Quality detection method and system for self-adhesive printed products based on artificial intelligence

Abstract

The present invention discloses a quality detection method and system for self-adhesive printed products based on artificial intelligence, and belongs to the technical field of printed product detection. The method comprises the following steps: activating each detection device for initial calibration, executing a production start signal to a production control port for the production of self-adhesive printed products, acquiring basic production data of self-adhesive printed products for processing, obtaining basic characteristic values ​​of self-adhesive printed products, and generating production quality constraint parameters of self-adhesive printed products, and monitoring the production of self-adhesive printed products through each detection device to obtain real-time production quality parameters of self-adhesive printed products, and combining the production quality constraint parameters and the real-time production quality parameters to obtain real-time production quality inspection values. The present invention achieves the effect of improving the timeliness of quality detection of self-adhesive printed products by combining the production quality constraint parameters and the real-time production quality parameters, and solves the problem of poor timeliness of quality detection of self-adhesive printed products in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of printed matter detection, and in particular to a quality detection method and system for self-adhesive printed matter based on artificial intelligence. Background Art

[0002] Self-adhesive printed products are widely used in labels, trademarks, packaging and other fields. With the development of self-adhesive printing technology, production efficiency and printing quality have been improved. However, there are many uncertain factors in the production process (such as equipment, materials, etc.), and the quality of self-adhesive printed products still often has problems. Therefore, it is of great significance to detect the quality of self-adhesive printed products.

[0003] For example, the invention patent with announcement number: CN118096745B announces a method and system for detecting the quality of printed products based on artificial intelligence, including: collecting equipment parameters in the production process of printed products, establishing a corresponding relationship between equipment parameters and printed content, configuring the fluctuation range of equipment parameters, and dividing the printed content into normal positions and defective positions according to the fluctuation range; superimposing detection rules on the printed content. By generating a detection report, the present invention can visualize the detection data and more intuitively display the defect data of the printed product; superimposing detection rules on the printed content, wherein the detection rules include spot-checking normal positions and must-check defective positions, building a network architecture, inserting convolutional layers, configuring output layers, and generating convolutional neural networks, so as to better provide decision support for producers. At the same time, while ensuring the detection effect, the equipment parameters are used to greatly reduce the workload of detection.

[0004] For example, a printed product quality detection method is announced in the invention patent with announcement number: CN106251341B, including: generating a standard character image information library based on the character image to be detected; determining the optimal horizontal and vertical scaling coefficients; preprocessing the character image to be detected to obtain a valid character image area; sequentially segmenting the characters in the valid character image area, and matching and detecting each segmented single character image; segmenting the next character based on the matching detection result of the current single character image, and matching and detecting the next segmented single character image until all the characters in the character image to be detected are detected; determining the printing quality of the character image to be detected based on the matching detection results of all the characters in the character image to be detected.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0006] In the prior art, the corresponding in-production inspection is usually performed on the printed matter in real life. The timeliness of the inspection only meets the needs of the production process. The production inspection of self-adhesive printed matter involves multiple inspection equipment. Once an operational defect occurs in the production, the quality inspection of the self-adhesive printed matter will be inaccurate. The quality inspection of self-adhesive printed matter has the problem of poor timeliness. Summary of the invention

[0007] The embodiment of the present application solves the problem of poor timeliness of quality inspection of self-adhesive printed products in the prior art by providing a quality inspection method and system for self-adhesive printed products based on artificial intelligence, and achieves accurate and effective quality inspection of self-adhesive printed products.

[0008] The embodiment of the present application provides a quality detection method and system for self-adhesive printed products based on artificial intelligence, including the following steps: the edge processor senses the production start signal, and activates each detection device for initial calibration, obtains the initial calibration result and performs corresponding calibration processing; the edge processor receives the calibration processing cutoff signal, and transmits the executable production start signal to the production control port to produce the self-adhesive printed products; the basic production data of the self-adhesive printed products is obtained for processing to obtain the basic characteristic values ​​of the self-adhesive printed products, and the production quality constraint parameters of the self-adhesive printed products are generated, and the production of the self-adhesive printed products is monitored through each detection device to obtain the real-time production quality parameters of the self-adhesive printed products; data fusion processing is performed according to the production quality constraint parameters of the self-adhesive printed products and the real-time production quality parameters of the self-adhesive printed products to obtain the real-time production quality inspection value of the self-adhesive printed products, and the corresponding production detection configuration is executed.

[0009] Furthermore, the activation of each detection device for initial calibration has the following specific process: activating each detection device for initial calibration, acquiring initial data of each detection device, analyzing to obtain initial verification values ​​of each detection device, wherein the initial verification values ​​are used to detect the initial operating state of each detection device; the initial data of each detection device include: operating frequency, response time, transient response voltage and transient response current.

[0010] Furthermore, the initial calibration result is obtained and the corresponding calibration processing is performed. The specific process is: obtain the preset initial verification threshold value of each detection device, compare the initial verification value of each detection device with the corresponding initial verification threshold value, when the initial verification value of a detection device is less than the initial verification threshold value of the detection device, then the initial calibration result of the detection device is defined as a normal state, and the calibration processing is not performed; when the initial verification value of a detection device is greater than or equal to the initial verification threshold value of the detection device, then the initial calibration result of the detection device is defined as an abnormal state, and the detection device is calibrated, and a calibration warning prompt message is simultaneously generated to the management port for display processing.

