Say goodbye to defects! Improve quality control and intelligent production in mica fabric weaving.
Published: 2026-06-25 17:52:41
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During the weaving process of mica fabric, defects such as broken warp and weft, excessive weft density, missing weft, clumps, and coarse knots frequently appear on the fabric surface, seriously affecting product quality, leading to product degradation and customer complaints, and becoming a major challenge for enterprise quality control. To address this challenge, our company has launched a product based on deep learning AI technology.Online fabric inspection system for mica cloth looms，Achieve the ability to handle multiple defectsReal-time, accurate identificationThis helps enterprises improve their quality control and intelligent manufacturing capabilities.
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System Introduction
This system integrates machine vision technology and deep learning algorithms, enabling comprehensive monitoring of the fabric surface condition during the weaving process and accurate identification of common defects such as warp breaks, weft breaks, dense weft, missing weft, tufts, coarse knots, and foreign objects. Users can flexibly set different defect handling methods according to actual quality requirements, achieving automatic machine shutdown or system alarm, effectively preventing the expansion of defects while maintaining production efficiency.
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Core functions and features
1. Intelligent recognition, defects have nowhere to hide.
The system can accurately detect a variety of common defects, including broken warp, broken weft, dense weft, missing weft, clumps, coarse knots, and foreign objects, with a resolution of 0.08mm. It fully covers a fabric width of 1200mm (customization is supported) and can still output high-definition images stably even on high-speed looms of 800 rpm.
2. Flexible response, balancing quality and efficiency
Based on AI algorithms, the system can handle different defects according to the settings: serious defects will be stopped immediately, while minor problems will be recorded and alarms will be set up without interrupting production, thus avoiding the expansion of defects and effectively ensuring the uptime rate.
3. Closed-loop operation, with full data traceability.
The system acquires weft insertion signals from the loom in real time and uses an anti-shake algorithm to clearly capture images of each weft. The data is transmitted at high speed via gigabit network and analyzed in real time by independently developed software. Defects are automatically archived, supporting the local saving and export of over 100,000 defect images for easy traceability analysis and process optimization.
4. Stable and reliable, adaptable to harsh environments
The equipment can operate continuously and stably in an environment of 0-40℃, has strong power adaptability, is easy to install, and can be quickly integrated into the existing production process. It is an efficient assistant for mica cloth manufacturers to achieve quality upgrades.
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Fabric defect pictures
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Technical Specifications Overview
? Detection width: 1200mm (customizable)
? Image resolution: 0.08mm
? Work schedule: 24-hour continuous operation
? Ambient temperature: 0-40℃
? Power supply: AC220V, 50Hz, voltage fluctuation ±5%
? Maximum compatible loom speed: 800 rpm
? Defect image storage: ≥100,000 images, export supported
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Application benefits
1. Significantly reduce the amount of downgraded fabric and improve the product qualification rate;
2. Timely intervention to prevent defects from continuing and escalating, and to reduce the waste of raw materials and labor time;
3. Support differentiated responses based on defect type to optimize production efficiency;
4. Provide data support for process improvement and quality traceability.
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The online fabric inspection system for mica cloth looms is dedicated to providing textile enterprises with efficient, reliable, and intelligent quality inspection solutions, helping them achieve high-quality and sustainable production.
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