CN110973686A - Method for establishing accurate moisture control model in silk making process - Google Patents
Method for establishing accurate moisture control model in silk making process Download PDFInfo
- Publication number
- CN110973686A CN110973686A CN201911283908.7A CN201911283908A CN110973686A CN 110973686 A CN110973686 A CN 110973686A CN 201911283908 A CN201911283908 A CN 201911283908A CN 110973686 A CN110973686 A CN 110973686A
- Authority
- CN
- China
- Prior art keywords
- parameter data
- optimal
- data
- tobacco
- time length
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- A—HUMAN NECESSITIES
- A24—TOBACCO; CIGARS; CIGARETTES; SIMULATED SMOKING DEVICES; SMOKERS' REQUISITES
- A24B—MANUFACTURE OR PREPARATION OF TOBACCO FOR SMOKING OR CHEWING; TOBACCO; SNUFF
- A24B9/00—Control of the moisture content of tobacco products, e.g. cigars, cigarettes, pipe tobacco
Landscapes
- Manufacture Of Tobacco Products (AREA)
Abstract
The invention relates to a method for establishing an accurate control model of water content in a tobacco processing process, which comprises the steps of comprehensively analyzing historical data under the condition of a whole batch of tobacco leaves with consistent water content, obtaining environmental parameter data experienced in the optimal tobacco shred control process by combining sensory evaluation of experts, then obtaining corresponding historical parameter data by utilizing the same environmental parameter data, obtaining parameter data for optimal tobacco shred control under the condition of the tobacco leaves with the same water content by again conducting sensory evaluation of the experts, and establishing a control model according to the parameter data so as to realize the relative consistency of the tobacco shred quality.
Description
Technical Field
The invention belongs to the technical field of accurate control of tobacco manufacturing, and particularly relates to a method for establishing an accurate control model of moisture in a tobacco processing process.
Background
The main components of cigarette processing are the main process quality and product quality control. The target for controlling the tobacco shred making process is the tobacco shred making moisture, and if the significant fluctuation of the tobacco shred making moisture in different batches is caused by the irregularity of units, personnel, external environment and the like, the stability and consistency of the finished tobacco shred moisture, namely the moisture content of the finished cigarette, can be directly influenced.
During the production process of the cut tobacco, moisture has important influence on the inherent quality of cigarettes. Researches find that when the moisture of the smoke is proper, the smoke is soft and fine, the irritation is small, and the sensory comfort is good; when the moisture content of the smoke is low, the smoke is dry, the irritation is increased, and the sensory comfort is reduced.
In the silk production process, the control of moisture is particularly important, and when the external environment temperature and humidity have seasonal differences, the difficulty of moisture control is increased. The influence of the environmental temperature and humidity on the quality of the tobacco shred making process can be fully known by adopting a scientific and effective method, so that the control method and mode are changed, and the stability of the cigarette quality is effectively ensured.
The characteristics of complicated and changeable environmental conditions, diversified production process modes and large hysteresis in the wire making working process cannot well meet the increasingly strict requirements on control precision and stability by adopting the traditional PID control mode.
Disclosure of Invention
The invention aims to provide a method for establishing a moisture accurate control model in a silk making process, which aims to solve the problem that the PID control mode in the prior art cannot well meet increasingly strict control accuracy and stability requirements.
The invention is realized by the following technical scheme:
a method for establishing a moisture accurate control model in a silk making process comprises the following steps:
1) acquiring control parameter data and corresponding environmental parameter data of a whole batch of tobacco leaf shredding process;
2) selecting N relatively stable test data with a first set time length from the control parameter data, wherein N is more than or equal to 2;
3) acquiring tobacco shreds corresponding to the test data;
4) the tobacco shreds are subjected to first sensory evaluation to obtain optimal parameter data corresponding to the optimal tobacco shreds;
5) obtaining corresponding test environment parameter data through the optimal parameter data;
6) selecting M detection control parameter data of a second set time length corresponding to the test environment parameter data, wherein M is more than or equal to 2;
7) acquiring tobacco shreds corresponding to the detection control parameter data;
8) performing sensory evaluation on the tobacco shreds for the second time to obtain optimal detection control parameter data, and calculating and judging the optimal detection control parameter data and the optimal parameter data in the step 4):
if the absolute value of the difference value between the optimal parameter data and the optimal detection control parameter data is within a set threshold range, determining the optimal parameter data as the optimal moisture control model of the corresponding test environment data;
if the absolute value of the difference value between the optimal parameter data and the optimal detection control parameter data is not in the set threshold range, entering step 9);
9) and repeating the steps 2) to 8) until the optimal moisture control model is determined.
