Characterization method for granularity distribution uniformity of tobacco stems

Abstract

The invention discloses a characterization method for granularity distribution uniformity of tobacco stems. The characterization method comprises the following steps: 1, measuring bulk density; 2, processing a sample; 3, measuring particle distribution, 4, normalizing the length, the diameter and the mass of particles, 5, judging the relative weight of an index, 6, calculating comprehensive dispersion, 7, calculating a granularity uniformity coefficient of a single sample, and 8, calculating a granularity uniformity coefficient of a processing batch. According to the method, the granularity distribution uniformity characterization of a single tobacco stem sample can be met, the granularity distribution uniformity characterization of tobacco stems in a processing batch can also be met, and the defects that the mass ratio in a limited length range in a traditional evaluation mode is one dimension and relatively rough are overcome, so that the granularity distribution uniformity of the tobacco stems can be quickly, accurately and objectively reflected.

Description

Technical Field

[0001] This invention relates to a method for characterizing the uniformity of tobacco stem particle size distribution, belonging to the field of cigarette processing. Background Technology

[0002] Tobacco stems are one of the main auxiliary raw materials in cigarette production, playing a crucial role in reducing costs and increasing efficiency, balancing smoke, improving combustion performance, and reducing tar and harmful substances in cigarette products. Therefore, cigarette manufacturers pay close attention to the quality of tobacco stems. The uniformity of tobacco stem particle size distribution is a key indicator of tobacco stem quality. During the leaf threshing and re-drying process, the particle size of tobacco stems can vary significantly due to factors such as fluctuations in raw tobacco leaf volume, adjustments to leaf-stem separation parameters, screening effects, and process pathways. Furthermore, different tobacco threshing and re-drying enterprises in the tobacco industry use slightly different screening methods and screen sizes, resulting in slight variations in the particle size of tobacco stems sourced from different production areas and grades. Better uniformity of tobacco stem particle size leads to better stability in the physicochemical properties, smoke indicators, and sensory quality of cigarette products. Conversely, poorer uniformity results in poorer stem stability and greater fluctuations in cigarette product quality.

[0003] A search of existing technical literature and invention patents revealed that the tobacco industry's current evaluation of tobacco stem particle size uniformity only considers two indicators: long stem rate (>20mm) and broken stem rate (≤10mm). This only addresses the mass percentage within a defined length range, neglecting the fineness of the particles. Furthermore, due to the significant differences in individual particle size and the large number of particles within a tobacco stem, characterizing the uniformity of particle size distribution is difficult, and the industry has not yet established a mature characterization method. Therefore, the existing evaluation system is limited to one dimension and is relatively coarse, failing to fully reflect the true distribution of tobacco stem particle size. No existing methods for characterizing the uniformity of tobacco stem particle size distribution have been reported. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method for characterizing the uniformity of tobacco stem particle size distribution. The method utilizes a multi-index comprehensive evaluation approach, which uses a single comprehensive value to characterize multiple indicators reflecting the size of tobacco stem particles, such as length, diameter, and weight. Furthermore, it employs a uniformity coefficient to quantitatively evaluate the particle size of the tobacco stem structure, thereby enabling a rapid, accurate, and objective reflection of the uniformity of tobacco stem particle size distribution.

