Printing color difference defect detection method and device based on artificial intelligence system

Abstract

The invention relates to a printing color difference defect detection technology, which is used for solving the problems that during color difference defect detection of printing on an aluminum-foil paper metal surface and an adhesive tape metal coating surface of a cigarette packaging material, due to environmental factors, a metal aluminum powder coating on the aluminum-foil paper metal surface and the adhesive tape surface reflects light and is poor in ink absorption property during printing; the problems of product raw material waste, production progress delay and production cost increase caused by erroneous judgment of product quality and incapability of timely adjustment of wrong production parameters due to non-uniform printing coating factors and interference of a color difference tester on own factors in the prior art are solved. The printing color difference defect detection device based on the artificial intelligence system comprises a color difference tester; interference of environmental factors, factors of aluminum-foil paper and an adhesive tape and factors of a tester is eliminated through the influence analysis module, so that a detection result can more accurately reflect the color difference condition of printing of the aluminum-foil paper and the adhesive tape, and a more accurate basis is provided for improving production.

Description

Technical Field

[0001] The invention relates to a printing technology of aluminum foil and adhesive tape for cigarette packaging materials, and in particular to a printing color difference defect detection method and device based on an artificial intelligence system. Background Art

[0002] Colorimeter is widely used in color management in industries such as plastics, printing, paints and inks, textiles and clothing. It measures and displays the color difference △E and △Lab value between the sample and the sample being tested based on the Lab and Lch principles of the CIE color space.

[0003] In the prior art, when the color difference tester is detecting color difference defects, it may misjudge the product quality due to interference from environmental factors, aluminum foil and tape factors, and tester factors, and cannot adjust the wrong production parameters in time, resulting in waste of product raw materials, delaying production progress, and increasing production costs; and the misjudgment of products can easily affect the consistency between product batches, making qualified products easily misjudged, and the staff needs to spend a lot of time to determine the cause of product color difference defects, affecting production efficiency;

[0004] In view of the above technical problems, this application proposes a solution. Summary of the invention

[0005] The purpose of the present invention is to eliminate the interference of environmental factors, aluminum foil and tape factors themselves and tester factors themselves through the impact analysis module, so that the detection results can more accurately reflect the color difference of aluminum foil and tape printing itself, and provide a more accurate basis for improving production; and accurate color difference detection data can ensure that the product meets the quality standards, avoid unnecessary production adjustments or product scrapping due to misjudgment, improve production efficiency and product quality, solve the problem that when color difference defect detection is performed, due to the interference of environmental factors, aluminum foil and tape factors themselves and tester factors themselves, misjudgment of product quality will occur, and the wrong production parameters cannot be adjusted in time, resulting in waste of product raw materials, delaying production progress, and increasing production costs. Therefore, an aluminum foil and printing color difference defect detection method and device based on an artificial intelligence system are proposed.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] The printing color difference defect detection method based on the artificial intelligence system, the color difference defect detection method of the aluminum foil metal surface and the tape metal coating surface of the cigarette packaging material comprises the following steps:

[0008] Step 1: Detect image acquisition. According to the width data of the aluminum foil and the tape and the corresponding height of the colorimeter body, the width data of the image data is obtained, and the number of colorimeter bodies required is calculated. Then, the corresponding number of colorimeter bodies are set to perform image acquisition operations on the aluminum foil and the tape.

[0009] Step 2: Color difference defect analysis. A color difference analysis module is provided inside the color difference tester body. The color difference analysis module automatically calculates the color difference data ΔE and ΔL, Δa, Δb data according to the preset L, a, b data, and determines whether there is a color difference problem in the aluminum foil and the tape in the monitoring area of ​​the corresponding color difference tester body;

[0010] Step 3: Image acquisition impact analysis. The colorimeter is equipped with an impact analysis module. The impact analysis module analyzes the impact of environmental factors during image acquisition, the factors of the aluminum foil and tape itself, and the tester itself, determines the impact of various factors on image color difference, and reversely infers the cause of this situation.

[0011] As a preferred embodiment of the present invention, the data processing steps of the color difference analysis module are as follows:

[0012] Step 1: According to the preset L, a, b data, automatically calculate the color difference data ΔE and brightness difference data ΔL, red-green component difference data Δa, yellow-blue component difference data Δb. If the color difference setting threshold ΔE max <ΔE, it is determined that the aluminum foil and tape in the monitoring area of ​​the corresponding color difference tester have color difference defects; otherwise, the other three sets of color difference data ΔL, Δa, and Δb are analyzed;

[0013] Step 2: If the brightness difference is set to a threshold value ΔL max <ΔL, it is determined that there is a brightness difference defect in the aluminum foil and tape in the monitoring area of ​​the color difference tester body; if the brightness difference is set to a threshold value Δa max <Δa, it is determined that there is a deviation between the aluminum foil and the tape in the red-green color direction in the monitoring area of ​​the color difference tester body; if the brightness difference is set to a threshold value Δb max <Δb, it is determined that there is a deviation in the yellow-blue color direction between the aluminum foil and the tape in the monitoring area of ​​the color difference tester body;

[0014] Step 3: If ΔE>ΔE max If one or more of the three data of ΔL, Δa, and Δb exceeds the corresponding set threshold, it is determined that the aluminum foil and tape in the monitoring area of ​​the corresponding color difference tester have color difference defects; if ΔE<ΔE max In the case of ΔE>80%*ΔE maxWhen one or more of the three data of ΔL, Δa, and Δb exceeds 80% of the corresponding set threshold, it is determined that there is a potential color difference problem in the aluminum foil and the tape in the monitoring area of ​​the corresponding color difference tester body.

[0015] As a preferred embodiment of the present invention, the impact analysis module analyzes the lighting impact of environmental factors, and the analysis steps are as follows:

[0016] Step 1: Light factors include light intensity, light color and light angle. The change of light intensity is detected. If the light intensity change value ΔGQ>q, it is determined that the light intensity has changed. q is the set light intensity change threshold.

