CN112485372A - Method for evaluating miscellaneous gas in flue gas - Google Patents
Method for evaluating miscellaneous gas in flue gas Download PDFInfo
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Abstract
The invention belongs to the technical field of tobacco detection, and particularly relates to a method for evaluating miscellaneous gases in smoke. The method comprises the steps of firstly, acquiring physical characteristic data of tobacco leaves to be evaluated, and carrying out conversion processing on the physical characteristic data to enable six comprehensive indexes obtained after the conversion processing to be related to each physical characteristic data before the conversion processing; the physical property data includes the following six kinds: thickness, filling value, tension, stem content, balanced water content and leaf surface density; inputting the six comprehensive indexes into the constructed miscellaneous gas evaluation model to obtain miscellaneous gas scoring results corresponding to the six comprehensive indexes. According to the method, a miscellaneous gas evaluation result is obtained without professional smoke panel evaluation personnel through cigarette sensory evaluation, the defects of strong professional dependence, long time consumption and the like of the traditional method are overcome, chemical components of the method are not required to be measured by using chemical agents, the sample is not damaged, and the method has the advantages of simplicity in operation, reagent saving, short time, low cost, no pollution and the like.
Description
Technical Field
The invention belongs to the technical field of tobacco detection, and particularly relates to a method for evaluating miscellaneous gases in smoke.
Background
In recent years, with the diversified requirements of the tobacco market and the continuous adjustment of cigarette product formulas, tobacco manufacturers have higher and higher requirements on the quality of raw materials. The quality of tobacco leaves is the most important influence factor of the quality of cigarette products, and good tobacco leaves cannot be separated from good cigarette products.
Some miscellaneous gas exists in the smoke generated by the combustion of the tobacco leaves, and the miscellaneous gas refers to unpleasant smell in the smoke, which can cause the quality reduction and the flavor style characteristic change of the tobacco leaf products. Miscellaneous gas is one of important indexes for cigarette sensory evaluation and has been generally concerned by cigarette workers.
The traditional miscellaneous gas evaluation needs to roll tobacco leaves after stem extraction and shredding into cigarette samples, and the evaluation is carried out by the smoke panel staff who organize professional qualifications, so that the time consumption is long, certain professional dependency is achieved, and meanwhile, the influence of the physical and mental states of the smoke panel staff is easily caused. As the chemical components in the tobacco leaves have a direct relation with the sensory evaluation indexes, more researches are carried out by directly forecasting and predicting the sensory evaluation by utilizing the chemical components or near infrared spectrum data, so that chemical components of samples need to be measured by using chemical agents, the time and the labor are consumed when the results are obtained, and the tobacco leaf samples are inevitably damaged to cause environmental pollution.
Disclosure of Invention
The invention provides a method for evaluating miscellaneous gas in flue gas, which is used for solving the problems of long time consumption and strong professional dependence of traditional methods for evaluating miscellaneous gas, time consumption and labor consumption of chemical composition evaluation of miscellaneous gas in flue gas and damage to tobacco leaf samples.
In order to solve the technical problem, the technical scheme of the invention comprises the following steps:
the invention provides a method for evaluating miscellaneous gas in flue gas, which comprises the following steps:
acquiring physical characteristic data of the tobacco leaves to be evaluated, and performing conversion treatment on the physical characteristic data to enable six comprehensive indexes obtained after the conversion treatment to be related to the physical characteristic data before each conversion treatment; the physical property data includes the following six kinds: thickness, filling value, tension, stem content, balanced water content and leaf surface density;
inputting the six comprehensive indexes into a constructed miscellaneous gas evaluation model to obtain miscellaneous gas scoring results corresponding to the six comprehensive indexes; the miscellaneous gas evaluation model is obtained by training six comprehensive indexes of evaluated tobacco leaves and corresponding evaluation results after smoking of the tobacco leaves.
The beneficial effects of the above technical scheme are: according to the method, on the basis of constructing the miscellaneous gas evaluation model, in order to evaluate the tobacco leaves to be evaluated, the physical characteristic data of the tobacco leaves to be evaluated are firstly obtained, then the physical characteristic data are converted, the obtained six comprehensive indexes are directly input into the miscellaneous gas evaluation model, and then the corresponding miscellaneous gas scoring result can be obtained, so that the miscellaneous gas in the smoke of the tobacco leaves to be evaluated can be simply and quickly evaluated. The method omits the tobacco leaf rolling link, and simultaneously, professional smoke panel evaluation personnel do not need to evaluate miscellaneous gas through sensory evaluation, so that the defects of long time consumption, professional dependence and the like are overcome; in addition, the invention does not need to use chemicals to measure the chemical components, does not damage the sample, does not pollute the environment, and has the advantages of simple operation, reagent saving, short time, low cost, no pollution and the like.
