The fiberglass electronic fabric inspection system relies on independently developed deep learning algorithms, machine vision technology, big data and other technologies to achieve real-time online detection and classification of various defects in fabrics.
Employing multiple inspection lines, a high-speed, high-performance computer, and a user-friendly interface, the equipment easily identifies various existing defects, ensuring stable, reliable, and efficient operation.
Function:
1. Real-time pattern recognition and automatic classification of detected defects, with an accuracy rate of up to 99%;
2. Real-time merging of defects detected by different cameras in the longitudinal and latitudinal directions.
3. Different types of defects are rated and scored according to customer requirements and standards, thereby automatically generating a rating result for the entire roll of fabric, which can be divided into categories such as first-class products and qualified products.
4. It can be installed to record or mark fabric defects as needed; and accurately locate the coordinates of the defects.
5. Real-time online detection of parameters such as warp density, weft density, actual length, width, and speed.
6. Analytical and statistical capabilities: Provides statistical reports and information under various conditions at any time. Based on data analysis, identifies the production locations where defects occur, optimizes processes, and reduces defect generation. Analysis and statistics can be performed according to different conditions such as treatment agent, yarn type, defect type, kiln number, loom type, and product specifications.
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