Intelligent control method and system for glass fiber self-adhesive tape production based on Internet of Things

Abstract

The present invention relates to the field of intelligent control of self-adhesive tape production, and to an intelligent control method and system for glass fiber self-adhesive tape production based on the Internet of Things. In the tape production process of the present invention, firstly, images of the tape raw material and the self-adhesive roller are collected, then the offset of the tape raw material is analyzed, and the tension value of the self-adhesive roller is collected to evaluate its tension compliance. According to this information, the self-adhesive roller is adjusted to ensure the accurate position of the tape, and then the adjusted tape is glued in sections. Then, by analyzing the gray value of the image of the glue-coated area, the proportion of bubbles and glue leaks, that is, the glue coating defect rate index, is evaluated. At the same time, the horizontal bar coordinates of the glue-coated area are analyzed to obtain the glue inclination index. Finally, the two indexes are combined to calculate the tape quality evaluation coefficient to monitor the state of the glue coating equipment. The whole process is intended to ensure the accuracy and quality of tape production and to promptly discover and solve potential problems.

Description

Technical Field

[0001] The invention belongs to the field of intelligent control of tape production, and relates to an intelligent control method and system for glass fiber self-adhesive tape production based on the Internet of Things. Background Art

[0002] With the development of big data technology, more and more companies are beginning to use data analysis to optimize the tape production process. In the production of glass fiber self-adhesive tape, by collecting and analyzing tape production data, it is possible to identify bottlenecks and problems in the tape production process, thereby optimizing the tape production process and equipment configuration, and improving production efficiency and product quality.

[0003] The existing intelligent control method for the production of glass fiber self-adhesive tape has some shortcomings: First, due to the lack of the ability to monitor and analyze the rollers, tape raw material offset, and roller tension in real time, the existing technology is difficult to promptly discover and solve potential tape production problems, which can easily lead to tape production failures and production line shutdowns, affecting the stability and reliability of the tape production process.

[0004] Secondly, existing methods often only consider the impact of a single factor on the quality of the tape, such as only considering the stickiness of the tape or the distribution of glue on the tape. Since the quality of the tape cannot be fully evaluated, the performance of the tape may be unstable during actual use, and problems such as insufficient stickiness, easy falling off or easy breakage may occur. Summary of the invention

[0005] In view of this, in order to solve the problems raised in the above background technology, an intelligent control method and system for glass fiber self-adhesive tape production based on the Internet of Things is proposed.

[0006] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides an intelligent control method for glass fiber self-adhesive tape production based on the Internet of Things, including: S1, tape image acquisition: collecting images of tape raw materials and self-adhesive rollers in the tape production process.

[0007] S2. Analysis of tape offset: Analyze the tape raw material offset based on the tape raw material image.

[0008] S3. Tension compliance analysis: collect the tension values ​​of each monitoring point on the self-adhesive roller within a set period, and analyze the tension compliance of the self-adhesive roller.

[0009] S4. Adjustment of tape offset: adjust the self-adhesive roller according to the tape material offset and the tension compliance of the self-adhesive roller.

[0010] S5. Gluing the tape in sections: Divide the adjusted tape raw material into sections to obtain tape in each area, and then glue the tape in each area.

[0011] S6. Analysis of glue coating defect rate index: Collect the glue coating area image of each section of the tape, obtain the gray value of each pixel in the glue coating area image of each section of the tape according to the glue coating area image of each section of the tape, and analyze the bubble ratio index in the glue coating area of ​​each section of the tape and glue leakage ratio index , where d represents the number corresponding to different tape areas, , and then analyze the glue coating defect rate index .

[0012] S7. Glue tilt index analysis: According to the glue coating area image of each section of the tape, the coordinates of each horizontal bar and each point of the glue coating area of ​​each section of the tape are obtained, and then the glue tilt index is analyzed. .

[0013] S8. Analysis of tape quality assessment coefficient: Analyze the tape quality assessment coefficient based on the glue coating defect rate index and the glue tilt index.

[0014] S9. Gluing equipment status monitoring: Determine whether the gluing equipment status is abnormal based on the tape quality assessment coefficient.

[0015] Preferably, the analysis of the offset of the tape raw material includes: recording the self-adhesive roller that releases the tape raw material as roller A, recording the roller that collects the tape raw material after being coated as roller B, identifying the contours of roller A and roller B in the image of the self-adhesive roller by an edge detection algorithm, and then obtaining the center coordinates of roller A and roller B from the contours of roller A and roller B by a circular fitting algorithm, obtaining the center lines of roller A and roller B according to the center coordinates of roller A and roller B, and detecting the tape raw material from the image of the tape raw material by a Hough transform algorithm. The center line of the tape raw material is obtained by fitting algorithm, and the angle a between the center line of the tape raw material and the center line of roller A and the angle between the center line of the tape raw material and the center line of roller B correspond to the inner angle b on the same side of the angle a between the center line of the tape raw material and the center line of roller A, and the angle a between the center line of the tape raw material and the center line of roller A and the inner angle b on the same side of the angle a between the center line of the tape raw material and the center line of roller A are compared, so as to obtain the angle difference. , analyze the tape material offset ,in Indicates the set allowable angle deviation value.

