Method for controlling the amount of water added in the feed by predicting the cut tobacco moisture content in the cut tobacco

Abstract

The method for controlling water adding amount in tobacco adding by predicting tobacco cut moisture content in tobacco cutting of the present application is to select at least two batches of tobacco cut of the same brand whose cut moisture content CPK index reaches the standard, and track the tobacco cut, and the tobacco moisture content in tobacco adding process; the method comprises: calculating the median M1 of the tobacco cut moisture content in the tobacco cutting process; calculating the upper quartile, lower quartile, median, upper limit and lower limit of the tobacco moisture content in the tobacco adding process of the tobacco cut; calculating the linear deviation E of the real-time tobacco moisture content in the actual tobacco adding process and the reference value, the skewness β of the tobacco moisture content and the actual deviation Ei; predicting the tobacco cut moisture content Q of the tobacco cut in the future tobacco cutting process; and adjusting the tobacco adding amount in the tobacco adding process.

Description

Technical Field

[0001] This invention belongs to the field of cigarette manufacturing technology. Specifically, it relates to a method for predicting the moisture content of cut leaf shreds by calculating the skewness, quartile linear skewness, and actual skewness of the moisture content output from the leaf feeder during the production process. Background Technology

[0002] Moisture content of shredded tobacco leaves is a key indicator in tobacco processing. This indicator plays a decisive role in the stability control of parameters such as the plate temperature and hot air temperature of the tobacco leaf dryer. However, since the moisture content of shredded tobacco leaves is the result of the moisture content control of the output from the previous process's leaf feeder, it is impossible to directly predict the control result of the shredded tobacco leaf moisture content during the leaf feeder's production. During production, to ensure that the moisture content of shredded tobacco leaves meets the standard for most production batches, operators typically adjust the control result of the shredded tobacco leaf moisture content based on the degree of moisture deviation, which can easily cause batch-to-batch quality fluctuations. This invention establishes a calculation model for the quartile skewness of the output moisture content of the leaf feeder, the skewness of the output moisture content of the leaf feeder, and the median of the baseline shredded tobacco leaf output moisture content. This enables a direct display of the shredded tobacco leaf moisture content during the leaf feeder's production, solving the problem of predicting the shredded tobacco leaf moisture content in advance.

[0003] Regarding the precise control of cut leaf moisture content, Li Siyuan et al.'s paper, "Application of Precise Control Mode for Cut Leaf Moisture Content in Cigarette Processing," investigated the impact of control modes for secondary rehydration feeding and water replenishment during the feeding process on the stability of cut leaf moisture content control. The results demonstrated that this mode can effectively improve the cut leaf moisture content Cpk and the cylinder wall temperature Cp during the drying process. While this control mode improves the accuracy of cut leaf moisture content control, it is not yet feasible to fully adopt this mode for all cigarette brands due to limitations in process design. Given the current industry-dominated processing mode of single-stage rehydration feeding, achieving simultaneous display of cut leaf moisture content results during the control of the moisture content at the leaf feeder's outlet is of high practical value.

[0004] Hongyun Honghe Tobacco (Group) Co., Ltd.'s "A Control Method for Improving the Moisture Content of Cut Leaf Shreds" calculates the offset ratio of loose rehydration water addition for the remaining weight of the production batch by using the confidence mean difference and volume difference of the electronic belt scale speed before the leaf feeder. This allows for control of the water addition in the loose rehydration equipment, achieving a unilateral offset between the moisture content of the cut leaf shreds and the standard center moisture content. While this method improves the accuracy of the moisture content of the cut leaf shreds, it fails to achieve simultaneous calculation and display of the moisture content of the cut leaf shreds during the moisture content control process at the leaf feeder's outlet.

