Accuracy evaluation for sub-aperture interferometry measurements of a synchrotron mirror using virtual experiments

Wiegmann, Axel; Stavridis, Manuel; Walzel, Monika; Siewert, Frank; Zeschke, Thomas; Schulz, Michael; Elster, Clemens

doi:10.1016/j.precisioneng.2010.08.007

Cited by 24 publications

(23 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is well demonstrated in different datasets for x direction, i.e. for different groups of datasets (11,12,13), (21,22,23) and (31, 32, 33), the errors are distributed (from left to right) in a increasing manner, first decreasing and then increasing manner, and decreasing manner, respectively. …”

Section: Simulation Verificationmentioning

confidence: 54%

“…Ye et al [10] used an optimal stitching planning method to measure large aspheric optical surface with ±4 mm range of probe and 20% of overlapped region. Wiegmann et al [11] evaluated the accuracy of the sub-aperture stitching method using virtual experiments and found that the overall accuracy of stitching result outperformed the direct measurement method by a factor of about 3. For surface measurement instruments such as coherence scanning interferometers, which are widely used today for precision surface measurement, some commercial products can provide a stitching function for relatively flat surfaces [12].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Gaussian process and image registration based stitching method for high dynamic range measurement of precision surfaces

Liu

Cheung

Cheng

et al. 2017

Precision Engineering

View full text Add to dashboard Cite

Please cite this article as: Liu MY, Cheung CF, Cheng CH, Su R, Leach R.K.A Gaussian process and image registration based stitching method for high dynamic range measurement of precision surfaces.Precision Engineering http://dx.doi.org/10. 1016/j.precisioneng.2017.04.017 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. A Gaussian Highlights： It makes use of Gaussian process to model the sub-aperture measurement datasets to obtain the mean surface for registration, which is a novel method as comparing to traditional filtering methods, and provides better registration accuracy. Image registration and z shift method are used to simplify the 6 degrees of freedom 3D point cloud registration to a 3 degrees of freedom registration. Edge intensity data fusion method is used to fuse the overlapped region to provide a better transition between two datasets. It provides a novel stitching solution for a wide range of optical measurement instruments for achieving high dynamic range optical measurement of precision surfaces Abstract: Optical instruments are widely used for precision surface measurement. However, the dynamic range of optical instruments, in terms of measurement area and resolution, is limited by the characteristics of the imaging and the detection systems. If a large area with a high resolution is required, multiple measurements need to be conducted and the resulting datasets needs to be stitched together. Traditional stitching methods use six degrees of freedom for the registration of the overlapped regions, which can result in high computational complexity. Moreover, measurement error increases with increasing measurement data. In this paper, a stitching method, based on a Gaussian process, image registration and edge intensity data fusion, is presented. Firstly, the stitched datasets are modelled by using a Gaussian process so as to determine the mean of each stitched tile. Secondly, the datasets are projected to a base plane. In this way, the three-dimensional datasets are transformed to two-dimensional (2D) images. The images are registered by using an (x, y) translation to simplify the complexity. By using a high precision linear stage that is integral to the measurement instrument, the rotational error becomes insignificant and the cumulative rotational error can be eliminated. The translational error can be compensated by the image registration process. The z direction registration is performed by a least-squares error algorithm and the (x, y, z) translational information is determined. Finally, the overlapped regions of the measurement datasets are fused together by the edge intensity ...

show abstract

Section: Simulation Verificationmentioning

confidence: 54%

Section: Introductionmentioning

confidence: 99%

A Gaussian process and image registration based stitching method for high dynamic range measurement of precision surfaces

Liu

Cheung

Cheng

et al. 2017

Precision Engineering

View full text Add to dashboard Cite

show abstract

“…This task can typically be solved only by mathematical simulations of the complete measuring system. For this purpose, at PTB a simulation environment for optical surface metrology has been built, which is named SimOptDevice (Simulation for Optical Device) [11,12]. In a virtual experiment, a model of the measurement device is used and the measurement process is simulated (Fig.…”

Section: Interferometric Measurement Of Aspheresmentioning

confidence: 99%

Traceability in interferometric form metrology

et al. 2015

View full text Add to dashboard Cite

The concept of traceability is presented for the interferometric form measurement of optical surfaces. The calibration chain for interferometric flatness measurement is evaluated in detail, showing that only a few influence quantities are significant. For spherical surfaces, the complexity increases as the measurement separates into sphericity and radius measurement. Traceability in asphere metrology is much more complex, and some aspects are discussed in terms of the example of the Tilted-Wave Interferometer concept.

show abstract

“…The computer model is implemented in MATLAB, which is a widespread tool for modeling and prototyping in the scientific community. It supports object-oriented programming approaches, which allow the modeling of a measuring system in a flexible way for various applications [23][24][25][26][27][28].…”

Section: Computer Modelingmentioning

confidence: 99%

Virtual experiment for near-field goniophotometric measurements

et al. 2014

Self Cite

View full text Add to dashboard Cite

Near-field goniometric measurements are employed to determine the photometric characteristics of light sources, i.e., the spatial and angular distribution of the emitted light. To this end, a complex measurement system consisting of a goniometer and a CCD-based imaging photometer is employed. In order to gain insight into the measurement system and to enable characterization of the whole measurement setup, we propose to apply a computer model to conduct virtual experiments. Within the computer model, the current state of all parts of the virtual experiment can be easily controlled. The reliability of the computer model is demonstrated by a comparison to actual measurement results. As an example for the application of the virtual experiment, we present an analysis of the impact of axial malpositions of the goniometer and camera.

show abstract

Accuracy evaluation for sub-aperture interferometry measurements of a synchrotron mirror using virtual experiments

Cited by 24 publications

References 24 publications

A Gaussian process and image registration based stitching method for high dynamic range measurement of precision surfaces

A Gaussian process and image registration based stitching method for high dynamic range measurement of precision surfaces

Traceability in interferometric form metrology

Virtual experiment for near-field goniophotometric measurements

Contact Info

Product

Resources

About