[0011] Furthermore, the basic production data of the self-adhesive printed matter is obtained and processed to obtain the basic characteristic values ​​of the self-adhesive printed matter. The specific process is: the basic production data of the self-adhesive printed matter includes substrate basic data and printing basic data; the substrate basic data includes: substrate thickness, substrate surface gloss and substrate ink absorption per unit area; the printing basic data includes: color type of the printing design drawing, color saturation of the printing design drawing, dot ratio of the printing design drawing and printing design pattern area; processing is performed based on the substrate basic data and the printing basic data to obtain the basic characteristic values ​​of the self-adhesive printed matter, and the basic characteristic values ​​are used to characterize the printing complexity of the self-adhesive printed matter.

[0012] Furthermore, the production quality constraint parameters of the self-adhesive printed product are generated by matching the basic characteristic values ​​of the self-adhesive printed product with the production quality constraint parameters corresponding to each basic characteristic value interval stored in the production database of the self-adhesive printed product, and counting the production quality constraint parameters corresponding to the interval in which the basic characteristic values ​​of the self-adhesive printed product are located, which are recorded as the production quality constraint parameters of the self-adhesive printed product; the production quality constraint parameters of the self-adhesive printed product include: the allowable error of the average color difference value, the allowable error of the printing speed, the allowable error of the printing pressure, the allowable error of the average thickness of the printing layer, and the allowable error of the paper warping.

[0013] Furthermore, the real-time production quality parameters of the self-adhesive printed matter are obtained by performing production inspection on the self-adhesive printed matter to obtain the real-time quality parameters of the self-adhesive printed matter; the real-time quality parameters include: the average color difference value of the color area of ​​the printed matter, the printing speed, the printing pressure, the average thickness of the printing layer and the average warping of the paper.

[0014] Furthermore, the data fusion processing is performed based on the production quality constraint parameters of the self-adhesive printed products and the real-time production quality parameters of the self-adhesive printed products. The specific process is: obtaining the operation influencing parameters of each detection equipment of the self-adhesive printed products, and processing them to obtain the real-time inspection value of the operation parameters of each detection equipment; based on the operation parameter verification value of each detection equipment, the production quality constraint parameters of the self-adhesive printed products and the real-time production quality parameters of the self-adhesive printed products are data-fused to obtain the real-time production quality inspection value of the self-adhesive printed products; the operation influencing parameters of each detection equipment include: real-time operating frequency, real-time voltage and real-time current.

[0015] Furthermore, the real-time production quality inspection value of the self-adhesive printed matter is specifically obtained by:

[0016]

[0017] In the formula, α represents the real-time production quality inspection value of the self-adhesive printed matter, E represents the average color difference value, ΔE represents the allowable error of the average color difference value, S represents the printing speed, S 1 It is represented as the standard value of printing speed, ΔS is represented as the permissible error of printing speed, A is represented as printing pressure, and A 1 It is represented by printing pressure, ΔA is the permissible error of printing pressure, C is the average thickness of the printing layer, and C 1 It is expressed as the reference value of the average thickness of the printing layer, ΔC is expressed as the allowable error of the average thickness of the printing layer, L is expressed as the paper warpage, ΔL is expressed as the allowable error of the paper warpage, γ i Represents the initial calibration value of the i-th detection device, γ si It is represented as the real-time inspection value of the operating parameters of the i-th detection device, i=1,2,...I, i is the number of the detection device, I is the total number of detection devices, and e is a natural constant.

[0018] Furthermore, the specific process of executing the corresponding production inspection configuration is: obtaining a preset real-time production quality inspection threshold, comparing the real-time production quality inspection value of the self-adhesive printed product with the real-time production quality inspection threshold, when the real-time production quality inspection value of the self-adhesive printed product is less than the real-time production quality inspection threshold, no adjustment is made, and when the real-time production quality inspection value of the self-adhesive printed product is greater than or equal to the real-time production quality inspection threshold, the production inspection configuration is adjusted.

[0019] The embodiment of the present application provides a quality inspection system for self-adhesive printed products based on artificial intelligence, including: an initial calibration module, which is used for the edge processor to sense the production start signal, and activate each detection device to perform initial calibration, obtain the initial calibration result and perform corresponding calibration processing; a production execution module, which is used for the edge processor to receive the calibration processing cutoff signal, and transmit the executable production start signal to the production control port to produce self-adhesive printed products; a production quality monitoring module, which is used to obtain the basic production data of the self-adhesive printed products for processing, obtain the basic characteristic value of the self-adhesive printed products, and generate the production quality constraint parameters of the self-adhesive printed products, and monitor the production of the self-adhesive printed products through each detection device to obtain the real-time production quality parameters of the self-adhesive printed products; a production quality inspection module, which is used to perform data fusion processing according to the production quality constraint parameters of the self-adhesive printed products and the real-time production quality parameters of the self-adhesive printed products, obtain the real-time production quality inspection value of the self-adhesive printed products, and execute the corresponding production inspection configuration.

[0020] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0021] 1. By obtaining the initial data of each detection equipment, analyzing the initial operating status of each detection equipment and performing initial calibration, the normal operation of each detection equipment is guaranteed, and the problem of inaccurate detection results caused by abnormal detection equipment is reduced. By obtaining the basic characteristic values ​​of self-adhesive printed products, the printing complexity of self-adhesive printed products is analyzed, and the corresponding production quality constraint parameters of self-adhesive printed products are obtained according to different printing complexities. It is realized that the corresponding error range is determined according to the different printing complexities of self-adhesive printed products, and the problem of inaccurate detection of self-adhesive printed products caused by the same error standard is reduced.

[0022] 2. By obtaining the real-time production quality inspection value of self-adhesive printed products and integrating the production quality constraint parameters of self-adhesive printed products to perform production quality inspection of self-adhesive printed products, it is possible to effectively and accurately perform quality inspection on printed products with different printing complexities, accurately improve the accuracy of quality inspection of self-adhesive printed products, and make corresponding production inspection configurations based on the inspection results, effectively controlling the production quality of self-adhesive printed products.

