Cigarette perfuming process parameter optimization method and device and storage medium

Abstract

The invention relates to an optimization method and device for cigarette flavoring technological parameters and a storage medium, and the optimization method for the cigarette flavoring technological parameters comprises the steps that according to obtained material parameters of cut tobacco particles, a flexible simulation model of the cut tobacco particles is constructed; according to the obtained construction parameters of the rotary drum spray perfuming equipment, constructing a numerical model of the rotary drum spray perfuming equipment; obtaining core regulation and control parameters of the cigarette perfuming process; based on the flexible simulation model, the numerical model and the core regulation and control parameters of the cigarette perfuming process, carrying out numerical simulation on the flowing process of cut tobacco particles in the rotary drum spray perfuming equipment to obtain a particle imbibition non-uniformity index; and based on the particle imbibition non-uniform index, adjusting the core regulation and control parameters of the cigarette flavoring process to obtain the optimal core regulation and control parameters of the cigarette flavoring process. By means of the perfuming device, the problem that perfuming uniformity is not stable is solved.

Description

Technical Field

[0001] This application relates to the engineering application of adding liquid materials to particulate matter by spraying, and in particular to methods, apparatus and storage media for optimizing cigarette flavoring process parameters. Background Technology

[0002] In cigarette production, the tobacco processing and flavoring process is a crucial step in determining the aroma quality and smoking experience of the finished cigarette. Typically, liquid flavoring agents are added to the tobacco shreds in a spray form within a rotating drum. Uneven distribution of liquid absorption by the tobacco particles can result in localized areas of overly strong or weak aroma, reducing the consistency of characteristic components released in the mainstream smoke and thus affecting the stability of the cigarette's taste and the consumer experience. With the increasing demand for premium cigarettes and personalized products, the industry has placed higher demands on the uniformity of flavoring. Tobacco shreds are granular fibrous materials formed from tobacco leaves through processes such as cutting, drying, and flavoring. Their complex physical morphology, with significant differences in particle size, shape, and moisture content distribution within the same material, can easily lead to adhesion, agglomeration, or stratification during the process, affecting the uniformity of particle mixing and flavoring. Current technologies often rely on experience-based control or simplified models, resulting in unstable flavoring uniformity.

[0003] Currently, no effective solution has been proposed to address the issue of unstable fragrance uniformity in related technologies. Summary of the Invention

[0004] This application provides a method, apparatus, and storage medium for optimizing cigarette flavoring process parameters, in order to at least solve the problem of unstable flavoring uniformity in related technologies.

[0005] In a first aspect, embodiments of this application provide a method for optimizing cigarette flavoring process parameters, the method comprising:

[0006] Based on the obtained material parameters of the tobacco particles, a flexible simulation model of the tobacco particles is constructed.

[0007] Based on the obtained construction parameters of the rotary drum spray fragrance device, a numerical model of the rotary drum spray fragrance device is constructed.

[0008] Obtain the core control parameters of the cigarette flavoring process; based on the flexible simulation model, the numerical model and the core control parameters of the cigarette flavoring process, numerically simulate the flow process of the tobacco particles in the rotating drum spray flavoring device, and obtain the particle liquid absorption unevenness index;

[0009] Based on the particle liquid absorption unevenness index, the core control parameters of the cigarette flavoring process are adjusted to obtain the optimal core control parameters of the cigarette flavoring process.

[0010] In some embodiments, the flexible simulation model is a bonded spherical column unit fiber particle model, which is composed of a finite number of spherical column units connected by virtual bonds;

[0011] The material parameters of the tobacco particles include the geometric parameters and physical parameters of the tobacco particles; the physical parameters of the tobacco particles include the tensile and compressive stiffness, shear stiffness, bending stiffness and torsional stiffness of the virtual bond.

[0012] In some embodiments, the numerical model of the rotary drum spray fragrance device includes a feeding conveyor belt, a rotary drum with built-in rakes, a spraying zone, and a receiving conveyor belt;

[0013] The construction parameters of the rotary drum spray fragrance device include geometric structural parameters and physical property parameters; the physical property parameters include the elastic modulus of the device components, the coefficient of friction of different contact surfaces, and the density of tobacco particles.

[0014] In some embodiments, the core control parameters of the cigarette flavoring process include drum rotation speed, feed conveyor belt speed, tobacco material mass flow rate, and tobacco particle length-to-diameter ratio.

[0015] In some embodiments, the flow process of the tobacco particles within the rotating drum spray flavoring device is numerically simulated based on the flexible simulation model, the numerical model, and the core control parameters of the cigarette flavoring process to obtain the particle liquid absorption unevenness index, including:

[0016] Based on the flexible simulation model, the numerical model, and the core control parameters of the cigarette flavoring process, the contact force and torque are calculated by using the discrete element method, combined with the preset motion equations of the spherical and cylindrical elements and the deformation constitutive equations of the virtual bonds.

[0017] Based on the contact force and the torque, the flow process of the tobacco particles in the rotating drum spray flavoring device is simulated to obtain the particle liquid absorption unevenness index.

[0018] In some embodiments, the simulation of the flow process of the tobacco particles within the rotating drum spray flavoring device based on the contact force and the torque, to obtain the particle liquid absorption unevenness index, includes:

[0019] Based on the contact force and the torque, the flow process of the tobacco particles in the rotating drum is simulated, and the residence time of each tobacco particle in the preset spray zone is recorded.

[0020] Based on the residence time, the particle liquid absorption unevenness index is obtained.

[0021] In some embodiments, before adjusting the core control parameters of the cigarette flavoring process based on the particle liquid absorption unevenness index, the process includes:

[0022] The flexible simulation model and the numerical model of the rotating drum spray fragrance device are corrected.

[0023] In some embodiments, the calibration of the flexible simulation model and the numerical model of the rotating drum spray fragrance device includes:

[0024] The Lacey index in numerical simulation and the Lacey index in real physical experiments were calculated using image analysis methods; the Lacey index is an indicator for quantifying the mixing uniformity of a particle system.

[0025] Based on the error between the numerical simulation of the Laissie index and the actual physical experiment of the Laissie index, the material parameters of the tobacco particles and the construction parameters of the rotating drum spray flavoring device are adjusted so that the error is within a preset range.

[0026] Secondly, embodiments of this application provide an apparatus for optimizing cigarette flavoring process parameters, the apparatus comprising:

[0027] The flexible simulation model construction module is used to construct a flexible simulation model of the tobacco particles based on the obtained material parameters of the tobacco particles.