[0017] Step 2: Use regression analysis to establish a model that reflects the relationship between brightness and color distortion. The reflected light intensity data GQ F =GQ Fmax *(GQ / GQ+k), GQ is the light intensity data, GQ Fmax is the maximum reflected light intensity, k is the set constant; the maximum light intensity data GQ of the light source max The light intensity data can be adjusted in the range of [0, GQ max ], [0, GQ max ] Divide the data into several segments according to the size of the data q, and then detect it from the time when the light intensity data is zero. After each detection, the light intensity data q is increased, and the ΔE detected each time is recorded. q , ΔL q , Δa q , Δb q Data; when the light intensity data reaches GQ max When the test is completed, stop and record several ΔE q The data is sorted according to the size of the data, and when the color difference data change value is determined to be the smallest, the light intensity data in this interval is most suitable for color difference detection;

[0018] Step 3: When the light intensity increases by FD GZ When the ratio of the light intensity data increase amplitude to the set light intensity change threshold is calculated, the ratio data is rounded to an integer, and the integer can be used to know the interval number between the light intensity data after the change and the color difference data corresponding to the minimum change value of the color difference data, and the color difference data after the change ΔE is obtained. TB ; The color difference data calculated after the light intensity data changes is ΔE JB , if |ΔE TB -ΔE JB|≤0.2, it is determined that the color difference of the aluminum foil and tape in the detection area is caused by the increase of light intensity; otherwise, it is determined that there are other interfering factors and the change of light color is detected.

[0019] As a preferred embodiment of the present invention, the impact analysis module analyzes the impact of the illumination angle of environmental factors, and the analysis steps are as follows:

[0020] Step 1: The product of the spectral distribution curve S(γ) of the light source and the reflected spectrum R(γ) of the object surface, after weighting by the visual system, determines the perceived color of the object YS=∫S(γ)*R(γ)*V(γ)*dγ, where γ is the wavelength of light and V(γ) is the sensitivity of the human eye to different wavelengths, i.e., the visual response function. When the color of the light changes, the spectral distribution curve S(γ) of the light source changes, i.e., the peak value FM of the spectral distribution curve D , peak position FM W changes, and the marked change values ​​are ΔFM D , ΔFM W , if the ratio of the change value of the peak size or peak position to the peak size value or peak position value exceeds 20%, it is determined that the illumination color has changed;

[0021] Step 2: Relationship between illumination angle data θ and reflected light intensity data I(θ), I(θ) = I 0 *cosθ,I 0 is the incident light intensity data. As the illumination angle data changes, the reflected light intensity gradually decreases. The color difference data changes caused by the illumination angle change are ΔE j , ΔL j , Δa j , Δb j , take ΔE j The illumination angle data corresponding to the minimum value is the optimal incident angle;

[0022] Step 3: Detect and analyze multiple sets of data at this angle, and the four color difference data obtained are ΔE n , ΔL n , Δa n and Δb n , n is the number of data collection times, the mean of these four color difference data and standard deviation σ E , σ L , σ a , σ b Calculate and determine the corresponding color difference deviation ranges are When the light angle changes, the detected color difference data ΔE j , ΔLj , Δa j , Δb j Compared with the calculated values ​​of the four color difference data at the corresponding angles, if the difference between the detected color difference data and the calculated color difference data is within the color difference deviation range, it is determined that the color difference problem of the aluminum foil and tape in the detection area is caused by the change of lighting angle; otherwise, it is determined that in addition to the influence of lighting angle, there are other interference factors.

[0023] As a preferred implementation of the present invention, the impact analysis module analyzes the impact of environmental factors, and the analysis steps are as follows:

[0024] Step 1: Environmental factors include ambient temperature, ambient humidity and pollutant content; detect and record the temperature data of the environment where the testing equipment is located, retrieve the ambient temperature data of the corresponding months in previous years, and then calculate the mean value μ of the ambient temperature data of the corresponding year. n and standard deviation σ n Calculation, n is the year count of historical data, then it is determined that the ambient temperature data of the corresponding year are distributed in [μ min -3σ min , μ max +3σ max ], for those not in [μ min -3σ min , μ max +3σ max ] range of data to be eliminated; if the change in ambient temperature exceeds the preset ambient temperature threshold h, it will cause the color difference data to change, then [μ min -3σ min , μ max +3σ max ] The range is divided into several temperature intervals according to the preset ambient temperature threshold h, and then the color difference data of each temperature interval is detected, and the temperature interval with the smallest color difference data is taken as the most suitable ambient temperature data, and the color difference data size of each temperature interval is recorded;

[0025] Step 2: When the ambient temperature data WD changes, the change range of the ambient temperature data is detected, and then the corresponding color difference data change value is inferred according to the change range of the ambient temperature data. If the color difference data inference value caused by the ambient temperature data change is not equal to the color difference data inference value detection value, and exceeds 20% of the color difference data inference value, it is determined that there are other interference factors; otherwise, it is determined that the color difference problem of the aluminum foil and the tape in the detection area is caused by the ambient temperature change;

[0026] Step 3: The ambient humidity data and pollutant data are processed in the same way as the ambient temperature data to obtain the color difference data corresponding to the humidity range and the color difference data corresponding to the pollutant concentration range; the influence of the three data of ambient temperature, ambient humidity and pollutant concentration on the color difference defect detection is comprehensively considered, ΔE HJ =γ 0 +γ 1 *WD+γ 2 *SD+γ 3 *WRW+ε, ε is the deviation value, γ 0 , γ 1 , γ 2 , γ 3 All are regression coefficients.

[0027] As a preferred embodiment of the present invention, the impact analysis module analyzes the impact of the aluminum foil and the tape themselves, and the analysis steps are as follows:

[0028] Step 1: The influencing factors of aluminum foil and tape include roughness, flatness, ink type, ink thickness and printing uniformity. The increase of roughness will cause ΔE to increase, ΔL to decrease, and Δa and Δb to approach zero; the decrease of flatness, change of ink type and change of printing uniformity will cause ΔE to increase, ΔL, Δa and Δb to be unstable; ink thickness, increase of ink thickness will cause ΔE, Δa and Δb to increase, and ΔL to decrease;

