CN103234936A - Method for accurately representing material processing strength of cigarette cut tobacco drying procedure - Google Patents
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- 238000012545 processing Methods 0.000 title claims abstract description 153
- 241000208125 Nicotiana Species 0.000 title claims abstract description 31
- 235000002637 Nicotiana tabacum Nutrition 0.000 title claims abstract description 31
- 235000019504 cigarettes Nutrition 0.000 title claims abstract description 25
- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000001035 drying Methods 0.000 title claims abstract description 22
- 239000000463 material Substances 0.000 title claims abstract description 9
- 238000001228 spectrum Methods 0.000 claims abstract description 10
- 238000012937 correction Methods 0.000 claims abstract description 5
- 238000001914 filtration Methods 0.000 claims abstract description 5
- 238000012360 testing method Methods 0.000 claims description 64
- 238000002329 infrared spectrum Methods 0.000 claims description 10
- 238000004611 spectroscopical analysis Methods 0.000 claims description 8
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 7
- 230000003595 spectral effect Effects 0.000 claims description 4
- 230000004069 differentiation Effects 0.000 claims description 2
- 239000000843 powder Substances 0.000 claims description 2
- 238000002360 preparation method Methods 0.000 claims description 2
- 238000005070 sampling Methods 0.000 claims description 2
- 238000000513 principal component analysis Methods 0.000 abstract description 5
- 230000000694 effects Effects 0.000 abstract description 4
- 238000004364 calculation method Methods 0.000 abstract description 2
- 238000009826 distribution Methods 0.000 description 13
- 238000005516 engineering process Methods 0.000 description 6
- 239000003205 fragrance Substances 0.000 description 4
- 238000010009 beating Methods 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 235000019633 pungent taste Nutrition 0.000 description 3
- 239000002994 raw material Substances 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 230000000391 smoking effect Effects 0.000 description 3
- 238000010438 heat treatment Methods 0.000 description 2
- 239000002304 perfume Substances 0.000 description 2
- 230000035807 sensation Effects 0.000 description 2
- 235000019615 sensations Nutrition 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000003754 machining Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000004886 process control Methods 0.000 description 1
- 238000004451 qualitative analysis Methods 0.000 description 1
- 210000000697 sensory organ Anatomy 0.000 description 1
- 235000019640 taste Nutrition 0.000 description 1
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Abstract
The invention discloses a method for accurately representing the material processing strength of a cigarette cut tobacco drying procedure. Respectively collecting the tobacco shreds before and after drying, carrying out spectrum scanning after balancing, carrying out principal component analysis on the spectrum data after multivariate scattering correction and second-order partial derivative plus Norris derivative filtering, respectively establishing class models of the undried tobacco shreds and the tobacco shreds with different drying processing gradients, and finally obtaining the inter-class average value of the Mahalanobis distance from each drying processing gradient tobacco shred to the undried tobacco shred class model through calculation so as to judge the processing strength. The qualitative and quantitative expression of the drying strength of the cut tobacco leaves is realized, the adjustment and control of the parameters of the cut tobacco drying procedure of the tobacco making line can be objectively guided, the degree that the existing processing strength judgment is easily affected by subjectivity is changed, and the objective judgment on the internal quality change of the cigarette can be better made. The operation method is simple and easy to implement, and the technical effect is obvious.
Description
Technical field
The invention belongs to the production of cigarettes technical field, be specifically related to a kind ofly in cigarette leaves and tobacco drying process processing procedure, accurately characterize the method that material processing intensity interior quality changes.
Background technology
2003 editions " cigarette process standard " proposed by " result controls to process control " new control theory the production of cigarettes process, and also control has proposed new requirement to cigarette throwing line critical process parameters Optimization in the development of Chinese style cigarette characteristic technology.Domestic each tobacco enterprise and scientific research institutions have carried out series of analysis and research round this requirement to technology, and propose leaf silk drying process processing strength concept in this process.But this concept only rests on by the machined parameters collocation and carries out on the vague description in conjunction with aesthetic quality's variation at present, still failing interior quality to processing intensity changes that the form of expression is carried out specifically, objective qualitative, quantitative expression, cause tobacco enterprise in actual production process, can't science, the drying process parameter adjustment of guidance system silk thread leaf silk and control objectively, be unfavorable for going deep into of characteristic technology research, make and strengthen processing technology to the product quality contribution rate, improve the quality of products, the effect of outstanding personalization of product is subjected to certain restriction.
