method according to claim 1, characterized in that, The determination of the tobacco shred ordering of the cigarette under test based on the maximum permeability, the minimum permeability, and the actual permeability includes: The first difference is calculated based on the difference between the actual permeability and the minimum permeability; Calculate the second difference based on the difference between the maximum and minimum permeability; The orderliness of the tobacco arrangement in the cigarette under test is determined based on the ratio between the first difference and the second difference.

3. The method according to claim 2, characterized in that, The numerical value of the tobacco shred arrangement order result of the tested cigarette is between 0 and 1. The larger the numerical value of the tobacco shred arrangement order result, the higher the tobacco shred arrangement order, and the smaller the numerical value of the tobacco shred arrangement order result, the lower the tobacco shred arrangement order.

4. The method according to claim 1, characterized in that, The maximum permeability of the ideal cigarette, calculated based on the predetermined ideal porosity and ideal pore radius, is obtained using the following algorithm: Where, k max K0 is the maximum penetration rate of an ideal cigarette, where K is the Kozeny constant and ɛ is the maximum penetration rate of the cigarette. max r represents the maximum ideal porosity of a predetermined ideal cigarette. max This represents the maximum ideal pore radius of a predetermined ideal cigarette.

5. The method according to claim 1, characterized in that, The minimum permeability of the ideal cigarette, calculated based on the predetermined ideal porosity and ideal pore radius, is obtained using the following algorithm: Where, k min K0 is the minimum permeability of an ideal cigarette, where K is the Kozeny constant and ɛ is the octane rating. min r represents the minimum ideal porosity of a predetermined ideal cigarette. min This is the minimum ideal pore radius of a predetermined ideal cigarette.

6. The method according to claim 4, characterized in that, The tobacco shreds in the ideal cigarette are all arranged parallel to the central axis of the ideal cigarette.

7. The method according to claim 1, characterized in that, The characteristic parameters of the cigarette to be tested are obtained as follows: The projected data image of the cigarette to be tested is obtained by scanning equipment; The projected data image is processed by a reconstruction algorithm to obtain a tomographic image of the cigarette to be tested. The tomographic image of the cigarette to be tested is segmented and preprocessed to extract pore structure feature information, which includes at least one of the following: size and shape of pores and tobacco shreds, pore volume, tobacco shred filling rate, and pore size distribution. Based on the aforementioned pore structure feature information, an effective pore network structure topology model and a pore throat ball-and-stick geometric model are established. Based on the effective pore network structure topology model and the pore throat ball-and-stick geometric model, the characteristic parameters of the cigarette to be tested are obtained.

8. A device for predicting the orderly arrangement of tobacco shreds, characterized in that, The device includes: The parameter acquisition module is used to acquire the characteristic parameters of the cigarette to be tested, including at least one of the following: porosity, actual permeability, specific surface area, and pore radius; The first calculation module is used to calculate the maximum and minimum permeability of the ideal cigarette based on the predetermined ideal porosity and ideal pore radius of the ideal cigarette. The second calculation module is used to determine the orderliness of the tobacco arrangement of the cigarette stick to be tested based on the maximum permeability, the minimum permeability, and the actual permeability.

9. An electronic device, comprising: One or more processors; A memory for storing one or more computer programs, characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 7.

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