An online fabric defect detection and alarm system based on machine vision
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A defect detection and alarm system technology, applied in the field of detection systems, can solve problems such as inability to intervene in fabric production, and achieve the effects of improving defect identification efficiency, reducing fabric defective rate, and reducing defective rate
What is AI technical title?
AI technical title is built by PatSnap AI team. It summarizes the technical point description of the patent document.
A defect detection and alarm system technology, applied in the field of detection systems, can solve problems such as inability to intervene in fabric production, and achieve the effects of improving defect identification efficiency, reducing fabric defective rate, and reducing defective rate
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[0024] The architecture of the online fabric defect detection and alarm system based on machine vision of the present invention will be described in detail below with reference to the accompanying drawings, but this does not constitute a limitation to the present invention.
[0025] An online fabric defect detection and alarm system based on machine vision of the present invention such as figure 1 shown. In the process of fabric production, high-definition and high-speed cameras are used to obtain online video of fabrics. The acquired online video is digitally processed by the video AD, collected and preprocessed by the video processor, and can be output to a video terminal, such as a liquid crystal display, etc. through the video processor. The collected video is processed by the main processor intelligently, mainly including video feature extraction, common defect detection (using multi-mode adaptive defect detection method), printing defect detection and other functions. ...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
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Abstract
The invention provides an on-line fabric flaw detection and alarming system based on machine vision. According to the invention, a high-resolution and high-speed camera is used for acquiring a fabric on-line video; the obtained on-line video is subjected to video AD digital processing, and is collected and pre-processed by using a video processor; the processed video is outputted to a video terminal through the video processor; the video is subjected to intelligent video processing by using a main processor; flaw detection is carried out with a multi-mode self-adaptive flaw detection method; if a flaw is detected, the main processor notifies a control device for stopping the machine from production, and alarms; in case of false detection, with a human-machine interaction interface, the production device is notified of continuing production; otherwise, production is stopped such that the amount of fabric with flaws can be reduced. With the on-line fabric flaw detection and alarming system based on machine vision, an on-line video detection method is introduced. With the adopted multi-mode self-adaptive flaw detection method, flaw identification efficiency is improved, and defect rate is reduced.
Description
technical field [0001] The invention belongs to the field of detection systems, and in particular relates to an online fabric defect detection and alarm system based on machine vision. Background technique [0002] In the textile industry, the defect detection of fabric products plays an important role. Improving the accuracy and efficiency of fabric defect detection will contribute to the customer satisfaction of the entire product and the overall benefit of the product. Generally speaking, after the fabric becomes a defective product due to fabric defects, its value will be reduced by 40% to 50%, or even lower. At present, there are mainly two methods for fabric defect detection: [0003] Manual detection mainly relies on human vision to detect defects. This method mainly consumes a lot of manpower, the efficiency of defect detection is low, and there is a certain rate of missed detection due to human visual fatigue and other reasons. [0004] The automatic detection me...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
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