[0016] Preferably, the analysis of the tension compliance of the self-adhesive roller includes: arranging tension sensors at preset monitoring points on roller A and roller B, extracting the tension values ​​of each monitoring point on roller A and roller B within a set period, comparing the tension values ​​of each monitoring point on roller A and roller B with the tension values ​​of its adjacent monitoring points within the set period, and obtaining the tension differences between each monitoring point on roller A and roller B and its adjacent monitoring points within the set period, which are recorded as and , where i represents the number corresponding to different monitoring points, , analyze the tension compliance of the self-adhesive roller ,in Indicates the tension fluctuation index of roller A ,in Indicates the tension fluctuation index of roller B , is the allowable tension error value between the monitoring point on the self-adhesive roller and its adjacent monitoring point, where Indicates the total number of monitoring points on the self-adhesive roller within the set period, where Indicates the similarity index of the tension values ​​of roller A and roller B, ,in represents the tension value of the i-th monitoring point on roller A within the set period, where It indicates the tension value of the i-th monitoring point on roller B within the set period. Represents the weight factor of the set tension fluctuation index, represents the weight factor of the set tension similarity index, and .

[0017] Preferably, the adjusting the self-adhesive roller comprises: comparing the tape material offset with a preset qualified offset, and if the tape material offset is greater than the preset qualified offset, adjusting the position of the self-adhesive roller according to the tape material offset.

[0018] The tension compliance of the self-adhesive roller is compared with the preset tension compliance threshold. If the tension compliance of the self-adhesive roller is less than or equal to the preset tension compliance threshold, the tension values ​​of each monitoring point on roller A and roller B are adjusted to the average tension value of the monitoring points on the self-adhesive roller.

[0019] Preferably, the analysis of the bubble ratio index in the glue-coated area of ​​each section of the tape includes: collecting the glue-coated area image of each section of the tape through a camera, and performing color threshold segmentation processing on it to obtain the grayscale value of each pixel in the glue-coated area image of each section of the tape, and comparing the grayscale value of each pixel with the preset bubble color threshold allowable range. If the grayscale value of a pixel falls within the preset bubble color threshold allowable range, the pixel is marked as a bubble pixel; if the grayscale value of a pixel does not fall within the preset bubble color threshold allowable range, the pixel is marked as a non-bubble pixel, and the number of bubble pixels in the glue-coated area of ​​each section of the tape is screened and counted. , and then obtain the total number of pixels in the glued area of ​​each section of the tape , analyze the bubble ratio index in the glue coating area of ​​each section of the tape .

[0020] Preferably, the specific formula for analyzing the glue coating defect rate index is: ,in It represents the weight factor of the bubble ratio index in the adhesive coating area of ​​the set tape. represents the weight factor of the ratio of missed glue in the glue coating area of ​​the set tape, and .

[0021] Preferably, the analysis of the glue tilt index includes: extracting the horizontal bars of the glue-coated area of ​​each section of the tape by an edge detection algorithm, and then obtaining the coordinates of each point of each horizontal bar of the glue-coated area of ​​each section of the tape by an image processing software. , where v represents the numbers corresponding to different points on the horizontal bar, , where u represents the number of the different horizontal bars corresponding to the glue-coated area of ​​the tape, , use the least squares method to fit the horizontal bars to obtain the fitting straight line equation of each horizontal bar in the glued area of ​​each section of the tape, and analyze the glue tilt index ,in It represents the slope of the equation of the fitted straight line of the u-th horizontal bar in the glued area of ​​the d-th section of the tape. ,in Represents the average slope of the horizontal bar of the adhesive area of ​​the tape in section d, , where D represents the total number of tape areas, U represents the total number of tape bars, and V represents the total number of points on the tape bars.

[0022] Preferably, the specific formula for analyzing the tape quality assessment coefficient is: ,in represents the tape quality assessment coefficient, Represents the weight factor of the set glue coating defect rate index, Indicates the weight factor of the set glue tilt index, .

[0023] Preferably, the determination of whether the state of the gluing equipment is abnormal includes: comparing the tape quality assessment coefficient with a preset tape quality qualification threshold; if the tape quality assessment coefficient is less than the preset tape quality qualification threshold, then the gluing state of the gluing equipment is abnormal, and then an early warning is issued to notify relevant personnel to conduct inspection.

[0024] The second aspect of the present invention provides an intelligent control system for glass fiber self-adhesive tape production based on the Internet of Things, including: a tape image acquisition module: used to collect images of tape raw materials and self-adhesive rollers during the tape production process.