[0005] The objective of this invention is achieved through the following technical solution: The method for characterizing the uniformity of tobacco stem particle size distribution according to the present invention is characterized by comprising the following steps: Step 1: Use a standard volume measuring cylinder to randomly select samples from a processing batch. The average bulk density of the tobacco stems was obtained by measuring a sample of tobacco stems using equation (1). : (1) In equation (1), Indicates the weight of the graduated cylinder. Indicates the stacking of graduated cylinders. The weight of each tobacco stem sample. Indicates the volume of the graduated cylinder. This indicates the number of samples taken in a processing batch, and ≥5; Step 2: After sieving out short and broken stems from each tobacco stem sample using a sieve, pour the mixture onto a dividing plate and mix them. Then, use the quartering method to divide each mixed sample into four parts, resulting in each sub-sample labeled A1, A2, ... A1. k ... A N ; Step 3, determine the first The reduced sample A k tobacco stem particle size distribution: The first The reduced sample A k The tobacco stems were laid flat on the conveyor belt of the tobacco stem comprehensive testing platform, and A was determined using the image method. k The length sequence of each tobacco stem particle Diameter sequence of tobacco stem particles Projected area sequence of tobacco stem particles ;in, A represents k The length of the i-th tobacco stem particle, A represents k The diameter of the i-th tobacco stem particle. A represents k The projected area of ​​the i-th tobacco stem particle. A represents k The total number of tobacco stem particles from the middle root; Calculate A using equation (2) k Mass sequence of each tobacco stem particle : (2) In equation (2), A represents k The mass of the i-th tobacco stem particle; Step 4: For each , and After normalization, the normalized length of the i-th tobacco stem particle is obtained. ,diameter ,quality ; Step 5: Construct the decision matrix ,in, The score represents the importance of the j-th indicator to the x-th indicator; and the weight of the j-th indicator is calculated using equation (6). Thus, to Normalization is performed to obtain the relative weight of the j-th indicator. ; (6) In equation (6), when j=1, Relative weights representing length When j=2, Represents the relative weight of the diameter When j=3, Relative weights representing quality ; Step 6: Calculate A using equation (7) k The overall dispersion of the i-th tobacco stem particle Thus, we obtain A k Comprehensive discreteness sequence ; (7) Step 7: Calculate A using equation (8) k tobacco stem particle size distribution uniformity coefficient Thus, the particle size uniformity coefficient sequence is obtained. ; (8) In equation (9), For adjustment coefficients, A represents k The mean of the overall dispersion is given by: (9) Step 8: Calculate the uniformity coefficient of tobacco stem particle size distribution for a processing batch using equation (10). : (10).

[0006] The present invention provides an electronic device, including a memory and a processor, characterized in that the memory is used to store a program supporting the processor in performing the method described therein, and the processor is configured to execute the program stored in the memory.

[0007] The present invention provides a computer-readable storage medium on which a computer program is stored, characterized in that the computer program is executed by a processor to perform the steps of the method described thereon.

[0008] Compared with existing technologies, the beneficial effects of this invention are reflected in: 1. This invention comprehensively evaluates the uniformity of tobacco stem distribution from three dimensions: length, diameter, and mass, thus overcoming the shortcomings of traditional methods that limit the mass proportion within a single length range and are relatively coarse.

[0009] 2. This invention can satisfy the characterization of particle size distribution uniformity of a single tobacco stem sample, as well as the characterization of particle size distribution uniformity of processed tobacco stem batches.

[0010] 3. This invention can objectively reflect the uniformity of tobacco stem particle size distribution, providing a reference for the selection of tobacco stem screening equipment, optimization of process parameters for leaf re-drying enterprises, and quality evaluation of tobacco stem procurement by cigarette manufacturing enterprises, thus strengthening the guarantee level of tobacco stem raw materials.

[0011] 4. This invention has the advantages of being fast, simple, and efficient, and can quantitatively, objectively, and accurately characterize the uniformity of tobacco stem particle distribution. Attached Figure Description

[0012] Figure 1 This is a schematic diagram illustrating the principle of the present invention for determining the particle size of tobacco stems; Figure 2 This is a schematic diagram of the workflow of the method for characterizing the uniformity of tobacco particle size distribution according to the present invention. Detailed Implementation

[0013] In this embodiment, a method for characterizing the uniformity of tobacco stem particle size distribution is described, such as... Figure 1 and Figure 2 As shown, it includes the following steps: Step 1: Use a standard volume measuring cylinder to randomly select samples from a processing batch. The average bulk density of the tobacco stems was obtained by measuring a sample of tobacco stems using equation (1). : (1) In equation (1), Indicates the weight of the graduated cylinder. Indicates the stacking of graduated cylinders. The weight of each tobacco stem sample Indicates the volume of the graduated cylinder. This indicates the number of samples taken in a processing batch, and ≥5.

[0014] Step 2: After sieving out short and broken stems from each tobacco stem sample using a sieve, pour the mixture onto a dividing plate and mix them. Then, use the quartering method to divide each mixed sample into smaller portions, which are then labeled as A1, A2, ... A1. k ... A N .