The first set time length is the same as the second set time length.
And the indexes of the first sensory evaluation and the second sensory evaluation at least comprise smoke, irritation and sensory comfort, and the indexes are respectively scored and then are synthesized to obtain comprehensive scores.
The environmental parameter data includes a temperature parameter and a humidity parameter.
The moisture content of the whole batch of tobacco leaves is within a set range.
And when any parameter in the test data with the first set time length or the detection control parameter data with the second set time length comprises a plurality of point values, selecting the average value as the corresponding parameter test data or the detection control parameter data.
When the control parameter data is two or more parameters,
s1, calibrating the influence degree of each parameter on the tobacco shreds at the same time or within the same time length range, and determining a correlation coefficient;
s2, analyzing the fluctuation range of each parameter data in the test data with the first set time length;
s3, analyzing the fluctuation range of each parameter data in the detection control parameter data of the second set time length;
and S4, integrating the parameter data fluctuation value points of the step S2 and the step S3, and comparing the parameter data fluctuation value points with corresponding parameter values in the optimal parameter data, wherein two fluctuation value points adjacent to the parameter values are the optimal control ranges of the corresponding parameters.
The invention has the advantages that;
according to the technical scheme, under the condition of a whole batch of tobacco leaves (equivalent to consistent moisture content), the historical data is comprehensively analyzed, the environmental parameter data experienced in the optimal tobacco shred control process is obtained by combining sensory evaluation of experts, then the corresponding historical parameter data is obtained by utilizing the same environmental parameter data, the parameter data for controlling the optimal tobacco shreds is determined according to a certain environmental parameter under the condition of the tobacco leaves with the same moisture content by means of sensory evaluation of the experts again, and a control model is established according to the parameter data, so that the tobacco shred quality is relatively consistent.
Detailed Description
The technical solutions of the present invention are described in detail below by examples, and the following examples are only exemplary and can be used only for explaining and explaining the technical solutions of the present invention, but not construed as limiting the technical solutions of the present invention.
The technical scheme is that a method for establishing an accurate quality control model by using historical data is adopted, the accurate intrinsic quantity control model is set under the condition that the moisture content of tobacco leaves in the previous tobacco leaf shredding process is in a set range, namely the moisture content is considered to be the same, and in the technical scheme, other parameters such as aroma and components of all parts in the tobacco leaves are not considered in the range considered by the technical scheme.
The technical scheme is characterized in that the moisture content of the cut tobacco is developed on the premise of influencing whether smoke is soft and fine in sense, stimulation is strong, and sense is comfortable, so that the technical scheme is important to accurately control moisture in the process of making the cut tobacco.
According to the technical scheme, control parameter data and corresponding environment parameter data of a plurality of full batches of tobacco leaves in the tobacco shred making process are selected, the tobacco shred making process can involve various parameters, the change of each parameter can affect the quality of tobacco shreds, and the periods of the acquired parameter data can be different according to the design of the process, so that the control parameters in a first set time length section are selected as basic data to ensure the representativeness of the control parameter data, all control parameter data of the tobacco shred making control are required to be included in the first set time length, the data in the time section are required to be processed in the early stage, and unusable data, error data, redundant data and the like are eliminated.
In the time length, if a certain parameter comprises a plurality of sampling periods and a plurality of data values, the processing mode of the technical scheme is that the data values are averaged to obtain an average value, then the maximum data value and the minimum data value are selected to be added and averaged to obtain a limit average value, the average value and the limit average value are subjected to difference calculation to obtain a difference value, the difference value is compared with a difference value range determined in advance, if the difference value range is within the range, the average value is used as the data value of the parameter, if the difference value range is not within the range, the maximum data value and the minimum data value are discarded, and then averaging is carried out to obtain the data value of which the corrected average value is the parameter.
