CN104297161B - Method and system for evaluating product color used for reconstituted tobacco production by papermaking method - Google Patents

Method and system for evaluating product color used for reconstituted tobacco production by papermaking method Download PDF

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CN104297161B
CN104297161B CN201410414931.6A CN201410414931A CN104297161B CN 104297161 B CN104297161 B CN 104297161B CN 201410414931 A CN201410414931 A CN 201410414931A CN 104297161 B CN104297161 B CN 104297161B
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CN104297161A (en
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周栋
严新龙
张克娟
李新生
张大坤
葛金元
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SHANGHAI TOBACCO GROUP TAICANG HAIYAN TOBACCO RECONSTITUTED TOBACCO CO Ltd
Shanghai Tobacco Group Co Ltd
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SHANGHAI TOBACCO GROUP TAICANG HAIYAN TOBACCO RECONSTITUTED TOBACCO CO Ltd
Shanghai Tobacco Group Co Ltd
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Abstract

The invention provides a method and a system for evaluating product color used for reconstituted tobacco production by a papermaking method. The method is characterized in that front and back surfaces of a sample in several samples to be detected is taken out in on-site produced tobacco leaf, luminance value, red-green value and yellow-blue value on the front and back surfaces can be obtained, after determining the brightness mean value, red-green mean value and yellow-blue mean value on the front and back surfaces of the sample to be detected, then the mean values are respectively compared with the corresponding mean values of the respective front and back surfaces of several contrast sample groups, brightness, red-green fluctuation limit absolute value and yellow-blue fluctuation limit absolute value of the sample to be detected and front and back surfaces of each contrast sample group are determined, unqualified parameter information of the front and back surfaces of the sample to be detected and the front and back surfaces of each contrast sample group are determined based on the front-back brightness, red-green fluctuation threshold and yellow-blue fluctuation threshold, finally color of the sample to be detected is evaluated based on the contrast sample group and the unqualified parameter information of the front and back surfaces, and then the color of the front and back surfaces colors of the on-site produced tobacco leaf can be evaluated.

Description

Product color judging method and system for paper-making reconstituted tobacco production
Technical Field
The invention relates to the field of tobacco leaf detection, in particular to a method and a system for judging product color in paper-making reconstituted tobacco production.
Background
For a long time, the evaluation and judgment of the color of the paper-making reconstituted tobacco finished products are based on the evaluation requirements on the product color in the standard YC/T16.3-2003 reconstituted tobacco part 3 paper-making method, namely: the color is uniform, and the color is consistent with the standard sample specified by the contract. The visual sensory detection method as the only detection method for the color of the paper-making reconstituted tobacco leaves only remains in a qualitative level for checking the color of the paper-making reconstituted tobacco leaves, and has defects in objectivity and scientificity. In actual production, when a standard YC/T16.3-2003 reconstituted tobacco part 3 paper-making method is used for detecting, assessing and accepting products, detection result errors are large due to influence factors such as weather, sensory sensitivity differences, light and the like. In recent years, with the perfect combination of a CIE Lab color space model and a computer image processing technology, the appearance of a chromaticity and brightness instrument is promoted, and the method plays an important role in the aspect of quantitative detection and analysis of the colors of tobacco leaves and paper-making reconstituted tobacco leaves. The chromameter quantifies the color of a characterized sample by applying the CIE Lab color space model. In recent years, some documents and patents about the application of a chromaticity and brightness meter to the color detection of paper-making reconstituted tobacco leaves are provided, however, most of the documents only introduce a detection method and a detection result, only Chinese patent document CN101482493A 'a paper-making reconstituted tobacco leaf appearance color detection method', and introduce a product appearance color evaluation method, only the color difference of the front side and the back side of a product is not considered in the patent, only the color of one side of the product is evaluated, the color is not respectively detected and evaluated, and meanwhile, a sample to be detected in the evaluation method needs to be subjected to constant temperature and constant humidity treatment, and in research, the color of the sample subjected to constant temperature and constant humidity treatment is slightly different from that of a product produced on line on site, and the accuracy of the detection result is influenced to a certain extent.
In fact, at present, no complete set of finished product color judging method suitable for the production field of the paper-making reconstituted tobacco leaves exists. The method for quantitatively evaluating the color of the reconstituted tobacco by the paper-making method established in the production field has three difficulties: the method comprises the following steps of (1) because the tobacco raw materials for producing the paper-making reconstituted tobacco are unstable in source, the color difference of the raw materials among batches is large, and the color of a finished product is greatly influenced, so that the color of products with the same grade and different batches cannot be judged by using a fixed assessment value and a fluctuation range; (II) the product judgment parameters comprise three color parameters of the front side and the back side respectively, and the fluctuation of the three color parameters of the front side and the back side of the product in production may have differences, for example, two parameters of the front side of the product fluctuate on a certain day, one parameter of the back side fluctuates, the three parameters of the front side fluctuate on the next day, and only one parameter of the back side fluctuates, so the judgment standard needs to set requirements for various fluctuation combinations respectively; and (III) the feedback of data detection is delayed, the fluctuation stability of the product color cannot be reflected in time, the judgment center values of the product colors are counted after a batch of products are produced all the time, and the data feedback is delayed seriously.
In order to improve the scientificity of the product color judgment standard and meet the actual needs of enterprises, a new method suitable for judging the product color in the production of paper-making reconstituted tobacco is urgently needed to be established.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, the present invention provides a method and a system for evaluating color of a product in the production of paper-making reconstituted tobacco, so as to evaluate whether the color of the tobacco produced on site is qualified.
In order to achieve the above objects and other related objects, the present invention provides a method for judging product color in the production of paper-making reconstituted tobacco, which at least comprises: detecting the front and back surfaces of each of a plurality of samples to be detected extracted from tobacco leaves produced on site to obtain the brightness values, red-green values and yellow-blue values of the front and back surfaces, and further determining the brightness average value, red-green average value and yellow-blue average value of the front and back surfaces of the samples to be detected; determining the brightness, red-green color and yellow-blue fluctuation limit absolute values of the front and back sides of the sample to be detected and each group of comparison sample group based on the determined brightness average value, red-green average value and yellow-blue average value of the front and back sides of the sample to be detected and the determined brightness average value, red-green average value and yellow-blue average value of the front and back sides of the multiple groups of comparison sample groups; determining unqualified parameter information of the front and back sides of the sample to be detected and the front and back sides of each group of comparison sample groups based on the front and back side brightness, red and green and yellow and blue fluctuation threshold values and the brightness, red and green and yellow and blue fluctuation limit absolute values between the front and back sides of the sample to be detected and each group of comparison sample groups; and determining whether the color of the sample to be detected is qualified or not based on the number of the groups of the comparison samples and the information of the unqualified parameters of the front and the back of the sample to be detected and the front and the back of each group of the comparison samples.