[0028] The numerical model construction module is used to construct a numerical model of the rotary drum spray fragrance device based on the obtained construction parameters of the rotary drum spray fragrance device;

[0029] The numerical simulation module is used to obtain the core control parameters of the cigarette flavoring process; based on the flexible simulation model, the numerical model and the core control parameters of the cigarette flavoring process, the flow process of the tobacco particles in the rotating drum spray flavoring device is numerically simulated to obtain the particle liquid absorption unevenness index.

[0030] The parameter optimization module is used to adjust the core control parameters of the cigarette flavoring process based on the particle liquid absorption unevenness index, so as to obtain the optimal core control parameters of the cigarette flavoring process.

[0031] Thirdly, embodiments of this application provide a storage medium storing a computer program that, when executed by a processor, implements the method for optimizing cigarette flavoring process parameters as described in the first aspect above.

[0032] Compared to related technologies, the method, apparatus, and storage medium for optimizing cigarette flavoring process parameters provided in this application's embodiments construct a flexible simulation model of tobacco particles based on the obtained material parameters of the tobacco particles; construct a numerical model of the rotary drum spray flavoring device based on the obtained construction parameters of the rotary drum spray flavoring device; obtain the core control parameters of the cigarette flavoring process; based on the flexible simulation model, numerical model, and core control parameters of the cigarette flavoring process, numerically simulate the flow process of tobacco particles in the rotary drum spray flavoring device to obtain the particle liquid absorption unevenness index; and adjust the core control parameters of the cigarette flavoring process based on the particle liquid absorption unevenness index to obtain the optimal core control parameters of the cigarette flavoring process, thus solving the problem of unstable flavoring uniformity.

[0033] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0034] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0035] Figure 1 This is a hardware structure block diagram of a terminal for a method of optimizing cigarette flavoring process parameters according to an embodiment of this application;

[0036] Figure 2 This is a flowchart of a method for optimizing cigarette flavoring process parameters according to an embodiment of this application;

[0037] Figure 3 This is a schematic diagram of a flexible simulation model of tobacco particles according to this embodiment;

[0038] Figure 4 This is a snapshot of a schematic diagram and numerical simulation of a cigarette rotary drum spray flavoring device according to an embodiment of this application;

[0039] Figure 5 It is a curve showing the change of the instantaneous average residence time of particles with time under different drum speeds according to the embodiments of this application;

[0040] Figure 6 The curves showing the steady-state average residence time of particles as a function of drum rotation speed at different drum speeds according to embodiments of this application are shown.

[0041] Figure 7 It is a curve showing the change of instantaneous liquid absorption non-uniformity index over time at different drum speeds according to embodiments of this application;

[0042] Figure 8The curves showing the steady-state average liquid absorption non-uniformity index as a function of drum rotation speed at different drum speeds according to embodiments of this application are shown.

[0043] Figure 9 It is a curve showing the steady-state average residence time of particles as a function of the feed conveyor speed under different feed conveyor speeds according to embodiments of this application;

[0044] Figure 10 It is a curve showing the steady-state average liquid absorption non-uniformity index as a function of the feed conveyor speed under different feed conveyor speeds according to embodiments of this application;

[0045] Figure 11 The curves showing the steady-state average residence time of particles as a function of the mass flow rate of tobacco material under different mass flow rates according to embodiments of this application are shown.

[0046] Figure 12 It is a curve showing the steady-state average liquid absorption non-uniformity index as a function of the mass flow rate of tobacco material under different mass flow rates according to embodiments of this application;

[0047] Figure 13 It is a curve showing the steady-state average residence time of tobacco particles as a function of the aspect ratio of tobacco particles under different aspect ratios according to embodiments of this application;

[0048] Figure 14 The curves showing the steady-state average liquid absorption non-uniformity index as a function of the aspect ratio of tobacco particles under different aspect ratios according to embodiments of this application are shown.

[0049] Figure 15 This is a flowchart illustrating a method for optimizing cigarette flavoring process parameters according to an embodiment of this application.

[0050] Figure 16 This is a structural block diagram of an apparatus for optimizing cigarette flavoring process parameters according to an embodiment of this application. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application. Furthermore, it is understood that although the efforts made in such a development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, modifications to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0052] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0053] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application means two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The terms “first,” “second,” “third,” etc., used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0054] The method embodiments provided in this example can be executed on a terminal, computer, or similar computing device. Taking running on a terminal as an example, Figure 1 This is a hardware structure block diagram of a terminal for a method of optimizing cigarette flavoring process parameters according to an embodiment of this application. For example... Figure 1 As shown, a terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. Optionally, the terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the terminal described above. For example, the terminal may also include components that are more... Figure 1The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0055] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the method for optimizing cigarette flavoring process parameters in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the aforementioned method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0056] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the terminal's communication provider. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0057] This embodiment provides a method for optimizing the parameters of the cigarette flavoring process. Figure 2 This is a flowchart of a method for optimizing cigarette flavoring process parameters according to an embodiment of this application, such as... Figure 2 As shown, the process includes the following steps:

[0058] Step S201: Based on the obtained material parameters of the tobacco particles, construct a flexible simulation model of the tobacco particles.

[0059] Specifically, based on the obtained material parameters of the tobacco particles, including geometric parameters (diameter, aspect ratio) and physical parameters (tensile and compressive stiffness, shear stiffness, bending stiffness, and torsional stiffness of virtual bonds, as well as particle friction coefficient, Poisson's ratio, elastic modulus, and density), the size and shape of the tobacco particle model are determined by the diameter and aspect ratio. The flexibility of the particles is determined by specifying the tensile, compressive, shear, bending, and torsional stiffness of the particles respectively. A flexible simulation model of tobacco particles can be constructed using DEM software with a keyed spherical column unit fiber particle model. This model is composed of a finite number of spherical column units connected by virtual bonds, which can accurately replicate the flexible characteristics and actual physical form of tobacco particles, providing a realistic particle model support for subsequent numerical simulation of the flow, mixing, and liquid absorption process of tobacco in a rotating drum. Figure 3 This is a schematic diagram of a flexible simulation model of tobacco particles according to this embodiment, as shown below. Figure 3 As shown, node 21 is the center of the end face hemisphere and also the connection point of adjacent spherical cylinder elements 22. r is the radius of the end face hemisphere. The part between nodes 21 is the spherical cylinder element 22. The gray virtual key 23 is used to connect adjacent spherical cylinder elements. b Indicates the length of the virtual key.