[0023] 3. The present invention combines real-time production quality inspection values, production quality constraint parameters and real-time inspection values ​​of operating parameters of various detection equipment, comprehensively considers multiple factors in the quality inspection process of self-adhesive printed products, can accurately inspect the production quality of self-adhesive printed products, and ensures the accuracy of the inspection. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flow chart of a quality detection method for self-adhesive printed matter based on artificial intelligence provided in an embodiment of the present application;

[0025] Figure 2 A schematic diagram of the structure of a quality inspection system for self-adhesive printed products based on artificial intelligence provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] The embodiments of the present application solve the problem of poor timeliness of quality inspection of self-adhesive printed products in the prior art by providing a quality inspection method and system for self-adhesive printed products based on artificial intelligence. The embodiments of the present application solve the problem of poor timeliness of quality inspection of self-adhesive printed products in the prior art by obtaining initial data of each inspection device, analyzing the initial operating status of each inspection device and performing initial calibration, thereby ensuring the normal operation of each inspection device and reducing the problem of inaccurate inspection results caused by abnormal inspection equipment. The embodiments of the present application also solve the problem of inaccurate inspection results caused by abnormal inspection equipment by obtaining basic characteristic values ​​of self-adhesive printed products, analyzing the printing complexity of self-adhesive printed products, and obtaining corresponding production quality constraint parameters of self-adhesive printed products according to different printing complexities. The corresponding error range is determined according to the different printing complexities of self-adhesive printed products, thereby reducing the problem of inaccurate inspection of self-adhesive printed products due to the same error standard.

[0027] The technical solution in the embodiment of the present application is to solve the problem of poor timeliness in the quality inspection of the above-mentioned self-adhesive printed matter, and the overall idea is as follows:

[0028] The initial calibration result of each detection device is obtained by acquiring the initial data of each detection device, and each detection device is initially calibrated. Then, the basic data of the substrate and the basic printing data of the self-adhesive printed product are obtained to obtain the basic characteristic values ​​of the self-adhesive printed product. The printing complexity of the self-adhesive printed product is analyzed according to the basic characteristic values, and the corresponding production quality constraint parameters of the self-adhesive printed product are generated. In combination with the real-time production quality parameters and production quality constraint parameters of the self-adhesive printed product, the production quality of the self-adhesive printed product is analyzed and adjusted. The initial calibration of each detection device is carried out and the production quality analysis is carried out in combination with the production quality constraint parameters, thereby realizing accurate and effective detection of the production quality of the self-adhesive printed product.

[0029] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0030] like Figure 1 As shown, it is a flow chart of the quality detection method of self-adhesive printed products based on artificial intelligence provided by an embodiment of the present application, and the method includes the following steps: the edge processor senses the production start signal, and activates each detection device for initial calibration, obtains the initial calibration result and performs corresponding calibration processing; the edge processor receives the calibration processing cutoff signal, and transmits the executable production start signal to the production control port to produce the self-adhesive printed products; the basic production data of the self-adhesive printed products is obtained for processing to obtain the basic characteristic values ​​of the self-adhesive printed products, and the production quality constraint parameters of the self-adhesive printed products are generated, and the production of the self-adhesive printed products is monitored by each detection device to obtain the real-time production quality parameters of the self-adhesive printed products; data fusion processing is performed according to the production quality constraint parameters of the self-adhesive printed products and the real-time production quality parameters of the self-adhesive printed products to obtain the real-time production quality inspection value of the self-adhesive printed products, and the corresponding production detection configuration is executed.

[0031] In this embodiment, the edge processor refers to a device for sensing a production start signal. The edge processor senses the production start signal through a connected sensor or directly receives a signal from a machine. After sensing the production start signal of the self-adhesive printed product, the edge processor activates and starts each detection device, and then starts initial calibration, evaluates the initial condition of each detection device, and calibrates according to the initial condition. After the calibration process of each detection device is completed, a calibration cutoff signal is sent to the edge processor. After receiving the calibration process cutoff signal, the edge processor sends an executable production start signal to the production control port to start production. The production control port is a port that controls the start and end of production.

[0032] Furthermore, the activation of each detection device for initial calibration has the following specific process: activating each detection device for initial calibration, acquiring initial data of each detection device, analyzing to obtain initial verification values ​​of each detection device, wherein the initial verification values ​​are used to detect the initial operating state of each detection device; the initial data of each detection device include: operating frequency, response time, transient response voltage and transient response current.

[0033] In this embodiment, the specific process of obtaining the initial verification value of each detection device is as follows:

[0034]

[0035] In the formula, γ i represents the initial calibration value of the i-th detection device, i=1,2,...I, I is the total number of detection devices, F i Represents the operating frequency of the i-th detection device, F i1 represents the preset reference value of the working frequency of the i-th detection device, T i represents the response time of the i-th detection device, T i1 represents the preset reference value of the response time of the i-th detection device, U i Represents the transient response voltage of the i-th detection device, U i1 Represents the preset transient response voltage reference value of the i-th detection device, I i Represents the transient response current of the i-th detection device, I i1 represents the preset transient response current reference value of the ith detection device, and e is a natural constant.

[0036] In this embodiment, the operating frequency represents the frequency used by each detection device when it is working, the response time represents the time required for each detection device to output the detection result from receiving the signal (such as voltage and current changes), the transient response voltage represents the response capability of each detection device to the voltage change in a short time (transient), and the transient response current represents the response capability of each detection device to the transient change of current. The operating frequency is obtained by a frequency meter, and the response time, transient response voltage and transient response current can be obtained by an oscilloscope. The operating frequency reference value, the response time reference value, the transient response voltage reference value and the transient response current reference value are obtained from the database.