Summary of the invention
The objective of the invention is at the deficiencies in the prior art, a kind of objective, easy method is provided, use near infrared qualitative analysis technology that the processing of the leaf silk drying process in cigarette throwing intensity is characterized, with the critical process parameter adjustment of guidance system silk thread and control, improve the technical merit of cigarette processing, fragrance style and the taste feature of outstanding cigarette product.
Purpose of the present invention is achieved through the following technical solutions.
Except as otherwise noted, percentage of the present invention is percent by weight.
A kind of method of accurate sign cigarette leaves and tobacco drying process material processing intensity may further comprise the steps:
(1) sampling and sample preparation: gather the pipe tobacco before dry, pipe tobacco is dried to water percentage under 20～30 ℃ of conditions of temperature be 11%～13% sample in contrast, gets the pipe tobaccos of different dry processing gradients simultaneously respectively as the test sample; With gather in the same old way with the test sample make powder respectively, place 22 ℃ of temperature, balance is to be detected after 48 hours under the relative humidity 60%RH environment; Described pipe tobacco is single-tobacco-typed cigarette or module cigarette;
(2) spectral scan: use near infrared spectrometer that each testing sample is carried out near infrared spectrum scanning, the near infrared spectrum sweep limit of each sample: 1400～2300nm, resolution: 4～8cm respectively
-1, scanning times: 30～80 times;
(3) spectrum pre-service: the spectroscopic data that spectral scan obtains obtains the pre-processed spectrum data of each testing sample again after polynary scatter correction, second order local derviation+Norris derivative filtering;
(4) spectroscopic data modeling: use major component-mahalanobis distance method the pre-processed spectrum data are analyzed, set up respectively test the class model of samples with different dry processing gradients in the same old way;
(5) differentiation of processing intensity: calculate each dry processing gradient test sample to mean value between the class of class model mahalanobis distance in the same old way, mean value is defined as weak processing intensity 0.5000～1.5999 when between the class of mahalanobis distance; Mean value is defined as medium processing intensity 1.6000～1.9999 when between the class of mahalanobis distance; Mean value is defined as and forces worker's intensity 2.0000～5.0000 when between the class of mahalanobis distance.
With respect to existing leaf silk dry tenacity assessment technique, the present invention has following advantage:
1, concrete qualitative, quantitative expression have been carried out in variation to leaf silk drying process processing intensity pipe tobacco interior quality, are conducive to the drying process parameter adjustment of guidance system silk thread leaf silk and control objectively.
2, broken through the restriction that leaf silk drying process processing intensity is described by high and the high and low and low collocation of machined parameters, can verify that the different machining parameters collocation is to the variation tendency that influences of cigarette interior quality.
3, the sense organ that has reduced leaf silk drying process processing intensity is described and is subjected to the subjectivity effect, can change to make comparatively objectively to the cigarette interior quality better and judge.
4, method of operating of the present invention is simple, and obvious technical effects can be utilized the potential quality of leaf silk raw material self, promotes its interior quality.
