CN114376259A - Automatic sorting method for raw material tobacco leaves - Google Patents
Automatic sorting method for raw material tobacco leaves Download PDFInfo
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- CN114376259A CN114376259A CN202210134871.7A CN202210134871A CN114376259A CN 114376259 A CN114376259 A CN 114376259A CN 202210134871 A CN202210134871 A CN 202210134871A CN 114376259 A CN114376259 A CN 114376259A
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- Prior art keywords
- tobacco
- tobacco leaf
- appearance
- raw material
- tobacco leaves
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Classifications
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- A—HUMAN NECESSITIES
- A24—TOBACCO; CIGARS; CIGARETTES; SIMULATED SMOKING DEVICES; SMOKERS' REQUISITES
- A24B—MANUFACTURE OR PREPARATION OF TOBACCO FOR SMOKING OR CHEWING; TOBACCO; SNUFF
- A24B3/00—Preparing tobacco in the factory
- A24B3/16—Classifying or aligning leaves
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
- B07C5/342—Sorting according to other particular properties according to optical properties, e.g. colour
- B07C5/3422—Sorting according to other particular properties according to optical properties, e.g. colour using video scanning devices, e.g. TV-cameras
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/36—Sorting apparatus characterised by the means used for distribution
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/36—Sorting apparatus characterised by the means used for distribution
- B07C5/363—Sorting apparatus characterised by the means used for distribution by means of air
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G15/00—Conveyors having endless load-conveying surfaces, i.e. belts and like continuous members, to which tractive effort is transmitted by means other than endless driving elements of similar configuration
- B65G15/30—Belts or like endless load-carriers
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
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- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Mechanical Engineering (AREA)
- Manufacture Of Tobacco Products (AREA)
Abstract
The invention relates to a raw material tobacco leaf automatic sorting method, which is characterized in that raw material tobacco leaves of a set grade from a set production area sequentially pass through a conveying belt of a tobacco leaf sorting system; the image photographing device is arranged above a conveying belt of the tobacco leaf sorting system and used for photographing the passing tobacco leaves and transmitting the obtained picture information to the control device; the control device compares the received picture information with a prestored tobacco leaf appearance classification standard picture, respectively transmits corresponding control information to a downstream sorting device, and transfers the tobacco leaves to corresponding classification conveying belts. According to the technical scheme, the correlation between the corresponding appearance and the sensory quality and the correlation between the corresponding appearance and the main chemical components are determined according to the appearance characteristic difference of the tobacco leaf raw materials, the appearance classification standard picture set is obtained, the raw material tobacco leaves meeting the appearance classification standard picture set are sorted according to the images detected by the photographing device, and the quality of the selected tobacco leaves is relatively stable.
Description
Technical Field
The invention belongs to the technical field of tobacco, and particularly relates to an automatic sorting method for raw material tobacco leaves.
Background
Because the tobacco producing areas are widely distributed, the ecological environment difference of each tobacco producing area is obvious, and according to the current tobacco grading standard, the tobacco with the same grade in different producing areas has obvious difference of the organoleptic style characteristics and the appearance and has obvious regional difference. Causes the unsuitable conditions of the aspects of tobacco production, purchase, use and the like, causes the fluctuation of the tobacco quality and further influences the use of the cigarette formula.
In order to solve the quality fluctuation of tobacco leaves, a series of technologies such as redrying, flavoring and the like are required to be carried out on purchased tobacco leaves to ensure the quality stability of cigarettes of the same brand as much as possible, and under the actual condition, when the cigarettes of the same brand adopt raw material tobacco leaves in different production areas, the quality still has great difference, which is also the problem to be solved at present.
Disclosure of Invention
The invention aims to provide an automatic sorting method for raw material tobacco leaves, which aims to solve the problem that the actual quality of the raw material tobacco leaves has better and larger difference according to the existing tobacco leaf grade standard.
In order to achieve the purpose, the technical scheme is realized by the following technical scheme:
an automatic sorting method for raw material tobacco leaves comprises the following steps:
s1, raw material tobacco leaves of set grades from a set production area sequentially pass through a conveying belt of a tobacco leaf sorting system;
s2, photographing the passing tobacco leaves by an image photographing device arranged above a conveying belt of the tobacco leaf sorting system, and transmitting the obtained picture information to a control device;
and S3, the control device compares the received picture information with the pre-stored tobacco leaf appearance classification standard picture, respectively transmits corresponding control information to a downstream sorting device, and transfers the tobacco leaves to corresponding classification conveyer belts.