[0060] Step S202: Based on the obtained construction parameters of the rotary drum spray fragrance device, construct a numerical model of the rotary drum spray fragrance device;

[0061] Specifically, based on the obtained construction parameters of the rotary drum spray fragrance equipment, a detailed numerical model of the equipment can be built using SolidWorks software. The model fully reproduces the core components of the equipment, including the feeding conveyor belt (e.g., matching the actual geometric dimensions of 490mm in length and 80mm in width), the rotating drum with built-in columnar rakes (e.g., 1mm in diameter, 22mm in length, 6 per circle) (e.g., 420mm in length, 100mm in radius, 3° horizontal inclination), the conical spray area (e.g., circular base radius 50mm, height 140mm), and the receiving conveyor belt (e.g., 1500mm in length, 300mm in width). Simultaneously, the physical characteristic parameters of the equipment (e.g., Young's modulus of the drum and conveyor belt 1.0×10⁻⁶) are also entered. 8 The friction coefficients between the conveyor belt surface and the particles, the roller wall and the rake nails and the particles, and between the particles are 0.6, 0.5, and 1.0 respectively (the density of tobacco particles is 264 kg / m³, etc.). This ensures that the model is highly consistent with the actual equipment in terms of geometry and physical properties, providing an accurate equipment scene carrier for subsequent numerical simulation of tobacco particle flow, mixing and spray flavoring processes using DEM software. Figure 4 This is a snapshot of a schematic diagram and numerical simulation of a cigarette rotary drum spray flavoring device according to an embodiment of this application, such as... Figure 4As shown in the figure above, the tobacco shreds enter the device through the feeding conveyor belt 42, and then enter the drum 43 with rakes 41 (the drum 43 has a certain inclination angle 46). In the spray zone 44 inside the drum 43, the tobacco particles 45 will come into contact with the atomized flavoring agent. The flavored tobacco shreds are finally sent out by the receiving conveyor belt 47. The figure below is a visualization result of numerical simulation based on the discrete element method (DEM). Different colored particles (such as blue and red particles) are used to simulate the flow, mixing and flavoring process of tobacco shreds in the equipment. It intuitively presents the dynamic behavior of tobacco shreds entering the drum from the feeding conveyor belt, being stirred by the rakes inside the drum, absorbing liquid through the spray zone, and finally flowing to the receiving conveyor belt.

[0062] Step S203: Obtain the core control parameters of the cigarette flavoring process; Based on the flexible simulation model, numerical model and core control parameters of the cigarette flavoring process, numerically simulate the flow process of tobacco particles in the rotating drum spray flavoring equipment to obtain the particle liquid absorption unevenness index.

[0063] Specifically, the system first acquires the core control parameters of the cigarette flavoring process. This parameter set covers key variables that affect the flavoring effect, including the drum rotation speed (adjustment range 20 rev / min~90 rev / min), the feed conveyor belt speed (adjustment range 0.3 m / s~0.8 m / s), the mass flow rate of tobacco material (adjustment range 0.032 kg / s~0.085 kg / s), and the aspect ratio of tobacco particles (adjustment range 9~20). Then, the constructed flexible simulation model of tobacco particles and the numerical model of the rotating drum spray flavoring equipment are imported into the DEM software. Combined with the above core control parameters, numerical simulation is carried out using the discrete element method. During the simulation, based on the preset equations of motion of the spherical-cylindrical unit and the constitutive equations of virtual bond deformation, the contact forces and torques between particles and between particles and equipment components are accurately calculated. This dynamically reproduces the entire process of tobacco particles flowing, mixing, entering the spray zone to absorb liquid, and finally flowing to the receiving conveyor belt within the drum. During the simulation, the cumulative residence time of each tobacco particle exiting the drum in the spray zone is statistically analyzed in real time using the position determination rules preset by the DEM software. This allows for the calculation of the particle liquid absorption non-uniformity index, which quantitatively characterizes the uniformity of flavoring, providing data support for subsequent optimization of process parameters.

[0064] Step S204: Based on the particle liquid absorption unevenness index, adjust the core control parameters of the cigarette flavoring process to obtain the optimal core control parameters of the cigarette flavoring process.

[0065] Specifically, after obtaining the particle liquid absorption unevenness index (COV), with minimizing the COV value as the core optimization objective, a systematic adjustment and verification was carried out on the core control parameters of the cigarette flavoring process (drum speed, feed conveyor speed, tobacco material mass flow rate, and tobacco particle length-to-diameter ratio). First, within the preset adjustment range of each parameter (drum speed 20 rev / min~90 rev / min, feed conveyor speed 0.3 m / s~0.8 m / s, material mass flow rate 0.032 kg / s~0.085 kg / s),... With parameters of kg / s and particle aspect ratio of 9-20, a controlled variable method was used to change individual parameters one by one. DEM numerical simulation was used to obtain the COV values ​​corresponding to different parameter values ​​(for each set of parameters, a DEM example was run; based on the example results, a time-averaged COV value was calculated to assess the degree of particle flavoring unevenness). The influence of each parameter on flavoring uniformity was analyzed. Subsequently, based on the single-parameter optimization results, the optimal value range of each parameter was selected for multi-parameter combination simulation. The COV values ​​under different combinations were compared to eliminate coupling interference between parameters (e.g., increasing the material mass flow rate increases particle residence time but has no significant impact on COV). Finally, through multiple rounds of simulation iteration and result verification, the optimal parameter combination that minimizes the particle liquid absorption unevenness index and conforms to actual production conditions was determined. The applicable boundaries of this optimal combination were also clarified. If the equipment geometry (e.g., drum size, spray zone shape) or tobacco physical properties (e.g., density, moisture content) changes significantly, adjustments can be made based on the same logic to ensure that the optimal core control parameters for the cigarette flavoring process, adapted to the current production conditions, are always obtained. The following is a detailed analysis of the influence of four parameters on the uniformity of flavoring: drum rotation speed, feed conveyor belt speed, tobacco material mass flow rate, and tobacco particle length-to-diameter ratio.