[0015] Step 3, determine the first The reduced sample A k tobacco stem particle size distribution: The first The reduced sample A k The tobacco stems were laid flat on the conveyor belt of the tobacco stem comprehensive testing platform, and A was determined using the image method. k The length sequence of each tobacco stem particle Diameter sequence of tobacco stem particles Projected area sequence of tobacco stem particles ;in, A represents k The length of the i-th tobacco stem particle, A represents k The diameter of the i-th tobacco stem particle. A represents k The projected area of ​​the i-th tobacco stem particle. A represents k The total number of tobacco stem particles in the middle root.

[0016] Calculate A using equation (2) k Mass sequence of each tobacco stem particle : (2) In equation (2), A represents k The mass of the i-th tobacco stem particle.

[0017] Step 4: Use equations (3)-(5) to respectively... , and After normalization, the normalized length of the i-th tobacco stem particle is obtained. ,diameter ,quality ; (3) (4) (5) In equations (3)-(5), , , A respectively k The minimum values ​​of length, diameter, and mass of tobacco stem particles. , , A respectively k The maximum values ​​of length, diameter, and mass of tobacco stem particles.

[0018] Step 5: Construct the decision matrix ,in, This represents the importance score between the j-th indicator and the x-th indicator; and =1 / When j=x, =1; where, This indicates the level of control over the length of the tobacco stem. This indicates the level of control over the diameter of the tobacco stem. This indicates the quality control level of the tobacco stems.

[0019] The weight of the j-th indicator is calculated using equation (6). This allows us to obtain the weights of the three indicators: length, diameter, and mass. ; and on Normalization is performed to obtain the relative weight of the j-th indicator. ; (6) In equation (6), when j=1, Relative weights representing length When j=2, Represents the relative weight of the diameter When j=3, Relative weights representing quality .

[0020] Step 6: Calculate A using equation (7) k The overall dispersion of the i-th tobacco stem particle Thus, we obtain A k Comprehensive discreteness sequence ; (7) Step 7: Calculate A using equation (8) k tobacco stem particle size distribution uniformity coefficient Thus, the particle size uniformity coefficient sequence is obtained. ; (8) In equation (8), For adjustment coefficients, A represents k The mean of the overall dispersion is given by: (9) Step 8: Calculate the uniformity coefficient of tobacco stem particle size distribution for a processing batch using equation (10). : (10).

[0021] In this embodiment, an electronic device includes a memory and a processor. The memory stores a program that supports the processor in executing the methods described above, and the processor is configured to execute the program stored in the memory.

[0022] In this embodiment, a computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the above-described method.

[0023] The present invention will be further described in conjunction with the following embodiments: Example 1 Taking a batch of tobacco stems processed by a tobacco re-drying enterprise as an example, the method of this invention is used to characterize the uniformity of tobacco stem particle distribution. The specific steps are as follows: Step 1: After production stabilizes, the bulk density of the tobacco stems is measured at the packaging area using a 5L standard volume graduated cylinder. Five samples are randomly selected from one processing batch. The weight of the graduated cylinder and the weight of the cylinder after it is filled with tobacco stems are shown in Table 1. The measured bulk density of this batch of tobacco stems is 0.82 g / cm³. 3 .

[0024] Table 1 Results of tobacco stem bulk density measurement (2) After removing the short and broken stems from each of the above 5 tobacco stem samples by sieving them with a sieve with a length of 20mm and a width of 5mm, pour them onto a sample dividing plate for mixing, and then divide each of the mixed samples into four parts by the quartering method, so that each of the divided samples is labeled as A1, A2, A3..., A5.

[0025] (3) Determine the tobacco stem particle size distribution of the first reduced sample A1: The first reduced sample A1 was laid flat on the conveyor belt of the tobacco stem comprehensive testing platform, and the length sequence of each tobacco stem particle in A1 was determined using the image method. Diameter sequence of tobacco stem particles Projected area sequence of tobacco stem particles The specific values ​​are shown in Tables 2, 3, and 4. The mass sequence of each tobacco stem particle in A1 is calculated using equation (2). Specific values ​​are shown in Table 5.