[0029] Step 2: If ΔE is judged to be increased, Δa and Δb are compared. If Δa and Δb are close to zero, it is judged to be a color difference defect caused by increased roughness; if Δa and Δb increase, it is judged to be a color difference defect caused by increased ink thickness or decreased roughness. The change of ink thickness is judged. If the ink thickness increases, the color difference value Δa caused by the increase in ink thickness is calculated based on the increase in ink thickness. Y1 and Δb Y1 , and Δa Y1 and Δb Y1 y is compared with the detected color difference values ​​Δa and Δb. If the two are equal, it is determined to be a color difference defect caused by increased ink thickness; if Δa Y1 <Δa and Δb Y1 <Δb, the color difference defect caused by the increase in ink thickness and the decrease in roughness is determined, and the color difference value Δa caused by the decrease in roughness is calculated C1 and Δb C1 If the sum of the two color difference data caused by the increase of ink thickness and the decrease of roughness is equal to Δa and Δb respectively, the color difference defect caused by the increase of ink thickness and the decrease of roughness is determined. Otherwise, other influencing factors are determined; CC 1 and CC 2These are the roughness data collected at two moments before and after;

[0030] Step 3: Comprehensively analyze the impact of five data, namely, roughness CC, flatness PZ, ink type YMH, ink thickness YMH and printing uniformity JY, on color difference defect detection, ΔE LB =ρ 0 +ρ 1 *CC+ρ 2 *PZ+ρ 3 *YML+ρ 4 *YMH+ρ 5 *JY+δ, δ is the deviation value, ρ 0 , 1 , 2 , 3 , 4 , 5 All are regression coefficients.

[0031] As a preferred implementation of the present invention, the impact analysis module analyzes the impact of the tester's own factors, and the analysis steps are as follows:

[0032] Step 1: The influencing factors of the tester itself include the image acquisition angle and image acquisition distance. When the image acquisition angle changes from the front to the tilted position, ΔE will increase, ΔL will decrease, and Δa and Δb will become unstable. When the image acquisition distance becomes closer, ΔE, ΔL, Δa and Δb will all increase. When the image acquisition distance becomes farther, ΔE and ΔL will decrease, and Δa and Δb will approach zero.

[0033] Step 2: If ΔE is judged to be increasing, Δa and Δb are compared. If Δa and Δb are unstable, it is judged to be a chromatic aberration defect caused by a change in the image acquisition angle; if both Δa and Δb are increasing, it is judged to be a chromatic aberration defect caused by a closer image acquisition distance, and an instrument adjustment signal is generated and transmitted to the operation adjustment module;

[0034] Step 3: Comprehensively analyze the impact of the two data of acquisition angle JD and acquisition distance JL on color difference defect detection. is the deviation value, ω 0 ,ω 1 ,ω 2 All are regression coefficients.

[0035] As a preferred embodiment of the present invention, the steps of influencing the analysis module to explore the causes of color difference defects are as follows:

[0036] Step 1: Statistic the impact of three factors: environmental factors, aluminum foil and tape factors, and tester factors. The statistical results are recorded as increasing ZD, decreasing JX, unstable BWD, less influential YXX, and approaching zero QJO.

[0037] Step 2: If it is determined that there are color difference defects in the monitoring area of ​​the aluminum foil and the tape, multiple color difference test results of the monitoring area of ​​the same color difference tester body are retrieved and arranged in the order of detection; if the color difference test results show that Δa and Δb are close to zero, the environmental pollutants, the surface roughness of the aluminum foil and the tape, and the change in image acquisition distance that cause Δa and Δb to approach zero are determined; if the color difference test results show that Δa and Δb are unstable, the change in image acquisition angle, flatness reduction, ink type change, and printing uniformity change that cause Δa and Δb to be unstable are determined; if Δa and Δb are unstable, but ΔL is stable, it is determined that it is caused by a change in the image acquisition angle, and the image acquisition angle is analyzed;

[0038] Step 3: If ΔE increases, and the changes in Δa and Δb are less than 10% of their respective corresponding set thresholds, it is determined that the color difference defect is caused by environmental factors, and the data change of ΔL is analyzed; if the change in ΔL is also less than 10% of the corresponding set threshold, it is determined that the image color difference defect is caused by the decrease in environmental humidity, otherwise, it is determined that the image color difference defect is caused by the change in ambient temperature;

[0039] Step 4: If ΔL, Δa and Δb all have obvious changes, then the three influencing factors, namely environmental factors, factors of the aluminum foil and tape itself, and factors of the tester itself, are identified one by one to determine the factors that cause the color difference defect of the image;

[0040] Step 5: Total change value ΔE of color difference data ZJ =ΔE GZ +ΔE HJ +ΔE LB +ΔE YQ When the color difference data output results show an increase or decrease, the four influencing factors of light, environment, aluminum foil and tape, and tester are checked simultaneously. If a factor in the influencing factors is found to have changed, the color difference data change value caused by the change of the factor is recorded, and then the color difference data change values ​​caused by the changes of each factor are accumulated and summed to obtain the inferred color difference total value ΔE ZT , if |ΔE ZT -ΔE ZJ || / ΔE ZT If the value is less than 0.2, the color difference defect is judged to be caused by the change of the corresponding influencing factors. Otherwise, the test is repeated.

[0041] As a preferred embodiment of the present invention, an operation adjustment module is also provided inside the color difference tester body, and the adjustment steps of the operation adjustment module are as follows:

[0042] Step 1: Receive the instrument angle adjustment signal, measure the current deflection angle value of the colorimeter, and calculate the difference between the detected deflection angle value and the preset angle value. The obtained angle difference value is the angle to be adjusted of the colorimeter.

[0043] Step 2: Receive the instrument distance adjustment signal, measure the distance data between the colorimeter body and the aluminum foil and tape, and calculate the difference between the detected distance data and the preset distance data. The obtained distance difference is the distance adjustment amount of the colorimeter body.