Description of drawings
Fig. 1 embodiment 1 original near infrared light spectrogram;
Fig. 2 embodiment 1 handles back near infrared light spectrogram;
Sample and processing gradient 1 test specimen class model distribution plan before Fig. 3-1 embodiment 1 operation;
Sample and processing gradient 2 test specimen class model distribution plans before Fig. 3-2 embodiment 1 operation;
Sample and processing gradient 3 test specimen class model distribution plans before Fig. 3-3 embodiment 1 operation;
Fig. 4 embodiment 2 original near infrared light spectrograms;
Fig. 5 embodiment 2 handles back near infrared light spectrogram;
Sample and processing gradient 1 test specimen class model distribution plan before Fig. 6-1 embodiment 2 operations;
Sample and processing gradient 2 test specimen class model distribution plans before Fig. 6-2 embodiment 2 operations;
Sample and processing gradient 3 test specimen class model distribution plans before Fig. 6-3 embodiment 2 operations;
Fig. 7 embodiment 3 original near infrared light spectrograms;
Fig. 8 embodiment 3 handles back near infrared light spectrogram;
Sample and processing gradient 1 test specimen class model distribution plan before Fig. 9-1 embodiment 3 operations;
Sample and processing gradient 2 test specimen class model distribution plans before Fig. 9-2 embodiment 3 operations;
Sample and processing gradient 3 test specimen class model distribution plans before Fig. 9-3 embodiment 3 operations;
Sample and processing gradient 4 test specimen class model distribution plans before Fig. 9-4 embodiment 3 operations.
Embodiment
Below in conjunction with drawings and Examples the present invention is described in further detail, but embodiment and accompanying drawing are not limited to the technical solution.
Except as otherwise noted, related technical term 2003 editions " the cigarette process standards " of all writing with reference to State Tobacco Monopoly Bureau.
(1) choose B2F single-tobacco-typed cigarette in 2009 as analytic target, before leaf silk drying process processing, carry out loosening and gaining moisture and chopping pre-service, make chopping after the pipe tobacco water percentage 20～23%.Gather the preceding sample of operation sample in contrast, adopt the method for 28 ℃ of heating of environment temperature, with raw material drying to 12.5～12.6%.Test by the combination of the listed machined parameters gradient of table 1 simultaneously, and the sample of getting processing gradient 1, processing gradient 2, processing gradient 3 after operation respectively is as the test sample.Again with gather in the same old way with test sample pulverize, climatic chamber (ambient temperature and humidity is 22 ℃, 60%RH) in balance 48 hours to be detected.
Table 1 embodiment 1 processing conditions is set
| ? | Supplied materials pipe tobacco water percentage (%) | The barrel temperature (℃) | Hot blast temperature (℃) |
| |
20 | 130 | 100 |
| |
21.6 | 155 | 120 |
| |
22.4 | 180 | 100 |
(2) select online near infrared spectrometer respectively to in the same old way, processing gradient 1 test sample, processing gradient 2 test samples, processing gradient 3 test samples carry out near infrared spectrum scanning.Each sample near infrared spectrum sweep limit: 1400～2300nm, resolution: 8cm
-1, scanning times: 30 times.The original near infrared light spectrogram of gained as shown in Figure 1.
(3) to the spectroscopic data of the spectroscopic data that obtains of scanning through polynary scatter correction, after the second order local derviation+filtering of Norris derivative obtains handling, form in the same old way, processing gradient 1 test sample, processing gradient 2 test samples, four groups of spectrum of processing gradient 3 test samples.Near infrared light spectrogram after the processing as shown in Figure 2.
(4) application principal component analysis (PCA) one mahalanobis distance method is set up the preceding sample of operation respectively with processing gradient 1 test specimen, the preceding sample of operation and sample and the class model of processing gradient 3 test specimens before processing gradient 2 test specimens, operation.The distribution plan of class model is shown in Fig. 3-1～3-3.
(5) obtained processing the mahalanobis distance of gradient 1 test specimen class model, processing gradient 2 test specimen class models, processing gradient 3 test specimen class models class model before the operation respectively by class model, the result is as shown in table 2.And calculate processing gradient 1 test specimen, processing gradient 2 test specimens, processing gradient 3 test specimens respectively to mean value between the class of the preceding class model mahalanobis distance of operation.The result is as shown in table 3, and as can be seen from Table 3, processing gradient 1 class model in 0.5000～1.5999 scope, can judge that processing gradient 1 belongs to weak processing intensity to mean value between the class of the preceding class model mahalanobis distance of operation; Processing gradient 2 class models in 1.6000～1.9999 scopes, can judge that processing gradient 2 belongs to medium processing intensity to mean value between the class of the preceding class model mahalanobis distance of operation; Mean value is in 2.0000～5.0000 scopes between the class of processing gradient 3 class models class model mahalanobis distance before the operation, can judge that processing gradient 3 belongs to force worker's intensity.
