Application of Robot in Printing Quality Inspection

In almost all modern mass production processes, the printed text, symbols, and product labels on the product packaging must be beautifully printed and free of defects and errors. However, the following problems may occur in practice, such as partial characters missing print, partial characters incomplete, and confusion between different characters, such as 5 and 6; 6 and 9 are printed and mixed. The position of the character is wrong, the font of the character is wrong or inconsistent. To solve the above problems, we must choose an excellent image processing system and perform 100% reliable inspection of these words and symbols to ensure 100% pass rate and achieve true “zero defect”. The texts and symbols that are examined and identified can be generated by the following methods: printing, marking, thermal transfer, and laser engraving. This further increases the difficulty of checking and identifying.

The items to be inspected may be single-row discharge on the conveyor belt, or they may be discharged in parallel as shown in FIG. 2 . The robot first stops the conveyor belt and moves the inspection head over the first product. The identification system starts automatically detecting and identifying the first product. The robot then moves the inspection head over the second product, and then the identification system automatically detects the second product, thus identifying the last product in the row. Re-start the conveyor to move the second row of products directly below the inspection system and start automatic inspection and identification of the product.

The text checked in Figure 3 is on a transparent sheet. The robot first stops the conveyor belt and moves the detection head at a constant speed. The recognition system automatically detects and recognizes the printed text and symbols at several specific locations. Then the material is restarted for a certain length, the robot moves in the reverse direction, and the inspection system starts automatic inspection and identification of the product.

System composition

The task here is the inspection of the product of Figure 3. The robot is a German single-axis robot of Bagra. Due to the small load and low moving speed, the model used is the LM-P404 R-AT5. The effective stroke is selected as 1500 mm according to the mission requirements. The drive motor is the stepper motor VRDM3910LWB from Baglara. The robot control system selects the Beagle's dedicated industrial control TLCC. The TLCC controls the TLC611 stepper motor driver via the CAN bus. The image processing system uses the detection system VE 4000 OCV/2 from German Vision Experts GmbH. Figure 3 is a photograph of the system in actual use. The rectangular coordinate robot and detection system are described in more detail below.

Cartesian Robot Introduction

The German Bagra company is one of the world's most famous robot suppliers, producing a wide range of linear motion units/rails, stepper motors, AC servo motors, linear motors and multi-axis CNC systems. Based on this, we can provide linear guides of various specifications, 2D and 3D standard robots, and user-specific robots and production lines in a short time. These robots can be equipped with welding torches, universal grippers or special tools for welding, handling, loading and unloading, packaging, palletizing, demolition, inspection, flaw detection, classification, assembly, labeling, coding, coding, (soft copying) ) spraying and a series of work. Since all parts of Baigegra's guide rails, drive motors, speed reducers, and control systems are all produced by themselves, the overall performance of the robot is even better. For more than a decade, the factory robots and production lines are all working properly. It is deeply loved by new and old customers in packaging machinery, printing machinery, machinery and electronics, automobiles, food, medicine and cosmetics production.

More than 120 experts and engineering technicians of Bagra Co., Ltd. have successfully developed and manufactured linear guide rails of various specifications, and on this basis, have worked closely with users to develop general-purpose and special-purpose robots. Thousands of sets have been provided for many manufacturers. Robots and production lines. One of the application areas is the detection of quality defects in product labels.

In the Cartesian robot, each axis mainly performs linear motion, and the motion directions are usually perpendicular to each other, so it is called a Cartesian coordinate robot. Cartesian robots can be classified into one-dimensional to multi-dimensional, each of which is a motion axis and consists of a linear motion unit. A three-dimensional orthogonal coordinate robot for spraying is composed of three linear motion units, and a palletizing robot is usually composed of several one-dimensional, two-dimensional and three-dimensional rectangular coordinate robots according to application requirements. The main technical data of the Bagra company's Cartesian coordinate robots are 0 to 18 meters of travel, 1 to 180 kilograms of load, and 0.05 millimeters of repeated positioning accuracy. The maximum speed of each axis is 5 meters per second. Figure 4 is a typical 3D Cartesian robot.