The invention also provides a product color judgment system for the production of paper-making reconstituted tobacco, which at least comprises the following components: the acquisition module is used for detecting the front and back surfaces of each of a plurality of samples to be detected extracted from tobacco leaves produced on site so as to obtain the brightness values, red-green values and yellow-blue values of the front and back surfaces, and further determine the brightness average value, red-green average value and yellow-blue average value of the front and back surfaces of the samples to be detected; the calculation module is used for determining the brightness, red-green color and yellow-blue fluctuation limit absolute values of the front and back surfaces of the sample to be detected and each group of comparison sample group based on the determined brightness average value, red-green average value and yellow-blue average value of the front and back surfaces of the sample to be detected and the determined brightness average value, red-green average value and yellow-blue average value of the front and back surfaces of the multiple groups of comparison sample groups; the comparison module is used for determining the unqualified parameter information of the front and back sides of the sample to be detected and the front and back sides of each group of comparison sample groups based on the front and back side brightness, red and green and yellow and blue fluctuation threshold values and the brightness, red and green and yellow and blue fluctuation limit absolute values between the sample to be detected and the front and back sides of each group of comparison sample groups; and the judging module is used for comprehensively determining whether the color of the sample to be detected is qualified or not based on the number of the groups of the comparison samples and the unqualified parameter information of the front and back surfaces of the sample to be detected and the front and back surfaces of each group of the comparison samples.
As mentioned above, the method and the system for judging the product color in the production of the paper-making reconstituted tobacco have the following beneficial effects: the color of the tobacco leaves produced in the current production site can be effectively detected to be qualified; the front and back colors of the tobacco leaves can be detected; in addition, the sample to be detected is a sample directly taken from a production field, and only needs to be placed in a sealed bag for storage, and does not need to be subjected to constant temperature and humidity treatment.
Drawings
FIG. 1 shows a flow chart of the product color evaluation method for the paper-making reconstituted tobacco production of the invention.
FIG. 2 is a schematic diagram of a product color evaluation system for use in the production of paper-making reconstituted tobacco according to the present invention.
Description of the element reference numerals
1 product color judging system
11 acquisition module
12 calculation module
13 comparison module
14 judging module
S1-S4
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention.
Please refer to fig. 1-2. It should be noted that the drawings provided in the present embodiment are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
As shown in figure 1, the invention provides a product color judging method for paper-making reconstituted tobacco production. The method according to the present invention is mainly accomplished by a product color evaluation system in a computer device, including but not limited to an application module, an operating system, a process controller, etc. installed in the computer device and capable of implementing the solution of the present invention. Wherein the computer device includes but is not limited to: computers, network servers, etc.
Wherein, the method of the invention at least comprises steps S1 to S4.
In step S1, the product color evaluation system detects front and back surfaces of each of a plurality of samples to be tested extracted from field-produced tobacco leaves to obtain brightness values, red-green values, and yellow-blue values of the front and back surfaces, and further calculates a brightness average value, a red-green average value, and a yellow-blue average value of the samples to be tested.
It should be noted that, in the method, a CIE Lab color space model is used to quantitatively represent the color of the sample, the CIE Lab color space model is a set of color-describing data model that converts the light wavelength into the brightness and hue according to the characteristics of human vision, wherein L describes the color range from black to white, L shows a value of 0 to show black and a value of 100 to show white, and the brightness gradually increases as the value of L increases from 0 to 100; a describes the range of colors from green to red, a shows that red appears in positive values and green appears in negative values; b describes the range of colors from blue to yellow, b shows yellow in positive values and blue in negative values; one color in the CIELab color space cannot be both blue and yellow, or both red and green at the same time, so a CIE Lab single number can be used to describe the red/green and yellow/blue characteristics.
Specifically, multiple pieces, for example, 10 pieces of samples to be tested are randomly extracted from the finished tobacco leaves produced on site, sealed in a sealed bag, and inspected by a chromameterMeasuring the brightness value L of the front and back color of each sample to be measuredIs just、LInverse directionRed green value aIs just、aInverse directionYellow-blue value bIs just、bInverse directionThe product color evaluation system obtains the detection result of the chroma brightness instrument and calculates the average brightness value of the front and back surfaces of the sample to be detected based on the following formulaAverage of red and greenAverage value of yellow and blue
Wherein n is the number of samples to be detected.
In step S2, the product color evaluation system determines the absolute values of the fluctuation limits of the brightness, the red-green color, and the yellow-blue color of the front and back sides of the sample to be tested and each of the comparison sample groups based on the determined average value of the brightness, the average value of the red-green color, and the average value of the yellow-blue color of the front and back sides of the sample to be tested, and the average value of the brightness, the average value of the red-green color, and the average value of the yellow-blue color of the front.
It should be noted that, because the number of sets of the comparison samples is different, the evaluation result is greatly influenced, the smaller the number of sets of the comparison samples is, the greater the contribution degree of the sample to be detected and the comparison sample to the whole color difference after being mixed, and conversely, the greater the number of sets of the comparison samples is, the smaller the contribution degree of the sample to be detected and the comparison sample to the whole color difference after being mixed is. Therefore, in order to improve the accuracy of the judgment, it is preferable that the number of sets of the comparative samples should be not less than 6; i.e. the sample to be tested must be colour-compared at least with the six days or groups of products it had previously been produced.
Specifically, the product color evaluation system calculates the absolute value Δ L of the brightness fluctuation limit of the front surface of the comparison sample group of the sample to be measured and each group based on the following formulaIs justAbsolute value of brightness fluctuation limit DeltaL of back surfaceInverse directionPositive red and green color fluctuation limit absolute value delta aIs justRed and green color fluctuation limit absolute value delta a of the reverse sideInverse directionPositive yellow-blue fluctuation limit absolute value delta bIs justYellow-blue fluctuation limit absolute value delta b of the reverse sideInverse direction：
Wherein,respectively the average value of the front brightness, the average value of the back brightness, the average value of the red and green of the front, the average value of the red and green of the back, the average value of the yellow and blue of the front and the average value of the yellow and blue of the back of the kth group comparison sample group;the average brightness value of the front surface, the average brightness value of the back surface, the average red and green color value of the front surface, the average red and green color value of the back surface, the average yellow and blue color value of the front surface and the average yellow and blue color value of the back surface of the sample to be detected are respectively.