[0037] In this embodiment, the operating frequency, response time, transient response voltage and transient response current of each detection device influence each other and are interrelated. When the operating frequency is higher, the response time will be shortened accordingly. If the operating frequency is too high, the transient response voltage and transient response current of each detection device will increase. If the operating frequency is too low, the response ability of each detection device to rapidly changing signals will be reduced. Detection devices with shorter response time require higher transient response voltage and transient response current to process rapidly changing signals. When the operating frequency increases, the response time will become shorter and higher transient response voltage and transient response current will be caused. When the transient response voltage is higher, the transient response current will also be higher. The greater the difference between the operating frequency, transient response voltage and transient response current of each detection device and the corresponding preset operating frequency reference value, transient response voltage reference value and transient response current reference value, the longer the response time and the corresponding initial calibration value of the detection device will also become larger.

[0038] Furthermore, the initial calibration result is obtained and the corresponding calibration processing is performed. The specific process is: obtain the preset initial verification threshold value of each detection device, compare the initial verification value of each detection device with the corresponding initial verification threshold value, when the initial verification value of a detection device is less than the initial verification threshold value of the detection device, then the initial calibration result of the detection device is defined as a normal state, and the calibration processing is not performed; when the initial verification value of a detection device is greater than or equal to the initial verification threshold value of the detection device, then the initial calibration result of the detection device is defined as an abnormal state, and the detection device is calibrated, and a calibration warning prompt message is simultaneously generated to the management port for display processing.

[0039] In this embodiment, when the initial verification value of a detection device is less than the initial verification threshold of the detection device, the initial calibration result of the detection device is normal, and the calibration process is not performed. The quality inspection of self-adhesive printed products is performed normally. When the initial verification value of a detection device is greater than or equal to the corresponding initial verification threshold, the initial calibration result of the detection device is abnormal. The detection device is initialized, and an early warning is issued for the operating status of the detection device to remind relevant personnel to replace or maintain the detection device, and a calibration early warning information value management port is generated to remind relevant personnel.

[0040] Furthermore, the basic production data of the self-adhesive printed matter is obtained and processed to obtain the basic characteristic values ​​of the self-adhesive printed matter. The specific process is: the basic production data of the self-adhesive printed matter includes substrate basic data and printing basic data; the substrate basic data includes: substrate thickness, substrate surface gloss and substrate ink absorption per unit area; the printing basic data includes: color type of the printing design drawing, color saturation of the printing design drawing, dot ratio of the printing design drawing and printing design pattern area; processing is performed based on the substrate basic data and the printing basic data to obtain the basic characteristic values ​​of the self-adhesive printed matter, and the basic characteristic values ​​are used to characterize the printing complexity of the self-adhesive printed matter.

[0041] In this embodiment, the basic characteristic value of the self-adhesive printed product is obtained by comprehensive processing of the substrate basic value and printing basic value of the self-adhesive printed product. The substrate basic value of the self-adhesive printed product is obtained by analyzing the substrate basic data of the self-adhesive printed product. The printing basic value of the self-adhesive printed product is obtained by analyzing the printing basic data of the self-adhesive printed product.

[0042] The specific process of obtaining the base value of the substrate of the self-adhesive printed matter is as follows:

[0043]

[0044] Where P B Represents the base value of the self-adhesive printed product, H represents the thickness of the substrate, H 1 represents the preset reference value of substrate thickness, G represents the surface gloss of the substrate, G 1 represents the preset reference value of substrate surface glossiness, K represents the amount of ink absorbed per unit area of ​​substrate, K 1 Represents the preset reference value of the amount of ink absorbed per unit area of ​​the substrate, b 1 represents the substrate thickness weight factor, b 2 represents the glossiness weight factor of the substrate surface, b 3 It represents the weight factor of the ink absorption per unit area of ​​the substrate, and e is a natural constant.

[0045] In this embodiment, the substrate thickness represents the thickness of the substrate used for the self-adhesive printed matter, the substrate surface gloss represents the degree of light reflection on the substrate surface, the substrate unit area ink absorption represents the amount of ink absorbed by the substrate unit area, the substrate thickness is obtained by a thickness meter, the substrate surface gloss is obtained by a gloss meter, and the substrate unit area ink absorption is obtained by an ink absorption meter. The substrate thickness reference value, the substrate surface gloss reference value, and the substrate unit area ink absorption reference value are obtained from a database.

[0046] In this embodiment, b 1 、b 2 and b 3The value range of is [0, 1]. The substrate thickness, substrate surface glossiness and substrate ink absorption per unit area of ​​the self-adhesive printed matter can be counted, and combined with a pre-defined mapping function, the weight factors corresponding to the substrate thickness, substrate surface glossiness and substrate ink absorption per unit area can be obtained. For example, the weight factors of substrate thickness, substrate surface glossiness, substrate ink absorption per unit area and substrate thickness, substrate surface glossiness and substrate ink absorption per unit area form a mapping function. In a specific application, the real-time substrate thickness, substrate surface glossiness and substrate ink absorption per unit area are input into the mapping function to obtain the corresponding weight factors.

