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Proceedings Paper

Nondestructive evaluation of surface roughness by speckle correlation techniques
Author(s): Joerg Peters; Armin Schoene
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Paper Abstract

The most established way to inspect surface roughness of machined surfaces is to measure with profilometers. These techniques are not applicable for on-line inspection. A few decades ago, the correlation between laser speckles of different light wavelengths and surface roughness was discovered. Since then several authors have been working on this topic. In measuring systems which are considered in this paper, the surface which is to be inspected is illuminated by a polychromatic laser beam. The scattered light is converted by an optical system, which ensures that the product of wavelength times focal length is constant. In the Fourier plane of each subsystem a CCD-array is installed. The CCD- data are captured by a frame grabber and stored for evaluation in a computer. One major problem in industrial processes where surface roughness measurements had ben tried was that the inspected metal workpieces may be tilted and, therefore, the direction of spectral reflection changes. In the method discussed in this paper an approximate value of the surface roughness can be obtained by determining the difference between the zero orders of the scattering patterns of the wavelengths. This difference can be approximated by the position of the maximum of the 2D- cross correlation function of related speckle patterns. The main benefit of the method described is the feasibility of measuring roughness during machining or other types of continuous or semi-continuous production processes. This is achieved by a synchronous detection of speckle patterns of the different wavelengths used. In the pilot project the shutter sped of the cameras is 1/10000 seconds, therefore, in this case only frequencies above 1kHz disturb the measuring results.

Paper Details

Date Published: 15 March 1998
PDF: 12 pages
Proc. SPIE 3399, Process Control and Sensors for Manufacturing, (15 March 1998); doi: 10.1117/12.302563
Show Author Affiliations
Joerg Peters, Univ. Bremen (Germany)
Armin Schoene, Univ. Bremen (Germany)

Published in SPIE Proceedings Vol. 3399:
Process Control and Sensors for Manufacturing
Richard H. Bossi; David M. Pepper, Editor(s)

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