In all the control parameter data of the whole batch of tobacco leaves, the unstable data part is excluded, a first set time length is selected, for example, 5 minutes, 10 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, 8 hours, 12 hours, 24 hours and the like, and the first set time length is selected according to requirements.
In the present embodiment, a total of 8 parameter data of the first set time length are selected as the test data, in other embodiments of the present application, more than 8 parameter data may be selected, and as for the specific number, it is not recommended to be less than 8 parameter data, otherwise, the representativeness is insufficient.
Carrying out sensory evaluation on the tobacco shreds in the 8 time periods by 8 experts, wherein in the technical scheme, three indexes of the evaluation are smoke, irritation and comfort respectively, and the evaluation indexes are respectively divided into three grades, and the scores are divided into three tenths, all the grades are summarized to obtain the tobacco shreds with the highest scores, and if the tobacco shreds with the highest scores are more than one, environment parameter data corresponding to a plurality of tobacco shreds are selected; and if the control parameter data corresponding to each tobacco shred is different, averaging the parameter values, and listing the obtained average value as the parameter value corresponding to the optimal parameter data.
The method comprises the steps of taking corresponding environment parameter data as testing environment parameter data, and selecting M detection control parameter data with second set time length from parameter data of the whole batch of tobacco leaves, wherein M is larger than or equal to 2.
And the test environment parameter data is different from the test data, and the cut tobacco at the corresponding time is extracted.
The tobacco shreds are subjected to second sensory evaluation, the experts in the second sensory evaluation may be the same as or different from the experts in the first sensory evaluation, and in the embodiment, the selected experts are the same.
The method of the second sensory evaluation is completely the same as the method of the first sensory evaluation, and the optimal cut tobacco and the corresponding optimal detection control parameter data are obtained through scoring.
If the absolute value of the difference value between the optimal parameter data and the optimal detection control parameter data is within a set threshold range, determining the optimal parameter data as the optimal moisture control model of the corresponding test environment data;
and if the absolute value of the difference value between the optimal parameter data and the optimal detection control parameter data is not in the set threshold range, reselecting until the optimal water control model is determined.
When the control parameter data is two or more parameters,
and S1, calibrating the influence degree of each parameter on the tobacco shreds at the same time or within the same time length range, and determining the correlation coefficient.
S2, analyzing the fluctuation range of each parameter data in the test data with the first set time length;
s3, analyzing the fluctuation range of each parameter data in the detection control parameter data of the second set time length;
and S4, integrating the parameter data fluctuation value points of the step S2 and the step S3, and comparing the parameter data fluctuation value points with corresponding parameter values in the optimal parameter data, wherein two fluctuation value points adjacent to the parameter values are the optimal control ranges of the corresponding parameters.
The method specifically comprises the following steps: for example, humidity parameters, if the range in the test data is 63-68; and detecting that the humidity range in the time period in the control parameter data is 65-70, forming the ranges of 63, 65, 68 and 70 of humidity in sequence, and if the humidity value in the time period corresponding to the optimal parameter data is 66, setting the humidity 65-68 as the optimal humidity control range.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. A method for establishing a moisture accurate control model in a silk making process is characterized by comprising the following steps:
1) acquiring control parameter data and corresponding environmental parameter data of a whole batch of tobacco leaf shredding process;
2) selecting N relatively stable test data with a first set time length from the control parameter data, wherein N is more than or equal to 2;
3) acquiring tobacco shreds corresponding to the test data;
4) the tobacco shreds are subjected to first sensory evaluation to obtain optimal parameter data corresponding to the optimal tobacco shreds;
5) obtaining corresponding test environment parameter data through the optimal parameter data;
6) selecting M detection control parameter data of a second set time length corresponding to the test environment parameter data, wherein M is more than or equal to 2;
7) acquiring tobacco shreds corresponding to the detection control parameter data;
8) performing sensory evaluation on the tobacco shreds for the second time to obtain optimal detection control parameter data, and calculating and judging the optimal detection control parameter data and the optimal parameter data in the step 4):
if the absolute value of the difference value between the optimal parameter data and the optimal detection control parameter data is within a set threshold range, determining the optimal parameter data as the optimal moisture control model of the corresponding test environment data;
if the absolute value of the difference value between the optimal parameter data and the optimal detection control parameter data is not in the set threshold range, entering step 9);
9) and repeating the steps 2) to 8) until the optimal moisture control model is determined.
