Abstract
The use of computer vision techniques to inspect surface roughness of a workpiece under a variation of turning operations has been reported in this paper. The surface image of the workpiece is first acquired using a digital camera and then the feature of the surface image is extracted. A polynomial network using a self-organizing adaptive modeling method is applied to constructing the relationships between the feature of the surface image and the actual surface roughness under a variation of turning operations. As a result, the surface roughness of the turned part can be predicted with reasonable accuracy if the image of the turned surface and turning conditions are given.
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