[0025] Tape offset analysis module: used to analyze the tape material offset based on the tape material image.

[0026] Tension compliance analysis module: used to collect the tension value of each monitoring point on the self-adhesive roller within a set period and analyze the tension compliance of the self-adhesive roller.

[0027] Adhesive tape offset adjustment module: used to adjust the self-adhesive roller according to the offset of the adhesive tape material and the tension compliance of the self-adhesive roller.

[0028] Adhesive tape segmentation gluing module: used to segment the adjusted adhesive tape raw material to obtain adhesive tape for each area, and then gluing the adhesive tape for each area.

[0029] Gluing defect rate index analysis module: used to collect the glue area image of each section of the tape, obtain the gray value of each pixel in the glue area image of each section of the tape according to the glue area image of each section of the tape, and analyze the bubble ratio index in the glue area of ​​each section of the tape and glue leakage ratio index , where d represents the number corresponding to different tape areas, , and then analyze the glue coating defect rate index .

[0030] Glue tilt index analysis module: used to obtain the coordinates of each horizontal bar and each point in the glue coating area of ​​each section of the tape according to the glue coating area image of each section of the tape, and then analyze the glue tilt index .

[0031] Adhesive tape quality assessment coefficient analysis module: used to analyze the adhesive tape quality assessment coefficient according to the glue coating defect rate index and the glue tilt degree index.

[0032] Gluing equipment status monitoring module: used to determine whether the glue coating equipment status is abnormal based on the tape quality assessment coefficient.

[0033] Compared with the prior art, the present invention has the following beneficial effects: (1) By acquiring the angle difference between the tape raw material and the roller in real time, the present invention can timely detect the deviation of the tape raw material and issue an early warning when the angle exceeds the set allowable angle deviation value, so that timely measures can be taken to make adjustments, thereby avoiding quality problems in the tape production process, reducing dependence on manual labor, reducing the error rate, and improving the stability and reliability of the production line.

[0034] (2) By comparing the tension difference between each monitoring point and its adjacent monitoring point within a set period, the present invention can timely discover abnormal tension points, which helps to quickly locate problems, reduce the risk of tape production interruption, and avoid tape quality problems caused by abnormal tension. By calculating the tension fluctuation index of roller A and roller B and the tension value similarity index between rollers, the tension compliance of the rollers can be comprehensively evaluated. This comprehensive evaluation method not only takes into account the tension stability of the roller itself, but also takes into account the tension consistency between rollers, thereby more comprehensively reflecting the overall condition of the roller tension.

[0035] (3) The present invention uses a camera to capture images of the glue-coated area and combines this with color threshold segmentation technology to accurately identify features such as bubbles and glue leaks. This image-based processing method is more accurate than traditional manual detection and can effectively reduce misjudgments and missed detections. Accurate quality detection helps ensure the high quality of tape products and improve customer satisfaction, which is of great significance for improving corporate image and enhancing product competitiveness.

[0036] (4) By recording and analyzing the fitted straight line equation and glue inclination index of the horizontal bar of the glue coating area of ​​each section of the tape, the enterprise can establish a complete quality database, which is helpful to trace and analyze the causes of quality problems and provide data support for the continuous improvement of product quality. This method is in line with the current development trend of industrial automation and intelligence, and is helpful to improve the technical level and competitiveness of the enterprise. By continuously optimizing the algorithm and introducing new technical means, the accuracy and efficiency of quality inspection can be further improved, thereby promoting the sustainable development of the enterprise.

[0037] (5) The present invention can more comprehensively evaluate the quality of the adhesive tape by comprehensively considering the glue coating defect rate index and the glue tilt index. These two indicators reflect the quality of the adhesive tape from the two aspects of glue coating integrity and coating uniformity, thereby ensuring comprehensive control of the quality of the adhesive tape. The adhesive tape quality evaluation coefficient can intuitively reflect the quality level of the adhesive tape. Once the evaluation coefficient exceeds the normal range, quality problems can be quickly discovered and corresponding measures can be taken to correct them, which helps to prevent the production of unqualified products in a timely manner and reduce quality losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0039] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0040] Figure 2 It is the module connection diagram of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not 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.

[0042] See also Figure 1 As shown, the present invention provides an intelligent control method for glass fiber self-adhesive tape production based on the Internet of Things, including: S1, tape image acquisition: collecting images of tape raw materials and self-adhesive rollers in the tape production process.

[0043] As a preferred embodiment, the collecting of images of the tape raw material and the self-adhesive roller in the tape production process includes: collecting images of the tape raw material and the self-adhesive roller in the tape production process by means of a camera.

[0044] The present invention collects images of tape raw materials and self-adhesive rollers in the tape production process through a camera, thereby realizing automation, real-time monitoring and precise control of the tape production process, improving the production efficiency and product quality of the tape, and having significant benefits and advantages.

