Online Surface Defect Detection System for Aluminum Plates and Strips
2026-03-18
Online Surface Defect Detection System for Aluminum Plates and Strips
1. System Application Background
With the rapid development of China's aluminum processing industry, high-value-added products including anodized aluminum, CTP plate bases, can-body aluminum and automotive aluminum sheets have become the core products of aluminum plate and strip manufacturers. Traditional manual visual inspection can no longer meet the demands of high-speed production, such as real-time monitoring, online early warning, defect analysis and finished product grading. Therefore, a machine vision-based online detection system is essential to achieve accurate, real-time surface quality control for high-precision aluminum plates and strips.
2. Core System Composition
The detection system consists of two core modules: hardware structure and software system, both designed for industrial aluminum processing scenarios.
2.1 Hardware Configuration
Key hardware components include high-intensity lighting sources, high-speed CCD cameras, image acquisition and processing systems, data interfaces, system servers, data servers and disk arrays. This hardware framework ensures stable signal collection and data storage under harsh production environments.
2.2 Software System (Windows-Based)
The software integrates professional image processing modules with powerful visual functions: system operation monitoring, quality defect collection, secondary image processing, real-time display, and report & grading modules, realizing full-process quality tracking and management.
3. Key Hardware Selection & Performance
3.1 Lighting Source Selection
High-intensity lighting is a critical part of the system, solving CCD signal acquisition difficulties caused by on-site harsh conditions and aluminum surface diffuse reflection.Halogen light sources (strong penetration) are suitable for hot rolling mills, while uniform scattering LED light sources are applied to finishing mills. Field tests prove that when rolling speed exceeds 500m/min, light intensity must be ≥35mcd.
3.2 CCD Camera Performance
The system adopts Canadian Dalsa high-speed CCD line-scan cameras, featuring continuous line-scan technology with a maximum tracking speed of 20,000 lines per second and a precision resolution of 0.2×0.2mm. It fully captures surface images, ensuring accurate detection of low-contrast defects.
4. Image Processing & Defect Detection Logic
4.1 Image Preprocessing
CCD signals transmitted synchronously by encoders are preprocessed via an acceleration card to enhance quality. Preprocessing steps include Fourier analysis for noise reduction, brightness and contrast adjustment, edge sharpening, and median filtering. This process suppresses interference, clarifies defect edges, and highlights defect features for accurate identification.
4.2 Gray Analysis & Defect Judgment
Theoretically, defect-free aluminum surfaces show continuous uniform gray values; in actual production, gray values fluctuate within a normal range. Once gray values exceed the threshold, combined with features such as brightness, contrast and occurrence frequency, the system preliminarily identifies potential defects.
4.3 Automatic Defect Recognition & Processing
The automatic recognition system matches collected signal features with preset standard ranges of common aluminum defects. After confirmation, defects are displayed in real time. The system also supports synchronous defect marking, full-roll surface quality grading, and complete quality data collection for traceability and production optimization.
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