For example, the product color evaluation system calculates the fluctuation limit absolute values of the brightness L, the red-green color a, and the yellow-blue color b of the front and back sides of the sample a1 and each group of comparison sample group P1 based on the average brightness value, the red-green average value, and the yellow average value of the front and back sides of the sample a1 to be tested, and the average brightness value, the red-green average value, and the average value of the front and back sides of the 7 group of comparison sample group P1 as shown in the following tables 1a and 1b, respectively:
table 1a (front):
table 1b (reverse):
for another example, the product color evaluation system calculates the absolute values of the fluctuation limits of the brightness L, the red-green color a, and the yellow-blue color b of the front and back sides of the sample a2 and each group of the comparative sample group P2 based on the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the sample group a2, and the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the 7 group of comparative sample group P2 as shown in the following tables:
table 2a (front):
table 2b (reverse):
for another example, the product color evaluation system calculates the absolute values of the fluctuation limits of the brightness L, the red-green color a, and the yellow-blue color b of the front and back sides of the sample A3 and each group of the comparative sample group P3 based on the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the sample A3, and the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the 7 group of comparative sample group P3 as shown in the following tables:
table 3a (front):
table 3b (reverse):
for another example, the product color evaluation system calculates the absolute values of the fluctuation limits of the brightness L, the red-green color a, and the yellow-blue color b of the front and back sides of the sample a4 and each group of the comparative sample group P4 based on the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the sample a4, and the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the 7 group of comparative sample group P4 as shown in the following tables:
table 4a (front):
table 4b (reverse):
for another example, the product color evaluation system calculates the absolute values of the fluctuation limits of the brightness L, the red-green color a, and the yellow-blue color b of the front and back sides of the sample a5 and each group of the comparative sample group P5 based on the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the sample a5, and the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the 7 group of comparative sample group P5 as shown in the following tables:
table 5a (front):
table 5b (reverse):
next, in step S3, the product color evaluation system determines the unqualified parameter information of the front and back sides of the sample to be tested and the front and back sides of each group of comparison sample groups based on the front and back side brightness, red and green and yellow blue fluctuation threshold values and the brightness, red and green and yellow blue fluctuation limit absolute values between the front and back sides of the sample to be tested and each group of comparison sample groups.
The fluctuation threshold values of the front-back brightness, the red-green color and the yellow-blue color are shown in the following table 6:
table 6:
parameter(s) Threshold value of brightness fluctuation Red and green color fluctuation threshold Yellow-blue fluctuation threshold
Front side ≤2.66 ≤1.53 ≤2.55
Back side of the plate ≤2.70 ≤1.51 ≤2.62
For example, the product color evaluation system determines that the unqualified parameters of the front surface of the sample a1 to be tested and the comparison sample groups with the numbers 2 and 3 are both yellow-blue, and the front surface and the comparison sample groups with other numbers have no unqualified parameters based on the absolute values of the fluctuation limits of brightness, red-green color and yellow-blue color between the front surface and the back surface of the sample a1 to be tested and the P1 of each comparison sample group in table 6 and tables 1a and 1 b; the unqualified parameters of the reverse side of the sample A1 to be detected and the comparison sample groups with the numbers 1 and 3 are red and green, and the reverse side of the sample A1 has no unqualified parameters with the comparison sample groups with other numbers.
For another example, the product color evaluation system determines that the unqualified parameters of the front surface of the sample a2 to be measured and the comparison sample group with the number of 1 are brightness and yellow blue, the unqualified parameters of the front surface and the comparison sample group with the number of 3 are red, green and yellow blue, and the front surface and the comparison sample groups with other numbers have no unqualified parameters based on the absolute values of the fluctuation limits of brightness, red, green and yellow blue between the front surface and the front surface of the sample a2 to be measured and the front surface of each comparison sample group P2 in table 6 and tables 2a and 2 b; the unqualified parameters of the back surface of the sample A2 to be tested and the comparison sample groups with the numbers 1 and 3 are brightness and red-green color, and the unqualified parameters of the back surface and the comparison sample groups with other numbers are not unqualified parameters.
For another example, the product color evaluation system determines that the unqualified parameters of the front surface of the sample A3 to be tested and the comparison sample groups with numbers 4 and 7 are brightness, red, green and yellow blue, and the front surface and the comparison sample groups with other numbers have no unqualified parameters based on the absolute values of the fluctuation limits of brightness, red, green and yellow blue between the front surface and the back surface of the sample A3 to be tested and the front surface and the back surface of each comparison sample group P3 in table 6 and tables 3a and 3 b; the unqualified parameters of the back surface of the sample A3 to be tested and the comparison sample groups with the numbers 4 and 5 are brightness, red, green and yellow blue, and the unqualified parameters of the back surface and the comparison sample groups with other numbers are not unqualified.
For another example, the product color evaluation system determines that the failure parameters of the front surface of the sample a4 to be measured and the reference sample group with the number of 1 are red and green, the failure parameters of the front surface and the reference sample group with the number of 5 are brightness and red and green, and the front surface and the reference sample groups with other numbers have no failure parameters based on the absolute values of the fluctuation limits of brightness, red and green, and yellow and blue between the front surface of the sample a4 to be measured and the front surface of each pair of reference sample groups P4 in table 6 and tables 4a and 4 b; the unqualified parameters of the back surface of the sample A4 to be tested and the comparison sample groups with the numbers 1 and 5 are brightness and red-green color, the unqualified parameters of the comparison sample group with the number 3 are red-green color, and the back surface of the sample A4 has no unqualified parameters with the comparison sample groups with other numbers.
For another example, the product color evaluation system determines that the failure parameters of the front face of the sample a5 to be measured and the reference sample group numbered 1 are luminance, the failure parameters of the front face and the reference sample group numbered 3 are luminance and red-green color, the failure parameters of the front face and the reference sample group numbered 4 are luminance and yellow-blue color, the failure parameters of the front face and the reference sample group numbered 5 are luminance, red-green color and yellow-blue color, and the failure parameters of the front face and the reference sample group numbered 5 have no failure parameters based on the absolute values of the fluctuation limits of luminance, red-green color and yellow-blue color between the front face of the sample a5 to be measured and the front face of each comparison sample group P5 in table 6 and tables 5a and 5b described above; the unqualified parameters of the back surface of the sample A5 to be detected and the comparison sample groups with the numbers 1 and 3 are brightness, red-green and yellow-blue, the unqualified parameters of the back surface and the comparison sample group with the number 5 are brightness and red-green, the unqualified parameters of the back surface and the comparison sample group with the number 7 are yellow-blue, and the back surface and the comparison sample groups with other numbers have no unqualified parameters.
Next, in step S4, the product color evaluation system determines whether the color of the sample to be tested is qualified based on the number of sets of the comparison samples and the information of the parameters of the obverse and reverse sides of the sample to be tested and the obverse and reverse sides of each set of the comparison samples.