[0047] In this embodiment, there is a certain correlation between the substrate thickness, substrate surface gloss and substrate unit area ink absorption of the self-adhesive printed matter. The ink absorption of thick substrates is usually lower, that is, the thicker the substrate thickness, the lower the substrate unit area ink absorption. The higher the substrate surface gloss, the smoother the substrate surface, the less likely the ink is to adhere, and the lower the substrate unit area ink absorption. The thicker the substrate thickness, the higher the substrate surface gloss, the greater the substrate unit area ink absorption, the greater the difficulty of printing the self-adhesive printed matter, and the greater the substrate base value of the self-adhesive printed matter.

[0048] The specific process of obtaining the printing basic value of self-adhesive printed products is as follows:

[0049]

[0050] Where P I Represents the printing base value of the self-adhesive printed matter, N represents the color type of the printed design, N 1 represents the color type threshold of the preset printing design, M represents the color saturation of the printing design, and M 1 represents the color saturation threshold of the preset printing design, B represents the dot ratio of the printing design, and B 1 represents the preset dot ratio critical value of the printing design, R represents the printing design pattern area, R 1 Represents the preset critical value of the printed design area, d 1 Represents the color type weight factor of the printed design, d 2 Represents the color saturation weight factor of the printed design, d 3 Represents the dot ratio weight factor of the printed design, d 4 Represents the area weight factor of the printed design pattern, and e is a natural constant.

[0051] In this embodiment, the color type of the printing design drawing represents the type of color used in the printing design drawing, the color saturation of the printing design drawing represents the brightness of the printing design drawing, the dot ratio of the printing design drawing represents the distribution density of the dots in the printing design drawing, the dot ratio refers to the ink dot density of the unit area in the printing design image, the printing design pattern area represents the area of ​​the printing design pattern, the color type of the printing design drawing, the color saturation of the printing design drawing, the dot ratio of the printing design drawing and the printing design pattern area are obtained through image analysis software, and the preset color type critical value of the printing design drawing, the preset color saturation critical value of the printing design drawing, the preset dot ratio critical value of the printing design drawing and the preset printing design pattern area critical value are obtained from the database.

[0052] In this embodiment, the color type of the printing design drawing and the weight factor of the color type of the printing design drawing are associated through a preset mapping relationship. For example, after the color type of the real-time printing design drawing is input into the preset mapping relationship, the corresponding weight factor is obtained. The color saturation of the printing design drawing and the weight factor of the color saturation of the printing design drawing are associated through a preset mapping relationship. For example, after the color saturation of the real-time printing design drawing is input into the preset mapping relationship, the corresponding weight factor is obtained. The dot ratio of the printing design drawing and the weight factor of the dot ratio of the printing design drawing are associated through a preset mapping relationship. For example, after the dot ratio of the real-time printing design drawing is input into the preset mapping relationship, the corresponding weight factor is obtained. The printing design pattern area and the weight factor of the printing design pattern area are associated through a preset mapping relationship. For example, after the real-time printing design pattern area is input into the preset mapping relationship, the corresponding weight factor is obtained.

[0053] In this embodiment, the color types, color saturation, dot ratio and area of ​​the printed design are mutually influenced. The more color types the printed design has, the richer and more accurate color expression can be obtained. More color types require more dot levels, which will increase the dot ratio of the printed design. More color types usually make the color saturation of the printed design higher. The higher the dot ratio of the printed design, the wider the color coverage and the richer the layering of the image. The higher the color saturation of the printed design and the larger the area of ​​the printed design, the higher the dot ratio of the printed design is required to ensure the consistency and saturation of the color. The color saturation is proportional to the dot ratio, and a higher saturation requires a higher dot ratio.

[0054] In this embodiment, the specific process of obtaining the basic characteristic value of the self-adhesive printed product is as follows:

[0055] PZ =log (1+e) (P B +P I ).

[0056] Where P Z Represents the basic characteristic value of the self-adhesive printed matter, P B Represents the base value of the self-adhesive printed matter, P I Represents the printing base value of self-adhesive printed materials.

[0057] In this embodiment, the basic characteristic value of the self-adhesive printed product represents the printing complexity of the self-adhesive printed product, that is, the printing difficulty of the self-adhesive printed product, and the substrate basic value of the self-adhesive printed product represents the printing difficulty of the substrate of the self-adhesive printed product. The larger the printing basic value of the self-adhesive printed product, the more complex the printing design drawing of the self-adhesive printed product is, that is, the printing difficulty of the printing design drawing. The larger the substrate basic value of the self-adhesive printed product and the printing basic value of the self-adhesive printed product are, the greater the printing complexity of the self-adhesive printed product, that is, the larger the basic characteristic value of the self-adhesive printed product is.

[0058] Furthermore, the production quality constraint parameters of the self-adhesive printed product are generated by matching the basic characteristic values ​​of the self-adhesive printed product with the production quality constraint parameters corresponding to each basic characteristic value interval stored in the production database of the self-adhesive printed product, and counting the production quality constraint parameters corresponding to the interval in which the basic characteristic values ​​of the self-adhesive printed product are located, which are recorded as the production quality constraint parameters of the self-adhesive printed product; the production quality constraint parameters of the self-adhesive printed product include: the allowable error of the average color difference value, the allowable error of the printing speed, the allowable error of the printing pressure, the allowable error of the average thickness of the printing layer, and the allowable error of the paper warping.

[0059] In this embodiment, the basic characteristic values ​​of the self-adhesive printed product are matched with the basic characteristic value intervals of the self-adhesive printed product stored in the database, and the production quality constraint parameters corresponding to the basic characteristic value intervals of the corresponding self-adhesive printed product are obtained, the allowable error of the average color difference value represents the allowable average color difference value, the allowable error of the ink density of the substrate represents the allowable error of the ink density of the substrate, the allowable error of the printing speed represents the allowable error of the printing speed, the allowable error of the printing pressure represents the allowable error of the printing pressure, the allowable error of the average thickness of the printing layer represents the allowable error of the average thickness of the printing layer, and the allowable error of the paper warpage represents the allowable paper warpage.

