Mr. Wolfram Acker Profile

Wolfram Acker

at Univ Hannover

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Proceedings Article | 21 April 2006 Paper

Surface inspection system for carriage parts

Berend Denkena, Wolfram Acker

Proceedings Volume 6198, 619801 (2006) https://doi.org/10.1117/12.662572

KEYWORDS: Projection systems, Cameras, Line scan cameras, Inspection, Visualization, Clouds, Spatial filters, Computer aided design, 3D modeling, Process modeling

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Quality standards are very high in carriage manufacturing, due to the fact, that the visual quality impression is highly relevant for the purchase decision for the customer. In carriage parts even very small dents can be visible on the varnished and polished surface by observing reflections. The industrial demands are to detect these form errors on the unvarnished part. In order to meet the requirements, a stripe projection system for automatic recognition of waviness and form errors is introduced¹. It bases on a modified stripe projection method using a high resolution line scan camera. Particular emphasis is put on achieving a short measuring time and a high resolution in depth, aiming at a reliable automatic recognition of dents and waviness of 10 μm on large curved surfaces of approximately 1 m width. The resulting point cloud needs to be filtered in order to detect dents. Therefore a spatial filtering technique is used. This works well on smoothly curved surfaces, if frequency parameters are well defined. On more complex parts like mudguards the method is restricted by the fact that frequencies near the define dent frequencies occur within the surface as well. To allow analysis of complex parts, the system is currently extended by including 3D CAD models into the process of inspection. For smoothly curved surfaces, the measuring speed of the prototype is mainly limited by the amount of light produced by the stripe projector. For complex surfaces the measuring speed is limited by the time consuming matching process. Currently, the development focuses on the improvement of the measuring speed.

Proceedings Article | 14 April 2006 Paper

Optical inspection system for implants

Berend Denkena, Wolfram Acker

Proceedings Volume 6191, 619118 (2006) https://doi.org/10.1117/12.662551

KEYWORDS: Image filtering, Cameras, 3D metrology, Bone, Surface finishing, 3D modeling, Light sources, Light emitting diodes, Linear filtering, Wavelets

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Hip and knee prostheses are complex products with high quality standards. The aim is to reproduce the behavior of a natural joint. This can be achieved by using a hard and a soft component. The research project "Optical Geometry Acquisition of Medical Implants and Prostheses", short "OptiGIP", explores methods for an automated quality assurance included in the production chain of these components. The approach is divided in two sections, a three dimensional and a two dimensional measurement technique. First a stripe projection method is used to produce a three dimensional model of the component. This model can be used to verify the geometry of the component. Furthermore it enables a new examination method, the Model-Based RSA, which is used to explore the effect of loosening. A late loosening of the components within the bones is the most important quality criterion for a successful implantation. The second part of described measurement method aims at a reduction of an early loosening of the prosthesis. Even very small scratches on the prosthesis's surface can have an impact on an early loosening because of friction between the soft and hard surface. Scratches produce bigger particles of the soft component than an undamaged surface would do. Recent research activities show that these bigger particles have an influence on an early loosening mechanism. The two-dimensional measurement checks the quality of the surface of the hard component of the implant. The approach is to use an extended dark field method. The prosthesis is illuminated from various angles producing a sequence of images. These images are filtered to distinguish between reflections from scratches and direct reflections. A combination of the filtered images shows the scratches.

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