In the detection and statistics of the samples, the number of allowable failure parameters is different with the group number of the comparative sample groups under the requirement of visual allowable color difference. For example, one group of samples X1 to be tested and each comparative sample group have only the same 1 unqualified parameter, the other group of samples X2 to be tested and each comparative sample group have 3 unqualified parameters, in the R group of comparative sample groups, if the number of the comparative sample groups having the same 1 unqualified parameter as that of sample X1 to be tested is R1, and the number of the comparative sample groups having the same 3 unqualified parameters as that of sample X2 is also R1, two groups of products obtained by mixing the samples X1 and X2 to be tested with the same comparative sample group respectively will have a large difference in overall color, and therefore, whether the color of the sample to be tested is qualified or not should be determined based on the number of the unqualified parameters and the number of the comparative sample groups, preferably, as shown in table 7 below:
table 7:
specifically, when the unqualified parameters of one surface of the sample to be measured are the same as those of the corresponding surfaces of different comparison sample groups, the product color evaluation system determines a threshold range based on the number of the unqualified parameters of one comparison sample group having the unqualified parameters with the sample to be measured and the group number of the comparison sample groups, and determines whether the surface color of the sample to be measured is qualified or not based on whether the group number of the comparison sample group having the unqualified parameters with the sample to be measured is within the determined threshold range or not.
For example, the product color evaluation system determines that the number of sets of the comparison sample group having 1 failure parameter with the front surface of the sample to be measured is 2 and the number of sets of the comparison sample group having 1 failure parameter with the back surface of the sample to be measured is 2 based on that the failure parameters of the front surface of the sample to be measured and the comparison sample groups numbered 2 and 3 are all yellow-blue and the failure parameters of the back surface of the sample to be measured and the comparison sample groups numbered 1 and 3 are all red-green, further, based on the number of groups of 7 for the comparative sample and 1 failure parameter, the threshold range was determined to be 4 or less from column 3 of line 3 of Table 7, based on the fact that the number of the sets of the comparison sample sets with 1 unqualified parameter on the front side is 2 and the number of the sets of the comparison sample sets with 1 unqualified parameter on the back side is 2, the color of the front side and the color of the back side of the sample A1 to be detected are judged to be qualified within the threshold range of less than or equal to 4, and then the color of the sample A1 to be detected is judged to be qualified.
For another example, the product color evaluation system determines that the number of sets of the comparison sample group having 3 defective parameters with the front surface of the sample to be tested is 2 and the number of sets of the comparison sample group having 3 defective parameters with the back surface is 2 based on the defective parameters of the front surface of the sample to be tested and the reference sample groups having numbers 4 and 7 are both luminance, red green and yellow blue, and determines that the threshold range is not more than 1 from column 3 of row 5 of table 7 based on the number of sets of the comparison sample group having 3 defective parameters with the front surface of the sample to be tested is 2 and the number of sets of the comparison sample group having 3 defective parameters with the back surface is 2 based on the number of sets of the comparison sample group having 3 defective parameters with the front surface of the sample to be tested is not more than 1, and determines that the colors of the front surface and the back surface of the sample to be tested are not more than 1 based on the number of sets of the comparison sample group having 3 defective parameters with the back surface of the comparison sample group being not more than 2, further, the sample a3 was judged to have a failed color.
Specifically, when the unqualified parameters of one surface of the sample to be measured are different from the corresponding surfaces of different comparison sample groups, but the numbers of the unqualified parameters are the same, the product color evaluation system determines a threshold range based on the number of the unqualified parameters of one comparison sample group having the unqualified parameters with the sample to be measured and the number of the comparison sample groups, and then determines whether the color of the surface of the sample to be measured is qualified or not based on whether the number of the comparison sample groups having the unqualified parameters with the sample to be measured is within the determined threshold range or not.
For example, the product color evaluation system determines that the group number of the comparison sample group having 2 defective parameters with the front surface of the sample to be tested is 2, the group number of the comparison sample group having 2 defective parameters with the back surface is 2, and the threshold range is determined to be not more than 2 from column 3 of row 4 of table 7 based on the group number of the comparison sample group of 2 defective parameters with the front surface of the sample to be tested is 2, and the group number of the comparison sample group having 2 defective parameters with the back surface of the sample to be tested is 2 based on the group number of the comparison sample group having 2 defective parameters with the front surface of the sample to be tested is 2, and judging that the colors of the front side and the back side of the sample A2 to be detected are all qualified when the determined threshold range is less than or equal to 2, and further judging that the color of the sample A2 to be detected is qualified.
Specifically, if the unqualified parameters of one surface of the sample to be measured are different from the corresponding surfaces of different comparison sample groups, and the number of the unqualified parameters is different, the product color evaluation system determines the threshold value range respectively based on the number of the unqualified parameters of each comparison sample group having the unqualified parameters with the sample to be measured and the group number of the comparison sample group, and determines whether the surface color of the sample to be measured is qualified or not based on whether the group number of the comparison sample group having the same unqualified parameters with the sample to be measured is in the determined corresponding threshold value range or not.
For example, the product color evaluation system determines that the number of sets of the reference sample group having 1 and 2 defective parameters from the front side of the sample to be measured is 1, the number of sets of the reference sample group having 1 and 2 defective parameters from the back side of the sample to be measured is 1, the number of sets of the reference sample group having 1 defective parameter from the back side of the sample to be measured is 1, and the number of sets of the reference sample group having 2 defective parameters from the back side of the sample to be measured is 2, based on the number of sets of the reference sample group being 7 and 1 defective parameter, the threshold range is not more than 4 from column 3 of line 3 of table 7, the threshold range is determined from column 3 of line 4 of table 7 based on the number of sets of the reference sample group being 7 and 2 defective parameters from column 3 of line 4 of table 7 based on the number of sets of the reference sample group being 7 and the number of defective parameters being 2 And if the range is less than or equal to 2, the product color evaluation system judges that the color of the front surface and the back surface of the sample to be detected is qualified and further judges that the color of the sample to be detected is qualified based on the fact that the number of the groups of the comparison sample group with 1 unqualified parameter on the front surface of the sample to be detected is 1, the number of the groups of the comparison sample group with 1 unqualified parameter on the back surface of the sample to be detected is 2, and the number of the groups of the comparison sample group with 2 unqualified parameters on the back surface of the sample to be detected is 2, and further judges that the color of the sample to be detected is.