[0005] Hongyun Honghe Tobacco (Group) Co., Ltd.'s "A Method for Accurate Control of Tobacco Leaf Moisture in the Processing Process" obtains the median standard value of the moisture content at the tobacco leaf feeder, calculates the corrected real-time water flow rate of the loosening and rehumidifying machine using a blade linear control system, and inputs this water flow rate into the loosening and rehumidifying machine to obtain the corrected water addition value. Ultimately, this method minimizes the deviation between the actual controlled median moisture content at the tobacco leaf feeder and the median standard value for the entire batch. While this method solves the problem of accurately controlling the moisture content of the leaf output, it fails to address the issue of synchronously calculating and displaying the moisture content of the shredded tobacco leaves during the control of the moisture content at the leaf feeder output. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of existing water addition methods and to provide a method for controlling the amount of water added during feeding by predicting the moisture content of the shredded food.

[0007] To achieve the purpose of this invention, the following technical solution is adopted:

[0008] This invention provides a method for controlling the amount of water added during feeding by predicting the moisture content of the shredded tobacco. The method involves selecting at least two batches of tobacco shreds of the same brand whose CPK moisture content meets the standard after shredding, and simultaneously tracking the moisture content of the finished tobacco leaves during the feeding process. The method includes the following steps:

[0009] (I) Calculate the median moisture content M1 of the tobacco shreds during the shredding process.

[0010] Export all the raw data of tobacco moisture content during the shredding process from at least two batches of tobacco shreds, concatenate them to form an n-sequence, and calculate the median M1 of the tobacco moisture content during the shredding process.

[0011] In the above-mentioned sequence, when the number n of the tobacco moisture content values ​​is odd; M1 is the [number]th ... Moisture content of tobacco shreds arranged in a specific sequence;

[0012] In the above-mentioned sequence, when the number n of the tobacco moisture content values ​​is even, M1 is the [number]th ... The moisture content of the tobacco shreds in the sequence number and the... The average moisture content of the tobacco shreds in each sequential number;

[0013] (II) Calculate the upper quartile, lower quartile, median, upper limit, and lower limit of the moisture content of the tobacco leaves at the corresponding feeding process for the above batches of tobacco shreds.

[0014] All the original data of the moisture content of the tobacco leaves during the feeding process of the above batch of tobacco shreds were exported and concatenated to form an m-sequence. The upper quartile (Q3), lower quartile (Q1), median (M2), upper limit (U), and lower limit (L) of the sequence were calculated.

[0015] (a) Upper four fractions (Q3)

[0016] Find The integer part is denoted as k, and the fractional part is denoted as f (0 ≤ f < 1), where m is the number of original data points for the tobacco leaf output moisture content in the above sequence during the feeding process.

[0017] Q3=X(k)+f*(X(k+1)-X(k))---Formula (1)

[0018] Where: X(k+1) is the moisture content of the tobacco leaves at the (k+1)th permutation number in the above sequence, and X(k) is the moisture content of the tobacco leaves at the kth permutation number in the above sequence;

[0019] (b) Lower quartile (Q1)

[0020] Find The integer part is denoted as k, and the fractional part is denoted as f (0 ≤ f < 1), where m is the number of original data points of the tobacco leaf output moisture content in the above sequence during the feeding process.

[0021] Q1=X(k)+f×(X(k+1)-X(k))---Formula (2)

[0022] Where: X(k+1) is the moisture content of the tobacco leaves at the (k+1)th permutation number in the above sequence, and X(k) is the moisture content of the tobacco leaves at the kth permutation number in the above sequence;

[0023] (c) Median (M2)

[0024] Following step (1), replace n with m and calculate the median moisture content M2 of the tobacco leaves output during the feeding process of the above sequence;

[0025] (d) Upper limit (U)

[0026] U=Q3+1.5×(Q3-Q1)---Formula (3)

[0027] (e) Lower limit (L)

[0028] L=Q1-1.5×(Q3-Q1)---Formula (4);

[0029] The upper quartile (Q3), lower quartile (Q1), median (M2), upper limit (U), and lower limit (L) are used as the reference values ​​for formula (5);

[0030] (III) Calculate: During the actual feeding process of this brand of tobacco leaves, compare the real-time output moisture content of the tobacco leaves with the baseline value in step (II) to obtain the linear deviation E of the feeding, the skewness β of the output moisture content of the tobacco leaves, and the actual deviation Ei.