[0066] In the numerical simulation, while keeping other parameters and conditions constant, the drum speed n was varied within the range of 20 rev / min to 90 rev / min. Figures 5 to 8 It represents the average residence time of particles in the spray zone and the liquid absorption non-uniformity index at different drum speeds n. For example... Figure 5 As shown, the instantaneous average residence time of particles in the spray zone peaks in the initial stage, which is related to the small number of particles in the drum and on the conveyor belt at the beginning. The average residence time subsequently reaches a steady-state value. Different colors in the legend correspond to rotational speed parameters from n=20 rev / min to 90 rev / min. Based on... Figure 5 The results were used to calculate the average residence time after 14 seconds, thus obtaining the steady-state average residence time of the particles. Figure 6As shown, when the drum speed n increases from 30 rev / min to 65 rev / min, the steady-state average residence time of the particles increases slowly; when n increases from 65 rev / min to 90 rev / min, the steady-state average residence time increases more rapidly. This is because the flow pattern of the particles inside the drum changes, the dynamic angle of repose increases significantly, more particles are thrown into the air, and the chance of immersing into the spray zone increases. Figure 7 The graph shows the change in the instantaneous liquid uptake non-uniformity index (COV) of the particles over time. After an initial fluctuation phase, the COV reaches a steady-state value. Different colors in the legend correspond to rotational speeds from n=20 rev / min to 90 rev / min. The steady-state average COV is obtained by calculating the time-averaged COV value after 14 seconds. Figure 8 As shown, with the increase of the drum rotation speed n, the steady-state average liquid absorption non-uniformity index of the particles tends to decrease, indicating that the fragrance uniformity has been improved.

[0067] In the numerical simulation, the speed v_belt of the feed conveyor belt was varied within the range of 0.3 m / s to 0.8 m / s. Figures 9 to 10 It represents the average residence time of particles in the spray zone and the liquid absorption non-uniformity index under different feed conveyor belt speeds. For example... Figure 9 As shown, when v_belt increases from 0.3 m / s to 0.35 m / s, the steady-state average residence time of particles in the spray zone decreases rapidly; when v_belt increases from 0.35 m / s to 0.8 m / s, the steady-state average residence time of particles in the spray zone decreases slowly. The feed conveyor belt speed v_belt affects the speed of particle movement along the axis inside the drum. When the v_belt value is small, the particle flows slowly along the axis towards the outlet inside the drum. Therefore, the residence time of particles in the drum is longer, increasing the chance of entering the spray zone. In addition, when v_belt = 0.3 m / s, particles form a larger accumulation inside the drum, allowing more particles to enter the spray zone and increasing the residence time. Figure 10 As shown, with the increase of the feed conveyor belt speed v_belt, the steady-state average liquid absorption non-uniformity index COV of the particles first increases rapidly and then increases slowly, and the uniformity of particle flavoring deteriorates.

[0068] In the numerical simulation, the mass flow rate Q of the tobacco material was varied within the range of 0.032 kg / s to 0.09 kg / s. Figures 11 to 12 It represents the average residence time of particles in the spray zone and the liquid absorption non-uniformity index under different tobacco material mass flow rates. For example... Figure 11As shown, generally, the steady-state average residence time of particles in the spray zone increases with increasing Q. An increase in Q leads to an increase in the filling value within the drum. When Q increases from 0.056 kg / s to 0.064 kg / s, the residence time increases rapidly, reflecting a significant change in the movement and distribution of particles within the drum. However, as... Figure 12 As shown, the steady-state average liquid absorption non-uniformity index (COV) of particles does not change significantly with the increase of Q.

[0069] In the numerical simulation, the aspect ratio AR of the tobacco particles was varied within the range of 9 to 20. Figures 13 to 14 It represents the average residence time and liquid absorption non-uniformity index of particles with different aspect ratios in the spray zone. For example... Figure 13 As shown, with the increase of the aspect ratio (AR) of the tobacco particles, the steady-state average residence time of the particles in the spray zone increases approximately linearly. This is because longer particles are geometrically more likely to come into contact with the spray zone (including local entry of particles into the spray zone); in addition, given the same total solid volume, longer particles accumulate to a greater height in the drum, which also increases the chance of particles entering the spray zone. Figure 14 As shown, with the increase of AR, the steady-state average liquid absorption non-uniformity index (COV) of the particles decreases, and the rate of decrease gradually slows down. Therefore, increasing the aspect ratio of the particles is beneficial to improving the uniformity of liquid absorption and flavoring.

[0070] In summary, for the current cigarette flavoring drum equipment, within the parameter range currently under investigation, the optimal parameter combination for achieving uniform cigarette flavoring is: drum speed n = 90 rev / min, conveyor belt speed v_belt = 0.3 m / s, tobacco material mass flow rate Q = 0.056 kg / s, and particle length-to-diameter ratio AR = 20.

[0071] Steps S201 to S204 above involve first constructing a simulation model of bonded spherical-cylindrical fiber particles that closely matches the actual flexibility of tobacco particles based on the material parameters of the tobacco particles. Then, a numerical model with parameters highly consistent with the actual equipment is constructed by combining the rotary drum spray flavoring equipment. Subsequently, the core control parameters of the cigarette flavoring process are obtained and introduced. The flow, mixing, and liquid absorption processes of tobacco particles in the equipment are numerically simulated, and the particle liquid absorption unevenness index (COV) is calculated. Finally, the core parameters are adjusted to obtain the optimal combination with the goal of minimizing COV. This breaks through the limitations of traditional cigarette flavoring processes that rely on experience-based control, and realizes a refined quantitative analysis of the flavoring process. It not only accurately reveals the influence mechanism of key parameters on the residence time of tobacco particles in the spray zone and the uniformity of liquid absorption, but also provides scientifically adapted optimal process parameters for different equipment structures and different tobacco characteristics. It effectively solves the problem of uneven flavoring caused by the complex physical form of tobacco, and ultimately significantly improves the stability of the aroma quality and smoking experience of the finished cigarette. It provides systematic technical support for the precise and standardized optimization of cigarette manufacturing and flavoring processes.

[0072] In some embodiments, the flexible simulation model is a fiber particle model of bonded spherical cylindrical units, which is composed of a finite number of spherical cylindrical units connected by virtual bonds.

[0073] The material parameters of tobacco particles include the geometric parameters and physical parameters of tobacco particles; the physical parameters of tobacco particles include the tensile and compressive stiffness, shear stiffness, bending stiffness and torsional stiffness of virtual bonds.

