Deflectometry for technical surfaces (DOTS)

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Quality control requires, for many production processes, a fast, robust, non contact and high precision measurement technique for 3D form measurement. In view of these requirements, optical, non-interferometric techniques appear very suitable. The applicability and accuracy of these techniques, however, strongly depends on the surface properties of the objects under consideration. This is especially true for the surface roughness which may be very different for various technical surfaces. Individual technical objects often have to some extent optically smooth (mirror like or specular) areas as well as rough areas, making high-precision, reliable measurements extremely challenging.Phase Measuring Deflectometry (PMD) is a geometric-optical metrology technique primarily used for 3D form measurement of mainly specular objects. Systems based on PMD are in principle well suited for the characterization of technical surfaces, as they are smaller, cheaper and faster compared to tactile form measurement systems. However, the theoretical framework of PMD presupposes perfectly specular surfaces, neglecting object surface roughness and waviness. Technical object surfaces usually do not fulfil these demands and lead to additional measurement errors not adequately characterized up to now.Thus, the goal of this project is to develop realistic surface models for PMD measurements on technical surfaces that can predict the surface-related statistic and decrease systematic measurement errors. The sub-goals to be accomplished are: i) Modelling of the relationship between shape of the measurement object, geometry of the PMD setup and phase measurement errors, supported by test measurements of sample objects and simulation of measurements; ii) Modelling of the propagation of phase measurement errors into the derived quantities of surface forms, gradients and curvatures. The model used for achievement of sub-goal i) is the Bidirectional Reflectance Distribution Function. The approaches to this function are the Phong-procedure and Monte-Carlo methods. Sub-goal ii) is obtained by employing Least Squares Integration as well as Radial Basis Function Integration.With the models developed, systematic PMD measurement errors can be predicted and their reasons identified, and thus they can be corrected. Also the statistic uncertainties can be quantitatively determined for different types of object surfaces. This makes it possible for the first time for PMD form measurements to i) systematically adapt the PMD setup and the measurement procedures to the object surface to be measured; ii) increase the PMD measurement accuracy by correcting object surface-related systematic errors; and iii) calculate spatially resolved statistic measurement uncertainty maps related to the object surface.At the end of the project an optimized deflectometric measurement process suitable for technical surfaces shall be available in order to close a significant gap for industrial quality control.