For another example, the product color evaluation system determines that the number of sets of the reference sample groups having 1 and 3 off-specification parameters from the front and the reference sample group having 1, the number of sets of the reference sample group having 2 off-specification parameters from the front of the test sample a5 is 2, the number of sets of the reference sample group having 1, the number of sets of the front and the reference sample group having 3 is luminance, the number of off-specification parameters from the front and the reference sample group having 4 is luminance and yellowish blue, the number of off-specification parameters from the front and the reference sample group having 5 is luminance, the number of red, green and yellowish blue, the number of off-specification parameters from the back and the reference sample group having 1 and 3 off-specification parameters from the front is luminance, the number of red, green and yellowish blue, the number of off-specification parameters from the back and the reference sample group having 5 is luminance and the number of red, the number of sets of the back and the reference sample group having 7 is yellowish blue, and determines that the number of sets of, The number of sets of the comparison sample groups with 1 and 2 unqualified parameters on the back surface of the sample to be tested is 1, the number of sets of the comparison sample groups with 3 unqualified parameters on the back surface of the sample to be tested is 2, the threshold range determined by the 3 rd column of the table 7 is less than or equal to 4 based on the number of sets of the comparison sample is 7 and 1 unqualified parameter, the threshold range determined by the 3 rd column of the 4 th column of the table 7 based on the number of sets of the comparison sample is less than or equal to 2 based on the number of sets of the comparison sample and the 2 unqualified parameters, the threshold range determined by the 3 rd column of the 5 th column of the table 7 is less than or equal to 1 based on the number of sets of the comparison sample groups with 1 unqualified parameter on the front surface of the sample to be tested and on the back surface of the comparison sample respectively, the number of sets of the comparison sample groups with 2 unqualified parameters on the front surface of the sample to be tested and on the back surface of the comparison sample are 2, the number of groups of comparison sample groups with 3 unqualified parameters on the front side of the sample to be detected is 1 within the determined threshold range of less than or equal to 2, the number of groups of comparison sample groups with 3 unqualified parameters on the back side of the sample to be detected is 2 within the determined threshold range of less than or equal to 1, the color of the front side of the sample to be detected A5 is judged to be qualified, the color of the back side of the sample to be detected is judged to be unqualified, and further, the color of the sample to be detected A5 is judged to be unqualified.
As shown in FIG. 2, the invention provides a product color evaluation system for use in the production of paper-making reconstituted tobacco. The product color evaluation system 1 includes at least: the device comprises an acquisition module 11, a calculation module 12, a comparison module 13 and an evaluation module 14.
The obtaining module 11 detects the front and back sides of each of a plurality of samples to be detected extracted from tobacco leaves produced on site to obtain the brightness values, red-green values and yellow-blue values of the front and back sides, and further determines the brightness average value, the red-green average value and the yellow-blue average value of the samples to be detected.
Specifically, a plurality of samples to be tested are randomly extracted from the finished tobacco leaves produced on site, for example, 10 samples to be tested are placed in a sealing bag to be sealed, and the brightness value L of the front and back side colors of each sample to be tested is detected by a chromameterIs just、LInverse directionRed green value aIs just、aInverse directionYellow-blue value bIs just、bInverse directionThe obtaining module 11 obtains the detection result of the chroma brightness meter, and calculates the average brightness value of the front and back sides of the sample to be detected based on the following formulaAverage of red and greenAverage value of yellow and blue
Wherein n is the number of samples to be detected.
The calculating module 12 determines the absolute values of the fluctuation limits of the brightness, the red-green color and the yellow-blue color of the front and the back of the sample to be measured and each group of comparison sample group based on the determined average value of the brightness, the average value of the red-green color and the average value of the yellow-blue color of the front and the back of the sample to be measured and the average value of the brightness, the average value of the red-green color and the average value of the yellow-blue color of the front and the.
It should be noted that, because the number of sets of the comparison samples is different, the evaluation result is greatly influenced, the smaller the number of sets of the comparison samples is, the greater the contribution degree of the sample to be detected and the comparison sample to the whole color difference after being mixed, and conversely, the greater the number of sets of the comparison samples is, the smaller the contribution degree of the sample to be detected and the comparison sample to the whole color difference after being mixed is. Therefore, in order to improve the accuracy of the judgment, it is preferable that the number of sets of the comparative samples should be not less than 6; i.e. the sample to be tested must be colour-compared at least with the six days or groups of products it had previously been produced.
Specifically, the calculating module 12 calculates the absolute value Δ L of the brightness fluctuation limit of the front surface of the comparison sample group of the sample to be measured and each group based on the following formulaIs justAbsolute value of brightness fluctuation limit of back surfaceΔLInverse directionPositive red and green color fluctuation limit absolute value delta aIs justRed and green color fluctuation limit absolute value delta a of the reverse sideInverse directionPositive yellow-blue fluctuation limit absolute value delta bIs justYellow-blue fluctuation limit absolute value delta b of the reverse sideInverse direction：
Wherein,respectively the average value of the front brightness, the average value of the back brightness, the average value of the red and green of the front, the average value of the red and green of the back, the average value of the yellow and blue of the front and the average value of the yellow and blue of the back of the kth group comparison sample group;the average brightness value of the front surface, the average brightness value of the back surface, the average red and green color value of the front surface, the average red and green color value of the back surface, the average yellow and blue color value of the front surface and the average yellow and blue color value of the back surface of the sample to be detected are respectively.
For example, the calculating module 12 calculates the absolute values of the fluctuation limits of the brightness L, the red-green color a, and the yellow-blue color b of the front and back sides of the sample a1 and each group of comparison sample group P1 based on the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the sample a1, and the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the 7 group of comparison sample group P1, as shown in the foregoing table 1.
For another example, the calculating module 12 calculates the absolute values of the fluctuation limits of the luminance L, the red-green color a, and the yellow-blue color b of the front and back sides of the sample a2 and each of the comparative sample groups P2 based on the average value of the luminance of the front and back sides, the average value of the red-green color, and the average value of the yellow-blue color of the sample a2, and the average value of the luminance of the front and back sides of the comparative sample group P2, the average value of the red-green color, and the average value of the yellow-blue color, respectively, as shown in the.
For another example, the calculating module 12 calculates the absolute values of the fluctuation limits of the brightness L, the red-green color a, and the yellow-blue color b of the front and back sides of the sample A3 and each group of the comparative sample group P3 based on the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the sample A3, and the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the 7 group of comparative sample groups P3, as shown in the foregoing.
For another example, the calculating module 12 calculates the absolute values of the fluctuation limits of the brightness L, the red-green color a, and the yellow-blue color b of the front and back sides of the sample a4 and each group of the comparative sample group P4 based on the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the sample a4, and the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the 7 group of comparative sample groups P4, as shown in the foregoing.
For another example, the calculating module 12 calculates the absolute values of the fluctuation limits of the brightness L, the red-green color a, and the yellow-blue color b of the front and back sides of the sample a5 and each group of the comparative sample group P5 based on the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the sample a5, and the average value of the brightness, the average value of the red-green, and the average value of the yellow-blue of the front and back sides of the 7 group of comparative sample groups P5, as shown in the foregoing.