[0060] Furthermore, the real-time production quality parameters of the self-adhesive printed matter are obtained by performing production inspection on the self-adhesive printed matter to obtain the real-time quality parameters of the self-adhesive printed matter; the real-time quality parameters include: the average color difference value of the color area of ​​the printed matter, the printing speed, the printing pressure, the average thickness of the printing layer and the average warping of the paper.

[0061] In this embodiment, the average color difference value of the color area of ​​the printed product represents the average difference between the color area of ​​the printed product and the standard color, the printing speed is the amount of printing work that can be completed by the printing machine per unit time, the printing pressure refers to the force applied between the printing plate and the substrate during the printing process, the average thickness of the printing layer refers to the thickness of the ink layer printed on the substrate, and the average warpage of the paper refers to the degree of bending or deformation of the paper during the printing and processing process. The average color difference value of the printed color area of ​​the self-adhesive printed product is obtained by obtaining the color data of the printed product and the color data of the printed design drawing by a colorimeter, and uploading all the color data to the color management software for analysis and calculation. The printing speed can be directly obtained through the printing machine, the printing pressure is obtained through a pressure sensor, the average thickness of the printing layer is obtained through a thickness meter, and the average warpage of the paper is obtained through a warpage tester.

[0062] Furthermore, the data fusion processing is performed based on the production quality constraint parameters of the self-adhesive printed products and the real-time production quality parameters of the self-adhesive printed products. The specific process is: obtaining the operation influencing parameters of each detection equipment of the self-adhesive printed products, and processing them to obtain the real-time inspection value of the operation parameters of each detection equipment; based on the operation parameter verification value of each detection equipment, the production quality constraint parameters of the self-adhesive printed products and the real-time production quality parameters of the self-adhesive printed products are data-fused to obtain the real-time production quality inspection value of the self-adhesive printed products; the operation influencing parameters of each detection equipment include: real-time operating frequency, real-time voltage and real-time current.

[0063] In this embodiment, the specific process of obtaining the real-time test value of the operating parameter of each detection device is as follows:

[0064]

[0065] In the formula, γ si represents the real-time test value of the operating parameters of the i-th detection device, i = 1, 2, ... I, I is the total number of detection devices, D si represents the real-time operating frequency of the i-th detection device, D si′ represents the real-time operating frequency reference value of the i-th detection device, U si Represents the real-time voltage of the i-th detection device, U si′ Represents the real-time voltage reference value of the i-th detection device, I si Represents the real-time current of the i-th detection device, I si′Represents the real-time current reference value of the i-th detection device.

[0066] In this embodiment, the real-time current and the real-time voltage are positively correlated, and changes in the real-time operating frequency will also cause changes in the real-time current and the real-time voltage. The real-time operating frequency, the real-time voltage and the real-time current affect the basic characteristics of each detection device. The real-time operating frequency, the real-time voltage and the real-time current have a direct impact on the quality detection results of the self-adhesive prints. Unstable real-time operating frequency, real-time voltage and real-time current will cause the performance of each detection device to be unstable, thereby making the obtained printing speed, printing pressure, average color difference value, average thickness of the printing layer and average warping unstable or inaccurate, which will affect the quality results of the self-adhesive prints.

[0067] In this embodiment, the real-time operating frequency represents the real-time operating frequency of the detection device, the real-time voltage represents the real-time voltage of the detection device, and the real-time current represents the real-time current of the detection device. The real-time operating frequency, real-time voltage and real-time current are obtained through the power quality analyzer.

[0068] Furthermore, the real-time production quality inspection value of the self-adhesive printed matter is specifically obtained by:

[0069]

[0070] In the formula, α represents the real-time production quality inspection value of the self-adhesive printed matter, E represents the average color difference value, ΔE represents the allowable error of the average color difference value, S represents the printing speed, S 1 It is represented as the standard value of printing speed, ΔS is represented as the permissible error of printing speed, A is represented as printing pressure, and A 1 It is represented by printing pressure, ΔA is the permissible error of printing pressure, C is the average thickness of the printing layer, and C 1 It is expressed as the reference value of the average thickness of the printing layer, ΔC is expressed as the allowable error of the average thickness of the printing layer, L is expressed as the paper warpage, ΔL is expressed as the allowable error of the paper warpage, γ i Represents the initial calibration value of the i-th detection device, γ si It is represented as the real-time inspection value of the operating parameters of the i-th detection device, i=1,2,...I, i is the number of the detection device, I is the total number of detection devices, and e is a natural constant.

[0071] In this embodiment, the average color difference value of the color area of ​​the printed matter, the printing speed, the printing pressure, the average thickness of the printing layer, the average warping of the paper, the initial verification value and the real-time verification value of the operating parameters all have a certain influence on the quality of the self-adhesive printed matter, and there is a certain correlation between them. A printing speed that is too high may cause uneven ink distribution or cause the printed design pattern to be blurred. A printing speed that is too fast may cause the ink to fail to be fully absorbed, thereby affecting the ink density and the average color difference value, and making the average thickness of the printing layer thinner. The printing pressure affects the amount of ink transferred to the paper. Excessive printing pressure may cause uneven ink distribution, thereby causing the average color difference value to increase, the paper warping to increase, and the average thickness of the printing layer to increase. The initial verification value represents the initial operating state of each detection device. The smaller the initial verification value of each detection device, the more stable the initial operating state of each detection device, and the more accurate the detection of the quality of the self-adhesive printed matter. The real-time verification value of the operating parameters represents the real-time operating state of each detection device. The smaller the real-time verification value of the operating parameters, the more stable the real-time operating state of the detection device, and the more accurate the detection of the quality of the self-adhesive printed matter. The larger the initial calibration value and the real-time inspection value of the operating parameters are, the less accurate the measurement values ​​of each detection device are, that is, the less accurate the real-time production quality inspection value of the self-adhesive printed product is.

