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IEEE Transactions on Instrumentation and Measurement
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Item-typ:Veröffentlichung, Geometric Partitioning of Complex Surface MeasurementsDimensional inspection of microparts is challenging. Optimized processes, such as microdeep-drawing with tailored tools, even increase the requirements. While the development of fast and precise data acquisition techniques is in progress and various solutions already exist, the geometrical evaluation of measuring data still shows open questions: 1) the evaluation methods for freeform surfaces do not provide information in a form that can be directly used to assess dimensional tolerances; 2) manual association of approximating geometric elements to points is not suited for high inspection rates; and 3) partitioning based on the nominal workpiece coordinate system is affected by alignment uncertainties. An algorithm was developed for the automated evaluation of surface measuring data composed of geometric primitives, such as planes, cylinders, and tori, which combines and optimizes the estimation of geometric parameters together with the automatic partitioning of the measured points. This article presents the extension of this holistic approximation (HA) with root point iteration in order to evaluate more complex geometric elements. The verification of the extended HA for a 2-D combination of lines and an ellipse shows no systematic error and achievable uncertainties below 0.8 μm for the approximated shape parameters of an ellipse for simulated surface data with uniformly distributed noise in the range of 1.0 μm. The validation in comparison with commercial metrology software finally exhibits the full potential of the extended HA. As a result, a fully automatic dimensional evaluation is possible, providing geometric parameters that can directly be compared to nominal specifications and tolerances.Wissenschaftlicher ArtikelBand:69Heft:7485 501 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Angular-Dependent Radius Measurements at Rotating Objects Using Underdetermined Sensor SystemsPrecise and contactless shape measurements of rotating objects is important, e.g., for monitoring and controlling the manufacturing quality in lathes. For this purpose, multisensor and single-sensor approaches based on optical distance and surface velocity measurements are state-of-the-art techniques. Two- and single-sensor systems are particularly promising to measure the angular-dependent radius of the cross section of the rotating object in a scanning regime with minimal optical access. Since a comparison between the different sensor systems is missing, the potential of these underdetermined sensor systems is unclear. In addition, displacements of the rotational axis and sensor misalignments are suspected to be crucial error sources, but the error is unknown. For this reason, an error analysis is performed regarding the resulting systematic error and the random error for the two- and single-sensor systems. As a result, the different sensor systems have an equal cross-sensitivity with respect to lateral displacements of the rotational axis from the sensor axes, but the two-sensor approach has the lowest sensitivity regarding sensor misalignments. For the studied measurement conditions, the systematic error dominates the sensor noise for the two-sensor system and the single-sensor system with combined distance and velocity measurement at an object mean radius >6 mm. The smallest total measurement uncertainty is obtained with the two-sensor system. Finally, the relevance of systematic error depends on the utilization, i.e., for instance on the absolute rotor radius, the stability of the rotor axis, the sensor position, the accuracy of the sensor alignment, and the uncertainty of the distance and/or velocity measurements.Wissenschaftlicher ArtikelBand:67Heft:273 83