Further, the tobacco leaf appearance classification standard picture is obtained through the following steps:
s11, determining the sensory quality evaluation value range of the raw material tobacco leaves corresponding to the cut tobacco of the set brand cigarette and the numerical value range of the main chemical components;
s12, selecting tobacco leaves in a specific tobacco leaf producing area, dividing the tobacco leaves into N parts according to set personalized appearance indexes, dividing the tobacco leaves in each part into M grades according to set grades to obtain L groups of tobacco leaf samples, wherein M, N and L are natural numbers, and numbering each group of tobacco leaf samples;
s13, carrying out electronic image acquisition on each group of tobacco leaf samples, carrying out quantitative evaluation on appearance indexes of each group of tobacco leaf samples, and matching the electronic images and the appearance index quantitative values with the numbers of each group of tobacco leaf samples;
s14, performing sensory quality evaluation on each group of tobacco leaf samples, and determining the sensory quality evaluation value of each group of tobacco leaf samples;
s15, comparing the sensory quality evaluation score obtained in the step S14 with the sensory quality evaluation score range obtained in the step S11 to obtain tobacco leaf samples with the P groups;
s16, performing main chemical component detection on the P groups of tobacco leaf samples in the step S15, and comparing the obtained data of the chemical components of each group of tobacco leaf samples with the value range of the main chemical components in the step S11 to obtain F groups of tobacco leaf samples;
s17, performing correlation analysis on the F groups of tobacco leaf samples in the step S16 and the corresponding appearance indexes to obtain a set number of highly observed appearance indexes, and forming a tobacco leaf appearance classification standard picture set by using appearance index quantification values corresponding to each group of tobacco leaf samples.
Further, after the tobacco leaves are graded according to the set grade, all tobacco leaf samples are numbered, and the number of each tobacco leaf sample comprises a tobacco leaf producing area, a tobacco leaf part, an individualized appearance index and the grade.
Further, the quantitative evaluation of the appearance indexes in step S3 includes color shade, color purity, cyan content, impurity content, maturity, leaf structure, gloss, softness, oil-wet feeling, and identity.
Further, the sensory quality evaluation includes aroma quality, aroma amount, offensive odor, irritation, dry feeling, sweetness, concentration and fineness.
Furthermore, the raw material tobacco leaves with the set grade are the tobacco leaves graded according to the current standard.
Furthermore, the sorting device is a blowing device or a pushing device.
The invention has the beneficial effects that:
according to the technical scheme, the correlation between the corresponding appearance and the sensory quality and the correlation between the corresponding appearance and the main chemical components are determined according to the appearance characteristic difference of the tobacco leaf raw materials, the appearance classification standard picture set is obtained, the raw material tobacco leaves meeting the appearance classification standard picture set are sorted according to the images detected by the photographing device, and the quality of the selected tobacco leaves is relatively stable.
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.
According to the technical scheme, firstly, a tobacco leaf appearance classification standard picture set is determined to serve as a standard for sorting the raw material tobacco leaves.
The technical scheme is explained by taking a golden leaf brand cigarette as an example, and the research on the tobacco leaf appearance classification standard picture set is carried out by selecting 5-8 core raw materials of the golden leaf brand.
Determining the sensory quality evaluation value range of the raw material tobacco leaves corresponding to the tobacco shreds of the gold leaf brand cigarettes and the numerical value range of the main chemical components. The two ranges are determined when the formula of the brand is designed, namely the two ranges exist, and after long-term production and optimization, the quality of the cigarettes can be ensured only within the ranges.
3-5 individualized appearance indexes of the tobacco shreds of the gold leaf brand cigarettes required by tobacco leaves in each specific production area are screened, the specific quantity is designed according to needs and can be more than 5, and the implementation of the technical scheme of the application is not influenced. The tobacco leaves in the specific production area are divided into N parts according to the set personalized appearance indexes, wherein the N parts are selected to be divided into 7 parts in the embodiment, and the labels are from 01 to 07. And dividing the tobacco leaves of each part into M grades according to a set grade, wherein the grade of the tobacco leaves of each part can be the same or different according to requirements, so as to obtain L groups of tobacco leaf samples, wherein N, M and L are natural numbers, and numbering each group of tobacco leaf samples.