[0031] (f) Feeding linear deviation

[0032] During the actual feeding process of this brand of tobacco leaves, when at least 10 data points on the moisture content of the tobacco leaves at the output are collected, the steps (a) to (e) above are followed to calculate the real-time upper quartile (Q3i), lower quartile (Q1i), median (Mi), upper limit (Ui), and lower limit (Li) of the tobacco leaves during the feeding process. Then, the real-time data are compared with the corresponding benchmark values ​​to calculate the linear skewness (E) of the moisture content of the tobacco leaves at the output during the feeding process.

[0033] E=[(Ui-U)+(Q3i-Q3)+(Mi-M)+(Q1i-Q1)+(Li-L)]÷5---Formula (5)

[0034] (g) Skewness β of discharge moisture content

[0035]

[0036] Where: xi represents each data point of the output moisture content during the actual feeding process of the tobacco leaves mentioned above; denoted as the average output moisture content during the above-mentioned tobacco leaf feeding process; s is the standard deviation of the output moisture content during the above-mentioned tobacco leaf feeding process.

[0037] q is the number of tobacco leaves with moisture content collected during the actual feeding process described above.

[0038] (h) Calculate the actual deviation (Ei) of the output moisture content of the tobacco leaves during the above-mentioned feeding process.

[0039] Ei=β×E---Formula(7)

[0040] (iv) Predict the moisture content Q of the tobacco leaves during the future shredding process.

[0041] Q = Ei + M1 --- Formula (8)

[0042] Where: Ei is the actual deviation of the tobacco leaf output moisture content in step (h); M1 is the median of the shredded moisture content in step (i);

[0043] (v) Adjusting the amount of tobacco added during the tobacco feeding process.

[0044] During the feeding process, when the predicted moisture content of the cut tobacco leaves Q is greater than A+0.2% or less than A-0.2%, where A is the calibrated moisture content of the cut tobacco leaves, the operator adjusts the predicted moisture content Q of the cut tobacco leaves by increasing or decreasing the amount of feed until the predicted moisture content Q of the cut tobacco leaves is within the range of A±0.2%.

[0045] Repeat steps (iii) to (v) every 3-5 minutes to recalculate the real-time linear deviation E of the feeding, the deviation β of the tobacco leaf output moisture content, and the actual deviation Ei, so as to predict the real-time moisture content Q of the cut tobacco leaves and adjust the feeding amount in real time during the tobacco feeding process.

[0046] This invention discloses a method for controlling the amount of water added during feeding by predicting the moisture content of the shredded food. The method specifies that the moisture content (CPK) meets the standard, meaning CPK > 1.33.

[0047]

[0048] Where: USL is the standard upper limit value of tobacco moisture; LSL is the standard lower limit value of tobacco moisture; MU is the standard center value of tobacco moisture. σ represents the average moisture content of the tobacco shreds; σ represents the standard deviation of the moisture content of the tobacco shreds.

[0049]

[0050] Where: Xi is the moisture content of each tobacco shred, and n is the number of tobacco shred moisture contents during the shredding process.

[0051] This invention provides a method for controlling the amount of water added during feeding by predicting the moisture content of the shredded tobacco leaves, wherein: during the feeding process, s is the standard deviation of the moisture content of the tobacco leaves at the output.

[0052]

[0053] in: Xi represents the average moisture content of the tobacco leaves during the feeding process; Xi is the moisture content of each tobacco leaf output, and q is the number of tobacco leaf output moisture contents.

