CN104697955A - Cigarette smoke index prediction method and system - Google Patents
Cigarette smoke index prediction method and system Download PDFInfo
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- CN104697955A CN104697955A CN201510143835.7A CN201510143835A CN104697955A CN 104697955 A CN104697955 A CN 104697955A CN 201510143835 A CN201510143835 A CN 201510143835A CN 104697955 A CN104697955 A CN 104697955A
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- 235000019504 cigarettes Nutrition 0.000 title claims abstract description 45
- 239000000779 smoke Substances 0.000 title claims abstract description 37
- 238000000034 method Methods 0.000 title claims abstract description 26
- 241000208125 Nicotiana Species 0.000 claims abstract description 90
- 235000002637 Nicotiana tabacum Nutrition 0.000 claims abstract description 90
- 239000000126 substance Substances 0.000 claims abstract description 79
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims description 89
- 239000003546 flue gas Substances 0.000 claims description 64
- SNICXCGAKADSCV-UHFFFAOYSA-N nicotine Natural products CN1CCCC1C1=CC=CN=C1 SNICXCGAKADSCV-UHFFFAOYSA-N 0.000 claims description 59
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 claims description 56
- SNICXCGAKADSCV-JTQLQIEISA-N (-)-Nicotine Chemical compound CN1CCC[C@H]1C1=CC=CN=C1 SNICXCGAKADSCV-JTQLQIEISA-N 0.000 claims description 41
- 229960002715 nicotine Drugs 0.000 claims description 41
- 239000003517 fume Substances 0.000 claims description 36
- ZAMOUSCENKQFHK-UHFFFAOYSA-N Chlorine atom Chemical compound [Cl] ZAMOUSCENKQFHK-UHFFFAOYSA-N 0.000 claims description 34
- ZLMJMSJWJFRBEC-UHFFFAOYSA-N Potassium Chemical compound [K] ZLMJMSJWJFRBEC-UHFFFAOYSA-N 0.000 claims description 34
- 239000000460 chlorine Substances 0.000 claims description 34
- 229910052801 chlorine Inorganic materials 0.000 claims description 34
- 239000011591 potassium Substances 0.000 claims description 34
- 229910052700 potassium Inorganic materials 0.000 claims description 34
- 229910052757 nitrogen Inorganic materials 0.000 claims description 28
- 229910002091 carbon monoxide Inorganic materials 0.000 claims description 25
- 238000004611 spectroscopical analysis Methods 0.000 claims description 16
- 230000001419 dependent effect Effects 0.000 claims description 12
- 238000002329 infrared spectrum Methods 0.000 claims description 10
- 238000004458 analytical method Methods 0.000 claims description 7
- 238000012417 linear regression Methods 0.000 claims description 6
- 239000000203 mixture Substances 0.000 abstract description 6
- 239000011269 tar Substances 0.000 description 18
- 238000004519 manufacturing process Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 3
- 238000012217 deletion Methods 0.000 description 2
- 230000037430 deletion Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000007599 discharging Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 229920002472 Starch Polymers 0.000 description 1
- 229930013930 alkaloid Natural products 0.000 description 1
- 150000003797 alkaloid derivatives Chemical class 0.000 description 1
- 150000001413 amino acids Chemical class 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 150000001735 carboxylic acids Chemical class 0.000 description 1
- 229920002678 cellulose Polymers 0.000 description 1
- 239000001913 cellulose Substances 0.000 description 1
- 239000011285 coke tar Substances 0.000 description 1
- 150000002148 esters Chemical class 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- 230000000391 smoking effect Effects 0.000 description 1
- 235000019698 starch Nutrition 0.000 description 1
- 239000008107 starch Substances 0.000 description 1
- 238000005979 thermal decomposition reaction Methods 0.000 description 1
- 238000009423 ventilation Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N2021/8466—Investigation of vegetal material, e.g. leaves, plants, fruits
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2201/00—Features of devices classified in G01N21/00
- G01N2201/12—Circuits of general importance; Signal processing
- G01N2201/129—Using chemometrical methods
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- Physics & Mathematics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention discloses a cigarette smoke index prediction method. The method comprises the steps of obtaining the general chemical composition content of cut tobacco to be predicted; inputting the general chemical composition content of the cut tobacco to be predicted to a smoke prediction model generated in advance, wherein the smoke prediction model is constructed according to the smoke index and the general chemical composition content; operating the smoke prediction model, and outputting the smoke index of the cut tobacco to be predicted. The smoke index can be predicted through the general chemical composition of the cut tobacco. The invention further discloses a cigarette smoke index prediction system.