Table 2 embodiment 1 mahalanobis distance result of calculation
| | Processing gradient | 2 is to the preceding between class distance of | Processing gradient | 3 is to the preceding between class distance of operation |
| 0.8528 | 1.2973 | 2.3496 | ||
| 1.1175 | 1.8945 | 2.6614 | ||
| 0.7615 | 1.341 | 2.3092 | ||
| 0.6472 | 1.3204 | 2.6334 | ||
| 1.0041 | 1.8649 | 2.1433 | ||
| 1.032 | 1.7342 | 3.1832 | ||
| 0.7871 | 1.4555 | 2.3945 | ||
| 0.8593 | 1.9303 | 2.7246 | ||
| 0.7827 | 1.6126 | 2.7113 | ||
| 0.831 | 1.5719 | 2.3252 | ||
| 1.0551 | 1.2973 | 2.8647 | ||
| 0.8241 | 1.8945 | 2.3888 | ||
| 1.0962 | 1.341 | 2.4348 | ||
| 1.3657 | 1.3204 | 2.6711 | ||
| 1.083 | 1.8649 | 2.034 | ||
| 1.0805 | 1.7342 | 2.554 | ||
| 1.4212 | 1.4555 | 2.2932 | ||
| 1.1028 | 1.9303 | 2.8306 | ||
| 1.0786 | 1.6126 | 2.695 | ||
| 1.4861 | 1.5719 | 2.7026 | ||
| 0.8528 | 1.7617 | 2.3496 | ||
| 0.8745 | 2.019 | 2.6614 | ||
| 0.8957 | 1.5082 | 2.3092 | ||
| 0.8634 | 1.7356 | 2.6334 | ||
| 1.0874 | 1.9157 | 2.1433 | ||
| 0.9877 | 1.9995 | 3.1832 | ||
| 0.8829 | 1.9145 | 2.3945 | ||
| 0.7895 | 1.7616 | 2.7246 | ||
| 0.8565 | 1.8288 | 2.7113 | ||
| 1.1964 | 1.8816 | 2.3252 |
Mean value between table 3 embodiment 1 mahalanobis distance class
| ? | Mean value between the mahalanobis distance |
| Processing gradient | |
| 1 is before operation | 0.9897 |
| |
1.6790 |
| |
2.5445 |
Different processing gradient aesthetic quality's smoking results such as table 4, in the table as can be seen, processing through processing gradient 1～gradient 2 is handled, aspects such as fragrance matter, assorted gas, fine and smooth degree, clean level continue to improve, develop to the direction of difference to gradient 3 its aesthetic qualities, aspects such as pungency, dry sensation, clean level descend to some extent.
Table 4 embodiment 1 different processing gradient aesthetic qualities change
Annotate: in the table score value for to compare in the same old way, in each project, be better than in the same old way beat on the occasion of, be inferior to the negative value of beating in the same old way.
(1) choose C4F single-tobacco-typed cigarette in 2010 as analytic target, test by the machined parameters gradient combination that table 5 is listed, other content is with embodiment 1.
Table 5 embodiment 2 processing conditionss are set
| ? | Supplied materials pipe tobacco water percentage (%) | The barrel temperature (℃) | Hot blast temperature (℃) |
| |
19.8 | 120 | 90 |
| |
21.4 | 145 | 100 |
| |
22.2 | 155 | 90 |
(2) select online near infrared spectrometer respectively to in the same old way, processing gradient 1 test sample, processing gradient 2 test samples, processing gradient 3 test samples carry out near infrared spectrum scanning.Each sample near infrared spectrum sweep limit: 1400～2300nm, resolution: 8cm
-1, scanning times: 40 times, other content is with embodiment 1.The original near infrared light spectrogram of gained as shown in Figure 4.
(3) content is with embodiment 1, and the near infrared light spectrogram after the processing as shown in Figure 5.