[0054] The present invention provides a method for controlling the amount of water added during feeding by predicting the moisture content of the shredded tobacco. In this method, the moisture content of a single shredded tobacco is detected every 3-10 seconds during the shredding process.

[0055] The present invention provides a method for controlling the amount of water added during feeding by predicting the moisture content of the shredded tobacco leaves, wherein: during the feeding process, the moisture content of the tobacco leaf is detected every 3-10 seconds.

[0056] The present invention discloses a method for controlling the amount of water added during feeding by predicting the moisture content of the shredded material during shredding, wherein: in the known shredding process in step (I) and the known feeding process in step (II), the moisture content is the moisture content during the stable stage of the shredding or feeding process.

[0057] The present invention provides a method for controlling the amount of water added during feeding by predicting the moisture content of the shredded tobacco leaves, wherein the method is applicable to the production of various grades of tobacco leaves.

[0058] The beneficial effects of the method of controlling the amount of water added in feeding by predicting the moisture content of the shredded food in the shredding process of the present invention are demonstrated through 500 batches of actual application. The unilateral deviation of the average moisture content of the shredded food is controlled within ±0.2%, and the pass rate of shredded food with a moisture content CPK≥1.33 reaches more than 99.5%, which shows good practical effect. Detailed Implementation

[0059] The method of controlling the amount of water added in the feeding process by predicting the moisture content of the shredded tobacco in the shredding process is to select 10 batches of tobacco shreds with a known moisture content CPK ≥ 1.33 of the same brand after shredding, and calculate CPK according to formula (9);

[0060]

[0061] Where: USL is the standard upper limit of tobacco moisture content; LSL is the standard lower limit of tobacco moisture content; MU is the standard center value of tobacco moisture content; for example: if the moisture content of the shredded tobacco is 20% ± 0.5%, then USL is 20.5%, LSL is 19.5%, and MU is 20%; σ represents the average moisture content of the tobacco shreds; σ represents the standard deviation of the moisture content of the tobacco shreds.

[0062]

[0063] Where: Xi is the moisture content of each tobacco shred, and n is the number of moisture content values ​​of the tobacco shreds during the shredding process;

[0064] Simultaneously, the moisture content of the tobacco leaves during the feeding process is tracked; this method includes the following steps:

[0065] (I) Calculate the median moisture content M1 of the tobacco shreds during the shredding process.

[0066] During the shredding process, the moisture content of each shredded tobacco was measured every 5 seconds. The raw moisture content data from all 10 batches of tobacco during the shredding process were exported and concatenated to form an n-sequence. The median moisture content M1 during the shredding process was calculated to be 20.15%.

[0067] In the above-mentioned sequence, when the number n of the tobacco moisture content values ​​is odd; M1 is the [number]th ... Moisture content of tobacco shreds arranged in a specific sequence;

[0068] In the above-mentioned sequence, when the number n of the tobacco moisture content values ​​is even, M1 is the [number]th ... The moisture content of the tobacco shreds in the sequence number and the... The average moisture content of the tobacco shreds in each sequential number;

[0069] (II) Calculate the upper quartile, lower quartile, median, upper limit, and lower limit of the moisture content of the tobacco leaves at the corresponding feeding process for the above batches of tobacco shreds.

[0070] During the feeding process, the output moisture content of a tobacco leaf is detected every 5 seconds. The original data of the output moisture content of the tobacco leaves corresponding to the above batch of tobacco shreds during the feeding process are all exported and concatenated to form an m sequence. The upper quartile (Q3), lower quartile (Q1), median (M2), upper limit (U), and lower limit (L) of the sequence are calculated.

[0071] (a) Upper four fractions (Q3)

[0072] Find The integer part is denoted as k, and the fractional part is denoted as f (0 ≤ f < 1), where m is the number of original data points for the tobacco leaf output moisture content in the above sequence during the feeding process.