[0026] Table 2 Results of length measurement of tobacco stem particle size distribution in sample A1 Table 3 Results of particle size distribution and diameter determination of tobacco stems in sample A1 Table 4 Results of Projected Area Measurement of Particle Size Distribution of Tobacco Stems in Sample A1 Table 5. Calculation results of tobacco stem particle size distribution in sample A1 (4) Dimensionless processing: The length, diameter and mass of tobacco stem particles of sample A1 were normalized to the dimensionless range, as shown in Tables 6, 7 and 8 respectively.

[0027] Table 6. Normalization of tobacco stem particle size and length in sample A1 Table 7 Normalized treatment of tobacco stem particle size in sample A1 Table 8 Normalization of tobacco stem particle size in sample A1 (5) Judgment index relative weight: Based on the test results of the correlation between the production consumption of stem wire and these three indicators, each judgment matrix is ​​constructed as shown in Table 9.

[0028] Table 9 Weight Judgment Matrix Relative weight of length index =0.571+0.333+0.637 / 3=0.514; Relative weight of diameter index =0.286+0.333+0.258 / 3=0.292; relative weights of quality indicators =0.143+0.333+0.105 / 3=0.194.

[0029] (6) Calculation of overall dispersion: For each tobacco stem of sample A1, calculate the geometric deviation after dimensionless processing, as shown in Table 10.

[0030] Table 10 Results of the calculation of the overall dispersion of sample A1 (7) Calculation of uniformity coefficient of tobacco stem particle size distribution in a single sample: As shown in Table 10, It is 0.679. The adjustment coefficient is 1, and the uniformity coefficient of tobacco stem particle size in sample A1 is... The value is 0.51, indicating that the particle size distribution uniformity of the tobacco stem sample is poor. The particle size uniformity coefficients of tobacco stem samples A2, A3, ..., A5 are shown in Table 11.

[0031] (8) Calculation of the uniformity coefficient of tobacco stem particle size distribution in processed batches: As shown in Table 11, the uniformity of tobacco stem particle size distribution in processed batches... The value is 0.55, according to the company's internal control standards. A value greater than 0.60 indicates that the uniformity of the particle size distribution of the tobacco stems in this batch does not meet the technical requirements, and further equipment or process improvements are needed. In addition, there are significant differences in the particle size distribution uniformity coefficient among different samples, with a maximum value of 0.62 and a minimum value of 0.47, which may be related to factors such as fluctuations in tobacco raw materials and leaf trimming parameters.

[0032] Table 11 Uniformity coefficient of particle size distribution in tobacco stem samples Example 2: The tobacco stem raw materials of a certain cigarette manufacturing enterprise come from 7 leaf-processing and re-drying enterprises. One batch of tobacco stems was randomly selected from each leaf-processing and re-drying enterprise, and the uniformity coefficient of particle size distribution of tobacco stems from different leaf-processing and re-drying enterprises was characterized. The results are shown in Table 12.

[0033] Table 12. Characterization results of uniformity of tobacco stem particle size distribution in different tobacco stem re-drying enterprises. Table 12 shows that the uniformity coefficient of tobacco stem particle size distribution varies to some extent among different tobacco stem processing enterprises. The highest uniformity coefficient (0.81) is found in batches processed by enterprise G, while the lowest (0.53) is found in batches processed by enterprise B. Furthermore, batches processed by enterprises B and E have uniformity coefficients less than 0.60, indicating varying levels of tobacco stem quality control among these enterprises, which affects the stability of subsequent cigarette products. The next step is to urge tobacco stem processing enterprises with weak quality control to improve their practices.

[0034] Example 3: Taking five batches of tobacco stems processed by a certain cigarette manufacturing enterprise in 2024 from a tobacco re-drying enterprise (A as an example), the uniformity coefficient of the particle size distribution of tobacco stems in different batches was characterized, and the results are shown in Table 13.

[0035] Table 13 Characterization results of the uniformity coefficient of tobacco stem particle size distribution in different processing batches of enterprise A (a tobacco leaf re-drying company). As shown in Table 13, the uniformity coefficient of tobacco stem particle size distribution in all five processing batches of the A-grade tobacco re-drying enterprise exceeded 0.60, meeting the internal control standard requirements. There were certain differences in the uniformity coefficient of tobacco stem particle size distribution among different processing batches. Among them, the uniformity coefficient of tobacco stem particle size distribution in batch AH003 was the lowest at 0.62, while that in batch AH004 was the highest at 0.79. The main reason for this difference may be related to factors such as the blending method (the uniformity of tobacco stem particle size distribution in batches processed from single-grade raw materials is generally better than that in modular formulations).