Furthermore, in order to simply and quickly obtain the miscellaneous gas evaluation model, the miscellaneous gas evaluation model is constructed by adopting a support vector machine.
Further, in order to make the six comprehensive indexes obtained by the conversion process include information included in each physical characteristic data before the conversion process, the conversion process is:
Y1=k11X1+k12X2+k13X3+k14X4+k15X5+k16X6+k17
Y2=k21X1+k22X2+k23X3+k24X4+k25X5+k26X6+k27
Y3=k31X1+k32X2+k33X3+k34X4+k35X5+k36X6+k37
Y4=k41X1+k42X2+k43X3+k44X4+k45X5+k46X6+k47
Y5=k51X1+k52X2+k53X3+k54X4+k55X5+k56X6+k57
Y6=k61X1+k62X2+k63X3+k64X4+k65X5+k66X6+k67
wherein, Y1、Y2、Y3、Y4、Y5、Y6Is six comprehensive indexes after conversion treatment; x1、X2、X3、X4、X5、X6Respectively carrying out thickness, filling value, tension, stem content, balanced water content and leaf surface density before conversion treatment; k is a radical of11、k12、k13、k14、k15、k16、k17、k21、k22、k23、k24、k25、k26、k27、k31、k32、k33、k34、k35、k36、k37、k41、k42、k43、k44、k45、k46、k47、k51、k52、k53、k54、k55、k56、k57、k61、k62、k63、k64、k65、k66And k67Are all conversion coefficients.
Further, the coefficient k is converted11=30.566,k12=-0.0992,k13=-0.02534,k14=-0.002913,k15=0.2667,k16=-0.05711,k17=-2.509,k21=6.254,k22,=1.255,k23=2.273,k24=0.002073,k25=0.7487,k26=-0.03147,k27=-15.937,k31=5.94,k32=-0.1258,k33=1.522,k34=-0.2746,k35=0.09892,k36=0.01469,k37=3.441,k41=16.399,k42=0.5262,k43=-0.4426,k44=-0.2115,k45=-0.2839,k46=-0.06018,k47=15.168,k51=-11.353,k52=-2.293,k53=-1.393,k54=-0.07207,k55=0.7193,k56=-0.01022,k57=5.69,k61=-4.486,k62=-2.637,k63=1.915,k64=0.05614,k65=-0.4199,k66=-0.02424,k67=13.287。
Drawings
FIG. 1 is a flow chart of a method of evaluating miscellaneous gases in a flue gas of the present invention;
FIG. 2 is a proportion diagram of plus or minus 0.5 between the evaluation value and the actual value of the miscellaneous gas in the modeling result of the invention;
FIG. 3 is a proportion diagram of plus or minus 0.4 between the evaluation value and the actual value of the miscellaneous gas in the modeling result of the invention;
FIG. 4 is a proportion diagram of plus or minus 0.5 between the evaluation value and the actual value of miscellaneous qi according to the prediction result of the present invention;
FIG. 5 is a ratio diagram of plus or minus 0.4 between the evaluation value and the actual value of miscellaneous qi according to the prediction result of the present invention.
Detailed Description
According to the invention, researches show that the physical characteristics (such as thickness, filling value, tension, stem percentage, equilibrium water content, leaf surface density and the like) of the tobacco leaves are related to the miscellaneous gas, and according to the phenomenon, the invention constructs a miscellaneous gas evaluation model, and the model is utilized to quickly, accurately, cheaply and simply evaluate the miscellaneous gas in the smoke.
The flow of the embodiment of the method for evaluating miscellaneous gases in flue gas is shown in figure 1, and the process is as follows:
firstly, 796 tobacco leaf samples of different producing areas are collected, and indexes such as the balance moisture content, filling value, thickness, tensile force, leaf surface density and stem content of the samples are quantitatively detected to obtain physical characteristic data of the tobacco leaf samples, wherein the physical characteristic data are shown in table 1 (only part of data are shown).