Then, the comparison module 13 determines the unqualified parameter information of the front and back sides of the sample to be measured and the front and back sides of each group of comparison sample group based on the front and back side brightness, red and green and yellow and blue fluctuation threshold values and the brightness, red and green and yellow and blue fluctuation limit absolute values between the front and back sides of the sample to be measured and each group of comparison sample group.
The fluctuation threshold values of the front-back brightness, the red-green color and the yellow-blue color are shown in the following table 6:
table 6:
parameter(s) Threshold value of brightness fluctuation Red and green color fluctuation threshold Yellow-blue fluctuation threshold
Front side ≤2.66 ≤1.53 ≤2.55
Back side of the plate ≤2.70 ≤1.51 ≤2.62
For example, the comparing module 13 determines that the unqualified parameters of the front surface of the sample a1 to be tested and the comparison sample groups with the numbers 2 and 3 are both yellow-blue and the front surface has no unqualified parameter with the comparison sample groups with other numbers based on the absolute values of the fluctuation limits of brightness, red-green color and yellow-blue color between the front surface and the back surface of the sample a1 to be tested and the P1 of each comparison sample group with the numbers 2 and 3 in table 6 and tables 1a and 1 b; the unqualified parameters of the reverse side of the sample A1 to be detected and the comparison sample groups with the numbers 1 and 3 are red and green, and the reverse side of the sample A1 has no unqualified parameters with the comparison sample groups with other numbers.
For another example, the comparison module 13 determines that the failure parameters of the front surface of the sample a2 to be measured and the comparison sample group with the number of 1 are brightness and yellow blue, the failure parameters of the front surface and the comparison sample group with the number of 3 are red, green and yellow blue, and the front surface and the comparison sample groups with other numbers have no failure parameters based on the absolute values of the fluctuation limits of brightness, red, green and yellow blue between the front surface of the sample a2 to be measured and the front surface of each comparison sample group P2 in table 6 and tables 2a and 2 b; the unqualified parameters of the back surface of the sample A2 to be tested and the comparison sample groups with the numbers 1 and 3 are brightness and red-green color, and the unqualified parameters of the back surface and the comparison sample groups with other numbers are not unqualified parameters.
For another example, the comparing module 13 determines that the unqualified parameters of the front surface of the sample A3 and the comparison sample groups with numbers 4 and 7 are both brightness, red, green and yellow blue, and the front surface and the comparison sample groups with other numbers have no unqualified parameters based on the absolute values of the fluctuation limits of brightness, red, green and yellow blue between the front surface and the back surface of the sample A3 to be tested and the front surface and the back surface of each comparison sample group P3 in table 6 and tables 3a and 3 b; the unqualified parameters of the back surface of the sample A3 to be tested and the comparison sample groups with the numbers 4 and 5 are brightness, red, green and yellow blue, and the unqualified parameters of the back surface and the comparison sample groups with other numbers are not unqualified.
For another example, the comparison module 13 determines that the failure parameters of the front surface of the sample a4 to be measured and the comparison sample group with the number of 1 are red and green, the failure parameters of the front surface and the comparison sample group with the number of 5 are brightness and red and green, and the front surface and the comparison sample groups with other numbers have no failure parameters based on the absolute values of the fluctuation limits of brightness, red and green, and yellow and blue between the front surface of the sample a4 to be measured and the front surface of each comparison sample group P4 in table 6 and tables 4a and 4 b; the unqualified parameters of the back surface of the sample A4 to be tested and the comparison sample groups with the numbers 1 and 5 are brightness and red-green color, the unqualified parameters of the comparison sample group with the number 3 are red-green color, and the back surface of the sample A4 has no unqualified parameters with the comparison sample groups with other numbers.
For another example, the comparison module 13 determines that the failure parameters of the front face of the sample a5 to be measured and the comparison sample group with the number of 1 are luminance, the failure parameters of the front face and the comparison sample group with the number of 3 are luminance and red-green, the failure parameters of the front face and the comparison sample group with the number of 4 are luminance and yellow-blue, the failure parameters of the front face and the comparison sample group with the number of 5 are luminance, red-green and yellow-blue, and the front face and the comparison sample groups with other numbers have no failure parameters based on the absolute values of the fluctuation limits of luminance, red-green and yellow-blue between the front face of the sample a5 to be measured and the front face of the comparison sample group P5 in table 6 and tables 5a and 5 b; the unqualified parameters of the back surface of the sample A5 to be detected and the comparison sample groups with the numbers 1 and 3 are brightness, red-green and yellow-blue, the unqualified parameters of the back surface and the comparison sample group with the number 5 are brightness and red-green, the unqualified parameters of the back surface and the comparison sample group with the number 7 are yellow-blue, and the back surface and the comparison sample groups with other numbers have no unqualified parameters.
Then, the evaluation module 14 determines whether the color of the sample to be tested is qualified or not based on the number of the sets of the comparison samples and the information of the unqualified parameters of the front and back surfaces of the sample to be tested and the front and back surfaces of each set of the comparison samples.
In the detection and statistics of the samples, the number of allowable failure parameters is different with the group number of the comparative sample groups under the requirement of visual allowable color difference. For example, one group of samples X1 to be tested and each group of comparative samples have only the same 1 failing parameter, the other group of samples X2 to be tested and each group of comparative samples have 3 failing parameters, in the group R of comparative samples, if the number of the group of the comparative samples having the same 1 failing parameter as that of sample X1 to be tested is R1, and the number of the group of the comparative samples having the 3 failing parameters as that of sample X2 is also R1, the two groups of products obtained by mixing the samples X1, X2 to be tested and the group of the comparative samples have a large difference in overall color, and therefore, whether the color of the sample to be tested is qualified or not is determined based on the number of the failing parameters and the group number of the comparative samples, preferably, as shown in the following table 7:
table 7:
specifically, when the unqualified parameters of a surface of the sample to be tested are the same as those of the corresponding surfaces of different comparison sample groups, the evaluation module 14 determines a threshold range based on the number of the unqualified parameters of one comparison sample group having the unqualified parameters with the sample to be tested and the group number of the comparison sample groups, and determines whether the color of the surface of the sample to be tested is qualified based on whether the group number of the comparison sample group having the unqualified parameters with the sample to be tested is within the determined threshold range.