(4) content is with embodiment 1, and the distribution plan of class model is shown in Fig. 6-1～6-3.
(5) calculate processing gradient 1 test specimen, processing gradient 2 test specimens, processing gradient 3 test specimens respectively to mean value between the class of the preceding class model mahalanobis distance of operation.The result is as shown in table 6, and as can be seen from Table 6, processing gradient 1 class model in 0.5000～1.5999 scope, can judge that processing gradient 1 belongs to weak processing intensity to mean value between the class of the preceding class model mahalanobis distance of operation; Mean value is in 2.0000～5.0000 scopes between the class of processing gradient 2 class models class model mahalanobis distance before the operation, can judge that processing gradient 2 belongs to force worker's intensity; Mean value is in 2.0000～5.0000 scopes between the class of processing gradient 3 class models class model mahalanobis distance before the operation, can judge that processing gradient 3 belongs to force worker's intensity.
Mean value between table 6 embodiment 2 mahalanobis distance classes
| ? | Mean value between the mahalanobis distance |
| Processing gradient | |
| 1 is before operation | 1.2684 |
| |
2.1191 |
| |
2.8218 |
Different processing gradient aesthetic quality's smoking results such as table 7 as can be seen from the table, are handled through the processing of processing gradient 1, and aspects such as fragrance matter, assorted gas, fine and smooth degree, clean level make moderate progress; Gradient 2, gradient 3 aesthetic qualities are comparatively approaching, and aspects such as pungency, dry sensation, clean level descend to some extent.
Table 7 embodiment 2 different processing gradient aesthetic qualities change
Annotate: in the table score value for to compare in the same old way, in each project, be better than in the same old way beat on the occasion of, be inferior to the negative value of beating in the same old way.
(1) choose high-grade cigarette module as analytic target, before leaf silk drying process processing, carry out loosening and gaining moisture and chopping pre-service, make chopping after the pipe tobacco water percentage 19.5～21.0%.Gather the preceding sample of operation sample in contrast, adopt the method for 25 ℃ of heating of environment temperature, with raw material drying to 12.3～12.5%.Test by the combination of the listed machined parameters gradient of table 8 simultaneously, and the sample of getting processing gradient 1, processing gradient 2, processing gradient 3, processing gradient 4 after operation respectively is as the test sample.Again with gather in the same old way with the test sample be cut into thread, climatic chamber (ambient temperature and humidity is 22 ℃, 60%RH) in balance 48 hours to be detected.
Table 8 embodiment 3 processing conditionss are set
| ? | Supplied materials pipe tobacco water percentage (%) | The barrel temperature (℃) | Hot blast temperature (℃) |
| |
19.8 | 120 | 110 |
| |
20.5 | 140 | 100 |
| |
20.6 | 130 | 120 |
| |
21.0 | 140 | 110 |
(2) select the hand-held near infrared spectrometer respectively to in the same old way, processing gradient 1 test sample, processing gradient 2 test samples, processing gradient 3, gradient 4 test samples carry out near infrared spectrum scanning.Each sample near infrared spectrum sweep limit: 1400～2300nm, resolution: 4cm
-1, scanning times: 50 times.The original near infrared light spectrogram of gained as shown in Figure 7.
(3) to the spectroscopic data of the spectroscopic data that obtains of scanning through polynary scatter correction, after the second order local derviation+filtering of Norris derivative obtains handling, form in the same old way, processing gradient 1 test sample, processing gradient 2 test samples, processing gradient 3, five groups of spectrum of processing gradient 4 test samples.Near infrared light spectrogram after the processing as shown in Figure 8.
(4) application principal component analysis (PCA) one mahalanobis distance method is set up the preceding sample of operation respectively with processing gradient 1 test specimen, the preceding sample of operation and sample and the class model of processing gradient 3 test specimens, the preceding sample of operation and processing gradient 4 test specimens before processing gradient 2 test specimens, operation.The distribution plan of class model is shown in Fig. 9-1～9-4.