[0074] Specifically, the flexible simulation model is not a simple simplification of tobacco particles into rigid bodies. Instead, it uses a finite number of spherical cylindrical units arranged according to the actual fiber morphology of tobacco, and connects adjacent spherical cylindrical units with virtual keys to form an overall structure. This accurately replicates the flexible deformation characteristics of tobacco particles, such as bending and torsion, that may occur during actual flow. The matching tobacco particle material parameters are further subdivided into two main categories: geometric parameters and physical parameters. Among them, geometric parameters are mainly used to define the size and shape of the model (e.g., determining the thickness of the spherical cylindrical units by diameter, and controlling the overall length and cross-sectional ratio of the tobacco particles by aspect ratio, ensuring the model...). The model's shape is consistent with the geometric characteristics of actual tobacco shreds, while the physical parameters of the tobacco particles are focused on ensuring the realism of the model's mechanical properties, especially the tensile and compressive stiffness, shear stiffness, bending stiffness, and torsional stiffness of the virtual bonds. These four types of stiffness parameters correspond to the virtual bonds' resistance to deformation when subjected to tensile / compression, shear, bending, and torsional forces, respectively. By accurately setting their values, the simulation model can exhibit a flexible response consistent with actual tobacco shreds during the simulation of tobacco particle collisions, friction, and stacking (such as slight deformation during inter-particle compression and shape adjustment during transportation), laying the foundation for the accuracy of subsequent numerical simulations.

[0075] The above embodiments, on the one hand, ensure that the simulation model of tobacco particles has both geometric realism and mechanical property conformity, avoiding simulation deviations caused by model simplification; on the other hand, they provide a high-precision particle model foundation for subsequent simulations of the flow, mixing, collision, and contact with atomized droplets of tobacco in the rotating drum, ensuring that the numerical simulation results can accurately reflect the movement state and liquid absorption law of tobacco during the actual flavoring process, and providing reliable data support for subsequent optimization of process parameters.

[0076] In some embodiments, the numerical model of the rotary drum spray fragrance device includes a feed conveyor belt, a rotary drum with built-in rakes, a spray zone, and a receiving conveyor belt;

[0077] The construction parameters of the rotary drum spray fragrance device include geometric structural parameters and physical property parameters; the physical property parameters include the elastic modulus of the device components, the coefficient of friction of different contact surfaces, and the density of tobacco particles.

[0078] Specifically, the numerical model of the rotary drum spray flavoring equipment is not a simple simplified structure, but a complete replication of the core functional modules of the actual production equipment. It includes a feeding conveyor belt for stably transporting tobacco particles into the drum, a rotary drum with columnar rakes installed on its inner wall to enhance the mixing effect of the tobacco (the arrangement and size of the rakes match the actual equipment design), a spray zone for atomizing and spraying the liquid flavoring agent (its spatial shape and spray range correspond to the real process scenario), and a receiving conveyor belt for receiving the tobacco particles after the flavoring process. The connection relationships and spatial positions of each module perfectly match the actual equipment's operating flow. Correspondingly, the construction parameters of the rotary drum spray flavoring equipment are further subdivided into geometric structural parameters to ensure the geometric accuracy of the model and parameters to ensure the authenticity of physical properties. The physical property parameters include geometric parameters covering the key dimensions of each component (such as the length and width of the feeding conveyor belt, the diameter and length of the rotating drum, the diameter and length of the rake, the height and radius of the circular base of the spray zone, and the length and width of the receiving conveyor belt), while the physical property parameters mainly include the basic mechanical properties and contact characteristics of each component of the equipment. Specifically, these include the elastic modulus of the equipment components (such as the drum wall, conveyor belt, and rake) (used to simulate the deformation characteristics of the components under stress), the coefficient of friction of different contact surfaces (the surface of the conveyor belt and the tobacco particles, the drum wall and the rake and the tobacco particles, and the friction between the tobacco particles) (used to accurately reproduce the frictional resistance effect of the particles during the conveying and mixing process), and the density of the tobacco particles themselves (used to calculate the motion state of the particles under gravity).

[0079] The above embodiments, through the precise definition of these parameters, enable the equipment numerical model to be consistent with the actual equipment in terms of appearance and structure, and to match the mechanical environment in real production in terms of physical interaction characteristics, providing highly realistic equipment scenario support for the subsequent numerical simulation of tobacco particle flow, mixing and flavoring processes.

[0080] In some embodiments, the core control parameters of the cigarette flavoring process include drum rotation speed, feed conveyor belt speed, tobacco material mass flow rate, and tobacco particle length-to-diameter ratio.

[0081] Specifically, the core control parameters of the cigarette flavoring process are not simple parameters of a single dimension, but a combination of key variables selected around the flow state of tobacco particles in the rotating drum, mixing efficiency, and contact effect with the atomized flavoring agent. Specifically, these include four core parameters: drum speed, feed conveyor belt speed, tobacco material mass flow rate, and tobacco particle length-to-diameter ratio. The rotational speed of the drum directly affects the movement of tobacco particles within the drum. Too low a speed leads to particle accumulation and insufficient mixing, while too high a speed may cause excessive centrifugal force, causing particles to scatter excessively and escape the spray zone. The adjustment range needs to cover the commonly used range of 20 rev / min to 90 rev / min in actual production to adapt to different flavoring requirements. The feed conveyor belt speed determines the rate at which tobacco particles enter the drum. Too fast a speed will shorten the residence time of particles within the drum, while too slow a speed may cause material congestion at the front end. It is typically adjusted within the range of 0.3 m / s to 0.8 m / s to balance conveying efficiency and flavoring effect. The mass flow rate of the tobacco material reflects the total amount of tobacco entering the equipment per unit time. Too high a flow rate can lead to overfilling of the drum and uneven mixing, while too low a flow rate will reduce production efficiency. It is generally controlled between 0.032 kg / s and 0.085 kg / s. Within the kg / s range; the aspect ratio of tobacco particles is a key parameter characterizing the physical morphology of tobacco, which directly affects the adhesion and aggregation characteristics between particles and the contact probability with the spray zone. Tobacco particles with different aspect ratios (9~20 range) will exhibit different dispersibility during the flow process, thus affecting the uniformity of liquid absorption.

[0082] In the above embodiments, the four parameters are interrelated and work together to affect the final effect of the fragrance addition process. Therefore, using them as core control parameters can provide a precise control direction and variable basis for subsequent optimization of fragrance uniformity through numerical simulation.

[0083] In some embodiments, based on flexible simulation models, numerical models, and core control parameters of the cigarette flavoring process, the flow process of tobacco particles in a rotating drum spray flavoring device is numerically simulated to obtain the particle liquid absorption unevenness index, including:

[0084] Based on the flexible simulation model, the numerical model, and the core control parameters of the cigarette flavoring process, the contact force and torque are calculated by using the discrete element method, combined with the preset motion equations of the spherical and cylindrical elements and the deformation constitutive equations of the virtual bonds.