[0073] Q3=X(k)+f*(X(k+1)-X(k))---Formula (1)

[0074] Where: X(k+1) is the moisture content of the tobacco leaves at the (k+1)th permutation number in the above sequence, and X(k) is the moisture content of the tobacco leaves at the kth permutation number in the above sequence;

[0075] (c) Lower quartile (Q1)

[0076] Find The integer part is denoted as k, and the fractional part is denoted as f (0 ≤ f < 1), where m is the number of original data points of the tobacco leaf output moisture content in the above sequence during the feeding process.

[0077] Q1=X(k)+f×(X(k+1)-X(k))---Formula (2)

[0078] Where: X(k+1) is the moisture content of the tobacco leaves at the (k+1)th permutation number in the above sequence, and X(k) is the moisture content of the tobacco leaves at the kth permutation number in the above sequence;

[0079] (c) Median (M2)

[0080] Following step (1), replace n with m and calculate the median moisture content M2 of the tobacco leaves output during the feeding process of the above sequence;

[0081] (d) Upper limit (U)

[0082] U=Q3+1.5×(Q3-Q1)---Formula (3)

[0083] (f) Lower limit (L)

[0084] L=Q1-1.5×(Q3-Q1)---Formula (4);

[0085] The upper quartile (Q3), lower quartile (Q1), median (M2), upper limit (U), and lower limit (L) are used as the reference values ​​for formula (5);

[0086] The baseline values ​​are calculated as follows: U = 21.93%, Q3 = 20.62%, M2 = 20.17%, Q1 = 19.75%, L = 19.25%. Based on these baseline values, the actual deviation Ei of the tobacco leaf output moisture content for the following actual production batches is calculated.

[0087] (III) Calculate: During the actual feeding process of this brand of tobacco leaves, compare the real-time output moisture content of the tobacco leaves with the baseline value in step (II) to obtain the linear deviation E of the feeding, the skewness β of the output moisture content of the tobacco leaves, and the actual deviation Ei.

[0088] (f) Feeding linear deviation

[0089] During the actual feeding process, the moisture content of a tobacco leaf was measured every 5 seconds. When 10 tobacco leaves' moisture content data were collected during the actual feeding process, steps (a) to (e) above were followed to calculate the real-time upper quartile (Q3i), lower quartile (Q1i), median (Mi), upper limit (Ui), and lower limit (Li) of that tobacco leaf during the feeding process. Then, the real-time data were compared with the corresponding benchmark values ​​to calculate the linear skewness (E) of the tobacco leaf's moisture content during the feeding process.

[0090] E=[(Ui-U)+(Q3i-Q3)+(Mi-M)+(Q1i-Q1)+(Li-L)]÷5---Formula (5)

[0091] (g) Skewness β of discharge moisture content

[0092]

[0093] Where: xi represents each data point of the output moisture content during the actual feeding process of the tobacco leaves mentioned above; is the average output moisture content during the above-mentioned tobacco leaf feeding process; S is the standard deviation of the output moisture content of tobacco leaves during the above-mentioned tobacco leaf feeding process; q is the number of tobacco leaf output moisture content samples collected during the actual tobacco leaf feeding process.

[0094] (h) Calculate the actual deviation (Ei) of the output moisture content of the tobacco leaves during the above-mentioned feeding process.

[0095] Ei=β×E---Formula(7)

[0096] The calculation results are as follows:

[0097]

[0098]

[0099] (iv) Predict the moisture content Q of the tobacco leaves during the future shredding process.

[0100] Q = Ei + M1 --- Formula (8)

[0101] Where: Ei is the actual deviation of the tobacco leaf output moisture content in step (h); M1 is the median of the shredded moisture content in step (i);

[0102]

[0103] (v) Adjusting the amount of tobacco added during the tobacco feeding process.

