The technological environment of industrial production processes faces constant
challenges and is subject to continuous change. Requirements regarding resource
and emission savings as well as lightweight construction, functionalization and individualization are key drivers of technical innovations. In particular, increasing
automation, process monitoring and fast component inspection are of growing
importance, which requires novel and innovative measurement approaches and
instruments.
In this thesis, a flexible, fiber-optic 3D endoscope based on fringe projection
profilometry is presented for in-situ wear monitoring in operating forming processes.
Due to specific measuring applications, different measuring head designs
and positioning configurations are required. Flexible positioning necessitates
strategies for registration of the reconstructed surface data in a fixed world
coordinate system, which is investigated in the context of different approaches.
Furthermore, algorithms and methods for adaptive data masking and improved
data fusion are developed and presented, allowing for low-noise and accurate
surface reconstruction while maintaining as many object points as possible.
Complementary, methods for the reduction of inaccurate deviation values are
developed to enable a high sensitivity and conclusiveness of the inspection.
Furthermore, approaches for fast point cloud classification by adapted search
trees and estimation methods are presented. Finally, the sensor is evaluated
on the basis of existing standards and further developed approaches, and the
influence of various environmental factors is investigated and quantified in
various experiments.
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