Analytische Chemie
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- 2020 (76) (entfernen)
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Eingeladener Vortrag
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Etalon features in transmittance spectra of films arise due to the coherent superposition of waves caused by reflections multiple times at the inner film boundaries. The fringe maxima occur at i𝜆 = 2nd cos 𝜑 with i - being an integer, 𝜆 - the wavelength, d - the film thickness, 𝜑 - the angle of incidence in respect to the film normal and n - the refractive index of the film. It is obvious that such features can hinder the interpretation of absorption bands when fringe amplitude and period are in the same range as the expected bands.
This poster discusses the suitability of two optical methods for the THz spectral range applied to Fourier Transform Spectroscopy.
Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging
(2020)
Block-sparse regularization is already well-known in active thermal imaging and is used for multiple measurement based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. To avoid time-consuming manually selected regularization parameters, we propose a learned block-sparse optimization approach using an iterative algorithm unfolded into a deep neural network. More precisely, we show the benefits of using a learned block iterative shrinkage thresholding algorithm that is able to learn the choice of regularization parameters. In addition, this algorithm enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present the algorithm and compare it with state of the art block iterative shrinkage thresholding using synthetically generated test data and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations than without learning. Thus, this new approach allows to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super resolution imaging.
The evaluation of measurement uncertainty is essential for testing and calibration laboratories. This paper provides a general process description for the determination of the measurement uncertainty of quantitative data and its application to the conformity assessment with examples, and how to deal with the uncertainty of qualitative (Boolean) results, e. g. when "Alarm" or "No alarm" occours in an instrument display.
Diese Richtlinie definiert Kenngrößen und Messverfahren, um Terahertzsysteme für die Zeitbereichsspektroskopie (TDS)zu spezifizieren. So können Hersteller ihre Systeme übereinstimmend beschreiben und Anwender einfach Systeme vergleichen. Systeme für die Terahertz-Zeitbereichsspektroskopie sind aktive Systeme und nutzen verschiedene Techniken sowohl zur Erzeugung als auch zur zeitaufgelösten Messung von breitbandigen Terahertzimpulsen. Die dazugehörigen Terahertzspektren und -Phasen werden nach einer zeitlichen Abtastung über eine Fourier-Transformation berechnet. In dieser Richtlinie wird ein Überblick über die Funktionsweisen von Zeitbereichsspektrometern gegeben, die eingesetzten Messverfahren näher erläutert sowie die benötigten Begriffe und Kenngrößen definiert. Die Richtlinie konzentriert sich dabei auf Systeme, die auf sogenannten Abtastmessverfahren (Sampling-Messverfahren) basieren.
The fourth industrial revolution (also known as “Industry 4.0”) promises to relieve people from manual and physical work by developing cyber-physical systems and smart automation and thereby achieving a more efficient, reliable and safe performance. This will change people’s work from being operators of the system into becoming strategical decision makers and flexible problem solvers. This shift will require a new division of work between people and technical systems, a new division of responsibilities and new ways of interacting with technology, which in turn will pose new demands on people. People will require different physical and cognitive capabilities, different competencies and new strategies to cope with the upcoming challenges. The focus of Industry 4.0 is therefore on designing systems with human in the centre: systems that will extend people’s capabilities, that will allow collaborative work and take advantage of performances in which either people or technology excel. This presentation will focus on the benefits of consideration of human-machine interaction in the context of industry 4.0.
The aim of this presentation is twofold: first, to present the field of psychology including its research methods and, second, to show on an example how psychology can be used in material research. The example is of the study of human factors in non-destructive testing (NDT), in which the author has more than 10 years of experience. The conclusion is that psychological methods can be used to identify human-related problems during different tasks and to generate mitigation strategies that can be used to decrease human error and enhance safety.
This presentation offers a holistic view on the assessment of reliability of NDT including the intrinsic reliability (typically expressed in terms of probability of detection (POD) curves), application, human and organisational factors. In addition to POD, advanced methods such as multiparameter POD, volume POD and POD for combined data are presented. Human and organisational factors in NDT require a systematic approach, i.e. it is not just the individual that determines how the inspections are carried out but also the interactions of individuals with the technology, team, organisation and the extra-organisational environment. Lessons learned from the literature as well as from own studies are presented.