In the application, when preparing tobacco leaf samples with different indexes and different grades, other indexes are kept basically consistent as much as possible, and the number of each tobacco leaf sample is about 100 tobacco leaves. The individual appearance indexes and grade division of the tobacco leaf samples are shown in table 1.
TABLE 1
And (3) marking each sample by year, first capital of county, position, index number and grade number, and ensuring that each sample corresponds to the serial number one by one, wherein the serial number of the kylin middle color group microstrip blue sample is 19QLA01001, the serial number of the Shaoswu upper maturity group high maturity sample is 19SWB06001, and so on.
And carrying out electronic image acquisition on each tobacco leaf sample, carrying out quantitative evaluation on appearance indexes of each tobacco leaf sample, wherein all equipment used in the electronic image acquisition is equipment for carrying out appearance detection on the tobacco leaves at present, no specific equipment is used, and then the electronic image and the appearance index quantitative value are matched with the serial number of each group of tobacco leaf samples.
Comparing the sensory quality evaluation value of each tobacco leaf sample with the sensory quality evaluation value range of the tobacco leaf corresponding to the tobacco shred of the golden leaf cigarette, wherein the tobacco leaf corresponding to the tobacco shred of the golden leaf cigarette is the raw material tobacco leaf corresponding to the tobacco shred for producing the golden leaf cigarette at present, and each score fluctuates when the sensory quality evaluation is carried out, so that the quality stability of the golden leaf cigarette can be ensured in the sensory quality evaluation range by determining the sensory quality evaluation range of the raw material tobacco leaf with the normal quality of the golden leaf cigarette. The present application is an assessment of sensory quality by product formulators.
In the present application, the evaluation indexes of sensory quality evaluation include aroma characteristics (aroma quality, aroma amount, offensive odor), taste characteristics (irritation, dryness, and aftersweetness), smoke characteristics (concentration, fineness), strength, and quality orientation.
Specifically, the middle tobacco leaf sensory quality evaluation total score is (aroma quality × 2.5+ aroma amount × 2.5+ miscellaneous gas × 1.5+ irritation × 1+ dry sensation × 0.5+ sweetness × 1.5+ fineness × 0.5) × 1.11.
The upper tobacco leaf sensory quality evaluation total score is (aroma quality × 2.5+ aroma amount × 2.5+ miscellaneous gas × 1.5+ irritation × 0.5+ dry sensation × 0.5+ aftersweetness × 1.5+ concentration × 0.5+ fineness × 0.5) × 1.11.
And obtaining P tobacco leaf samples which accord with the range of the sensory quality evaluation value after comparison, wherein P is a natural number, and the number of P is less than or equal to the total number of the tobacco leaf samples.
And then, carrying out chemical component analysis on each tobacco leaf sample in the P tobacco leaf samples, and determining the contents of starch, nicotine, total nitrogen, potassium, chlorine, total sugar and reducing sugar in the tobacco leaves according to the specified methods of YC/T216-2013, YC/T468-2013, YC/T161-2002, YC/T217-2007, YC/T162-2002 and YC/T159-2002. Protein content was calculated by multiplying (total nitrogen-nicotine nitrogen) by the protein coefficient.
And obtaining chemical component data of each tobacco leaf sample, and comparing the chemical component data with the chemical component data range of the tobacco leaves corresponding to the tobacco shreds of the cigarettes of the set brand to obtain F tobacco leaf samples which accord with the chemical component data range and are the raw material tobacco leaves which accord with the cigarettes of the set brand in the specific tobacco leaf production area.
And analyzing the contribution degree of the appearance quality of the tobacco leaves to the sensory quality and the main chemical components by using stepwise regression models, partial least squares regression models and other regression models for the correlation between the sensory principal value and the main chemical components of the F tobacco leaf samples, and screening and determining the appearance sorting index of the tobacco leaves in each region by combining correlation analysis and regression analysis.
And establishing raw material tobacco leaf appearance electronic atlases of the golden leaf brand cigarettes in different areas according to the acquired electronic image set.