[0036] Example 4: A tobacco leaf re-drying enterprise carried out a technological transformation, changing the tobacco stem screening equipment from vibrating screening to drum screening. The uniformity coefficient of tobacco stem particle size distribution and related quality indicators of tobacco stems in the processed batches before and after the technological transformation were characterized and tested. The results are shown in Table 14.

[0037] Table 14. Quality test results of tobacco stems before and after technological transformation of a tobacco re-drying enterprise. As shown in Table 14, compared with before the technological upgrade, the uniformity coefficient of tobacco stem particle size distribution in the processed batches increased by 36.84 percentage points after the upgrade. Simultaneously, the long stem rate increased by 3.66%, and the broken stem rate decreased by 1.45%. This indicates that the replacement of vibrating screen with drum screen in the technological upgrade has achieved significant results in improving tobacco stem quality. This example also demonstrates that the uniformity coefficient of tobacco stem particle size distribution in the processed batches can evaluate tobacco stem quality in the same way as traditional indicators such as long stem rate and broken stem rate. This provides a basis for optimizing process equipment parameters in leaf re-drying enterprises and ensuring the quality control of tobacco stem procurement in the cigarette industry.

Claims

1. A method for characterizing the uniformity of tobacco stem particle size distribution, characterized in that, Includes the following steps: Step 1: Use a standard volume measuring cylinder to randomly select samples from a processing batch. The average bulk density of the tobacco stems was obtained by measuring a sample of tobacco stems using equation (1). : (1) In equation (1), Indicates the weight of the graduated cylinder. Indicates the stacking of graduated cylinders. The weight of each tobacco stem sample Indicates the volume of the graduated cylinder. This indicates the number of samples taken in a processing batch, and ≥5; Step 2: After sieving out short and broken stems from each tobacco stem sample using a sieve, pour the mixture onto a dividing plate and mix them. Then, use the quartering method to divide each mixed sample into smaller portions, which are then denoted as A1, A2, ... A1. k ... A N ; Step 3, determine the first The reduced sample A k tobacco stem particle size distribution: The first The reduced sample A k The tobacco stems were laid flat on the conveyor belt of the tobacco stem comprehensive testing platform, and A was determined using the image method. k The length sequence of each tobacco stem particle Diameter sequence of tobacco stem particles Projected area sequence of tobacco stem particles ;in, A represents k The length of the i-th tobacco stem particle, A represents k The diameter of the i-th tobacco stem particle. A represents k The projected area of ​​the i-th tobacco stem particle. A represents k The total number of tobacco stem particles from the middle root; Calculate A using equation (2) k Mass sequence of each tobacco stem particle : (2) In equation (2), A represents k The mass of the i-th tobacco stem particle; Step 4: For each , and After normalization, the normalized length of the i-th tobacco stem particle is obtained. ,diameter ,quality ; Step 5: Construct the decision matrix ,in, The score represents the importance of the j-th indicator to the x-th indicator; and the weight of the j-th indicator is calculated using equation (6). Thus, to Normalization is performed to obtain the relative weight of the j-th indicator. ; (6) In equation (6), when j=1, Relative weights representing length When j=2, Represents the relative weight of the diameter When j=3, Relative weights representing quality ; Step 6: Calculate A using equation (7) k The overall dispersion of the i-th tobacco stem particle Thus, we obtain A k Comprehensive discreteness sequence ; (7) Step 7: Calculate A using equation (8) k tobacco stem particle size distribution uniformity coefficient Thus, the particle size uniformity coefficient sequence is obtained. ; (8) In equation (9), For adjustment coefficients, A represents k The mean of the overall dispersion is given by: (9) Step 8: Calculate the uniformity coefficient of tobacco stem particle size distribution for a processing batch using equation (10). : (10)。 2. An electronic device, comprising a memory and a processor, characterized in that, The memory is used to store a program that supports the processor in executing the method of claim 1, the processor being configured to execute the program stored in the memory.

3. A computer-readable storage medium storing a computer program, characterized in that, The computer program is executed by the processor to perform the steps of the method of claim 1.

Images