2. The method for establishing the moisture precision control model in the silk making process according to claim 1, wherein the first set time length is the same as the second set time length.
3. The method for establishing the accurate control model of the moisture in the silk making process according to claim 1, wherein the indexes of the first sensory evaluation and the second sensory evaluation at least comprise smoke, irritation and sensory comfort, and the indexes are respectively scored and then are combined to obtain a combined score.
4. The method for establishing the accurate control model of the moisture in the silk making process according to claim 1, wherein the environmental parameter data comprises a temperature parameter and a humidity parameter.
5. The method for establishing the tobacco shred processing process water accurate control model according to claim 1, wherein the water content of the whole batch of tobacco leaves is within a set range.
6. The method for establishing the moisture accurate control model in the silk making process according to claim 1, wherein when any one of the test data of the first set time length or the detection control parameter data of the second set time length comprises a plurality of point values, the average value of the parameters is selected as the corresponding parameter test data or detection control parameter data.
7. The method for establishing the accurate control model of moisture in the silk making process according to claim 1, wherein when the control parameter data is two or more parameters,
s1, calibrating the influence degree of each parameter on the tobacco shreds at the same time or within the same time length range, and determining a correlation coefficient;
s2, analyzing the fluctuation range of each parameter data in the test data with the first set time length;
s3, analyzing the fluctuation range of each parameter data in the detection control parameter data of the second set time length;
and S4, integrating the parameter data fluctuation value points of the step S2 and the step S3, and comparing the parameter data fluctuation value points with corresponding parameter values in the optimal parameter data, wherein two fluctuation value points adjacent to the parameter values are the optimal control ranges of the corresponding parameters.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911283908.7A CN110973686B (en) | 2019-12-13 | 2019-12-13 | Method for establishing accurate moisture control model in silk making process |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911283908.7A CN110973686B (en) | 2019-12-13 | 2019-12-13 | Method for establishing accurate moisture control model in silk making process |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110973686A true CN110973686A (en) | 2020-04-10 |
| CN110973686B CN110973686B (en) | 2022-02-08 |
Family
ID=70093492
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911283908.7A Active CN110973686B (en) | 2019-12-13 | 2019-12-13 | Method for establishing accurate moisture control model in silk making process |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110973686B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112931919A (en) * | 2021-02-02 | 2021-06-11 | 龙岩烟草工业有限责任公司 | Method and device for controlling moisture content of cut tobacco |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106418633A (en) * | 2016-11-30 | 2017-02-22 | 福建中烟工业有限责任公司 | Method and device for optimizing tobacco shred process parameters of cigarette |
| CN107144672A (en) * | 2017-06-29 | 2017-09-08 | 浙江中烟工业有限责任公司 | A kind of analysis method for optimizing cigarette sensory evaluation |
| CN108142976A (en) * | 2017-11-29 | 2018-06-12 | 昆明理工大学 | A kind of cut tobacco Drying Technology Parameter optimization method |
| CN109645540A (en) * | 2018-11-19 | 2019-04-19 | 武汉华喻燃能工程技术有限公司 | A kind of barn tele-control system based on Internet of Things |
| CN110109344A (en) * | 2019-05-20 | 2019-08-09 | 长沙学院 | A kind of drum-type cut-tobacco drier baking silk pilot process control method |
| US20190350251A1 (en) * | 2017-01-30 | 2019-11-21 | Japan Tobacco Inc. | Method for manufacturing tobacco raw material, and tobacco raw material |
-
2019