And (4) storing the manufactured raw material tobacco leaf appearance electronic atlas in a control device. The utility model provides an among the system that carries out automatic sorting, including the conveyer belt, drive through the motor and rotate, a raw materials tobacco leaf for carrying by the sorting, top at the conveyer belt is provided with the camera, a raw materials tobacco leaf for shoot through, mainly used shoots the appearance characteristic of raw materials tobacco leaf, of course, if the categorised index that can not be clear and definite including making a video recording of tobacco leaf outward appearance, then can set up the device that prior art is used for the outward appearance to detect simultaneously on the conveyer belt, and camera and outward appearance detection's device all with controlling means signal connection, in this application, controlling means is the control chip of current conventional use, industrial computer and so on.
At the downstream direction of conveyer belt, be provided with at least one sorting unit to sorting unit and controlling means's output signal of telecommunication are connected, and in this application, sorting unit can be gas blowing device or pusher, and wherein gas blowing device passes through solenoid valve control, and pusher drives push pedal class device for the cylinder, and the raw materials tobacco leaf on the conveyer belt pushes away and closes corresponding categorised conveyer belt, and in this application, categorised conveyer belt is at least one, and with the conveyer belt parallel or one end is relative with the conveyer belt. When the number of the sorting conveyor belts is one, only the raw material tobacco leaves which are in accordance with the tobacco leaf appearance sorting standard picture set on the conveyor belts are transferred to the sorting conveyor belts, and the rest raw material tobacco leaves continuously move on the conveyor belts.
When the number of the classification conveyor belts is two or more, the tobacco leaf appearance classification standard picture set can be divided into two or more parts from high to low according to the similarity of the tobacco leaf appearance classification standard picture set and the raw material tobacco leaves of the cigarettes of the set brands, and the parts correspond to the data of the classification conveyor belts. So as to realize more accurate sorting of the raw material tobacco leaves.
Raw material tobacco leaves of set grade from a set production area sequentially pass through a conveying belt of a tobacco leaf sorting system.
And the image photographing device arranged above the conveying belt of the tobacco leaf sorting system photographs the passing tobacco leaves and transmits the obtained picture information to the control device.
The control device compares the received picture information with a prestored tobacco leaf appearance classification standard picture, respectively transmits corresponding control information to a downstream sorting device, and transfers the tobacco leaves to corresponding classification conveying belts.
Finally, it should be noted that: the above examples are intended only to illustrate the technical solution of the invention, and not to limit it; although the invention of the present application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: it is to be understood that modifications may be made to the above-described embodiments, or equivalents may be substituted for some of the features of the embodiments, without departing from the spirit or scope of the present invention.
Claims (7)
1. The automatic sorting method of the raw material tobacco leaves is characterized by comprising the following steps:
s1, raw material tobacco leaves of set grades from a set production area sequentially pass through a conveying belt of a tobacco leaf sorting system;
s2, photographing the passing tobacco leaves by an image photographing device arranged above a conveying belt of the tobacco leaf sorting system, and transmitting the obtained picture information to a control device;
and S3, the control device compares the received picture information with the pre-stored tobacco leaf appearance classification standard picture, respectively transmits corresponding control information to a downstream sorting device, and transfers the tobacco leaves to corresponding classification conveyer belts.
2. The method for automatically sorting raw material tobacco leaves according to claim 1, wherein the tobacco leaf appearance classification standard picture is obtained by the following steps:
s11, determining the sensory quality evaluation value range of the raw material tobacco leaves corresponding to the cut tobacco of the set brand cigarette and the numerical value range of the main chemical components;
s12, selecting tobacco leaves in a specific tobacco leaf producing area, dividing the tobacco leaves into N parts according to set personalized appearance indexes, dividing the tobacco leaves in each part into M grades according to set grades to obtain L groups of tobacco leaf samples, wherein M, N and L are natural numbers, and numbering each group of tobacco leaf samples;
s13, carrying out electronic image acquisition on each group of tobacco leaf samples, carrying out quantitative evaluation on appearance indexes of each group of tobacco leaf samples, and matching the electronic images and the appearance index quantitative values with the numbers of each group of tobacco leaf samples;
s14, performing sensory quality evaluation on each group of tobacco leaf samples, and determining the sensory quality evaluation value of each group of tobacco leaf samples;
s15, comparing the sensory quality evaluation score obtained in the step S14 with the sensory quality evaluation score range obtained in the step S11 to obtain tobacco leaf samples with the P groups;
s16, performing main chemical component detection on the P groups of tobacco leaf samples in the step S15, and comparing the obtained data of the chemical components of each group of tobacco leaf samples with the value range of the main chemical components in the step S11 to obtain F groups of tobacco leaf samples;
s17, performing correlation analysis on the F groups of tobacco leaf samples in the step S16 and the corresponding appearance indexes to obtain a set number of highly observed appearance indexes, and forming a tobacco leaf appearance classification standard picture set by using appearance index quantification values corresponding to each group of tobacco leaf samples.
