Content
Overview
In a virtual experiment a measurement process is modeled mathematically and simulated on a computer. The employed mathematical model of the physical experiment is sought to be as realistic as possible. Virtual experiments allow different scenarios to be easily explored. In this way, measurement processes can be designed and specified with the help of the computer. Virtual experiments can be used to estimate the accuracy that is reached by a real measurement device. Dominant sources of uncertainty can be identified and quantitatively explored by carrying out a sensitivity analysis of the virtual experiment. The results obtained can be used to optimize the considered measurement system. Virtual experiments can help in the development of procedures from data analysis for real experiments, for example to assess and compare different estimation procedures under realistic conditions, or to validate assumptions made about the distribution of measured data.
Research
The research of PTB’s Working Group 8.42 focuses on virtual experiments for optical measurement devices and the development of procedures from data analysis for evaluating corresponding measurements. To this end, the simulation environment SimOptDevice has been developed as a software library, which is successfully employed in many applications regarding length-/form- and coordinate measurements, as well as photometry. SimOptDevice is regularly maintained and its functionality improved. It is currently applied to the tilted-wave interferometer, which is suitable for the optical form measurement of aspheres and freeforms. Methods of data analysis in conjunction with virtual experiments are developed and applied to solve the involved inverse problem and to calibrate the measurement process. Other research topics include the evaluation of uncertainties associated with real measurements utilizing the results of the corresponding virtual experiment, or the use of methods from deep learning in connection with virtual experiments. For example, virtual experiments can be used to create a database needed to train a neural network that is designed for analyzing experimental data.
Publications
Publication single view
Article
| Title: | Coupled distance sensor systems for high-accuracy topography measurement: Accounting for scanning stage and systematic sensor errors |
|---|---|
| Author(s): | C. Elster, I. Weingärtner;M. Schulz |
| Journal: | Precision Engineering |
| Year: | 2006 |
| Volume: | 30 |
| Issue: | 1 |
| Pages: | 32--38 |
| DOI: | 10.1016/j.precisioneng.2005.04.001 |
| ISSN: | 01416359 |
| Web URL: | http://www.sciencedirect.com/science/article/pii/S0141635905000504 |
| Keywords: | Angular measurement,Distance sensor,High accuracy,High resolution,Least-squares,Topography,Uncertainty |
| Tags: | 8.42,Form,SimOpt |
| Abstract: | Scanning topography measurements using systems of coupled distance sensors suffer from the presence of scanning stage and systematic sensor errors. While scanning stage errors can be estimated for suitably-designed sensor systems, it is usually not possible to simultaneously estimate both scanning stage and systematic sensor errors. Additional angular scanning stage measurements can solve this problem, and potentials and limitations of such a proceeding will be assessed. It is shown that perfect topography reconstruction can be achieved in the presence of systematic sensor and certain scanning stage errors provided that the measurements are noise-free and no further systematic errors emerge. In general, the topography is reconstructed by the application of least-squares, and the uncertainty associated with the reconstructed topography is derived. Resulting topography accuracies are evaluated for different noise levels of the distance sensor and angular scanning stage measurements, and practical considerations are discussed. The gain in accuracy due to accounting for scanning stage and systematic sensor errors can be large, and high accuracies can be reached. |