Description
Technical field
The present invention relates to field of cigarette producing technology, particularly relate to a kind of cigarette smoke index prediction method and system.
Background technology
In recent years, along with society strengthens smoking and healthy concern, in flue gas, the detection of tar, nicotine, carbon monoxide becomes one of whether qualified major criterion of cigarette.Tar in cigarette smoke is organism unburnt product under the weary oxygen condition of high temperature mainly, and major part is condensed-nuclei aromatics; Carbon monoxide is that many tobacco components such as starch, cellulose, sugar, carboxylic acid, ester, amino acid etc. are formed by thermal decomposition and burning; Nicotine directly can volatilize and enter flue gas, and the alkaloid in tobacco leaf is higher, and flue gas alkaline components content is higher.Therefore, there is with pipe tobacco routine chemical components association in cigarette smoke index.At present, the detection of traditional coke tar in cigarette, nicotine, carbon monoxide only considered the physical index such as Cigarette Draw Resistance, ventilation, cannot predict based on the chemical composition of pipe tobacco.
Summary of the invention
The invention provides a kind of cigarette smoke index prediction method and system, fume indication can be predicted fast and accurately by the chemical composition in pipe tobacco.
The invention provides a kind of cigarette smoke index prediction method, comprising:
Obtain the routine chemical components content of pipe tobacco to be measured;
Input the routine chemical components content of described pipe tobacco to be measured to the flue gas forecast model generated in advance, described flue gas forecast model is the model built according to fume indication and routine chemical components content;
Run described flue gas forecast model, export the fume indication of pipe tobacco to be measured.
Preferably, also comprise before the routine chemical components content of described acquisition pipe tobacco to be measured:
Near infrared spectra collection is carried out to described pipe tobacco to be measured, generates described pipe tobacco spectroscopic data to be measured;
Analyze described spectroscopic data, generate the routine chemical components content of described pipe tobacco to be measured.
Preferably, the described flue gas forecast model that generates in advance comprises:
Obtain the Test Data of Cigarette Smoke of regular period inner wrap strip and the routine chemical components content of cigarette shreds;
Described routine chemical components content is defined as independent variable, Test Data of Cigarette Smoke is defined as dependent variable;
Multiple linear regression analysis is carried out to described independent variable and dependent variable, generates flue gas forecast model.
Preferably, described routine chemical components comprises: total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine;
Described fume indication comprises: tar index, nicotine index and carbon monoxide index.
Preferably, described flue gas forecast model comprises:
Tar predictive equation: Y
tar=-3.207+0.588X
total reducing sugar-0.46X
reducing sugar+ 0.293X
total nitrogen+ 3.849X
nicotine-2.726X
potassium+ 6.853X
chlorine;
Nicotine predictive equation: Y
nicotine=-0.192+0.048X
total reducing sugar-0.036X
reducing sugar+ 0.363X
nicotine-0.249X
potassium+ 0.524X
chlorine;
Carbon monoxide predictive equation: Y
carbon monoxide=1.477+0.078X
total reducing sugar+ 0.108X
reducing sugar+ 0.103X
total nitrogen+ 3.046X
nicotine-3.645X
potassium+ 6.735
chlorine.
A kind of cigarette smoke index prediction system, comprising:
Acquiring unit, for obtaining the routine chemical components content of pipe tobacco to be measured;
Input block, for inputting the routine chemical components content of described pipe tobacco to be measured to the flue gas forecast model generated in advance, described flue gas forecast model is the model built according to fume indication and routine chemical components content;
Flue gas forecast model, for the routine chemical components content according to described pipe tobacco to be measured, exports the fume indication of pipe tobacco to be measured.
Preferably, described system also comprises: near-infrared spectrometers;
Described near-infrared spectrometers is used for: carry out near infrared spectra collection to described pipe tobacco to be measured, generates described pipe tobacco spectroscopic data to be measured, analyzes described spectroscopic data, generate the routine chemical components content of described pipe tobacco to be measured.