(5) calculate mean value between the class of processing gradient 1 test specimen, processing gradient 2 test specimens, processing gradient 3 test specimens, processing gradient 4 test specimens class model mahalanobis distance before the operation respectively.The result is as shown in table 9, and as can be seen from Table 9, processing gradient 1 class model in 1.6000～1.999 scopes, can judge that processing gradient 1 belongs to medium processing intensity to mean value between the class of the preceding class model mahalanobis distance of operation; Processing gradient 2 class models in 1.6000～1.9999 scopes, can judge that processing gradient 2 belongs to medium processing intensity to mean value between the class of the preceding class model mahalanobis distance of operation; Mean value is in 2.0000～5.0000 scopes between the class of processing gradient 3 class models class model mahalanobis distance before the operation, can judge that processing gradient 3 belongs to force worker's intensity; Mean value is in 2.0000～5.0000 scopes between the class of processing gradient 4 class models class model mahalanobis distance before the operation, can judge that processing gradient 4 belongs to force worker's intensity.
Mean value between table 9 embodiment 3 mahalanobis distance classes
| ? | Mean value between the mahalanobis distance |
| Processing gradient | |
| 1 is before operation | 1.6143 |
| |
1.8225 |
| |
2.8562 |
| |
3.2379 |
Different processing gradient aesthetic quality's smoking results such as table 10, as can be seen, 2 aesthetic qualities are comparatively approaching through processing gradient 1, processing gradient in the table, and fragrance matter, perfume quantity, assorted gas, concentration, clean level make moderate progress; Gradient 4 aesthetic qualities are comparatively approaching through processing gradient 3, processing, and perfume quantity, concentration make moderate progress, and assorted gas, fine and smooth degree, pungency, clean level descend to some extent.
Table 10 embodiment 3 different processing gradient aesthetic qualities change
Annotate: in the table score value for to compare in the same old way, in each project, be better than in the same old way beat on the occasion of, be inferior to the negative value of beating in the same old way.
Claims (1)
1. one kind accurately characterizes the method that cigarette leaves and tobacco drying process material is processed intensity, may further comprise the steps:
(1) sampling and sample preparation: gather the pipe tobacco before dry, pipe tobacco is dried to water percentage under 20～30 ℃ of conditions of temperature be 11%～13% sample in contrast, gets the pipe tobaccos of different dry processing gradients simultaneously respectively as the test sample; With gather in the same old way with the test sample make powder respectively, place 22 ℃ of temperature, balance is to be detected after 48 hours under the relative humidity 60%RH environment; Described pipe tobacco is single-tobacco-typed cigarette or module cigarette;
(2) spectral scan: use near infrared spectrometer that each testing sample is carried out near infrared spectrum scanning, the near infrared spectrum sweep limit of each sample: 1400～2300nm, resolution: 4～8cm respectively
-1, scanning times: 30～80 times;
(3) spectrum pre-service: the spectroscopic data that spectral scan obtains obtains the pre-processed spectrum data of each testing sample again after polynary scatter correction, second order local derviation+Norris derivative filtering;
(4) spectroscopic data modeling: use major component-mahalanobis distance method the pre-processed spectrum data are analyzed, set up respectively test the class model of samples with different dry processing gradients in the same old way;
(5) differentiation of processing intensity: calculate each dry processing gradient test sample to mean value between the class of class model mahalanobis distance in the same old way, mean value is defined as weak processing intensity 0.5000～1.5999 when between the class of mahalanobis distance; Mean value is defined as medium processing intensity 1.6000～1.9999 when between the class of mahalanobis distance; Mean value is defined as and forces worker's intensity 2.0000～5.0000 when between the class of mahalanobis distance.
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| CN114642267A (en) * | 2022-04-01 | 2022-06-21 | 湖北中烟工业有限责任公司 | Method and device for regulating and controlling hot processing strength of cut tobacco drying process and electronic equipment |
| CN114642267B (en) * | 2022-04-01 | 2023-03-14 | 湖北中烟工业有限责任公司 | Method and device for regulating hot processing strength of cut tobacco drying process and electronic equipment |
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