[0044] As a preferred embodiment of the present invention, it includes a colorimeter body, a display screen is arranged above the front surface of the colorimeter body, a control button is arranged on the side of the front surface of the colorimeter body corresponding to the display screen, a measuring port is installed at the lower end of the colorimeter body, a clamping frame is installed below the outer side wall of the colorimeter body, and a mechanical arm is rotatably connected to one side of the outer side wall of the clamping frame through a rotating seat.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1. The impact analysis module eliminates interference from environmental factors, aluminum foil and tape factors, and tester factors, so that the test results can more accurately reflect the color difference of aluminum foil and tape printing, providing a more accurate basis for improving production; and accurate color difference test data can ensure that products meet quality standards, avoid unnecessary production adjustments or product scrapping due to misjudgment, and improve production efficiency and product quality; accurately determine the cause of color difference defects and make adjustments, the stability of the production process will be enhanced, thereby improving the economic benefits of the enterprise;

[0047] 2. By eliminating influencing factors and reducing the judgment scope through the impact analysis module, it is possible to more accurately determine whether the product meets the standards. Reducing the judgment scope makes it easier to eliminate irrelevant factors and reduce the risk of misjudgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0049] Figure 1 is a system structure diagram of the present invention;

[0050] Figure 2 It is a structural diagram of the color difference tester of the present invention;

[0051] In the figure: 1. Color difference tester body; 2. Display screen; 3. Control button; 4. Measuring port; 5. Clamping frame; 6. Robotic arm. DETAILED DESCRIPTION

[0052] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Example:

[0054] See also Figure 1-2 As shown, a printing color difference defect detection method and device based on an artificial intelligence system includes a color difference analysis module, an impact analysis module and an operation adjustment module;

[0055] This scheme's printing color difference detection is mainly for a type of paper used to package cigarettes. This scheme can be used for similar products such as lining paper and tape. The lining paper includes the commonly used aluminum foil paper.

[0056] Detect image acquisition, fix the colorimeter body 1 at a set height above the aluminum foil, so that the colorimeter body 1 can obtain image data of the corresponding area size through the measuring port 4 at the lower end, obtain the width data of the image data according to the width data of the aluminum foil and the tape and the corresponding height of the colorimeter body 1, calculate the number of colorimeter bodies 1 required, and then set the corresponding number of colorimeter bodies 1 to perform image acquisition operations on the aluminum foil and the tape;

[0057] The color difference analysis module automatically calculates the color difference data ΔE and the brightness difference data ΔL, the red-green component difference data Δa, and the yellow-blue component difference data Δb according to the preset L, a, and b data. max <ΔE, it is determined that the aluminum foil and the tape in the monitoring area of ​​the corresponding color difference tester body 1 have color difference defects; otherwise, the other three sets of color difference data ΔL, Δa, and Δb are analyzed;

[0058] If the brightness difference is set to a threshold value ΔL max <ΔL, it is determined that the aluminum foil and tape in the monitoring area of ​​the color difference tester body 1 have brightness difference defects; if the brightness difference is set to a threshold value Δa max <Δa, it is determined that the aluminum foil and tape in the monitoring area of ​​the color difference tester body 1 have deviations in the red-green color direction; if the brightness difference is set to a threshold value Δb max <Δb, it is determined that the aluminum foil and the tape in the monitoring area of ​​the corresponding color difference tester body 1 have deviations in the yellow-blue color direction;

[0059] If ΔE>ΔE maxWhen one or more of the three data ΔL, Δa, and Δb exceeds the corresponding set threshold, it is determined that the aluminum foil and tape in the monitoring area of ​​the corresponding color difference tester body 1 have color difference defects; when ΔE<ΔE max In the case of ΔE>80%*ΔE max When one or more of the three data of ΔL, Δa and Δb exceeds 80% of the corresponding set threshold, it is determined that the aluminum foil and the tape in the monitoring area of ​​the corresponding color difference tester body 1 have potential color difference problems;

[0060] After determining that the aluminum foil and tape in the detection area have color difference problems, the influence of environmental factors during image acquisition, factors of the aluminum foil and tape themselves, and factors of the tester itself are analyzed;

[0061] Judgment of the influence of environmental factors: Light factors, ambient temperature, ambient humidity and environmental pollutants can all cause differences in color difference test results; Light factors include light intensity, light color and light angle;

[0062] Light intensity. An increase in light intensity will cause ΔE q , ΔL q , Δa q , Δb q All four data increase, and the decrease in light intensity will cause ΔE q Increase, ΔL q , Δa q , Δb q The three types of data are reduced; the change of light intensity is detected. If the light intensity change value ΔGQ>q, it is determined that the light intensity has changed, and q is the set light intensity change threshold; color difference data Regression analysis was used to establish a model reflecting the relationship between brightness and color distortion, and the reflected light intensity data GQ F =GQ Fmax *(GQ / GQ+k), GQ is the light intensity data, GQ Fmax is the maximum reflected light intensity, k is the set constant; the maximum light intensity data GQ of the light source max The light intensity data can be adjusted in the range of [0, GQ max ], [0, GQ max ] Divide the data into several segments according to the size of the data q, and then detect it from the time when the light intensity data is zero. After each detection, the light intensity data q is increased, and the ΔE detected each time is recorded. q , ΔL q , Δa q , Δb q Data; when the light intensity data reaches GQ max When the test is completed, stop and record several ΔEq The data is sorted according to the size of the data. When the color difference data change value is the smallest, the light intensity data in this interval is most suitable for color difference detection; when the light intensity increases and the increase is FD GZ When the ratio of the light intensity data increase amplitude to the set light intensity change threshold is calculated, the ratio data is rounded to an integer, and the integer can be used to know the interval number between the light intensity data after the change and the color difference data corresponding to the minimum change value of the color difference data, and the color difference data after the change ΔE is obtained. TB ; The color difference data calculated after the light intensity data changes is ΔE JB , if |ΔE TB -ΔE JB | / ΔE TB If the value is ≤0.2, the color difference of the aluminum foil and tape in the detection area is determined to be caused by the increase of light intensity; otherwise, it is determined that there are other interference factors, and the change of light color is detected;

[0063] Light color, both warm and cold light will cause ΔE y increases, and causes ΔL y The decrease and increase of the corresponding color of light will cause Δa y , Δb y The color direction of the two data changes, resulting in Δa y , Δb y Increase or decrease; the core influence of light color lies in its different spectral distribution, which causes the light reflected by the object to have different performances in different bands. The product of the spectral distribution curve S(γ) of the light source and the surface reflection spectrum R(γ) of the object, after weighting by the visual system, determines the perceived color of the object YS=∫S(γ)*R(γ)*V(γ)*dγ, where γ is the wavelength of light and V(γ) is the sensitivity of the human eye to different wavelengths, that is, the visual response function; when the light color changes, the spectral distribution curve S(γ) of the light source changes, that is, the peak value FM of the spectral distribution curve D , peak position FM W changes, and the marked change values ​​are ΔFM D , ΔFM W , if the ratio of the change value of the peak size or peak position to the peak size value or peak position value exceeds 20%, it is determined that the illumination color has changed;