Preferably, described routine chemical components comprises: total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine;
Described fume indication comprises: tar index, nicotine index and carbon monoxide index.
Preferably, described flue gas forecast model comprises:
Tar predictive equation: Y
tar=-3.207+0.588X
total reducing sugar-0.46X
reducing sugar+ 0.293X
total nitrogen+ 3.849X
nicotine-2.726X
potassium+ 6.853X
chlorine;
Nicotine predictive equation: Y
nicotine=-0.192+0.048X
total reducing sugar-0.036X
reducing sugar+ 0.363X
nicotine-0.249X
potassium+ 0.524X
chlorine;
Carbon monoxide predictive equation: Y
carbon monoxide=1.477+0.078X
total reducing sugar+ 0.108X
reducing sugar+ 0.103X
total nitrogen+ 3.046X
nicotine-3.645X
potassium+ 6.735
chlorine.
From such scheme, a kind of cigarette smoke index prediction method provided by the invention, first by obtaining the routine chemical components content of pipe tobacco to be measured, then routine chemical components content is input in the flue gas forecast model built according to fume indication and routine chemical components content generated in advance, run flue gas forecast model, draw the fume indication of pipe tobacco to be measured, achieve and by the routine chemical components of pipe tobacco, fume indication is predicted.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
The process flow diagram of Fig. 1 a kind of cigarette smoke index prediction method disclosed in the embodiment of the present invention;
The process flow diagram of Fig. 2 a kind of cigarette smoke index prediction method disclosed in another embodiment of the present invention;
Fig. 3 is the disclosed process flow diagram generating flue gas forecast model of the embodiment of the present invention;
The structured flowchart of Fig. 4 a kind of cigarette smoke index prediction system disclosed in the embodiment of the present invention;
The structured flowchart of Fig. 5 a kind of cigarette smoke index prediction system disclosed in another embodiment of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
As shown in Figure 1, a kind of cigarette smoke index prediction method disclosed in the embodiment of the present invention, comprising:
S101, obtain the routine chemical components content of pipe tobacco to be measured;
The flue gas forecast model that S102, the routine chemical components content inputting pipe tobacco to be measured extremely generate in advance, flue gas forecast model is the model built according to fume indication and routine chemical components content;
S103, operation flue gas forecast model, export the fume indication of pipe tobacco to be measured.
Concrete, the course of work of above-described embodiment is: when needing to predict the fume indication of cigarette, first the routine chemical components content of pipe tobacco to be measured is obtained, then the routine chemical components content of the pipe tobacco to be measured got is input in the flue gas forecast model generated in advance, described flue gas forecast model is the model built according to fume indication and routine chemical components content, then run flue gas forecast model, export the fume indication of the pipe tobacco to be measured of the routine chemical components content prediction according to pipe tobacco to be measured.
As shown in Figure 2, a kind of cigarette smoke index prediction method disclosed in another embodiment of the present invention, comprising:
S201, near infrared spectra collection is carried out to pipe tobacco to be measured, generate pipe tobacco spectroscopic data to be measured;
S202, analysis spectroscopic data, generate the routine chemical components content of pipe tobacco to be measured;
S203, obtain the routine chemical components content of pipe tobacco to be measured;
The flue gas forecast model that S204, the routine chemical components content inputting described pipe tobacco to be measured extremely generate in advance, described flue gas forecast model is the model built according to fume indication and routine chemical components content;
S205, run described flue gas forecast model, export the fume indication of pipe tobacco to be measured.
Concrete, the course of work of above-described embodiment is: when needing to predict the fume indication of cigarette, first near infrared spectra collection is carried out to pipe tobacco to be measured, generate the spectroscopic data of pipe tobacco to be measured, when carrying out near infrared spectra collection to pipe tobacco to be measured, can be online acquisition, during online acquisition, near infrared spectrometer be arranged on above Primary Processing Workshop of Cigarette production line outfeed belt, the tobacco sample when production line discharging is stablized on scanning belt; Also can off-line collection, namely artificial to tobacco sample sampling, then the tobacco sample of constant weight is put into sample cup, by near infrared spectrometer, the sample in sample cup is scanned.Then near infrared spectrometer is analyzed scanning the spectroscopic data obtained, and generates the routine chemical components content of pipe tobacco to be measured; Described routine chemical components comprises total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine.