3. The method for automatically sorting the raw material tobacco leaves according to claim 2, wherein all tobacco leaf samples are numbered after the tobacco leaves are graded according to a set grade, and the number of each tobacco leaf sample comprises a tobacco leaf producing area, a tobacco leaf part, an individualized appearance index and a grade.
4. The automatic raw material tobacco sorting method according to claim 2, wherein the quantitative evaluation of appearance indexes comprises color shade, color purity, cyan content, impurity content, maturity, leaf structure, glossiness, softness, oil-wet feeling and identity.
5. The method for automatically sorting the raw material tobacco leaves according to claim 2, wherein the sensory quality evaluation includes aroma quality, aroma amount, offensive odor, irritation, dry feeling, sweetness, concentration and fineness.
6. The method for automatically sorting raw material tobacco leaves according to claim 1, wherein the raw material tobacco leaves of a set grade are tobacco leaves classified according to an existing standard.
7. The method for automatically sorting the raw material tobacco leaves according to claim 1, wherein the sorting device is an air blowing device or a pushing device.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202210134871.7A CN114376259B (en) | 2022-02-14 | 2022-02-14 | Automatic sorting method for raw tobacco leaves |
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| CN202210134871.7A CN114376259B (en) | 2022-02-14 | 2022-02-14 | Automatic sorting method for raw tobacco leaves |
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| CN114376259A true CN114376259A (en) | 2022-04-22 |
| CN114376259B CN114376259B (en) | 2023-05-16 |
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU5407686A (en) * | 1985-02-25 | 1986-08-28 | Philip Morris Products Inc. | Method and apparatus for detecting and removing foreign material from a stream of particulate matter |
| CN107589228A (en) * | 2017-11-08 | 2018-01-16 | 江苏中烟工业有限责任公司 | The method that sorting tobacco leaf industrial usability is predicted by tobacco leaf characteristic look index |
| CN109877050A (en) * | 2019-04-24 | 2019-06-14 | 江苏启赋信息科技有限公司 | A kind of tobacco leaf automatic letter sorting machine |
| CN110170461A (en) * | 2019-06-05 | 2019-08-27 | 常熟市百联自动机械有限公司 | Tobacco leaf Automated Sorting System |
| CN111838742A (en) * | 2020-08-13 | 2020-10-30 | 河南中烟工业有限责任公司 | Formula threshing method based on classified use of tobacco flakes of different specifications |
| CN111990677A (en) * | 2020-08-26 | 2020-11-27 | 中国烟草总公司郑州烟草研究院 | Threshing and redrying process based on automatic raw tobacco selection |
-
2022
- 2022-02-14 CN CN202210134871.7A patent/CN114376259B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU5407686A (en) * | 1985-02-25 | 1986-08-28 | Philip Morris Products Inc. | Method and apparatus for detecting and removing foreign material from a stream of particulate matter |
| CN107589228A (en) * | 2017-11-08 | 2018-01-16 | 江苏中烟工业有限责任公司 | The method that sorting tobacco leaf industrial usability is predicted by tobacco leaf characteristic look index |
| CN109877050A (en) * | 2019-04-24 | 2019-06-14 | 江苏启赋信息科技有限公司 | A kind of tobacco leaf automatic letter sorting machine |
| CN110170461A (en) * | 2019-06-05 | 2019-08-27 | 常熟市百联自动机械有限公司 | Tobacco leaf Automated Sorting System |
| CN111838742A (en) * | 2020-08-13 | 2020-10-30 | 河南中烟工业有限责任公司 | Formula threshing method based on classified use of tobacco flakes of different specifications |
| CN111990677A (en) * | 2020-08-26 | 2020-11-27 | 中国烟草总公司郑州烟草研究院 | Threshing and redrying process based on automatic raw tobacco selection |
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