[0045] S2. Analysis of tape offset: Analyze the tape raw material offset based on the tape raw material image.

[0046] Furthermore, the analysis of the offset of the tape raw material includes: recording the self-adhesive roller that releases the tape raw material as roller A, recording the roller that collects the tape raw material after being coated as roller B, identifying the contours of roller A and roller B in the image of the self-adhesive roller by an edge detection algorithm, and then obtaining the center coordinates of roller A and roller B from the contours of roller A and roller B by a circular fitting algorithm, obtaining the center lines of roller A and roller B according to the center coordinates of roller A and roller B, and detecting the tape raw material from the image of the tape raw material by a Hough transform algorithm. The center line of the tape raw material is obtained by fitting algorithm, and the angle a between the center line of the tape raw material and the center line of roller A and the angle between the center line of the tape raw material and the center line of roller B correspond to the inner angle b on the same side of the angle a between the center line of the tape raw material and the center line of roller A, and the angle a between the center line of the tape raw material and the center line of roller A and the inner angle b on the same side of the angle a between the center line of the tape raw material and the center line of roller A are compared, so as to obtain the angle difference. , analyze the tape material offset ,in Indicates the set allowable angle deviation value.

[0047] The present invention can timely discover the deviation of the tape raw material by acquiring the angle difference between the tape raw material and the roller in real time, and issue a warning when the set allowable angle deviation value is exceeded, so as to take timely measures to make adjustments, avoid quality problems in the tape production process, reduce dependence on manual labor, reduce error rate, and improve the stability and reliability of the production line.

[0048] S3. Tension compliance analysis: collect the tension values ​​of each monitoring point on the self-adhesive roller within a set period, and analyze the tension compliance of the self-adhesive roller.

[0049] Further, the analysis of the tension compliance of the self-adhesive roller includes: arranging tension sensors at preset monitoring points on roller A and roller B, extracting the tension values ​​of each monitoring point on roller A and roller B within a set period, comparing the tension values ​​of each monitoring point on roller A and roller B with the tension values ​​of its adjacent monitoring points within the set period, and obtaining the tension differences between each monitoring point on roller A and roller B and its adjacent monitoring points within the set period, which are recorded as and , where i represents the number corresponding to different monitoring points, , analyze the tension compliance of the self-adhesive roller ,in Indicates the tension fluctuation index of roller A ,in Indicates the tension fluctuation index of roller B , is the allowable tension error value between the monitoring point on the self-adhesive roller and its adjacent monitoring point, where Indicates the total number of monitoring points on the self-adhesive roller within the set period, where Indicates the similarity index of the tension values ​​of roller A and roller B, ,in represents the tension value of the i-th monitoring point on roller A within the set period, where It indicates the tension value of the i-th monitoring point on roller B within the set period. Represents the weight factor of the set tension fluctuation index, represents the weight factor of the set tension similarity index, and .

[0050] It should be noted that, in one embodiment, It can be set to 0.5. It can be set to 0.5. During the tape production process, the stability of the tension is directly related to the quality of the product. If the tension fluctuates too much, it may cause the tape to stretch, break, or unevenly apply glue. By paying attention to the tension similarity between the rollers, the performance of the entire system can be optimized. When the tension between the rollers is similar, the working state of the entire system is more stable, which can reduce failures and downtime and improve production efficiency. Therefore, the weights of the tension fluctuation index of the self-adhesive roller and the tension similarity index of the two self-adhesive rollers are equal.

[0051] By comparing the tension difference between each monitoring point and its adjacent monitoring point within a set period, the present invention can timely discover abnormal tension points, which is helpful to quickly locate the problem, reduce the risk of tape production interruption, and avoid tape quality problems caused by abnormal tension. By calculating the tension fluctuation index of roller A and roller B and the tension value similarity index between rollers, the tension compliance of the rollers can be comprehensively evaluated. This comprehensive evaluation method not only takes into account the tension stability of the roller itself, but also takes into account the tension consistency between rollers, thereby more comprehensively reflecting the overall condition of the roller tension.

[0052] S4. Adjustment of tape offset: adjust the self-adhesive roller according to the tape material offset and the tension compliance of the self-adhesive roller.

[0053] The adjusting of the self-adhesive roller includes: comparing the tape material offset with a preset qualified offset, and if the tape material offset is greater than the preset qualified offset, adjusting the position of the self-adhesive roller according to the tape material offset.

[0054] As a preferred embodiment, the position of the self-adhesive roller is adjusted, including: if the offset of the tape raw material is greater than a preset qualified offset, the control system determines the offset direction of the tape raw material according to the offset of the tape raw material. If the offset of the tape raw material is a positive number, roller A is controlled to move to the right and roller B to move to the left; if the offset of the tape raw material is a negative number, roller A is controlled to move to the left and roller B to move to the right. During the adjustment process, the control system will continuously monitor the offset of the tape raw material. When the offset of the tape raw material is less than the preset qualified offset, the adjustment stops automatically.

