ResearchProject Area A
Subproject A2

Subproject A2 Multiscale Geometry Measurement

The focus of sub project A2 is the development of a robot-assisted multi sensor system for the automated 3D acquisition of complex geometries. The results of such measurements are used to classify components with respect to their damage and abrasion occurrences on a macroscopic level and furthermore to characterize their local topographies on a microscopic level. The multiscale measurement system is used for a first diagnosis of worn components and in between certain regeneration processes to make a statement about the current objects state.


Edge measurement. Deflector mirrors are used to aim a laser line onto a turbine blade. The polyview objective allows the camera to capture the line from multiple perspectives and thus measure the edge.

The results of a first diagnosis for worn turbine components is the basis for decisions in the regeneration process and therefore crucial for the process itself. In order to repair such components the degree of damaging has to be estimated. For that, the current geometrical state as well as microscopic structures and the surface roughness must be known in detail.

Currently, the decision making of the previously mentioned regeneration processes are based on human visual inspections and experiences. In order to fully automate the regeneration process, a suitable, automated measurement routine has to be developed. Since conventional single-sensor-systems do not offer the possibility to cover the spectrum of required scales, the main objective of sub project A2 was to develop a robot based, non-destructive multiscale sensor system. For an accurate positioning, the measurement system was attached to an industrial robot with six degrees of freedom.

After a successful measurement, the acquired data from all used sensors can be fused into a single dataset, providing a holistic model of the measurement object. That model can then be examined for features like abrasions and damages which are furthermore classified to make a valid assertion about the components current state.

Gathered data is used by other sub-projects to run simulations or plan tool paths for further processing steps.

The pose of the robot endeffector with the attached multi sensor system is determined by a high accurate laser tracker, which later connects the individual measurements with each other. Each sensor and its corresponding measurement principle is shown in the following order: Fringeprojection and the resulting stitched 3D-Mesh of a worn turbine blade, the edge sensor with poly-view optics, the BRDF-sensor for an approximation of the bidirectional reflectance distribution function and a measurement of the surface topographies using the low coherence interferometer with an extension arm measuring a turbine blisk.


Within the first funding periods, a variety of sensors for robot based applications were developed. Each sensor was built for a special use case: A fringe projection based system was used for a high resolution macroscopic acquisition of the measurement objects geometry. In order to inspect the edges of complex geometries, a special edge sensor with poly-view-optics was developed. For performance testings based on e.g. computational fluid dynamics, the roughness of a surface can be measured with a Low-Coherence-Interferometer (LCI). For non-geometrical characterization, a sensor was developed, which is able to approximate the bidirectional reflectance distribution function (BRDF) and therefore make an assumption about the surfaces reflection properties to detect damages such as burns. In order to transform the acquired data from different sensors in a single coordinate system, a high resolution laser tracker was used to determine the position of the robots end effector.

Roughness measurement of a blisk with a low-coherence-interferometer (LCI). The multisensorsystem with a fringe projection system, a BRDF- and edge-sensor and the LCI is shown.


Current research is focused on the fusion of measurement data of individual modularities. Based on the acquired data, sets of damages are to be detected and classified. The extracted features are then combined to a single data base which will be provided to following sub projects in the regeneration path.

In order to automate the measurement process, another topic of interest is an adaptive, intelligent path planning which leads to the possibility to measure prior unknown geometries. Furthermore intelligent measurement poses are supposed to reduce measurement uncertainties which can occur during the process.


  • Li, Y.; Kästner, M.; Reithmeier, E. (2017) Vibration-insensitive Low Coherence Interferometer (LCI) for the Measurement of Technical SurfacesMeasurement
    DOI: 10.1016/j.measurement.2017.03.010
  • Schlobohm J.; Bruchwald, O.; Frackowiak, W.; Li, Y.; Kästner, M.; Pösch, A.; Reimche, W.; Reithmeier, E.; Maier, H. J. (2016) Turbine blade wear and damage – An overview of advanced characterization techniquesMaterials Testing 58 (5), S. 389–394
    DOI: 10.3139/120.110872
  • Schlobohm, J.; Li, Y.; Pösch, A.; Kästner, M.; Reithmeier, E. (2016) Multiscale measurement of air foils with data fusion of three optical inspection systemsIn: CIRP Journal of Manufacturing Science and Technology 2016
    DOI: 10.1016/j.cirpj.2016.07.006
  • Zou, Y.; Li, Y.; Kästner, M.; Reithmeier, E. (2016) Low-coherence interferometry based roughness measurement on turbine blade surfaces using wavelet analysisIn: Optics and Lasers in Engineering 82, S. 113–121
    DOI: 10.1016/j.optlaseng.2016.02.011
  • Li, Y.; Kästner, M.; Reithmeier, E. (2015) High-precision surface measurement with an automated multiangle low coherence interferometerApplied Optics 54 (6), S. 1232
    DOI: 10.1364/AO.54.001232
All publications of the Collaborative Research Centre


PD Dr.-Ing. Dipl.-Phys. Markus Kästner
Prof. Dr.-Ing. Eduard Reithmeier


M. Sc. Tim Betker
Nienburger Str. 17
30167 Hannover
Nienburger Str. 17
30167 Hannover
M. Sc. Nils Melchert
Nienburger Str. 17
30167 Hannover
Nienburger Str. 17
30167 Hannover