For example, the evaluation module 14 determines that the number of sets of the comparison sample group having 1 failure parameter with the front surface of the sample to be tested is 2 and the number of sets of the comparison sample group having 1 failure parameter with the back surface of the sample to be tested is 2 based on that the failure parameters of the front surface of the sample to be tested and the comparison sample groups numbered 2 and 3 are all yellow-blue and the failure parameters of the back surface of the sample to be tested and the comparison sample groups numbered 1 and 3 are all red-green, further, based on the number of groups of 7 for the comparative sample and 1 failure parameter, the threshold range was determined to be 4 or less from column 3 of line 3 of Table 7, the judging module 14 judges that the colors of the front and back sides of the sample to be detected a1 are all qualified and further judges that the color of the sample to be detected a1 is qualified based on the fact that the number of the comparison sample groups with 1 unqualified parameter on the front side is 2 and the number of the comparison sample groups with 1 unqualified parameter on the back side is 2, both within the threshold range of less than or equal to 4.
For another example, the evaluation module 14 determines that the color of the front and back surfaces of the sample to be measured A3 is not qualified based on that the unqualified parameters of the front surface of the sample to be measured A3 and the unqualified parameters of the reference sample groups numbered 4 and 7 are brightness, red, green and yellow blue, the group number of the reference sample group having 3 unqualified parameters with the front surface of the sample to be measured is 2, the group number of the reference sample group having 3 unqualified parameters with the back surface is 2, and further the group number of the reference sample group having 3 unqualified parameters with the back surface is 2, and the group number of the reference sample group having 3 unqualified parameters with the back surface is not more than 1, both of the group number of the reference sample group having 3 unqualified parameters with the front surface of the sample to be measured A3 is not more than 1, further, the sample a3 was judged to have a failed color.
Specifically, when the unqualified parameters of a surface of the sample to be tested are different from the corresponding surfaces of different comparison sample sets, but the numbers of the unqualified parameters are the same, the evaluation module 14 determines a threshold range based on the number of the unqualified parameters of one comparison sample set having the unqualified parameters with the sample to be tested and the number of the comparison sample sets, and determines whether the color of the surface of the sample to be tested is qualified based on whether the number of the comparison sample sets having the unqualified parameters with the sample to be tested is within the determined threshold range.
For example, the evaluation module 14 determines that the threshold range is not more than 2 based on the positive side and the number of failed sample groups of sample a2 being 2 failed parameters, the number of failed sample groups of sample a being 2 failed parameters, the number of sample groups of sample b being 2 parameters, the threshold range being not more than 2, and judging that the colors of the front side and the back side of the sample A2 to be detected are qualified, and further judging that the color of the sample A2 to be detected is qualified.
Specifically, if the unqualified parameters of a surface of the sample to be tested are different from the corresponding surfaces of different comparison sample groups, and the numbers of the unqualified parameters are different, the evaluation module 14 determines the threshold value ranges respectively based on the number of the unqualified parameters of each comparison sample group having the unqualified parameters with the sample to be tested and the number of the comparison sample groups, and determines whether the color of the surface of the sample to be tested is qualified or not based on whether the number of the comparison sample groups having the same unqualified parameters with the sample to be tested is within the determined corresponding threshold value ranges respectively.
For example, the evaluation module 14 determines that the number of sets of the comparison sample group having 1 and 2 failure parameters with respect to the front surface of the sample to be tested is 1, the number of sets of the comparison sample group having 1 and 2 failure parameters with respect to the back surface of the sample to be tested is 1, the number of sets of the comparison sample group having 1 failure parameter with respect to the back surface of the sample to be tested is 1, the number of sets of the comparison sample group having 2 failure parameters with respect to the back surface of the sample to be tested is 1, and the number of sets of the comparison sample group having 2 failure parameters with respect to the back surface of the sample to be tested is 2, based on that the number of sets of the comparison sample group is 7 and 1 failure parameter, the threshold range is determined to be not more than 4 in column 3 of table 7, the number of sets of the comparison sample group is 7, and the 2 failure parameters are determined to be the threshold range in column 3 of table 7, the threshold range is determined to be not more than 4 in column 3 of line 4 of table 7, based on that the number of the comparison sample group is 7 If the color of the front surface of the sample to be detected is less than or equal to 2, the judging module 14 judges that the color of the front surface of the sample to be detected is qualified and further judges that the color of the front surface of the sample to be detected is qualified based on the fact that the number of the groups of the comparison sample group with 1 unqualified parameter on the front surface of the sample to be detected is 1, the number of the groups of the comparison sample group with 1 unqualified parameter on the back surface of the sample to be detected is 1, the number of the groups of the comparison sample group with 2 unqualified parameters on the back surface of the sample to be detected is 2, and the color of the.
For another example, the evaluation module 14 determines that the number of sets of the comparison sample group having 1 and 3 rejection parameters with respect to the front face of the sample to be measured is 1, the number of sets of the comparison sample group having 2 rejection parameters with respect to the front face of the sample to be measured is 2, based on the fact that the rejection parameters of the comparison sample group having 1 on the front face and 3 are luminance, the rejection parameters of the comparison sample group having 3 on the front face are luminance and red-green, the rejection parameters of the comparison sample group having 5 on the front face are luminance, red-green and yellow-blue, the rejection parameters of the comparison sample group having 1 and 3 on the back face are both luminance, red-green and yellow-blue, the rejection parameters of the comparison sample group having 5 on the back face are luminance and red-green, and the rejection parameters of the comparison sample group having 7 on the back face are yellow-blue, and determines that the number of sets of the comparison sample group having 1 and 3 rejection parameters with respect to the front face of the sample to be measured is, The number of sets of the comparison sample groups having 1 and 2 defective parameters with respect to the back surface of the sample to be measured is 1, respectively, the number of sets of the comparison sample groups having 3 defective parameters with respect to the back surface of the sample to be measured is 2, further, the threshold range determined in column 3 of line 3 of Table 7 is not more than 4 based on the number of sets of the comparison sample is 7 and 1 defective parameter, the threshold range determined in column 3 of line 4 of Table 7 is not more than 2 based on the number of sets of the comparison sample and 2 defective parameters, the threshold range determined in column 3 of line 5 of Table 7 based on the number of sets of the comparison sample groups having 1 defective parameter with respect to the front surface and the back surface of the sample to be measured is not more than 1 based on the comparison sample groups having 1 defective parameter with respect to the front surface and the back surface of the sample to be measured, the number of sets of the comparison sample groups having 2 defective parameters with respect to the front surface and the back surface of the sample to be measured is 2 and 1 based on the comparison sample groups, the number of groups of comparison sample groups with 3 unqualified parameters on the front side of the sample to be detected is 1 within the determined threshold range of less than or equal to 2, the number of groups of comparison sample groups with 3 unqualified parameters on the back side of the sample to be detected is 2 within the determined threshold range of less than or equal to 1, the color of the front side of the sample to be detected A5 is judged to be qualified, the color of the back side of the sample to be detected is judged to be unqualified, and further, the color of the sample to be detected A5 is judged to be unqualified.
