Wednesday 21 May 2014

Inspecting cylindrical surfaces!

A new industrial vision system, trevista Cylinder, from Stemmer Imaging allows automated inspection of milled, polished and galvanised cylindrical components for defects such as scratches, dents, discolouration and stress marks. Using a patented inspection process, trevista Cylinder goes beyond the limits of conventional vision systems to provide reliable inspection of a range of surfaces from glossy components to diffusely scattering surfaces and even black plastic.

Supplied as a complete system with structured diffuse illumination, lens, camera, software and PC, trevista Cylinder, is based on a patented "shape from shading" technology. Information on the three- dimensional shape of an object can be deduced from the shading of its surfaces.

The cylindrical objects are rotated along their longitudinal axis under the special dome- shaped diffuser. During the rotation the line scan camera surveys the object with a scanning speed up to 4x. The profile data obtained are planar images of the uncoiled material surface. These synthetic images contain topographic information and a special calculation algorithm allows inspection for characteristics such as scratches, dents, discoloration and stress marks according to their inclination, curvature and texture.
The topographic images allow the display of three- dimensional surface shape, revealing defects down to just a few micrometres depth. These defects can be located quickly, reliably and free of interference, and can be readily distinguished from irrelevant stains caused by lubricants for example. 


The image processing algorithms can be integrated into the popular Sherlock advanced machine vision software interface from Teledyne DALSA or Stemmer’s own Common Vision Blox imaging toolkit. This provides a powerful and easy- to-handle complete solution which can be easily integrated into a wide variety of production processes. The system allows early detection of manufacturing defects in the value chain, thus reducing costs for quality assurance. 

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