[0055] The tension compliance of the self-adhesive roller is compared with the preset tension compliance threshold. If the tension compliance of the self-adhesive roller is less than or equal to the preset tension compliance threshold, the tension values ​​of each monitoring point on roller A and roller B are adjusted to the average tension value of the monitoring points on the self-adhesive roller.

[0056] The present invention compares the offset of the tape raw material with the qualified offset and timely adjusts the position of the self-adhesive roller, thereby avoiding tape quality problems caused by the offset, thereby improving product quality stability. Timely adjustment of the tension of the self-adhesive roller can ensure the continuous and stable operation of the production line, avoid downtime caused by equipment failure or product quality problems, thereby improving tape production efficiency. This automated adjustment mechanism can reduce dependence on operators, reduce the frequency and difficulty of manual intervention, and improve the degree of automation of the production line.

[0057] S5. Gluing the tape in sections: Divide the adjusted tape raw material into sections to obtain tape in each area, and then glue the tape in each area.

[0058] As a preferred embodiment, the step of segmenting the adjusted tape raw material to obtain the respective regional tape segments includes: segmenting the adjusted tape into equidistant segments to obtain the respective regional tape segments.

[0059] The present invention can adjust the glue coating amount of each section area according to actual needs through segmented glue coating, avoid unnecessary waste, optimize the use efficiency of the adhesive tape, and reduce production costs.

[0060] S6. Analysis of glue coating defect rate index: Collect the glue coating area image of each section of the tape, obtain the gray value of each pixel in the glue coating area image of each section of the tape according to the glue coating area image of each section of the tape, and analyze the bubble ratio index in the glue coating area of ​​each section of the tape and glue leakage ratio index , where d represents the number corresponding to different tape areas, , and then analyze the glue coating defect rate index .

[0061] Furthermore, the analysis of the bubble ratio index in the glued area of ​​each section of the tape includes: collecting the glued area image of each section of the tape through a camera, and performing color threshold segmentation processing on it to obtain the grayscale value of each pixel in the glued area image of each section of the tape, and comparing the grayscale value of each pixel with the preset bubble color threshold allowable range. If the grayscale value of a pixel falls within the preset bubble color threshold allowable range, the pixel is marked as a bubble pixel; if the grayscale value of a pixel does not fall within the preset bubble color threshold allowable range, the pixel is marked as a non-bubble pixel, and the number of bubble pixels in the glued area of ​​each section of the tape is screened and counted. , and then obtain the total number of pixels in the glued area of ​​each section of the tape , analyze the bubble ratio index in the glue coating area of ​​each section of the tape .

[0062] The analysis of the glue missing ratio index in the glue coating area of ​​each section of the tape includes: comparing the gray value of each pixel with the preset allowable range of the glue missing color threshold; if the gray value of a pixel belongs to the preset allowable range of the glue missing color threshold, the pixel is marked as a glue missing pixel; if the gray value of a pixel does not belong to the preset allowable range of the glue missing color threshold, the pixel is marked as a non-glue missing pixel, and the number of glue missing pixels in the glue coating area of ​​each section of the tape is screened and counted. , analyze the proportion of glue leakage in the glue coating area of ​​each section of the tape .

[0063] Furthermore, the specific formula for analyzing the glue coating defect rate index is: ,in It represents the weight factor of the bubble ratio index in the adhesive coating area of ​​the set tape. represents the weight factor of the ratio of missed glue in the glue coating area of ​​the set tape, and .

[0064] It should be noted that, in one embodiment, It can be set to 0.5. It can be set to 0.5. Bubbles and glue leaks are both possible defects in the gluing process, and their impact on product quality cannot be ignored. Setting the weight factors of the two to be the same can ensure that when evaluating the gluing quality, the impact of bubbles and glue leaks are taken into account at the same time, thereby obtaining a more comprehensive and accurate gluing defect rate index.

[0065] The present invention collects images of the glue-coated area through a camera and combines them with color threshold segmentation technology to accurately identify features such as bubbles and missing glue. This image-based processing method is more accurate than traditional manual detection and can effectively reduce misjudgments and missed detections. Accurate quality detection helps to ensure the high quality of tape products and improve customer satisfaction, which is of great significance for improving corporate image and enhancing product competitiveness.

[0066] S7. Glue tilt index analysis: According to the glue coating area image of each section of the tape, the coordinates of each horizontal bar and each point of the glue coating area of ​​each section of the tape are obtained, and then the glue tilt index is analyzed. .

