Roughness Detection Based on 3D Shape Reconstruction of Workpiece Surface Micro-Vision Image

Abstract:

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The Shape from Shading (SFS) method is adopted to detect the micro-topography and roughness parameter of machining surface based on computer micro-vision in this paper. According to the reflection features of micro metal surface, the illumination model is improved by the weighting superposition of the diffuse component of the simplified Oren-Nayar model and the specular component of the Torrance-Sparrow model. The minimized calculation method of SFS is given based on the improved illumination model. The 3D topography reconstruction and the roughness parameter detection of the turning surface are accomplished. The experimental results show that this method can rapidly realize the accurate detection of surface roughness parameter, and provides new ideas and methods for detection the roughness on-line in machining process.

Info:

Periodical:

Edited by:

Bo Zhao, Guanglin Wang, Wei Ma, Zhibo Yang and Yanyan Yan

Pages:

373-378

DOI:

10.4028/www.scientific.net/KEM.455.373

Citation:

J. M. Zheng et al., "Roughness Detection Based on 3D Shape Reconstruction of Workpiece Surface Micro-Vision Image", Key Engineering Materials, Vol. 455, pp. 373-378, 2011

Online since:

December 2010

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Price:

$35.00

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