In conclusion, the product color evaluation method and system for the paper-making reconstituted tobacco production comprehensively consider the influence of the parameter fluctuation number, the group number of the comparison sample group and the product color evaluation standard on the product color evaluation, so that the evaluation result can better meet the actual effect; moreover, the sample to be detected is directly obtained from a production field, and only needs to be placed in a sealing bag for storage, and does not need to be subjected to constant temperature and humidity treatment; and moreover, the front and back colors of the product are judged, so that the judgment is more comprehensive. Therefore, the invention effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.

Claims (4)

1. The product color judging method for the paper-making process reconstituted tobacco production is characterized by at least comprising the following steps of:
detecting the front and back surfaces of each of a plurality of samples to be detected extracted from tobacco leaves produced on site to obtain the brightness values, red-green values and yellow-blue values of the front and back surfaces, and further determining the brightness average value, red-green average value and yellow-blue average value of the front and back surfaces of the samples to be detected;
determining the brightness, red-green color and yellow-blue fluctuation limit absolute values of the front and back sides of the sample to be detected and each group of comparison sample group based on the determined brightness average value, red-green average value and yellow-blue average value of the front and back sides of the sample to be detected and the determined brightness average value, red-green average value and yellow-blue average value of the front and back sides of the multiple groups of comparison sample groups;
determining unqualified parameter information of the front and back sides of the sample to be detected and the front and back sides of each group of comparison sample groups based on the front and back side brightness, red and green and yellow and blue fluctuation threshold values and the brightness, red and green and yellow and blue fluctuation limit absolute values between the front and back sides of the sample to be detected and each group of comparison sample groups;
determining whether the color of the sample to be detected is qualified or not based on the number of groups of the comparison samples and the information of the unqualified parameters of the front and back sides of the sample to be detected and the front and back sides of each group of the comparison samples;
when the unqualified parameters of one surface of the sample to be detected are the same as those of the corresponding surfaces of different comparison sample groups, determining a threshold range based on the number of the unqualified parameters of one comparison sample group with the unqualified parameters of the sample to be detected and the group number of the comparison sample groups, and determining whether the color of the surface of the sample to be detected is qualified or not based on whether the group number of the comparison sample group with the unqualified parameters of the sample to be detected is in the determined threshold range or not;
when the unqualified parameters of one surface of the sample to be detected are different from the corresponding surfaces of different comparison sample groups, but the numbers of the unqualified parameters are the same, determining a threshold value range based on the number of the unqualified parameters of one comparison sample group with the unqualified parameters of the sample to be detected and the group number of the comparison sample group, and determining whether the color of the surface of the sample to be detected is qualified or not based on whether the group number of the comparison sample group with the unqualified parameters of the sample to be detected is in the determined threshold value range or not;
if the unqualified parameters of one surface of the sample to be detected are different from the corresponding surfaces of different comparison sample groups, and the number of the unqualified parameters is different, respectively determining the threshold value range based on the number of the unqualified parameters of each comparison sample group having the unqualified parameters with the sample to be detected and the group number of the comparison sample group, and respectively determining whether the color of the surface of the sample to be detected is qualified or not based on whether the group number of the comparison sample group having the same unqualified parameters with the sample to be detected is in the determined corresponding threshold value range or not.
2. The method for judging the product color in the production of paper-making reconstituted tobacco according to claim 1, characterized in that: the number of groups of the comparative sample group was not less than 6.
3. The product color judging system for the production of the paper-making reconstituted tobacco is characterized by at least comprising the following components in parts by weight:
the acquisition module is used for detecting the front and back surfaces of each of a plurality of samples to be detected extracted from tobacco leaves produced on site so as to obtain the brightness values, red-green values and yellow-blue values of the front and back surfaces, and further determine the brightness average value, red-green average value and yellow-blue average value of the front and back surfaces of the samples to be detected;
the calculation module is used for determining the brightness, red-green color and yellow-blue fluctuation limit absolute values of the front and back surfaces of the sample to be detected and each group of comparison sample group based on the determined brightness average value, red-green average value and yellow-blue average value of the front and back surfaces of the sample to be detected and the determined brightness average value, red-green average value and yellow-blue average value of the front and back surfaces of the multiple groups of comparison sample groups;
the comparison module is used for determining the unqualified parameter information of the front and back sides of the sample to be detected and the front and back sides of each group of comparison sample groups based on the front and back side brightness, red and green and yellow and blue fluctuation threshold values and the brightness, red and green and yellow and blue fluctuation limit absolute values between the sample to be detected and the front and back sides of each group of comparison sample groups;
the judging module is used for comprehensively determining whether the color of the sample to be detected is qualified or not based on the number of the groups of the comparison samples and the unqualified parameter information of the front and back surfaces of the sample to be detected and each group of the comparison samples;
when the unqualified parameters of one surface of the sample to be detected are the same as those of the corresponding surfaces of different comparison sample groups, the judging module determines a threshold range based on the number of the unqualified parameters of one comparison sample group with the unqualified parameters of the sample to be detected and the group number of the comparison sample groups, and then comprehensively determines whether the surface color of the sample to be detected is qualified or not based on whether the group number of the comparison sample group with the unqualified parameters of the sample to be detected is within the determined threshold range or not;
when the unqualified parameters of one surface of the sample to be detected are different from the corresponding surfaces of different comparison sample groups, but the numbers of the unqualified parameters are the same, the judging module determines a threshold range based on the number of the unqualified parameters of one comparison sample group with the unqualified parameters of the sample to be detected and the number of the comparison sample groups, and then comprehensively determines whether the color of the surface of the sample to be detected is qualified or not based on whether the number of the comparison sample groups with the unqualified parameters of the sample to be detected is within the determined threshold range or not;
if the unqualified parameters of one surface of the sample to be detected are different from the corresponding surfaces of different comparison sample groups, and the number of the unqualified parameters is different, the judging module firstly determines the threshold value range respectively based on the number of the unqualified parameters of each comparison sample group having the unqualified parameters with the sample to be detected and the group number of the comparison sample group, and then comprehensively determines whether the surface color of the sample to be detected is qualified or not based on the group number of the comparison sample group having the same unqualified parameters with the sample to be detected and whether the group number of the comparison sample group is in the determined corresponding threshold value range.
4. The product color evaluation system for use in papermaking-process reconstituted tobacco production according to claim 3, characterized in that: the number of groups of the comparative sample group was not less than 6.
CN201410414931.6A 2014-08-21 2014-08-21 Method and system for evaluating product color used for reconstituted tobacco production by papermaking method Active CN104297161B (en)

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