[0067] Furthermore, the analysis of the glue tilt index includes: extracting the horizontal bars of the glue-coated area of ​​each section of the tape by an edge detection algorithm, and then obtaining the coordinates of each point of each horizontal bar of the glue-coated area of ​​each section of the tape by an image processing software. , where v represents the numbers corresponding to different points on the horizontal bar, , where u represents the number of the different horizontal bars corresponding to the glue-coated area of ​​the tape, , use the least squares method to fit the horizontal bars to obtain the fitting straight line equation of each horizontal bar in the glued area of ​​each section of the tape, and analyze the glue tilt index ,in It represents the slope of the equation of the fitted straight line of the u-th horizontal bar in the glued area of ​​the d-th section of the tape. ,in Represents the average slope of the horizontal bar of the adhesive area of ​​the tape in section d, , where D represents the total number of tape areas, U represents the total number of tape bars, and V represents the total number of points on the tape bars.

[0068] By recording and analyzing the fitted straight line equations and glue inclination index of the horizontal bars in the glue coating areas of each section of the tape, the present invention enables the enterprise to establish a complete quality database, which is helpful to trace and analyze the causes of quality problems and provide data support for the continuous improvement of product quality. This method is in line with the current development trend of industrial automation and intelligence, and is helpful to improve the technical level and competitiveness of the enterprise. By continuously optimizing the algorithm and introducing new technical means, the accuracy and efficiency of quality inspection can be further improved, thereby promoting the sustainable development of the enterprise.

[0069] S8. Analysis of tape quality assessment coefficient: Analyze the tape quality assessment coefficient based on the glue coating defect rate index and the glue tilt index.

[0070] Furthermore, the specific formula for analyzing the tape quality assessment coefficient is: ,in represents the tape quality assessment coefficient, Represents the weight factor of the set glue coating defect rate index, Indicates the weight factor of the set glue tilt index, .

[0071] It should be noted that, as an embodiment, It can be set to 0.6. It can be set to 0.4. In the production process of tapes, the glue defect rate is a key quality control indicator. By reducing the glue defect rate, the product qualification rate and customer satisfaction can be significantly improved. Although the glue tilt index is also an important indicator in the quality evaluation of tapes, its impact on product quality is relatively minor compared to the glue defect rate. Glue tilt mainly affects the appearance and glue uniformity of the tape, and is unlikely to directly lead to functional failure of the tape. Therefore, the weight factor of the glue defect rate index is greater than the weight factor of the glue tilt index.

[0072] S9. Gluing equipment status monitoring: Determine whether the gluing equipment status is abnormal based on the tape quality assessment coefficient.

[0073] Furthermore, the determination of whether the state of the gluing equipment is abnormal includes: comparing the tape quality assessment coefficient with a preset tape quality qualification threshold; if the tape quality assessment coefficient is less than the preset tape quality qualification threshold, then the gluing state of the gluing equipment is abnormal, and then an early warning is issued to notify relevant personnel to conduct inspection.

[0074] See also Figure 2 As shown, the second aspect of the present invention provides an intelligent control system for the production of glass fiber self-adhesive tape based on the Internet of Things, including: a tape image acquisition module, a tape offset analysis module, a tension compliance analysis module, a tape offset adjustment module, a tape segmented gluing module, a gluing defect rate index analysis module, a glue inclination index analysis module, a tape quality assessment coefficient analysis module, and a gluing equipment status monitoring module.

[0075] The tape offset analysis module is respectively connected to the tape image acquisition module and the tape offset adjustment module; the tape offset adjustment module is respectively connected to the tension compliance analysis module, the tape offset analysis module, and the tape segmented gluing module; the tape quality assessment coefficient analysis module is respectively connected to the gluing defect rate index analysis module, the glue inclination index analysis module, and the gluing equipment status monitoring module.

[0076] Tape image acquisition module: used to collect images of tape raw materials and self-adhesive rollers during the tape production process.

[0077] Tape offset analysis module: used to analyze the tape material offset based on the tape material image.

[0078] Tension compliance analysis module: used to collect the tension value of each monitoring point on the self-adhesive roller within a set period and analyze the tension compliance of the self-adhesive roller.

[0079] Adhesive tape offset adjustment module: used to adjust the self-adhesive roller according to the offset of the adhesive tape material and the tension compliance of the self-adhesive roller.

[0080] Adhesive tape segmentation gluing module: used to segment the adjusted adhesive tape raw material to obtain adhesive tape for each area, and then gluing the adhesive tape for each area.

[0081] Gluing defect rate index analysis module: used to collect the glue area image of each section of the tape, obtain the gray value of each pixel in the glue area image of each section of the tape according to the glue area image of each section of the tape, and analyze the bubble ratio index in the glue area of ​​each section of the tape and glue leakage ratio index , where d represents the number corresponding to different tape areas, , and then analyze the glue coating defect rate index .

[0082] Glue tilt index analysis module: used to obtain the coordinates of each horizontal bar and each point in the glue coating area of ​​each section of the tape according to the glue coating area image of each section of the tape, and then analyze the glue tilt index .