- 2019-12-13 CN CN201911283908.7A patent/CN110973686B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106418633A (en) * | 2016-11-30 | 2017-02-22 | 福建中烟工业有限责任公司 | Method and device for optimizing tobacco shred process parameters of cigarette |
| US20190350251A1 (en) * | 2017-01-30 | 2019-11-21 | Japan Tobacco Inc. | Method for manufacturing tobacco raw material, and tobacco raw material |
| CN107144672A (en) * | 2017-06-29 | 2017-09-08 | 浙江中烟工业有限责任公司 | A kind of analysis method for optimizing cigarette sensory evaluation |
| CN108142976A (en) * | 2017-11-29 | 2018-06-12 | 昆明理工大学 | A kind of cut tobacco Drying Technology Parameter optimization method |
| CN109645540A (en) * | 2018-11-19 | 2019-04-19 | 武汉华喻燃能工程技术有限公司 | A kind of barn tele-control system based on Internet of Things |
| CN110109344A (en) * | 2019-05-20 | 2019-08-09 | 长沙学院 | A kind of drum-type cut-tobacco drier baking silk pilot process control method |
Non-Patent Citations (1)
| Title |
|---|
| 邢蕾: "烟草制丝过程中含水率在线监测及控制改进", 《中国优秀硕士学位论文全文数据库工程科技Ⅰ辑》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112931919A (en) * | 2021-02-02 | 2021-06-11 | 龙岩烟草工业有限责任公司 | Method and device for controlling moisture content of cut tobacco |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110973686B (en) | 2022-02-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110973687B (en) | Accurate control method for moisture in silk making process | |
| CN108181263B (en) | Tobacco leaf position feature extraction and discrimination method based on near infrared spectrum | |
| CN110196265B (en) | Method for evaluating distribution stability of cut tobacco in cigarette branches in batch based on distribution probability | |
| CN110132880B (en) | Tobacco leaf overall sensory quality evaluation method based on near infrared spectrum | |
| CN104931430A (en) | Quality evaluation model for natural ageing of redried strips and building method thereof | |
| CN110973686B (en) | Method for establishing accurate moisture control model in silk making process | |
| CN105891147A (en) | Near infrared spectrum information extraction method based on canonical correlation coefficients | |
| CN109994162B (en) | Quantitative evaluation method for suitability of chemical components of flue-cured tobacco leaves guided by sensory quality | |
| CN103892435B (en) | Method for preparing tobacco powder raw materials and stabilizing quality of reconstituted tobacco | |
| CN107807206B (en) | Method for judging suitable alcoholization environment and suitable alcoholization time of tobacco lamina based on industrial demand | |
| CN114403487B (en) | Water adding control method for loosening and dampening | |
| CN111642782A (en) | Tobacco leaf raw material efficacy positioning method based on cigarette formula requirements | |
| CN112903679A (en) | Method for detecting blending proportion and blending uniformity of cut stems of cigarettes based on RGB image processing | |
| CN113627709A (en) | System and method for evaluating gorgeous quality based on infrared spectrum detection | |
| CN112834441A (en) | Method for detecting blending proportion and blending uniformity of expanded cut tobacco of cigarette | |
| CN107941997A (en) | Draw the method that flue-cured tobacco cultivars planting area is selected and verified outside a kind of | |
| CN110675919A (en) | Method and system for predicting moisture at inlet of cut tobacco drying process based on K-nearest neighbor method | |
| CN115017700A (en) | Cigarette shred making process variable selection and weighting method based on SCAD algorithm | |
| CN113455696A (en) | Method for judging alcoholization process through tobacco carotenoid degradation rate | |
| CN107704690B (en) | The method that the affecting parameters that a kind of pair of tea green-keeping is spread optimize | |
| CN108416489B (en) | Processing method and processing system for sensory evaluation data of tobacco products | |
| CN109283902B (en) | Method for determining temperature of cylinder wall on line based on content of L-proline in cut tobacco | |
| CN115119952B (en) | Method for predicting width of filamentous cut stems after tobacco stems are pressed | |
| Mukhopadhyay | Statistical process control procedure for controlling moisture content in tobacco | |
| JP2021153503A (en) | Black tea production method and fermentation optimal period determination device in the method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |