Fiberglass product line
Online fabric inspection on looms
The online defect detection system for looms is installed at the weaving point of the loom to continuously and uninterruptedly inspect the fabric, promptly detecting various defects. For serious defects, the machine is stopped and alarms are triggered, requiring manual handling. Tolerable yarn defects are statistically recorded as raw data for grade evaluation. This can minimize the impact of defects on the final fabric, and can even ensure that the woven fabric is of acceptable quality, eliminating the need for further inspection and repair. The data file of this roll of fabric can be printed or copied on the host computer and shipped directly to the factory, reducing processes and lowering costs.

Function:

1. Suitable for: electronic cloth, ultra-thin electronic cloth, cotton cloth, gauze, etc.;
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Applicable scenarios: Electronic cloth/ultra-thin electronic cloth/cotton cloth/gauze, etc.;
Inquiry Hotline 400-8800-716
Product Features
01
Accurate detection of multiple types of defects
Detectable defects: various common defects, such as broken weft, double weft, sparse and dense lines, thick knots, weft shrinkage; missing warp, broken warp, warp shrinkage, loose warp, tight warp, reed marks, waste yarn woven in, joints, skipped patterns; weaving holes, poor edges, excessively long rough edges, stains, tears, breaks, with a detection rate of over 95%.
02
Defect AI Classification
Artificial intelligence methods are used to intelligently classify detected defects, with a classification accuracy rate of over 85%.
03
Flexible handling
Different defects can be handled differently, such as stopping for correction or recording without stopping, as needed.
04
Network statistical analysis
A database is used to store detailed records and images of defects for each roll of fabric, with a single machine capable of permanently storing all data for 10 years. Defect images from the current roll and any roll within the past three months can be viewed. Network connectivity allows for statistical analysis of data across the entire workshop, identifying the causes of defects, which is beneficial for quality control and improvement.
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