[0083] Adhesive tape quality assessment coefficient analysis module: used to analyze the adhesive tape quality assessment coefficient according to the glue coating defect rate index and the glue tilt degree index.

[0084] Gluing equipment status monitoring module: used to determine whether the glue coating equipment status is abnormal based on the tape quality assessment coefficient.

[0085] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. An intelligent control method for glass fiber self-adhesive tape production based on the Internet of Things, characterized in that: The method includes: S1. Tape image acquisition: collect images of tape raw materials and self-adhesive rollers during the tape production process; S2. Analysis of tape offset: analyzing the tape raw material offset according to the tape raw material image; S3. Tension compliance analysis: collect the tension values ​​of each monitoring point on the self-adhesive roller within a set period, and analyze the tension compliance of the self-adhesive roller; The analysis of the tension compliance of the self-adhesive roller includes: The tension sensors are arranged at the preset monitoring points on roller A and roller B, and the tension values ​​of the monitoring points on roller A and roller B within the set period are extracted. The tension values ​​of the monitoring points on roller A and roller B within the set period are compared with the tension values ​​of the adjacent monitoring points, and the tension differences between the monitoring points on roller A and roller B within the set period and the adjacent monitoring points are obtained, which are recorded as and , where i represents the number corresponding to different monitoring points, , analyze the tension compliance of the self-adhesive roller ,in Indicates the tension fluctuation index of roller A ,in Indicates the tension fluctuation index of roller B , is the allowable tension error value between the monitoring point on the self-adhesive roller and its adjacent monitoring point, where Indicates the total number of monitoring points on the self-adhesive roller within the set period, where Indicates the similarity index of the tension values ​​of roller A and roller B, ,in represents the tension value of the i-th monitoring point on roller A within the set period, where It indicates the tension value of the i-th monitoring point on roller B within the set period. Represents the weight factor of the set tension fluctuation index, represents the weight factor of the set tension similarity index, and ; S4. Tape offset adjustment: adjust the self-adhesive roller according to the tape material offset and the tension compliance of the self-adhesive roller; S5, applying glue to the tape in sections: the adjusted tape raw material is divided into sections to obtain tapes in each section area, and then the tapes in each section area are applied with glue; S6. Analysis of glue coating defect rate index: Collect the glue coating area image of each section of the tape, obtain the gray value of each pixel in the glue coating area image of each section of the tape according to the glue coating area image of each section of the tape, and analyze the bubble ratio index in the glue coating area of ​​each section of the tape and glue leakage ratio index , where d represents the number corresponding to different tape areas, , and then analyze the glue coating defect rate index ; S7. Glue tilt index analysis: According to the glue coating area image of each section of the tape, the coordinates of each horizontal bar and each point of the glue coating area of ​​each section of the tape are obtained, and then the glue tilt index is analyzed. ; The analysis of the glue tilt index includes: The horizontal bars of the glued area of ​​each section of the tape are extracted by edge detection algorithm, and then the coordinates of each point of each horizontal bar in the glued area of ​​each section of the tape are obtained by image processing software. , where v represents the numbers corresponding to different points on the horizontal bar, , where u represents the number of the different horizontal bars corresponding to the glue-coated area of ​​the tape, , use the least squares method to fit the horizontal bars to obtain the fitting straight line equation of each horizontal bar in the glued area of ​​each section of the tape, and analyze the glue tilt index ,in It represents the slope of the equation of the fitted straight line of the u-th horizontal bar in the glued area of ​​the d-th section of the tape. ,in Represents the average slope of the horizontal bar of the adhesive area of ​​the tape in section d, , where D represents the total number of tape areas, U represents the total number of tape bars, and V represents the total number of points on the tape bars; S8. Analysis of tape quality assessment coefficient: Analyze the tape quality assessment coefficient based on the glue coating defect rate index and the glue tilt index; S9. Gluing equipment status monitoring: Determine whether the gluing equipment status is abnormal based on the tape quality assessment coefficient.

2. The intelligent control method for glass fiber self-adhesive tape production based on the Internet of Things according to claim 1 is characterized in that: The analysis of the tape raw material offset includes: The self-adhesive roller that releases the tape raw material is recorded as roller A, and the roller that collects the tape raw material after coating is recorded as roller B. The contours of roller A and roller B in the image of the self-adhesive roller are identified by the edge detection algorithm, and then the center coordinates of roller A and roller B are obtained from the contours of roller A and roller B by the circular fitting algorithm. The center lines of roller A and roller B are obtained according to the center coordinates of roller A and roller B. The center line of the tape raw material is obtained from the image of the tape raw material by the Hough transform algorithm, and then the fitting algorithm is used to obtain the center line of the tape raw material. The method obtains the angle a between the center line of the tape raw material and the center line of roller A and the angle between the center line of the tape raw material and the center line of roller B, which corresponds to the inner angle b on the same side of the angle a between the center line of the tape raw material and the center line of roller A; the angle a between the center line of the tape raw material and the center line of roller A is compared with the inner angle b on the same side of the angle a between the center line of the tape raw material and the center line of roller A in the angle between the center line of the tape raw material and the center line of roller B, thereby obtaining the angle difference. , analyze the tape material offset ,in Indicates the set allowable angle deviation value.