[0064] Illumination angle, chromatic aberration caused by illumination angle change; Relationship between illumination angle data θ and reflected light intensity data I(θ), I(θ)=I 0 *cosθ,I 0is the incident light intensity data. As the illumination angle data changes, the reflected light intensity gradually decreases. The color difference data changes caused by the illumination angle change are ΔE i , ΔL j , Δa j , Δb j , take ΔE j The illumination angle data corresponding to the minimum value in the optimal incident angle is the optimal incident angle. At this angle, multiple sets of data are tested and analyzed, and the four color difference data obtained are ΔE n , ΔL n , Δa n and Δb n , n is the number of data collection times, the mean of these four color difference data and standard deviation σ E , σ L , σ a , σ b Calculate and determine the corresponding color difference deviation ranges are When the light angle changes, the detected color difference data ΔE j , ΔL j , Δa j , Δb j Compare with the calculated values ​​of the four color difference data at the corresponding angles. If the difference between the detected color difference data and the calculated color difference data is within the color difference deviation range, it is determined that the color difference problem of the aluminum foil and tape in the detection area is caused by the change of the illumination angle; otherwise, it is determined that in addition to the influence of the illumination angle, there are other interference factors;

[0065] The influence of three data, namely, light intensity, light color and light angle, on color difference defect detection, ΔE GZ =β 0 +β 1 *GQ+β 2 *YS+β 3 *θ+∈, ∈ is the deviation range, β 0 , β 1 , β 2 , β 3 are all regression coefficients; the model can be used to predict the changing trend of color difference values ​​under different lighting factors. When the light intensity, light color or light angle changes, the prediction model can be used to calculate the change in color difference value, and compare the calculated color difference value with the set color difference threshold. If the calculated color difference value is greater than the set color difference threshold, it is determined that the detected color difference exceeds the set range and the detection area has a color difference defect;

[0066] Ambient temperature: temperature changes will cause ΔE to increase, temperature increase will cause ΔL to increase, temperature decrease will cause ΔL to decrease, and temperature changes will have little effect on Δa and Δb; the temperature data of the environment where the detection equipment is located is detected and recorded, and the ambient temperature data of the corresponding months in previous years is retrieved, and then the average value μ of the ambient temperature data of the corresponding year is calculated. n and standard deviation σ n Calculation, n is the year count of historical data, then it is determined that the ambient temperature data of the corresponding year are distributed in [μ min -3σ min , μ max +3σ max ], for those not in [μ min -3σ min , μ max +3σ max ] range of data to be eliminated; if the change in ambient temperature exceeds the preset ambient temperature threshold h, it will cause the color difference data to change, then [μ min -3σ min , μ max +3σ max ] The range is divided into several temperature intervals according to the preset ambient temperature threshold h, and then the color difference data of each temperature interval is detected, and the temperature interval with the smallest color difference data is taken as the most suitable ambient temperature data, and the size of the color difference data of each temperature interval is recorded; when the ambient temperature data WD changes, the change amplitude of the ambient temperature data is detected, and then the corresponding color difference data change value is inferred according to the change amplitude of the ambient temperature data. If the color difference data inference value caused by the ambient temperature data change is not equal to the color difference data inference value detection value, and exceeds 20% of the color difference data inference value, it is determined that there are other interference factors; otherwise, it is determined that the color difference problem of the aluminum foil and tape in the detection area is caused by the ambient temperature change;

[0067] Ambient humidity: low ambient humidity has little effect on the four data of ΔE, ΔL, Δa, and Δb. A high humidity environment will cause ΔE to increase, ΔL to decrease, Δa to decrease, and Δb to increase. If the ambient humidity data SD increases, and the detection amplitude value of the four data of ΔE, ΔL, Δa, and Δb is not equal to the calculated amplitude value, it is determined that there are other interference factors. Otherwise, it is determined that the color difference problem of the aluminum foil and tape in the detection area is caused by the increase in ambient humidity. Pollutants: the influence of pollutants will cause ΔE to increase, ΔL to decrease, and Δa and Δb to approach zero. If the detection environment is affected by pollutants WRW, and the detection changes of the four data of ΔE, ΔL, Δa, and Δb are different from the calculated changes, it is determined that there are other interference factors. Otherwise, it is determined that the color difference problem of the aluminum foil and tape in the detection area is caused by pollutants.

[0068] The environmental humidity data and pollutant data are processed in the same way as the environmental temperature data to obtain the color difference data corresponding to the humidity range and the color difference data corresponding to the pollutant concentration range; the influence of the three data of environmental temperature, environmental humidity and pollutant concentration on the color difference defect detection is comprehensively considered, ΔE HJ =γ 0 +γ 1 *WD+γ 2 *SD+γ 3 *WRW+ε, ε is the deviation value, γ 0 , γ 1 , γ 2 , γ 3 All are regression coefficients.

[0069] Aluminum foil and tape are affected by their own factors: roughness, flatness, ink type, ink thickness and printing uniformity will cause differences in color difference detection results; the increase in roughness will cause ΔE to increase, ΔL to decrease, and Δa and Δb to approach zero; the decrease in flatness, changes in ink type and changes in printing uniformity will cause ΔE to increase, ΔL, Δa and Δb to be unstable; ink thickness, increased ink thickness will cause ΔE, Δa and Δb to increase, and ΔL to decrease;

[0070] The influence of five data, namely, roughness CC, flatness PZ, ink type YML, ink thickness YMH and printing uniformity JY, on color difference defect detection, ΔE LB =ρ 0 +ρ 1 *CC+ρ 2 *PZ+ρ 3 *YML+ρ 4 *YMH+ρ 5 *JY+δ, δ is the deviation value, ρ 0 , 1 , 2 , 3 , 4 , 5 All are regression coefficients;

[0071] If ΔE is judged to be increased, Δa and Δb are compared. If Δa and Δb are close to zero, it is judged to be a color difference defect caused by increased roughness. If Δa and Δb increase, it is judged to be a color difference defect caused by increased ink thickness or decreased roughness. The change of ink thickness is judged. If the ink thickness increases, the color difference value Δa caused by the increase in ink thickness is calculated based on the increase in ink thickness. Y1 and Δb Y1 , and Δa Y1 and Δb Y1y is compared with the detected color difference values ​​Δa and Δb. If the two are equal, it is determined to be a color difference defect caused by increased ink thickness; if Δa Y1 <Δa and Δb Y1 <Δb, the color difference defect caused by the increase in ink thickness and the decrease in roughness is determined, and the color difference value Δa caused by the decrease in roughness is calculated C1 and Δb C1 If the sum of the two color difference data caused by the increase of ink thickness and the decrease of roughness is equal to Δa and Δb respectively, the color difference defect caused by the increase of ink thickness and the decrease of roughness is determined. Otherwise, other influencing factors are determined; CC 1 and CC 2 These are the roughness data collected at the two moments before and after.

