Visual Appearance Inspection

Product Introduction

Surface defects not only affect the aesthetics and comfort of the product, but also generally have a negative impact on its performance. Therefore, manufacturers place great importance on surface defects. However, traditional manual inspection is inaccurate, lacks real-time capability, is labor-intensive, and is highly influenced by human experience and subjective factors. Machine vision-based inspection methods largely overcome these drawbacks.

The Simida Intelligent Visual Appearance Inspection System captures product surface images using appropriate light sources and image sensors, extracts feature information from the images through corresponding image processing algorithms, and then locates, identifies, and classifies surface defects based on this information. It achieves comprehensive inspection of appearance defects in fiber yarn cakes, precise detection of surface defects on metal materials, and challenging detection of surface blemishes on printed products.

Inspection for all appearance defects in fiber yarn cakes

Detection of all defects on various fiber yarn cakes, including the top and bottom surfaces, the 360° circumference surface, and the paper tube.

1) Inspect the surface of the spool for hairiness, stiffness, and entanglement.

2) Poor silk cake formation and surface stain detection

3) Paper Tube Color and Defect Detection

4) Defect Classification