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Online detection method of printing machine based on machine vision

A detection method and machine vision technology, applied in the direction of optical testing flaws/defects, etc., can solve the problems of inability to guarantee the detection quality, high labor intensity, visual fatigue, etc., and achieve the effect of avoiding repetition, fast response, and ensuring accuracy.

Inactive Publication Date: 2011-11-30
张爱明
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Aiming at the problems that the online manual detection of calico defects in the prior art is labor-intensive and prone to visual fatigue, the inspection quality cannot be guaranteed and the product delivery rate is low, the present invention provides an online detection method for calico defects by a machine vision system Overcome the instability factors caused by human eye detection

Method used

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  • Online detection method of printing machine based on machine vision
  • Online detection method of printing machine based on machine vision
  • Online detection method of printing machine based on machine vision

Examples

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Embodiment Construction

[0018] Such as figure 1 As shown, the hardware part is composed of an industrial camera 1, a light source 2, and a printing machine controller 3. The industrial camera of this embodiment adopts In-Sight1403C of Cognex Company, with a resolution of 1600×1200, capable of high-resolution inspection of various color applications. The light source is a ring light that surrounds the camera. The control system is built into the printing machine controller and consists of trigger signal generation module, image template pre-storage module, ingested image preprocessing module, image comparison module, feedback alarm and other modules. Such as figure 2 The flow chart of online detection is shown, and the following is a detailed description of the process.

[0019] 1. The pattern determined during plate making is stored in the printing machine controller as a standard image template;

[0020] 2. Set the allowable value of the defect area and image grayscale error;

[0021] 3. The t...

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PUM

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Abstract

The invention relates to the field of machine vision, in particular to a printing machine vision online detection method. It solves the problems of poor real-time response, heavy labor, high labor intensity and low detection level of manual detection of printed defective products. The present invention uses the image scanning device to scan the image of the printed product line by line and transmit it to the controller of the printing machine. After image processing, it is compared with the data segment corresponding to the printed image file prestored in the vision controller. If there is inaccurate registration, For defects such as missing printing, ghosting, and color difference, the interface circuit of the machine vision controller outputs a fault signal to prompt the operator to dispose of it or feedback the fault code to the upper controller, and the upper controller performs the next step of control. The invention has fast detection response speed, high precision, real-time detection during the printing process, and avoids printing defective products to the greatest extent.

Description

technical field [0001] The invention relates to the technical field of on-line detection by using a machine vision system, in particular to a method for on-line detection of defects of the calico by using a machine vision system at a printed cloth production site. Background technique [0002] In the production workshop of printing and dyeing calico in assembly line operation, the defects of calico need to be detected online. In the prior art, the on-line detection of calico defects relies on manual detection, and 2-4 people are arranged on both sides of the printing machine to visually inspect and process the defects of calico, and 1 person is arranged at the drying place to carry out inspection. Product quality tracking and testing. Its disadvantages include: high temperature and humidity on site, harsh working environment for workers to detect, and high labor intensity; workers who work for a long time are prone to visual fatigue, especially when the pattern is complex, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/88
Inventor 张爱明
Owner 张爱明
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