[0072] The influence of the tester's own factors: The image acquisition angle and image acquisition distance will cause differences in color difference detection results; the image acquisition angle changes from the front to the tilt, which will cause ΔE to increase, ΔL to decrease, and Δa and Δb to be unstable; the image acquisition distance becomes closer, which will cause ΔE, ΔL, Δa and Δb to increase; the image acquisition distance becomes farther, which will cause ΔE and ΔL to decrease, and Δa and Δb to approach zero;

[0073] Comprehensively analyze the impact of the two data of acquisition angle JD and acquisition distance JL on color difference defect detection. is the deviation value, ω 0 ,ω 1 ,ω 2 All are regression coefficients;

[0074] If ΔE is judged to be increasing, Δa and Δb are compared. If Δa and Δb are unstable, it is judged to be a chromatic aberration defect caused by a change in the image acquisition angle, an instrument angle adjustment signal is generated, and the instrument angle adjustment signal is transmitted to the operation adjustment module; if both Δa and Δb increase, it is judged to be a chromatic aberration defect caused by a closer image acquisition distance, an instrument distance adjustment signal is generated, and the instrument distance adjustment signal is transmitted to the operation adjustment module.

[0075] The influencing results caused by the above influencing factors are statistically recorded as five types: increased ZD, reduced JX, unstable BWD, less affected YXX and approaching zero QJO; if it is determined that there are color difference defects in the aluminum foil and tape monitoring area, the multiple color difference detection results of the monitoring area of ​​the same color difference tester body 1 are arranged in the detection order. If the results of Δa and Δb approaching zero appear, the environmental pollutants, aluminum foil, tape roughness and image acquisition distance changes that cause Δa and Δb to approach zero are determined; if the results of Δa and Δb being unstable appear, the image acquisition angle change, flatness reduction, ink type change and printing uniformity change that cause Δa and Δb to be unstable are determined. If Δa and Δb are unstable, but ΔL is stable, it is determined that it is caused by the change of image acquisition angle, and the image acquisition angle is analyzed;

[0076] The total change value of color difference data ΔE ZJ =ΔE GZ +ΔE HJ +ΔE LB +ΔE YQ When the color difference data output results show an increase or decrease, the four influencing factors of light, environment, aluminum foil, tape and tester are checked simultaneously. If a factor in the influencing factors is found to have changed, the color difference data change value caused by the change of the factor is recorded, and then the color difference data change values ​​caused by the changes of each factor are accumulated and summed to obtain the inferred color difference total value ΔE ZT , if |ΔE ZT -ΔE ZJ || / ΔE ZT If the value is less than 0.2, the color difference defect is judged to be caused by the change of the corresponding influencing factors. Otherwise, the test is repeated.

[0077] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A printing color difference defect detection method based on an artificial intelligence system, characterized in that: The method for detecting color difference defects on the metal surface of aluminum foil paper and the metal coating surface of tape used as cigarette packaging materials comprises the following steps: Step 1: Detect image acquisition, set a number of color difference tester bodies (1) to perform image acquisition operation on aluminum foil; Step 2: Color difference defect analysis: a color difference analysis module is provided inside the color difference tester body (1). The color difference analysis module automatically calculates the color difference data ΔE and ΔL, Δa, Δb data according to the preset L, a, b data, and determines whether there is a color difference problem in the aluminum foil and the tape in the monitoring area of ​​the corresponding color difference tester body (1); Step 3: Image acquisition impact analysis. The color difference tester body (1) is provided with an impact analysis module. The impact analysis module analyzes the impact of the lighting factor, environmental factor, aluminum foil and tape itself and the tester itself during image acquisition, determines the impact of the four factors on the image color difference, and reversely infers the specific factors that cause the impact. Step 4: After successful setting, the instrument will automatically perform color measurement on the metal surface of the aluminum foil paper of the cigarette packaging material and the metal coating surface of the tape during the printing process, and display the measurement results on the display screen; the measurement results usually include the analysis results of the Lab* value and the color difference value. The quality control requirement for general products is that △E (color difference value) is less than or equal to 2.

0.

2. The printing color difference defect detection method based on the artificial intelligence system according to claim 1 is characterized in that: The data processing steps of the color difference analysis module are as follows: Step 1: According to the preset L, a, b data, automatically calculate the color difference data ΔE and brightness difference data ΔL, red-green component difference data Δa, yellow-blue component difference data Δb. If the color difference setting threshold ΔE max <ΔE, it is determined that the aluminum foil and the tape in the monitoring area of ​​the corresponding color difference tester body 1 have color difference defects; otherwise, the other three sets of color difference data ΔL, Δa, and Δb are analyzed; Step 2: If the brightness difference is set to a threshold value ΔL max <ΔL, it is determined that the aluminum foil and the tape in the monitoring area of ​​the color difference tester body 1 have brightness difference defects; if the brightness difference is set to a threshold value Δa max <Δa, it is determined that the aluminum foil and the tape in the monitoring area of ​​the color difference tester body 1 have deviations in the red-green color direction; if the brightness difference is set to a threshold value Δb max <Δb, it is determined that there is a deviation in the yellow-blue color direction between the aluminum foil and the adhesive tape in the monitoring area of ​​the color difference tester body 1; Step 3: If ΔE>ΔE max When one or more of the three data ΔL, Δa, and Δb exceeds the corresponding set threshold, it is determined that the aluminum foil and the tape in the monitoring area of ​​the corresponding color difference tester body 1 have color difference defects; when ΔE<ΔE max In the case of ΔE>80%*ΔE max When one or more of the three data of ΔL, Δa, and Δb exceeds 80% of the corresponding set threshold, it is determined that the aluminum foil and the tape in the monitoring area of ​​the corresponding color difference tester body 1 have potential color difference problems.

