China Automated Vision Inspection Solutions

Fiberglass Fabric Inspection Machine

Detectable Defect Types:
Holes, scratches, stains, color deviations, coating defects, etc. (as illustrated)

Inspection Target:
Fiberglass fabrics

Overview

The online inspection system can detect defects in real-time during production and provide product quality information. It records quality data to optimize production processes. The system performs non-contact edge defect detection, surface flaw inspection, and dimensional measurement for products of varying widths and machine speeds.

RVT-Fiberglass Vision employs high-resolution line-scan cameras to capture fiberglass fabric images. Specialized image processing and analysis software based on an industrial control computer automatically detects surface defects, measures dimensions, and logs defect data into a categorized database. The system features a user-friendly Windows-based graphical interface.

Highlights

-- Recipe Management

The software allows customized parameter settings for each product type, saved as a “recipe.” During production, simply selecting the recipe automatically loads the corresponding parameters.

-- Classification

Defects are accurately classified using AI-based analysis of captured images, enabling customized criteria for different defect types.

-- Defect Recording (Database Functionality)

Defect characteristics and image data are stored in database files for offline queries, reporting, and printing.

-- Real-Time Interface Display

Instantly shows detected defect images, characteristic data, and trend charts.

Machine Performance Specification

Core Components:
High-performance industrial computer
Proprietary image processing software (fully independent IP)
High-res line-scan cameras (2K-16K resolution)
Long-life LED illumination
Dedicated tooling & fixtures
Performance:
Scalable camera array for adjustable resolution
Max. line speed: 500 m/min
Capabilities:
Surface defect detection pre/post-production
Automatic defect coordinate logging (machine & cross directions)
AI-based defect classification
Automatic defect image archiving
Auto-generated roll quality reports & defect distribution maps