Then near infrared spectrometer, obtain the routine chemical components content of pipe tobacco to be measured, the i.e. content of total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine, then the content of the total reducing sugar of acquisition, reducing sugar, total nitrogen, nicotine, potassium and chlorine is inputed to the flue gas forecast model generated in advance, described flue gas forecast model is the model built according to fume indication and routine chemical components content, building process as shown in Figure 3:
S301, the acquisition Test Data of Cigarette Smoke of regular period inner wrap strip and the routine chemical components content of cigarette shreds;
S302, routine chemical components content is defined as independent variable, Test Data of Cigarette Smoke is defined as dependent variable;
S303, multiple linear regression analysis is carried out to independent variable and dependent variable, generate flue gas forecast model.
Concrete, when building flue gas forecast model, first routine chemical components data and the Test Data of Cigarette Smoke of each batch of different size pipe tobacco in the regular period is obtained, namely the tar index in total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine and flue gas, nicotine index and carbon monoxide index is obtained, in order to make the model built more accurate, sampled point is throughout whole Primary Processing.Then the content of total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine is defined as independent variable, be dependent variable by tar index, nicotine index and carbon monoxide index definition, multiple linear regression analysis is carried out to independent variable and dependent variable, in the model that " entering ", " progressively ", " deletion " method are set up, choose t inspection the most significant, residual error is minimum, is flue gas forecast model.The flue gas forecast model finally formed comprises: tar predictive equation: Y
tar=-3.207+0.588X
total reducing sugar-0.46X
reducing sugar+ 0.293X
total nitrogen+ 3.849X
nicotine-2.726X
potassium+ 6.853X
chlorine, nicotine predictive equation: Y
nicotine=-0.192+0.048X
total reducing sugar-0.036X
reducing sugar+ 0.363X
nicotine-0.249X
potassium+ 0.524X
chlorinewith carbon monoxide predictive equation: Y
carbon monoxide=1.477+0.078X
total reducing sugar+ 0.108X
reducing sugar+ 0.103X
total nitrogen+ 3.046X
nicotine-3.645X
potassium+ 6.735
chlorine.
Then the routine chemical components content of pipe tobacco to be measured obtained and the content of total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine are inputed to flue gas forecast model, and run flue gas forecast model, export the fume indication of pipe tobacco to be measured, namely export tar index, nicotine index and carbon monoxide index.
As shown in Figure 4, a kind of cigarette smoke index prediction system disclosed in the embodiment of the present invention, comprising: acquiring unit 41, input block 42 and flue gas forecast model 43; Wherein:
Acquiring unit 41, for obtaining the routine chemical components content of pipe tobacco to be measured;
Input block 42, for inputting the routine chemical components content of pipe tobacco to be measured to the flue gas forecast model 43 generated in advance, flue gas forecast model 43 is the model built according to fume indication and routine chemical components content;
Flue gas forecast model 43, for the routine chemical components content according to pipe tobacco to be measured, exports the fume indication of pipe tobacco to be measured.
Concrete, the principle of work of above-described embodiment is: when needing to predict the fume indication of cigarette, first the routine chemical components content of pipe tobacco to be measured is obtained by acquiring unit 41, then by input block 42 the routine chemical components content of the pipe tobacco to be measured got is input in the flue gas forecast model generated in advance, described flue gas forecast model is the model built according to fume indication and routine chemical components content, then run flue gas forecast model 43, export the fume indication of the pipe tobacco to be measured of the routine chemical components content prediction according to pipe tobacco to be measured.
As shown in Figure 5, a kind of cigarette smoke index prediction system disclosed in another embodiment of the present invention, comprising: near-infrared spectrometers 51, acquiring unit 52, input block 53 and flue gas forecast model 54; Wherein:
Near-infrared spectrometers 51 for: near infrared spectra collection is carried out to pipe tobacco to be measured, generates pipe tobacco spectroscopic data to be measured, analyze described spectroscopic data, generate the routine chemical components content of described pipe tobacco to be measured;
Acquiring unit 52, for obtaining the routine chemical components content of pipe tobacco to be measured;
Input block 53, for inputting the routine chemical components content of pipe tobacco to be measured to the flue gas forecast model 54 generated in advance, flue gas forecast model 54 is the model built according to fume indication and routine chemical components content;
Flue gas forecast model 54, for the routine chemical components content according to pipe tobacco to be measured, exports the fume indication of pipe tobacco to be measured.