3. The printing color difference defect detection method based on the artificial intelligence system according to claim 1 is characterized in that: The impact analysis module analyzes the light intensity data. The analysis steps are as follows: Step 1: Light factors include light intensity, light color and light angle. The change of light intensity is detected. If the light intensity change value ΔGQ>q, it is determined that the light intensity has changed. q is the set light intensity change threshold. Step 2: Use regression analysis to establish a model that reflects the relationship between brightness and color distortion. The reflected light intensity data GQ F =GQ Fmax *(GQ / GQ+k), GQ is the light intensity data, GQ Fmax is the maximum reflected light intensity, k is the set constant; the maximum light intensity data GQ of the light source max The light intensity data can be adjusted in the range of [0, GQ max ], [0, GQ max ] Divide the data into several segments according to the size of the data q, and then detect it from the time when the light intensity data is zero. After each detection, the light intensity data q is increased, and the ΔE detected each time is recorded. q , ΔL q , Δa q , Δb q Data; when the light intensity data reaches GQ max When the test is completed, stop and record several ΔE q The data is sorted according to the size of the data, and when the color difference data change value is determined to be the smallest, the light intensity data in this interval is most suitable for color difference detection; Step 3: When the light intensity increases by FD GZ When the ratio of the light intensity data increase amplitude to the set light intensity change threshold is calculated, the ratio data is rounded to an integer, and the integer can be used to know the interval number between the light intensity data after the change and the color difference data corresponding to the minimum change value of the color difference data, and the color difference data after the change ΔE is obtained. TB ; The color difference data calculated after the light intensity data changes is ΔE JB , if |ΔE TB -ΔE JB |≤0.2, it is determined that the color difference of the aluminum foil and tape in the detection area is caused by the increase of light intensity; otherwise, it is determined that there are other interfering factors and the change of light color is detected.

4. The printing color difference defect detection method based on the artificial intelligence system according to claim 3 is characterized in that: The impact analysis module analyzes the impact of lighting color and lighting angle. The analysis steps are as follows: Step 1: The product of the spectral distribution curve S(γ) of the light source and the reflected spectrum R(γ) of the object surface, after weighting by the visual system, determines the perceived color of the object YS=∫S(γ)*R(γ)*V(γ)*dγ, where γ is the wavelength of light and V(γ) is the sensitivity of the human eye to different wavelengths, i.e., the visual response function. When the color of the light changes, the spectral distribution curve S(γ) of the light source changes, i.e., the peak value FM of the spectral distribution curve D , peak position FM W changes, and the marked change values ​​are ΔFM D , ΔFM W , if the ratio of the change value of the peak size or peak position to the peak size value or peak position value exceeds 20%, it is determined that the illumination color has changed; Step 2: The relationship between the illumination angle data θ and the reflected light intensity data I(θ), I(θ) = I0*cosθ, I0 is the incident light intensity data, as the illumination angle data changes, the reflected light intensity gradually weakens; the color difference data changes caused by the change in illumination angle are ΔE j , ΔL j , Δa j , Δb j , take ΔE j The illumination angle data corresponding to the minimum value is the optimal incident angle; Step 3: Detect and analyze multiple sets of data at this angle, and the four color difference data obtained are ΔE n , ΔL n , Δa n and Δb n , n is the number of data collection times, the mean of these four color difference data and standard deviation σ E , σ L , σ a , σ b Calculate and determine the corresponding color difference deviation ranges are When the light angle changes, the detected color difference data ΔE j , ΔL j , Δa j , Δb j Compared with the calculated values ​​of the four color difference data at the corresponding angles, if the difference between the detected color difference data and the calculated color difference data is within the color difference deviation range, it is determined that the color difference problem of the aluminum foil and tape in the detection area is caused by the change of lighting angle; otherwise, it is determined that in addition to the influence of lighting angle, there are other interference factors.

5. The printing color difference defect detection method based on the artificial intelligence system according to claim 4 is characterized in that: The impact analysis module analyzes the impact of environmental factors. The analysis steps are as follows: Step 1: Environmental factors include ambient temperature, ambient humidity and pollutant content; detect and record the temperature data of the environment where the testing equipment is located, retrieve the ambient temperature data of the corresponding months in previous years, and then calculate the mean value μ of the ambient temperature data of the corresponding year. n and standard deviation σ n Calculation, n is the year count of historical data, then it is determined that the ambient temperature data of the corresponding year are distributed in [μ min -3σ min , μ max +3σ max ], for those not in [μ min -3σ min , μ max +3σ max ] range of data to be eliminated; if the change in ambient temperature exceeds the preset ambient temperature threshold h, it will cause the color difference data to change, then [μ min -3σ min , μ max +3σ max ] The range is divided into several temperature intervals according to the preset ambient temperature threshold h, and then the color difference data of each temperature interval is detected, and the temperature interval with the smallest color difference data is taken as the most suitable ambient temperature data, and the color difference data size of each temperature interval is recorded; Step 2: When the ambient temperature data WD changes, the change range of the ambient temperature data is detected, and then the corresponding color difference data change value is inferred according to the change range of the ambient temperature data. If the color difference data inference value caused by the ambient temperature data change is not equal to the color difference data inference value detection value, and exceeds 20% of the color difference data inference value, it is determined that there are other interference factors; otherwise, it is determined that the color difference problem of the aluminum foil and the tape in the detection area is caused by the ambient temperature change; Step 3: The ambient humidity data and pollutant data are processed in the same way as the ambient temperature data to obtain the color difference data corresponding to the humidity range and the color difference data corresponding to the pollutant concentration range; the influence of the three data of ambient temperature, ambient humidity and pollutant concentration on the color difference defect detection is comprehensively considered, ΔE HJ =γ0+γ1*WD+γ2*SD+γ3*WRW+ε, ε is the deviation value, γ0, γ1, γ2, γ3 are all regression coefficients.