[0104] During the feeding process, when the predicted moisture content of the cut tobacco leaves Q is greater than A+0.2% or less than A-0.2%, where A is the standard moisture content of the cut tobacco leaves (A=20%), the operator can adjust the predicted moisture content Q by increasing or decreasing the amount of feed until the predicted moisture content Q is within the range of A±0.2%. In step (IV), Q is between 20.2% and 19.8%, and there is no need to adjust the amount of water added during the feeding process.

[0105] Repeat steps (iii) to (v) every 4 minutes to recalculate the real-time linear deviation E of the feeding, the deviation β of the tobacco leaf output moisture content, and the actual deviation Ei, so as to predict the real-time moisture content Q of the cut tobacco leaves and adjust the feeding amount in real time during the tobacco feeding process.

[0106] In the known shredding process in step (I) and the known feeding process in step (II), the moisture content is the moisture content during the stable phase of the shredding or feeding process. The method of this invention is applicable to the production of various grades of tobacco leaves.

[0107] Finally, it should be noted that the present invention is not limited to the above-described embodiments, and various modifications can be made within the scope of knowledge possessed by those skilled in the art.

Claims

1. A method for controlling the amount of water added during feeding by predicting the moisture content of the shredded food, characterized in that: After selecting shredded tobacco, at least two batches of tobacco shredded tobacco of the same brand with known CPK moisture content meeting the standard are selected. Simultaneously, the moisture content of the finished tobacco leaves during the feeding process is tracked. This method includes the following steps: (a) Calculate the median moisture content M1 of the tobacco shreds during the shredding process. The raw data of the moisture content of the tobacco shreds during the shredding process were all exported and concatenated to form an n-sequence. The median moisture content M1 of the tobacco shredding process during the shredding process was then calculated. In the above-mentioned concatenated sequence, when the number n of the shredded moisture content values ​​is odd; M1 is the nth value in the above sequence. Moisture content of the shredded vegetables arranged in sequence; In the above-mentioned sequence, when the number n of the shredded moisture content values ​​is even, M1 is the nth value in the above sequence. The moisture content of the shredded vegetables in the sequence number and the... The average moisture content of the shredded vegetables arranged in sequence; (ii) Calculate the upper quartile, lower quartile, median, upper limit, and lower limit of the moisture content of the tobacco leaves during the corresponding feeding process. All the original data of the moisture content of the tobacco leaves during the feeding process corresponding to the above tobacco shreds were exported and concatenated to form an m-sequence. The upper quartile Q3, lower quartile Q1, median M2, upper limit U and lower limit L of the sequence were calculated. (a) Upper quartile Q3 Find The integer part is denoted as k, and the fractional part is denoted as f, where 0 ≤ f < 1, and m is the number of original data points of tobacco leaf output moisture content in the above sequence during the feeding process. ---Official (1) Where: X(k+1) is the moisture content of the tobacco leaves at the (k+1)th permutation number in the above sequence, and X(k) is the moisture content of the tobacco leaves at the kth permutation number in the above sequence; (b) Lower quartile Q1 Find The integer part is denoted as k, and the fractional part is denoted as f, where 0 ≤ f < 1, and m is the number of original data points for the moisture content of the tobacco leaves in the above sequence during the feeding process. ---Official (2) Where: X(k+1) is the moisture content of the tobacco leaves at the (k+1)th permutation number in the above sequence, and X(k) is the moisture content of the tobacco leaves at the kth permutation number in the above sequence; (c) Median M2 Following step (1), replace n with m and calculate the median moisture content M2 of the tobacco leaves output during the feeding process of the above sequence; (d) Upper limit U ---Official (3) (e) Lower limit L --- Official (4); The upper quartile Q3, lower quartile Q1, median M2, upper limit U and lower limit L are used as the reference values ​​for formula (5); (III) Calculate: During the actual feeding process of this brand of tobacco leaves, compare the real-time output moisture content of the tobacco leaves with the baseline value in step (II) to obtain the feeding linear deviation E of the output moisture content of the tobacco leaves, the skewness β of the output moisture content of the tobacco leaves, and the actual deviation Ei. (f) Feeding linear deviation During the actual feeding process of this brand of tobacco leaves, once at least 10 data points on the moisture content of the finished tobacco leaves are collected, steps (a) to (e) above are followed to calculate the real-time upper quartile Q3i, lower quartile Q1i, median Mi, upper limit Ui, and lower limit Li of this brand of tobacco leaves during the feeding process. Then, the real-time data are compared with the corresponding benchmark values ​​to calculate the feeding linear deviation E of the moisture content of the finished tobacco leaves during the feeding process. ---Official (5) (g) Skewness β of discharge moisture content ---Official (6) For each data point of the output moisture content during the actual feeding process of the above-mentioned tobacco leaves; This represents the average moisture content of the output material during the aforementioned tobacco leaf feeding process. denoted as , where is the standard deviation of the moisture content of the tobacco leaves at the output during the aforementioned tobacco leaf feeding process; q represents the number of moisture content values ​​at the output of the tobacco leaves. (h) Calculate: the actual deviation Ei of the output moisture content of the tobacco leaves during the above-mentioned feeding process. ---Official (7) (iv) Predict the moisture content Q of the tobacco leaves during the future shredding process. ---Official (8) Where: Ei is the actual deviation of the tobacco leaf output moisture content in step (h); M1 is the median of the shredded moisture content in step (i); (v) Adjusting the amount of tobacco added during the tobacco feeding process. During the feeding process, when the predicted moisture content of the cut tobacco leaves Q is greater than A+0.2% or less than A-0.2%, where A is the calibrated moisture content of the cut tobacco leaves, the operator adjusts the predicted moisture content Q by increasing or decreasing the amount of feed until the predicted moisture content Q is within the range of A±0.2%. Repeat steps (iii) to (v) every 3-5 minutes to recalculate the real-time linear deviation E of the feeding, the deviation β of the tobacco leaf output moisture content, and the actual deviation Ei, so as to predict the real-time shredded moisture content Q and adjust the feeding amount in real time during the tobacco leaf feeding process.