[0085] Based on the contact force and the torque, the flow process of the tobacco particles in the rotating drum spray flavoring device is simulated to obtain the particle liquid absorption unevenness index.

[0086] First, the completed flexible simulation model, equipment numerical model, and core control parameters are imported into Discrete Element Method (DEM) simulation software. Using DEM as the core computational framework, and combining pre-defined spherical-cylindrical element motion equations (covering translational and rotational motion equations) and virtual bond deformation constitutive equations, the contact interactions between tobacco particles and between particles and equipment components (drum wall, rake, conveyor belt) are comprehensively quantified, thereby obtaining the contact force and torque data driving particle motion. The translational and rotational motion equations are as follows:

[0087] ;

[0088] ;

[0089] in, Here is the equation of translational motion of the particle. Here is the equation of motion for the particle, m p Where is the mass of the spherical cylinder unit, g is the gravitational acceleration vector, and F is the mass of the spherical cylinder unit. c It is the contact force vector of particle-particle and particle-wall interactions, ω p J is the angular velocity vector of the spherical cylindrical element. p It is the rotational inertia tensor, M c The contact force Fc is a torque vector generated by the contact force. In the calculation of the contact force Fc, the normal component is calculated using the Hertz model based on the current overlap between the two spherical cylindrical elements. The tangential component of the contact force during the static friction stage depends on the current normal force, tangential displacement, and loading path, and is calculated according to the Mindlin-Deresiewicz theory, with an upper limit of the product of the friction coefficient μ and the current normal contact force. The tangential component of the contact force during the sliding friction stage is equal to the product of the friction coefficient μ and the current normal contact force. The force and torque vectors acting on the spherical cylindrical element by the virtual key are represented as Fc, respectively. b and M b .

[0090] The constitutive equations for virtual key deformation (including the equations for normal force, tangential force, torque, and bending moment) are as follows:

[0091] ;

[0092] ;

[0093] ;

[0094] ;

[0095] in, For normal force, For tangential force, For torque, For bending moment; , θ T and θ B These are virtual keys (length l) bond The normal deformation, tangential deformation, torsion angle, and bending angle of E. a and E b These are the normal and flexural modulus of the virtual bond, respectively. and These are the tangential and torsional elastic moduli of the virtual key, respectively; A, I p I and I represent the area of ​​the virtual bond cross section, the polar moment of inertia, and the planar moment of inertia, respectively.

[0096] Secondly, based on the contact force and torque calculated above, the entire process of tobacco particles entering the rotating drum from the feeding conveyor belt is dynamically reproduced in DEM software. Inside the drum, the particles are stirred by rakes, subjected to gravity and centrifugal force, flow and mix, then pass through the spray zone to complete liquid absorption, and finally flow out of the drum to the receiving conveyor belt. During the simulation, the spatial coordinates of each particle are tracked in real time using the software's preset position determination rules, and its cumulative residence time (t) in the spray zone is calculated. i Meanwhile, the total number of particles (N) that finally flowed out of the drum was recorded. Then, the particle liquid absorption unevenness index, which can quantify the uniformity of liquid absorption of tobacco particles, was calculated, providing a key evaluation index for subsequent process parameter optimization.

[0097] Through the above steps, a precise quantitative simulation of the tobacco flavoring process was achieved: by using the discrete element method, combined with the motion equations of spherical and cylindrical elements and the constitutive equations of virtual bond deformation, the contact forces and torques between tobacco particles and between particles and equipment components were accurately calculated, restoring the flexible deformation and complex motion characteristics of tobacco. Furthermore, based on the equipment numerical model and process control parameters, the entire process of tobacco flow, mixing, and liquid absorption in the drum was dynamically reproduced. The resulting particle liquid absorption non-uniformity index breaks through the limitations of traditional empirical flavoring, realizes the quantitative evaluation of flavoring uniformity, provides a scientific basis for subsequent process parameter optimization, effectively improves the accuracy and stability of the cigarette flavoring process, and helps to achieve uniform and controllable cigarette aroma quality.

[0098] In some embodiments, based on contact force and torque, the flow process of tobacco particles in a rotating drum spray flavoring device is simulated to obtain a particle liquid absorption unevenness index, including:

[0099] Based on contact force and torque, the flow process of tobacco particles in a rotating drum is simulated, and the residence time of each tobacco particle in the preset spray zone is recorded.

[0100] The liquid absorption unevenness index of the particles is obtained based on the residence time.

[0101] Specifically, the calculated contact force and torque are used as the driving force to dynamically reproduce the flow and mixing process of tobacco particles after they enter the rotating drum with built-in rakes from the feed conveyor belt in the numerical model. This process is driven by the rotation of the drum, the stirring of the rakes, and the combined effects of gravity and centrifugal force. At the same time, a spray zone space range matching the actual process is preset in the model. Through the software's built-in position tracking function, the cumulative residence time (t) of each tobacco particle from entering the spray zone until it leaves is recorded in real time. i Simultaneously, record the total number of particles (N) that finally exit the drum; after all tobacco particles have completed the flow process and exited from the receiving conveyor belt, calculate the average residence time t of all particles in the spray zone based on statistical methods. ave Then, the particle liquid absorption unevenness index (COV) is calculated using the following formula:

[0102] ;

[0103] Where N is the number of tobacco particles flowing out of the roller (after spraying and flavoring), and t i It is the cumulative residence time t of particles i exiting the roller in the spray zone. ave This represents the average residence time of all particles exiting the roller in the spray zone. The particle liquid absorption non-uniformity index (COV) reflects the degree of difference in particle residence time in the spray zone. The amount of liquid absorbed by a particle in the spray zone is positively correlated with its residence time in that zone. Therefore, the degree of difference in particle residence time in the spray zone can characterize the uniformity of particle liquid absorption. The smaller the COV, the more uniform the particle liquid absorption, and the better the uniformity of cigarette flavoring.

[0104] Through the above steps, a precise quantitative evaluation of the uniformity of flavoring in tobacco shreds is achieved: driven by contact force and torque, the flow process of tobacco shreds in the drum is dynamically simulated, while the residence time of each particle in the spray zone is accurately recorded. Then, the particle liquid absorption unevenness index is calculated by statistical methods. This not only breaks through the limitation of traditional processes that cannot quantify the uniformity of flavoring, but also provides objective and quantifiable evaluation indicators for process parameter optimization. It enables cigarette flavoring to shift from experience-based to data-driven, effectively improving the controllability of the flavoring process and the stability of cigarette aroma quality.