TABLE 1 tobacco leaf physical Property data
Thickness (mm) | Filling value (cm)3/g) | Pulling force (N) | Cut-off percentage (%) | Equilibrium moisture content (%) | Leaf area Density (g/m)2) |
0.082 | 4.84 | 1.33 | 31.398 | 12.129 | 75.243 |
0.086 | 3.73 | 1.951 | 29.752 | 11.778 | 71.08 |
0.076 | 3.27 | 2.099 | 36.036 | 13.573 | 72.848 |
0.068 | 3.68 | 2.004 | 31.566 | 12.961 | 70.723 |
0.111 | 4.75 | 1.728 | 36.424 | 12.618 | 66.2 |
0.055 | 3.45 | 1.64 | 32.586 | 12.621 | 64.055 |
0.098 | 4.17 | 1.55 | 29.293 | 11.631 | 70.12 |
0.102 | 4.14 | 1.154 | 32.372 | 11.038 | 68.169 |
0.085 | 3.54 | 1.489 | 34.708 | 12.055 | 71.276 |
0.088 | 3.9 | 1.839 | 28.155 | 12.861 | 80.056 |
And step two, utilizing smoke panel evaluators to evaluate the tobacco leaf samples to obtain a miscellaneous gas evaluation result. In this example, the highest score was 9 points and the lowest score was 0 points, and the higher the score result of miscellaneous gas was, the less the miscellaneous gas content was. The miscellaneous gas scoring result can be refined to a small number, for example, the miscellaneous gas scoring can be 3.5 points, 4.6 points, and the like.
And step three, substituting the physical characteristic data of the tobacco leaf sample in the step one into the following conversion equation to obtain six comprehensive indexes shown in the table 2 (only part of data is shown and corresponds to the table 1). The conversion equation is as follows:
Y1=30.566X1-0.0992X2-0.02534X3-0.002913X4+0.2667X5-0.05711X6-2.509
Y2=6.254X1+1.255X2+2.273X3+0.002073X4+0.7487X5-0.03147X6-15.937
Y3=5.94X1-0.1258X2+1.522X3-0.2746X4+0.09892X5+0.01469X6+3.441
Y4=-16.399X1+0.5262X2-0.4426X3-0.2115X4-0.2839X5-0.06018X6+15.168
Y5=-11.353X1-2.293X2-1.393X3-0.07207X4+0.7193X5-0.01022X6+5.69
Y6=-4.486X1-2.637X2+1.915X3+0.05614X4-0.4199X5-0.02424X6+13.287
wherein, Y1、Y2、Y3、Y4、Y5、Y6Is six comprehensive indexes obtained after conversion treatment; x1、X2、X3、X4、X5、X6The thickness, filling value, tensile force, stem percentage, equilibrium water content and leaf surface density before conversion treatment are respectively.
Table 2 six comprehensive indexes obtained by conversion
Y1 | Y2 | Y3 | Y4 | Y5 | Y6 |
-1.6703 | -0.5721 | -0.9753 | 1.1697 | -2.5028 | -2.4501 |
-1.3038 | -0.7148 | 0.4891 | 0.9424 | -0.9534 | 1.8037 |
-1.2091 | 0.4087 | -0.8065 | -1.1467 | 0.831 | 2.9033 |
-1.5204 | 0.3566 | 0.0845 | 0.4896 | 0.0154 | 1.7346 |
-0.1532 | 0.6996 | -1.6494 | -0.1881 | -3.0963 | -1.2816 |
-1.5983 | -0.7197 | -0.9308 | 1.0248 | 0.9485 | 2.057 |
-0.9537 | -1.2294 | -0.0087 | 1.3518 | -1.6053 | -0.1222 |
-0.8741 | -2.5677 | -1.5181 | 1.0803 | -1.6582 | -0.3571 |
-1.256 | -1.7846 | -1.5271 | -0.0751 | -0.0219 | 1.5745 |
-1.4764 | -0.2437 | 0.9881 | 0.5395 | -0.4099 | 0.3724 |
-1.6703 | -0.5721 | -0.9753 | 1.1697 | -2.5028 | -2.4501 |
-1.3038 | -0.7148 | 0.4891 | 0.9424 | -0.9534 | 1.8037 |
And step four, taking six comprehensive indexes of 796 tobacco leaf samples as input, taking the miscellaneous gas grading result of the 796 tobacco leaf samples as output, training a support vector machine model by using the data, and obtaining a miscellaneous gas evaluation model after training. In the construction process of the support vector machine, the penalty factor of the selected radial basis kernel function is 10, and the insensitive function is selected to be 0.05. After the modeling is finished, the proportion of the difference between the evaluation value of the miscellaneous gas and the actual value plus or minus 0.5 in the modeling result is 92.45 percent, as shown in figure 2; the proportion of the difference between the evaluation value of miscellaneous gases and the actual value plus or minus 0.4 is 88.80%. As shown in fig. 3. Thus, the construction of the miscellaneous gas evaluation model is completed.