3. The intelligent control method for glass fiber self-adhesive tape production based on the Internet of Things according to claim 2 is characterized in that: The step of adjusting the self-adhesive roller comprises: The offset of the tape material is compared with the preset qualified offset. If the offset of the tape material is greater than the preset qualified offset, the position of the self-adhesive roller is adjusted according to the offset of the tape material; The tension compliance of the self-adhesive roller is compared with the preset tension compliance threshold. If the tension compliance of the self-adhesive roller is less than or equal to the preset tension compliance threshold, the tension values ​​of each monitoring point on roller A and roller B are adjusted to the average tension value of the monitoring points on the self-adhesive roller.

4. The intelligent control method for glass fiber self-adhesive tape production based on the Internet of Things according to claim 1 is characterized in that: The analysis of the bubble ratio index in the glue coating area of ​​each section of the tape includes: The image of the glued area of ​​each section of the tape is collected by a camera, and color threshold segmentation processing is performed on it to obtain the grayscale value of each pixel in the image of the glued area of ​​each section of the tape, and the grayscale value of each pixel is compared with the preset bubble color threshold allowable range. If the grayscale value of a pixel belongs to the preset bubble color threshold allowable range, the pixel is marked as a bubble pixel; if the grayscale value of a pixel does not belong to the preset bubble color threshold allowable range, the pixel is marked as a non-bubble pixel, and the number of bubble pixels in the glued area of ​​each section of the tape is screened and counted. , and then obtain the total number of pixels in the glued area of ​​each section of the tape , analyze the bubble ratio index in the glue coating area of ​​each section of the tape .

5. The intelligent control method for glass fiber self-adhesive tape production based on the Internet of Things according to claim 1 is characterized in that: The specific formula for analyzing the glue coating defect rate index is: ,in It represents the weight factor of the bubble ratio index in the adhesive coating area of ​​the set tape. represents the weight factor of the ratio of missed glue in the glue coating area of ​​the set tape, and .

6. The intelligent control method for glass fiber self-adhesive tape production based on the Internet of Things according to claim 1 is characterized in that: The specific formula for analyzing the tape quality evaluation coefficient is: ,in represents the tape quality assessment coefficient, Represents the weight factor of the set glue coating defect rate index, Indicates the weight factor of the set glue tilt index, .

7. The intelligent control method for glass fiber self-adhesive tape production based on the Internet of Things according to claim 1 is characterized in that: The step of determining whether the state of the glue coating device is abnormal includes: The tape quality assessment coefficient is compared with the preset tape quality qualification threshold. If the tape quality assessment coefficient is less than the preset tape quality qualification threshold, the gluing status of the gluing equipment is abnormal, and an early warning is issued to notify relevant personnel to conduct inspection.

8. An intelligent control system for glass fiber self-adhesive tape production based on the Internet of Things, used to execute the method according to any one of claims 1 to 7, characterized in that: include: Tape image acquisition module: used to collect images of tape raw materials and self-adhesive rollers during the tape production process; Tape offset analysis module: used to analyze the tape material offset according to the tape material image; Tension compliance analysis module: used to collect the tension value of each monitoring point on the self-adhesive roller within a set period and analyze the tension compliance of the self-adhesive roller; Adhesive tape offset adjustment module: used to adjust the self-adhesive roller according to the offset of the adhesive tape material and the tension compliance of the self-adhesive roller; Adhesive tape segmentation gluing module: used to segment the adjusted adhesive tape raw material to obtain adhesive tape in each area, and then gluing the adhesive tape in each area; Gluing defect rate index analysis module: used to collect the glue area image of each section of the tape, obtain the gray value of each pixel in the glue area image of each section of the tape according to the glue area image of each section of the tape, and analyze the bubble ratio index in the glue area of ​​each section of the tape and glue leakage ratio index , where d represents the number corresponding to different tape areas, , and then analyze the glue coating defect rate index ; Glue tilt index analysis module: used to obtain the coordinates of each horizontal bar and each point in the glue coating area of ​​each section of the tape according to the glue coating area image of each section of the tape, and then analyze the glue tilt index ; Adhesive tape quality assessment coefficient analysis module: used to analyze the adhesive tape quality assessment coefficient according to the glue coating defect rate index and the glue tilt index; Gluing equipment status monitoring module: used to determine whether the glue coating equipment status is abnormal based on the tape quality assessment coefficient.

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