Machine Vision System

Machine vision is the function of making the machine's eyes and parts of the human brain automatic, such as shape measurement, print quality defect recognition and product appearance quality recognition. Machine vision systems are often used for detection and identification in high-volume production processes that are fully automated, highly reliable, and contactless. The common vision system generally includes the following parts: light source, lens, CCD camera, image acquisition card, image processing software, monitor, communication/input/output unit, etc. There are also many smart cameras that have their own lens, CCD camera, high-speed CPU, memory, commonly used image processing software, communication ports and/or input/output units. The CCD camera has a color camera and a black and white camera. This article only introduces the CCD black-and-white camera.

First, the CCD camera converts the captured target into a grayscale image signal, which is first amplified and then digitized as a digital image. The digital images are stored in a two-dimensional matrix. For example, each digital image of the Vision Components GmbH smart camera VC2028 is a 640*480 two-dimensional matrix. Each element of this matrix is ​​called a pixel, and its value is usually 0~255. The pixel values ​​0 to 255 correspond to the darkest and brightest parts of the target. The image processing software extracts the characteristics of the target in the image based on information such as pixel distribution and brightness change in the image, such as: area, length, number, position, etc., and then compares and matches the stored template, and finally gives the result, such as: size, Angle, offset, number, presence/absence, etc.

2.2.1 System Hardware Configuration

In this article, the CCD camera used the smart camera VC2028 from German Vision Components GmbH. The configuration is as follows: CCD chip is Sony 1/2” 640*480 dots, 25 frames per second, memory configuration is 16MB SDRAM, 2 MB Flash Eprom, 8 bit overlay, CPU is TMS320C62XX, speed is 1200MIPS (1200 per second) Millions of instructions.. VC2028 through its own RS232 port can be sent to the PC location data. VC2028 also comes with 4 digital input and 4 digital output. According to the field of view and height of the corresponding lens selection.

2.2.2 Identify System Functions

The detection system is the E 4000 OCV/2 system of German Vision Experts GmbH. It consists of a smart CCD camera VC2028 and patented identification software. It can detect various symbols such as symbols that can be printed, code symbols, thermal transfer, laser engraving Wait. All the following problems can be found with 100% assurance: The entire misspelled character, some missing characters, some characters are incomplete, and confusion between different characters, such as 5 and 6; 6 and 9 are imprinted, the characters are not in the correct position, and the character's font is not correct. Or inconsistent. The system can recognize a variety of symbols. When the contrast between the symbol to be identified in the image and the background changes slightly, such as a problem with the lighting system, or even when there is a regular texture in the image background, the system can work well. The system is also very flexible. It can detect only 10 products in one minute and 100,000 products in one hour. It can detect 300 characters at the same time and can detect the collection of symbols containing 10 fonts at the same time. Detect up to 100,000 products per hour. Each image can have 400 symbols and detect 10 different font symbols at the same time. The detected object can be rotated and detected in real-time during the movement. The detection data is automatically given. The self-check and external signal start the company. The detected symbols can be reduced and enlarged, and the position data of the symbol is given.

The operator does not require any programming experience, and very complex inspection tasks can be set up within minutes. The operator only uses the manual operator to define the window of the area to be inspected, teaches the test system all the symbols to be identified, and enters several parameters through the operation menu. The operator can fully master the system after a few hours of training.

This article describes the Cartesian robot Cartesian coordinate robot and the German Vision Experts GmbH E4000 OCV/2 inspection system. Germany's Vision Experts GmbH's E 4000 OCV/2 inspection system is mounted on the Bagra company's single-axis Cartesian robot and has been used successfully by many users for text symbol testing. The system is very reliable and can find 100% of the following issues: the entire missed character, part of the missing characters, some characters are incomplete, and confusion between different characters, such as 5 and 6; 6 and 9 are printed and mixed, the character position is wrong, The font of the character is incorrect or inconsistent. The detection system has largely replaced a similar system in the United States in Europe and has become the most reliable system on the European and American markets.

With the rapid development of high-volume, fully automated production and the fact that many products are to be tested 100% in many production processes, such Cartesian coordinate robots and image processing systems will have a broader range of market prospects and development potential.

Source: Jiagong Machine Grid