[0072] Furthermore, the specific process of executing the corresponding production inspection configuration is: obtaining a preset real-time production quality inspection threshold, comparing the real-time production quality inspection value of the self-adhesive printed product with the real-time production quality inspection threshold, when the real-time production quality inspection value of the self-adhesive printed product is less than the real-time production quality inspection threshold, no adjustment is made, and when the real-time production quality inspection value of the self-adhesive printed product is greater than or equal to the real-time production quality inspection threshold, the production inspection configuration is adjusted.

[0073] In this embodiment, when the real-time production quality inspection value of the self-adhesive printed product is less than the real-time production quality inspection threshold, it means that the printing quality of the self-adhesive printed product is qualified, and no adjustment is made. When the real-time production quality inspection value of the self-adhesive printed product is greater than or equal to the real-time production quality inspection threshold, the quality of the self-adhesive printed product is unqualified. At this time, the production inspection configuration needs to be adjusted. At this time, the printing speed can be adjusted according to the preset printing speed. It should be noted that the preset printing speed is a relatively slow printing speed set when the real-time production quality inspection value of the self-adhesive printed product exceeds the threshold. At this time, it is necessary to mark the unqualified and self-adhesive printed products, and send relevant information to the staff for further inspection, and adjust the printing speed and printing pressure as well as the ink output of the ink supply system to control the ink density, and notify the relevant staff to timely overhaul the relevant equipment to ensure the working stability of the relevant equipment. It should be noted that the relevant equipment refers to the working equipment and detection equipment in the printing process.

[0074] like Figure 2 As shown, it is a diagram of a quality detection system for self-adhesive printed products based on artificial intelligence provided in an embodiment of the present application. The quality detection system for self-adhesive printed products based on artificial intelligence provided in an embodiment of the present application includes: an initial calibration module, which is used for the edge processor to sense the production start signal, and activate each detection device to perform initial calibration, obtain the initial calibration result and perform corresponding calibration processing; a production execution module, which is used for the edge processor to receive the calibration processing cutoff signal, and transmit the executable production start signal to the production control port to produce the self-adhesive printed products; a production quality monitoring module, which is used to obtain the basic production data of the self-adhesive printed products for processing, obtain the basic characteristic value of the self-adhesive printed products, and generate the production quality constraint parameters of the self-adhesive printed products, and monitor the production of the self-adhesive printed products through each detection device to obtain the real-time production quality parameters of the self-adhesive printed products; a production quality inspection module, which is used to perform data fusion processing according to the production quality constraint parameters of the self-adhesive printed products and the real-time production quality parameters of the self-adhesive printed products, obtain the real-time production quality inspection value of the self-adhesive printed products, and execute the corresponding production inspection configuration.

[0075] In summary, the embodiments of the present application ensure the normal operation of each detection device by obtaining the initial data of each detection device, analyzing the initial operating status of each detection device and performing initial calibration, thereby reducing the problem of inaccurate detection results caused by abnormal detection equipment. By obtaining the basic characteristic values ​​of self-adhesive printed products, analyzing the printing complexity of self-adhesive printed products, and obtaining corresponding production quality constraint parameters of self-adhesive printed products according to different printing complexities, the corresponding error range is determined according to the different printing complexities of self-adhesive printed products, thereby reducing the problem of inaccurate detection of self-adhesive printed products caused by the same error standard.

[0076] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0077] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0078] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0079] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0080] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0081] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A quality inspection method for self-adhesive printed products based on artificial intelligence, characterized in that: The following steps are involved: The edge processor senses the production start signal and activates each detection device for initial calibration, obtains the initial calibration result and performs corresponding calibration processing; The edge processor receives the calibration processing cut-off signal and transmits an executable production start signal to the production control port to produce the self-adhesive printed matter; The basic production data of the self-adhesive printed products is obtained and processed to obtain the basic characteristic values ​​of the self-adhesive printed products, and the production quality constraint parameters of the self-adhesive printed products are generated. The production of the self-adhesive printed products is monitored through various detection equipment to obtain the real-time production quality parameters of the self-adhesive printed products; Data fusion processing is performed according to the production quality constraint parameters of the self-adhesive printed products and the real-time production quality parameters of the self-adhesive printed products to obtain the real-time production quality inspection value of the self-adhesive printed products and execute the corresponding production inspection configuration.

2. The quality inspection method for self-adhesive printed matter based on artificial intelligence as claimed in claim 1, characterized in that: The specific process of activating each detection device for initial calibration is as follows: Activate each detection device for initial calibration, obtain initial data of each detection device, and analyze to obtain initial calibration values ​​of each detection device, wherein the initial calibration values ​​are used to detect the initial operating state of each detection device; The initial data of each detection device includes: operating frequency, response time, transient response voltage and transient response current.

3. The quality inspection method for self-adhesive printed matter based on artificial intelligence as claimed in claim 1, characterized in that: The specific process of obtaining the initial calibration result and performing the corresponding calibration process is as follows: Obtain the preset initial verification threshold of each detection device, compare the initial verification value of each detection device with the corresponding initial verification threshold; when the initial verification value of a detection device is less than the initial verification threshold of the detection device, define the initial calibration result of the detection device as normal, and do not perform calibration processing; when the initial verification value of a detection device is greater than or equal to the initial verification threshold of the detection device, define the initial calibration result of the detection device as abnormal, perform calibration processing on the detection device, and simultaneously generate calibration warning prompt information to the management port for display processing.