Acquiring physical characteristic data of the tobacco leaves to be evaluated, and performing conversion processing on the physical characteristic data to obtain physical characteristic data after conversion processing, namely six comprehensive indexes; and inputting the physical characteristic data after the conversion treatment into the miscellaneous gas evaluation model constructed in the fourth step to obtain a miscellaneous gas evaluation result corresponding to the physical characteristic data after the conversion treatment.
The accuracy of the miscellaneous gas evaluation model is further verified by comparing the miscellaneous gas evaluation value (obtained through the miscellaneous gas evaluation model) of the independent sample with the actual value (the scoring result of the evacuee). Wherein, the ratio of the difference between the evaluation value and the actual value of the miscellaneous gases in the flue gas of the forecast result, plus or minus 0.5, is 90.95%, as shown in fig. 4; the ratio of positive and negative 0.4 in the difference between the evaluation value and the actual value of the miscellaneous gases in the flue gas as a result of the prediction is 81.41%, as shown in fig. 5. Further proving the accuracy of the miscellaneous gas evaluation model.
It should be noted that the method converts the physical characteristic data, and the converted physical characteristic data is the combination of the physical characteristic data before conversion, so that the information content of the six comprehensive indexes is large, and the method is greatly helpful for establishing a more accurate miscellaneous gas evaluation model subsequently.
According to the method for evaluating the miscellaneous gas in the flue gas, after the miscellaneous gas evaluation model is constructed, six comprehensive indexes of the tobacco leaves to be evaluated are directly input into the miscellaneous gas evaluation model, and the method is simple and rapid; and the method does not need to use chemicals to determine chemical components, does not damage samples, does not pollute the environment, is simple to operate, saves reagents, and has short time, low cost and no pollution.
Claims (4)
1. A method for evaluating miscellaneous gases in flue gas is characterized by comprising the following steps:
acquiring physical characteristic data of the tobacco leaves to be evaluated, and performing conversion treatment on the physical characteristic data to enable six comprehensive indexes obtained after the conversion treatment to be related to the physical characteristic data before each conversion treatment; the physical property data includes the following six kinds: thickness, filling value, tension, stem content, balanced water content and leaf surface density;
inputting the six comprehensive indexes into a constructed miscellaneous gas evaluation model to obtain miscellaneous gas scoring results corresponding to the six comprehensive indexes; the miscellaneous gas evaluation model is obtained by training six comprehensive indexes of evaluated tobacco leaves and corresponding evaluation results after smoking of the tobacco leaves.
2. The method for evaluating miscellaneous gases in flue gas according to claim 1, wherein the miscellaneous gas evaluation model is constructed by a support vector machine.
3. The method for evaluating miscellaneous gases in flue gases according to claim 1, wherein the conversion treatment is:
Y1=k11X1+k12X2+k13X3+k14X4+k15X5+k16X6+k17
Y2=k21X1+k22X2+k23X3+k24X4+k25X5+k26X6+k27
Y3=k31X1+k32X2+k33X3+k34X4+k35X5+k36X6+k37
Y4=k41X 1+k42X2+k43X3+k44X4+k45X5+k46X6+k47
Y5=k51X1+k52X2+k53X3+k54X4+k55X5+k56X6+k57
Y6=k61X1+k62X2+k63X3+k64X4+k65X5+k66X6+k67
wherein, Y1、Y2、Y3、Y4、Y5、Y6Is six comprehensive indexes obtained after conversion treatment; x1、X2、X3、X4、X5、X6Respectively carrying out thickness, filling value, tension, stem content, balanced water content and leaf surface density before conversion treatment; k is a radical of11、k12、k13、k14、k15、k16、k17、k21、k22、k23、k24、k25、k26、k27、k31、k32、k33、k34、k35、k36、k37、k41、k42、k43、k44、k45、k46、k47、k51、k52、k53、k54、k55、k56、k57、k61、k62、k63、k64、k65、k66And k67Are all conversion coefficients.