2. The method for controlling the amount of water added during feeding by predicting the moisture content of the shredded material as described in claim 1, characterized in that: The moisture content CPK meeting the standard means that CPK > 1.

33. ----Official (9) Where: USL is the standard upper limit value of tobacco moisture; LSL is the standard lower limit value of tobacco moisture; MU is the standard center value of tobacco moisture. σ represents the average moisture content of the tobacco shreds; σ represents the standard deviation of the moisture content of the tobacco shreds. ----Official (10) Where: Xi is the moisture content of each shredded product, and n is the number of moisture contents of the shredded products during the shredding process.

3. The method for controlling the amount of water added during feeding by predicting the moisture content of the shredded material as described in claim 2, characterized in that: During the feeding process, The standard deviation of the moisture content of tobacco leaves. --Formula (11) in: Xi represents the average moisture content of the tobacco leaves during the feeding process; Xi is the moisture content of each tobacco leaf output, and q is the number of tobacco leaf output moisture contents.

4. The method for controlling the amount of water added during feeding by predicting the moisture content of the shredded material as described in claim 3, characterized in that: During the shredding process, the moisture content of each shredded tobacco is measured every 3-10 seconds.

5. The method for controlling the amount of water added during feeding by predicting the moisture content of the shredded material as described in claim 4, characterized in that: During the feeding process, the moisture content of a tobacco leaf is measured every 3-10 seconds.

6. The method for controlling the amount of water added during feeding by predicting the moisture content of the shredded material as described in claim 5, characterized in that: In the known shredding process in step (I) and the known feeding process in step (II), the moisture content is the moisture content during the stable phase of the shredding or feeding process.

7. The method for controlling the amount of water added during feeding by predicting the moisture content of the shredded material as described in claim 6, characterized in that: The method is applicable to the production of various grades of tobacco leaves.

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