4. The quality inspection method for self-adhesive printed matter based on artificial intelligence as claimed in claim 1, characterized in that: The basic production data of the self-adhesive printed product is obtained and processed to obtain the basic characteristic value of the self-adhesive printed product. The specific process is as follows: The basic production data of the self-adhesive printed product includes substrate basic data and printing basic data; The basic data of the substrate include: substrate thickness, substrate surface glossiness and substrate ink absorption per unit area; The printing basic data includes: the color type of the printing design, the color saturation of the printing design, the dot ratio of the printing design and the area of ​​the printing design pattern; The basic characteristic values ​​of the self-adhesive printed matter are obtained by processing the basic data of the substrate and the basic data of printing, and the basic characteristic values ​​are used to characterize the printing complexity of the self-adhesive printed matter.

5. The quality inspection method for self-adhesive printed matter based on artificial intelligence as claimed in claim 1, characterized in that: The specific process of generating the production quality constraint parameters of the self-adhesive printed matter is as follows: Matching the basic characteristic values ​​of the self-adhesive printed product with the production quality constraint parameters corresponding to each basic characteristic value interval stored in the production database of the self-adhesive printed product, and counting the production quality constraint parameters corresponding to the intervals where the basic characteristic values ​​of the self-adhesive printed product are located, and recording them as the production quality constraint parameters of the self-adhesive printed product; The production quality constraint parameters of the self-adhesive printed product include: an allowable error of average color difference value, an allowable error of printing speed, an allowable error of printing pressure, an allowable error of average thickness of printing layer, and an allowable error of paper warpage.

6. The quality inspection method for self-adhesive printed matter based on artificial intelligence as claimed in claim 5, characterized in that: The specific process of obtaining the real-time production quality parameters of the self-adhesive printed matter is as follows: Conduct production inspection on self-adhesive printed products to obtain real-time quality parameters of self-adhesive printed products; The real-time quality parameters include: average color difference value of color area of ​​printed matter, printing speed, printing pressure, average thickness of printing layer and average warpage of paper.

7. The quality inspection method for self-adhesive printed matter based on artificial intelligence as claimed in claim 6, characterized in that: The data fusion processing is performed according to the production quality constraint parameters of the self-adhesive printed product and the real-time production quality parameters of the self-adhesive printed product. The specific process is as follows: Obtaining the operation influencing parameters of each detection device of the self-adhesive printed matter, and processing to obtain the real-time inspection value of the operation parameters of each detection device; Based on the operation parameter verification value of each detection device, the production quality constraint parameters of the self-adhesive printing product and the real-time production quality parameters of the self-adhesive printing product are subjected to data fusion processing to obtain the real-time production quality inspection value of the self-adhesive printing product; The operation influencing parameters of each detection device include: real-time operating frequency, real-time voltage and real-time current.

8. The quality inspection method for self-adhesive printed matter based on artificial intelligence as claimed in claim 6, characterized in that: The real-time production quality inspection value of the self-adhesive printed matter is specifically obtained by: Wherein, α represents the real-time production quality inspection value of the self-adhesive printed matter, E represents the average color difference value, ΔE represents the permissible error of the average color difference value, S represents the printing speed, S1 represents the standard value of the printing speed, ΔS represents the permissible error of the printing speed, A represents the printing pressure, A1 represents the printing pressure, ΔA represents the permissible error of the printing pressure, C represents the average thickness of the printing layer, C1 represents the reference value of the average thickness of the printing layer, ΔC represents the permissible error of the average thickness of the printing layer, L represents the paper warpage, ΔL represents the permissible error of the paper warpage, γi represents the initial calibration value of the i-th detection device, γsi represents the real-time inspection value of the operating parameters of the i-th detection device, i=1,2,...I, i is the number of the detection device, I is the total number of detection devices, and e is a natural constant.

9. The quality inspection method for self-adhesive printed matter based on artificial intelligence as claimed in claim 8, characterized in that: The specific process of executing the corresponding production test configuration is as follows: Get the preset real-time production quality inspection threshold, compare the real-time production quality inspection value of the self-adhesive printed product with the real-time production quality inspection threshold, when the real-time production quality inspection value of the self-adhesive printed product is less than the real-time production quality inspection threshold, no adjustment is made, when the real-time production quality inspection value of the self-adhesive printed product is greater than or equal to the real-time production quality inspection threshold, adjust the production inspection configuration.

10. A system using the quality inspection method for self-adhesive printed matter based on artificial intelligence as claimed in any one of claims 1 to 9, characterized in that: include: The initial calibration module is used for the edge processor to sense the production start signal, activate each detection device for initial calibration, obtain the initial calibration result and perform corresponding calibration processing; A production execution module is used for the edge processor to receive the calibration processing cut-off signal and transmit an executable production start signal to the production control port to produce the self-adhesive printed matter; The production quality monitoring module is used to obtain the basic production data of the self-adhesive printed products for processing, obtain the basic characteristic values ​​of the self-adhesive printed products, generate the production quality constraint parameters of the self-adhesive printed products, and monitor the production of the self-adhesive printed products through various detection equipment to obtain the real-time production quality parameters of the self-adhesive printed products; The production quality inspection module is used to perform data fusion processing according to the production quality constraint parameters of the self-adhesive printed products and the real-time production quality parameters of the self-adhesive printed products, obtain the real-time production quality inspection value of the self-adhesive printed products, and execute the corresponding production inspection configuration.

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