Concrete, the principle of work of above-described embodiment is: when needing to predict the fume indication of cigarette, first by near-infrared spectrometers 51, near infrared spectra collection is carried out to pipe tobacco to be measured, generate the spectroscopic data of pipe tobacco to be measured, when carrying out near infrared spectra collection to pipe tobacco to be measured, can be online acquisition, during online acquisition, near infrared spectrometer 51 be arranged on above Primary Processing Workshop of Cigarette production line outfeed belt, the tobacco sample when production line discharging is stablized on scanning belt; Also can off-line collection, namely artificial to tobacco sample sampling, then the tobacco sample of constant weight is put into sample cup, scanned by the sample near infrared spectrometer 51 pairs of sample cups.Then near infrared spectrometer 51 is analyzed scanning the spectroscopic data obtained, and generates the routine chemical components content of pipe tobacco to be measured; Described routine chemical components comprises total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine.
Then near infrared spectrometer 51, the routine chemical components content of pipe tobacco to be measured is obtained by acquiring unit 52, the i.e. content of total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine, then by input block 53, the content of the total reducing sugar of acquisition, reducing sugar, total nitrogen, nicotine, potassium and chlorine is inputed to the flue gas forecast model 54 generated in advance, described flue gas forecast model 54 is the model built according to fume indication and routine chemical components content, building process as shown in Figure 3:
S301, the acquisition Test Data of Cigarette Smoke of regular period inner wrap strip and the routine chemical components content of cigarette shreds;
S302, routine chemical components content is defined as independent variable, Test Data of Cigarette Smoke is defined as dependent variable;
S303, multiple linear regression analysis is carried out to independent variable and dependent variable, generate flue gas forecast model.
Concrete, when building flue gas forecast model 54, first routine chemical components data and the Test Data of Cigarette Smoke of each batch of different size pipe tobacco in the regular period is obtained, namely the tar index in total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine and flue gas, nicotine index and carbon monoxide index is obtained, in order to make the model built more accurate, sampled point is throughout whole Primary Processing.Then the content of total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine is defined as independent variable, be dependent variable by tar index, nicotine index and carbon monoxide index definition, multiple linear regression analysis is carried out to independent variable and dependent variable, in the model that " entering ", " progressively ", " deletion " method are set up, choose t inspection the most significant, residual error is minimum, is flue gas forecast model.The flue gas forecast model finally formed comprises: tar predictive equation: Y
tar=-3.207+0.588X
total reducing sugar-0.46X
reducing sugar+ 0.293X
total nitrogen+ 3.849X
nicotine-2.726X
potassium+ 6.853X
chlorine, nicotine predictive equation: Y
nicotine=-0.192+0.048X
total reducing sugar-0.036X
reducing sugar+ 0.363X
nicotine-0.249X
potassium+ 0.524X
chlorinewith carbon monoxide predictive equation: Y
carbon monoxide=1.477+0.078X
total reducing sugar+ 0.108X
reducing sugar+ 0.103X
total nitrogen+ 3.046X
nicotine-3.645X
potassium+ 6.735
chlorine.
Then the routine chemical components content of pipe tobacco to be measured obtained and the content of total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine are inputed to flue gas forecast model 54, and run flue gas forecast model 54, export the fume indication of pipe tobacco to be measured, namely export tar index, nicotine index and carbon monoxide index.
If the function described in the present embodiment method using the form of SFU software functional unit realize and as independently production marketing or use time, can be stored in a computing equipment read/write memory medium.Based on such understanding, the part of the part that the embodiment of the present invention contributes to prior art or this technical scheme can embody with the form of software product, this software product is stored in a storage medium, comprising some instructions in order to make a computing equipment (can be personal computer, server, mobile computing device or the network equipment etc.) perform all or part of step of method described in each embodiment of the present invention.And aforesaid storage medium comprises: USB flash disk, portable hard drive, ROM (read-only memory) (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disc or CD etc. various can be program code stored medium.
In this instructions, each embodiment adopts the mode of going forward one by one to describe, and what each embodiment stressed is the difference with other embodiment, between each embodiment same or similar part mutually see.