[0105] In some embodiments, before adjusting the core control parameters of the cigarette flavoring process based on the particle liquid absorption unevenness index, the process includes:

[0106] The numerical models of the flexible simulation model and the rotating drum spray fragrance device were calibrated.

[0107] In some embodiments, the numerical models of the flexible simulation model and the rotating drum spray fragrance device are calibrated, including:

[0108] The Lacey index in numerical simulation and the Lacey index in real physical experiments were calculated using image analysis methods; the Lacey index is an indicator for quantifying the mixing uniformity of a particle system.

[0109] Based on the error between the numerical simulation of the Laissie index and the actual physical experiment of the Laissie index, the material parameters of the tobacco particles and the construction parameters of the rotating drum spray flavoring device were adjusted to keep the error within the preset range.

[0110] Specifically, image analysis was first used to acquire and analyze images of the mixing state of the tobacco particle system in the numerical simulation scenario and the mixing state of tobacco particles in the real physical experiment. Then, the simulated Lacey index and the real physical experiment Lacey index, used to quantify the mixing uniformity of the particle system, were calculated. The errors of these two indices were then compared. If the error exceeded a preset range, the material parameters of the tobacco particles (such as the stiffness of virtual bonds, particle friction coefficient, etc.) and the construction parameters of the rotating drum spray flavoring device (such as the elastic modulus of device components, friction coefficients of various contact surfaces, geometric dimensions, etc.) were adjusted accordingly. Through repeated iterative adjustments and verifications, the errors of the simulated Lacey index and the real physical experiment Lacey index were kept within a preset acceptable range. This ensured that the flexible simulation model and the equipment numerical model could accurately reproduce the actual mixing behavior of tobacco particles, providing a highly reliable model foundation for the subsequent numerical simulation of the flavoring process. The specific steps of model calibration are as follows:

[0111] In the numerical simulation, equal amounts of red and blue tobacco particles were placed on opposite sides of the feed conveyor belt. After entering the drum, the two types of particles mixed together. The mixed particles flowed out from the other side of the inclined drum and landed on the receiving conveyor belt. Two positions were set on the conveyor belt to examine the uniformity of particle mixing in two adjacent stages before and after the same batch of feed from the same drum, comparing the differences in mixing uniformity of particles flowing out at different times within the same batch. The receiving conveyor belt was divided into position 1 and position 2. Using image analysis, the Lexis index M of the mixing of red and blue particles at positions 1 and 2 on the receiving conveyor belt could be calculated separately. Table 1 shows the Lexis index at positions 1 and 2 on the receiving conveyor belt under different drum rotation speeds and feed conveyor belt speeds, including numerical simulation results and experimental results. The error between the two results is between 4.2% and 8.7%, which is within the acceptable range. Therefore, the numerical model was corrected.

[0112] Table 1. Comparison of experimental and numerical simulation results for the Lycee index of particles at positions 1 and 2 on the receiving conveyor belt.

[0113]

[0114] The method for calculating the Lexis index M using image analysis is summarized as follows. The formula for calculating the Lexis index of particles at positions 1 and 2 on the receiving conveyor belt is:

[0115] ;

[0116] In the formula, This represents the variance of a perfectly separated mixture. This represents the mixing variance of the particles on the current receiving conveyor belt. The variance under a perfectly mixed and homogeneous state is:

[0117] ;

[0118] ;

[0119] ;

[0120] in, This represents the concentration of red particles relative to the total number of particles in the system, where n is the number of grid cells containing the particles. It is the average number of particles in each grid. Represents a grid The concentration of red particles relative to the total particles in this grid. The value of M ranges from 0 to 1: M = 0 indicates that the binary substances in the system have not mixed at all relative to the initial state, and M = 1 indicates that the two components are completely mixed.

[0121] Based on images of particles on the received conveyor belt (DEM simulation images or experimental photographs), the Lexi index M can be calculated using image processing software such as ImageJ® through the following steps:

[0122] (1) Automatically select the area where particles exist inside the drum;

[0123] (2) The extracted image is copied, and the copied image is grayscaled and filtered to obtain a black and white binary image. The black part in the image represents the area occupied by all particles.

[0124] (3) Then convert the original image to the HSB channel, extract the S (Saturation) channel image and perform grayscale and filtering to obtain the second black and white binary image. In this image, the black part represents the area occupied by the red particles.

[0125] (4) Use a script file to generate identical grids for both black and white images, and count the number of black pixels (representing the area occupied by the particles) in all grids of both images. The number of black pixels in grid i of the second image. Divide by the number of black pixels in grid i corresponding to the first image. ,Right now The concentration of the stained particles in grid i was obtained. Therefore, the Leice index M can be calculated using the above equation.

[0126] Through the above model calibration steps, a precise match between the simulation model and the real scene was achieved: using the Laixi index, which quantifies the uniformity of particle mixing, as a bridge, the numerical simulation and real experimental results were compared through image analysis, and then the parameters of the tobacco material and the equipment construction parameters were adjusted in a targeted manner until the error between the two reached the preset range. This effectively solved the simulation distortion problem caused by parameter deviation in the simulation model, ensuring that the model can realistically reproduce the tobacco mixing behavior, providing a highly reliable basis for subsequent flavoring process simulation and parameter optimization, avoiding deviation in the optimization direction due to model inaccuracy, and ensuring the practicality and effectiveness of the final process parameters.

[0127] Figure 15 This is a flowchart illustrating a method for optimizing cigarette flavoring process parameters according to an embodiment of this application, as shown below. Figure 15 As shown, the process includes the following steps:

[0128] Step S151, the process begins.

[0129] Step S152, numerical modeling, constructing a flexible tobacco particle model and a rotating drum spray model respectively.

[0130] Step S153: DEM numerical simulation of particle flow, mixing, and particle-spray zone contact.

[0131] Step S154: Experimentally calibrate the numerical model.

[0132] Step S155: Analyze the influence of key parameters on the mixing of tobacco particles and the uniformity of liquid absorption.

[0133] Step S156: Obtain the optimized parameter combination to achieve better uniformity of tobacco flavoring.

[0134] Step S157, process ends.