4. The method for evaluating miscellaneous gases in flue gases according to claim 3, wherein the conversion coefficient k is11=30.566,k12=-0.0992,k13=-0.02534,k14=-0.002913,k15=0.2667,k16=-0.05711,k17=-2.509,k21=6.254,k22,=1.255,k23=2.273,k24=0.002073,k25=0.7487,k26=-0.03147,k27=-15.937,k31=5.94,k32=-0.1258,k33=1.522,k34=-0.2746,k35=0.09892,k36=0.01469,k37=3.441,k41=16.399,k42=0.5262,k43=-0.4426,k44=-0.2115,k45=-0.2839,k46=-0.06018,k47=15.168,k51=-11.353,k52=-2.293,k53=-1.393,k54=-0.07207,k55=0.7193,k56=-0.01022,k57=5.69,k61=-4.486,k62=-2.637,k63=1.915,k64=0.05614,k65=-0.4199,k66=-0.02424,k67=13.287。
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Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113945563A (en) * | 2021-10-19 | 2022-01-18 | 中国烟草总公司湖北省公司 | Method for evaluating quality uniformity of cigar wrapper tobacco leaves |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102981409A (en) * | 2012-12-11 | 2013-03-20 | 富通集团有限公司 | Method for optimizing operation of coaxial cable sheathing machine |
CN107403188A (en) * | 2017-06-28 | 2017-11-28 | 中国农业大学 | A kind of quality evaluation method and device |
CN107767946A (en) * | 2017-09-26 | 2018-03-06 | 浙江工业大学 | Breast cancer diagnosis system based on PCA (principal component analysis) and PSO-KE (particle swarm optimization-Key) L M (model-based regression) models |
CN109461025A (en) * | 2018-10-23 | 2019-03-12 | 国网湖南省电力公司节能管理分公司 | A kind of electric energy substitution potential customers' prediction technique based on machine learning |
CN110414821A (en) * | 2019-07-22 | 2019-11-05 | 中国农业科学院烟草研究所 | A kind of cured tobacco leaf quality overall evaluation method based on safety indexes |
-
2020
- 2020-11-17 CN CN202011286237.2A patent/CN112485372A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102981409A (en) * | 2012-12-11 | 2013-03-20 | 富通集团有限公司 | Method for optimizing operation of coaxial cable sheathing machine |
CN107403188A (en) * | 2017-06-28 | 2017-11-28 | 中国农业大学 | A kind of quality evaluation method and device |
CN107767946A (en) * | 2017-09-26 | 2018-03-06 | 浙江工业大学 | Breast cancer diagnosis system based on PCA (principal component analysis) and PSO-KE (particle swarm optimization-Key) L M (model-based regression) models |
CN109461025A (en) * | 2018-10-23 | 2019-03-12 | 国网湖南省电力公司节能管理分公司 | A kind of electric energy substitution potential customers' prediction technique based on machine learning |
CN110414821A (en) * | 2019-07-22 | 2019-11-05 | 中国农业科学院烟草研究所 | A kind of cured tobacco leaf quality overall evaluation method based on safety indexes |
Non-Patent Citations (6)
Title |
---|
刘阳等: "环秦岭区域烤烟物理特性及其与评吸质量的关系", 《福建农林大学学报(自然科学版)》 * |
常安然等: "基于烤烟理化指标构建烤烟感官质量预测模型", 《江西农业学报》 * |
王娟等: "烟叶抗张强度与烟叶质量评价指标的关系研究", 《科技资讯》 * |
薛超群等: "烤烟烟叶物理特性的变化及其与评吸质量的关系", 《烟草科技》 * |
邓小华等: "烟叶质量评价指标间的典型相关分析", 《中国烟草学报》 * |
郭东锋等: "烟叶平衡含水率与感官质量关系研究", 《湖南文理学院学报(自然科学版)》 * |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113945563A (en) * | 2021-10-19 | 2022-01-18 | 中国烟草总公司湖北省公司 | Method for evaluating quality uniformity of cigar wrapper tobacco leaves |
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