To the above-mentioned explanation of the disclosed embodiments, professional and technical personnel in the field are realized or uses the present invention.To be apparent for those skilled in the art to the multiple amendment of these embodiments, General Principle as defined herein can without departing from the spirit or scope of the present invention, realize in other embodiments.Therefore, the present invention can not be restricted to these embodiments shown in this article, but will meet the widest scope consistent with principle disclosed herein and features of novelty.
Claims (9)
1. a cigarette smoke index prediction method, is characterized in that, comprising:
Obtain the routine chemical components content of pipe tobacco to be measured;
Input the routine chemical components content of described pipe tobacco to be measured to the flue gas forecast model generated in advance, described flue gas forecast model is the model built according to fume indication and routine chemical components content;
Run described flue gas forecast model, export the fume indication of pipe tobacco to be measured.
2. method according to claim 1, is characterized in that, also comprises before the routine chemical components content of described acquisition pipe tobacco to be measured:
Near infrared spectra collection is carried out to pipe tobacco to be measured, generates described pipe tobacco spectroscopic data to be measured;
Analyze described spectroscopic data, generate the routine chemical components content of described pipe tobacco to be measured.
3. method according to claim 2, is characterized in that, the described flue gas forecast model that generates in advance comprises:
Obtain the Test Data of Cigarette Smoke of regular period inner wrap strip and the routine chemical components content of cigarette shreds;
Described routine chemical components content is defined as independent variable, Test Data of Cigarette Smoke is defined as dependent variable;
Multiple linear regression analysis is carried out to described independent variable and dependent variable, generates flue gas forecast model.
4. method according to claim 3, is characterized in that, described routine chemical components comprises: total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine;
Described fume indication comprises: tar index, nicotine index and carbon monoxide index.
5. method according to claim 4, is characterized in that, described flue gas forecast model comprises:
Tar predictive equation: Y
tar=-3.207+0.588X
total reducing sugar-0.46X
reducing sugar+ 0.293X
total nitrogen+ 3.849X
nicotine-2.726X
potassium+ 6.853X
chlorine;
Nicotine predictive equation: Y
nicotine=-0.192+0.048X
total reducing sugar-0.036X
reducing sugar+ 0.363X
nicotine-0.249X
potassium+ 0.524X
chlorine;
Carbon monoxide predictive equation: Y
carbon monoxide=1.477+0.078X
total reducing sugar+ 0.108X
reducing sugar+ 0.103X
total nitrogen+ 3.046X
nicotine-3.645X
potassium+ 6.735
chlorine.
6. a cigarette smoke index prediction system, is characterized in that, comprising:
Acquiring unit, for obtaining the routine chemical components content of pipe tobacco to be measured;
Input block, for inputting the routine chemical components content of described pipe tobacco to be measured to the flue gas forecast model generated in advance, described flue gas forecast model is the model built according to fume indication and routine chemical components content;
Flue gas forecast model, for the routine chemical components content according to described pipe tobacco to be measured, exports the fume indication of pipe tobacco to be measured.
7. system according to claim 6, is characterized in that, also comprises: near-infrared spectrometers;
Described near-infrared spectrometers is used for: carry out near infrared spectra collection to described pipe tobacco to be measured, generates described pipe tobacco spectroscopic data to be measured, analyzes described spectroscopic data, generate the routine chemical components content of described pipe tobacco to be measured.
8. system according to claim 7, is characterized in that, described routine chemical components comprises: total reducing sugar, reducing sugar, total nitrogen, nicotine, potassium and chlorine;
Described fume indication comprises: tar index, nicotine index and carbon monoxide index.
9. system according to claim 8, is characterized in that, described flue gas forecast model comprises:
Tar predictive equation: Y
tar=-3.207+0.588X
total reducing sugar-0.46X
reducing sugar+ 0.293X
total nitrogen+ 3.849X
nicotine-2.726X
potassium+ 6.853X
chlorine;
Nicotine predictive equation: Y
nicotine=-0.192+0.048X
total reducing sugar-0.036X
reducing sugar+ 0.363X
nicotine-0.249
potassium+ 0.524X
chlorine;
Carbon monoxide predictive equation: Y
carbon monoxide=1.477+0.078X
total reducing sugar+ 0.108
reducing sugar+ 0.103X
total nitrogen+ 3.046X
nicotine-3.645X
potassium+ 6.735
chlorine.
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