[0135] This embodiment also provides an optimization device for cigarette flavoring process parameters. This device is used to implement the above embodiments and preferred embodiments, and will not be repeated for details already described. As used below, the terms "module," "unit," "subunit," etc., can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0136] Figure 16This is a structural block diagram of an apparatus for optimizing cigarette flavoring process parameters according to an embodiment of this application, as shown below. Figure 16 As shown, the device includes:

[0137] The flexible simulation model construction module 161 is used to construct a flexible simulation model of the tobacco particles based on the obtained material parameters of the tobacco particles;

[0138] The numerical model construction module 162 is used to construct a numerical model of the rotary drum spray fragrance device based on the obtained construction parameters of the rotary drum spray fragrance device;

[0139] Numerical simulation module 163 is used to obtain the core control parameters of the cigarette flavoring process; based on the flexible simulation model, the numerical model and the core control parameters of the cigarette flavoring process, the flow process of the tobacco particles in the rotating drum spray flavoring device is numerically simulated to obtain the particle liquid absorption unevenness index.

[0140] The parameter optimization module 164 is used to adjust the core control parameters of the cigarette flavoring process based on the particle liquid absorption unevenness index, so as to obtain the optimal core control parameters of the cigarette flavoring process.

[0141] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can reside in the same processor; or the above modules can be located in different processors in any combination. Specific examples in this embodiment can be found in the examples described in the above embodiments and optional implementations, and will not be repeated in this embodiment.

[0142] Furthermore, in conjunction with the optimization methods for cigarette flavoring process parameters in the above embodiments, this application embodiment can provide a storage medium for implementation. This storage medium stores a computer program; when executed by a processor, the computer program implements any one of the optimization methods for cigarette flavoring process parameters in the above embodiments.

[0143] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0144] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0145] Those skilled in the art should understand that the technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments have been described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0146] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for optimizing cigarette flavoring process parameters, characterized in that, include: Based on the obtained material parameters of the tobacco particles, a flexible simulation model of the tobacco particles is constructed. Based on the obtained construction parameters of the rotary drum spray fragrance device, a numerical model of the rotary drum spray fragrance device is constructed. Obtain the core control parameters of the cigarette flavoring process; Based on the flexible simulation model, the numerical model, and the core control parameters of the cigarette flavoring process, the flow process of the tobacco particles in the rotary drum spray flavoring device is numerically simulated to obtain the particle liquid absorption unevenness index. Based on the particle liquid absorption unevenness index, the core control parameters of the cigarette flavoring process are adjusted to obtain the optimal core control parameters of the cigarette flavoring process.

2. The method for optimizing cigarette flavoring process parameters according to claim 1, characterized in that, The flexible simulation model is a bonded spherical column unit fiber particle model, which is composed of a finite number of spherical column units connected by virtual bonds. The material parameters of the tobacco particles include the geometric parameters and physical parameters of the tobacco particles; the physical parameters of the tobacco particles include the tensile and compressive stiffness, shear stiffness, bending stiffness and torsional stiffness of the virtual bond.

3. The method for optimizing cigarette flavoring process parameters according to claim 1, characterized in that, The numerical model of the rotary drum spray fragrance device includes a feeding conveyor belt, a rotary drum with built-in rakes, a spraying zone, and a receiving conveyor belt; The construction parameters of the rotary drum spray fragrance device include geometric structural parameters and physical property parameters; the physical property parameters include the elastic modulus of the device components, the coefficient of friction of different contact surfaces, and the density of tobacco particles.

4. The method for optimizing cigarette flavoring process parameters according to claim 1, characterized in that, The core control parameters of the cigarette flavoring process include drum rotation speed, feed conveyor belt speed, tobacco material mass flow rate, and tobacco particle length-to-diameter ratio.

5. The method for optimizing cigarette flavoring process parameters according to claim 1, characterized in that, Based on the flexible simulation model, the numerical model, and the core control parameters of the cigarette flavoring process, the flow process of the tobacco particles within the rotating drum spray flavoring device is numerically simulated to obtain the particle liquid absorption unevenness index, including: Based on the flexible simulation model, the numerical model, and the core control parameters of the cigarette flavoring process, the contact force and torque are calculated by using the discrete element method, combined with the preset motion equations of the spherical and cylindrical elements and the deformation constitutive equations of the virtual bonds. Based on the contact force and the torque, the flow process of the tobacco particles in the rotating drum spray flavoring device is simulated to obtain the particle liquid absorption unevenness index.

6. The method for optimizing cigarette flavoring process parameters according to claim 5, characterized in that, The process of simulating the flow of tobacco particles within the rotating drum spray flavoring device based on the contact force and the torque is used to obtain the particle liquid absorption unevenness index, including: Based on the contact force and the torque, the flow process of the tobacco particles in the rotating drum is simulated, and the residence time of each tobacco particle in the preset spray zone is recorded. Based on the residence time, the particle liquid absorption unevenness index is obtained.

7. The method for optimizing cigarette flavoring process parameters according to claim 1, characterized in that, Before adjusting the core control parameters of the cigarette flavoring process based on the particle liquid absorption unevenness index, the process includes: The flexible simulation model and the numerical model of the rotating drum spray fragrance device are corrected.

8. The method for optimizing cigarette flavoring process parameters according to claim 7, characterized in that, The calibration of the flexible simulation model and the numerical model of the rotating drum spray fragrance device includes: The Lacey index in numerical simulation and the Lacey index in real physical experiments were calculated using image analysis methods; the Lacey index is an indicator for quantifying the mixing uniformity of a particle system. Based on the error between the numerical simulation of the Laissie index and the actual physical experiment of the Laissie index, the material parameters of the tobacco particles and the construction parameters of the rotating drum spray flavoring device are adjusted so that the error is within a preset range.

9. An optimization device for cigarette flavoring process parameters, characterized in that, The device includes: The flexible simulation model construction module is used to construct a flexible simulation model of the tobacco particles based on the obtained material parameters of the tobacco particles. The numerical model construction module is used to construct a numerical model of the rotary drum spray fragrance device based on the obtained construction parameters of the rotary drum spray fragrance device; The numerical simulation module is used to obtain the core control parameters of the cigarette flavoring process; based on the flexible simulation model, the numerical model and the core control parameters of the cigarette flavoring process, the flow process of the tobacco particles in the rotating drum spray flavoring device is numerically simulated to obtain the particle liquid absorption unevenness index. The parameter optimization module is used to adjust the core control parameters of the cigarette flavoring process based on the particle liquid absorption unevenness index, so as to obtain the optimal core control parameters of the cigarette flavoring process.

10. A storage medium, characterized in that, The storage medium stores a computer program, wherein the computer program is configured to execute, when running, a method for optimizing the cigarette flavoring process parameters as described in any one of claims 1 to 8.

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