6. The printing color difference defect detection method based on the artificial intelligence system according to claim 5 is characterized in that: The impact analysis module analyzes the impact of the aluminum foil and tape themselves. The analysis steps are as follows: Step 1: The influencing factors of the aluminum foil metal layer of aluminum foil and tape include roughness, flatness, ink type, ink thickness and printing uniformity; if ΔE is judged to be increased, Δa and Δb are compared. If Δa and Δb are close to zero, it is judged to be a color difference defect caused by increased roughness; if Δa and Δb increase, it is judged to be a color difference defect caused by increased ink thickness or decreased roughness. The change of ink thickness is judged. If the ink thickness increases, the color difference value Δa caused by the increase in ink thickness is calculated based on the comparison of the increase in ink thickness. Y1 and Δb Y1 , and Δa Y1 and Δb Y1 y is compared with the detected color difference values ​​Δa and Δb; Step 2: If the two are equal, it is determined that the color difference defect is caused by the increase in ink thickness; if Δa Y1 <Δa and Δb Y1 <Δb, the color difference defect caused by the increase in the thickness of the aluminum foil coating ink and the decrease in roughness is determined, and the color difference value Δa caused by the decrease in roughness is calculated C1 and Δb C1 If the sum of the two color difference data caused by the increase of ink thickness and the decrease of roughness is equal to Δa and Δb respectively, the color difference defect caused by the increase of ink thickness and the decrease of roughness is determined, otherwise, other influencing factors are determined; CC1 and CC2 are the roughness data collected at two moments before and after, respectively; Step 3: Comprehensively analyze the influence of five data, namely, roughness CC, flatness PZ, ink type YML, ink thickness YMH and printing uniformity JY, on color difference defect detection, ΔE LB =ρ0+ρ1*CC+ρ2*PZ+ρ3*YML+ρ4*YMH+ρ5*JY+β, β is the deviation value, and ρ0, ρ1, ρ2, ρ3, ρ4, and ρ5 are all regression coefficients.

7. The printing color difference defect detection method based on the artificial intelligence system according to claim 6 is characterized in that: The impact analysis module analyzes the impact of the tester's own factors. The analysis steps are as follows: Step 1: The influencing factors of the tester itself include the image acquisition angle and the image acquisition distance; if ΔE is judged to be increasing, Δa and Δb are compared. If Δa and Δb are unstable, it is judged to be a color difference defect caused by the change of image acquisition angle; Step 2: If both Δa and Δb increase, it is determined that the color difference defect is caused by the image acquisition distance becoming closer, and an instrument adjustment signal is generated and transmitted to the operation adjustment module; Step 3: Comprehensively analyze the impact of the two data of acquisition angle JD and acquisition distance JL on color difference defect detection. is the deviation value, ω0, ω1, ω2 are all regression coefficients.

8. The method for detecting color difference defects in printing based on an artificial intelligence system according to claim 7, characterized in that: The steps for the impact analysis module to explore the causes of color difference defects are as follows: Step 1: Statistic the impact of three factors: environmental factors, aluminum foil and tape factors, and tester factors. The statistical results are recorded as increasing ZD, decreasing JX, unstable BWD, less influential YXX, and approaching zero QJO. Step 2: If it is determined that there are color difference defects in the monitoring area of ​​the aluminum foil and the tape, multiple color difference detection results of the monitoring area of ​​the same color difference tester body 1 are retrieved and arranged in the detection order; if the color difference detection results show that Δa and Δb are close to zero, the environmental pollutants, the roughness of the metal surface of the aluminum foil and the tape, and the change in image acquisition distance that cause Δa and Δb to approach zero are determined; if the color difference detection results show that Δa and Δb are unstable, the change in image acquisition angle, flatness reduction, ink type change, and printing uniformity change that cause Δa and Δb to be unstable are determined; if Δa and Δb are unstable, but ΔL is stable, it is determined that it is caused by a change in the image acquisition angle, and the image acquisition angle is analyzed; Step 3: If ΔE increases, and the changes in Δa and Δb are less than 10% of their respective corresponding set thresholds, it is determined that the color difference defect is caused by environmental factors, and the data change of ΔL is analyzed; if the change in ΔL is also less than 10% of the corresponding set threshold, it is determined that the image color difference defect is caused by the decrease in environmental humidity, otherwise, it is determined that the image color difference defect is caused by the change in ambient temperature; Step 4: If the rise and fall changes of ΔL, Δa and Δb exceed 50% of the preset change value, the three influencing factors of environmental factors, aluminum foil and tape factors, and tester factors are identified one by one to determine the influencing factors that cause image color difference defects; Step 5: Total change value ΔE of color difference data ZJ =ΔE GZ +ΔE HJ +ΔE LB +ΔE YQ When the color difference data output results show an increase or decrease, the four influencing factors of light, environment, aluminum foil and tester are checked simultaneously. If a factor in the influencing factors is found to have changed, the color difference data change value caused by the change of the factor is recorded, and then the color difference data change values ​​caused by the changes of each factor are accumulated and summed to obtain the inferred color difference total value ΔE ZT , if |ΔE ZT -ΔE ZJ | / ΔE ZT If the value is less than 0.2, the color difference defect is judged to be caused by the change of the corresponding influencing factors. Otherwise, the test is repeated.

9. The printing color difference defect detection method based on the artificial intelligence system according to claim 8 is characterized in that: An operation adjustment module is also provided inside the color difference tester body (1). The adjustment steps of the operation adjustment module are as follows: Step 1: receiving an instrument angle adjustment signal, measuring the current deflection angle value of the color difference tester body (1), and calculating the difference between the detected deflection angle value and the preset angle value, and the obtained angle difference value is the angle to be adjusted of the color difference tester body (1); Step 2: Receive the instrument distance adjustment signal, measure the distance data between the color difference tester body (1) and the aluminum foil and the tape, and calculate the difference between the detected distance data and the preset distance data. The distance difference value obtained is the distance adjustment amount of the color difference tester body (1).

10. A printing color difference defect detection device based on an artificial intelligence system, applied to the printing color difference defect detection method based on an artificial intelligence system as described in any one of claims 1 to 9, characterized in that: The color difference tester comprises a color difference tester body (1), a display screen (2) is arranged above the front surface of the color difference tester body (1), a control button (3) is arranged on the side of the front surface of the color difference tester body (1) corresponding to the display screen (2), a measuring port (4) is installed at the lower end of the color difference tester body (1), a clamping frame (5) is installed below the outer side wall of the color difference tester body (1), and a mechanical arm (6) is rotatably connected to one side of the outer side wall of the clamping frame (5) via a rotating seat.

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