MASS MATRIX ESTIMATION FOR THE DISCRETIZED DYNAMIC MODEL OF RAILWAY CAR BODIES

A method has been developed for estimating the mass matrix for the dynamical model with discretized masses of railway car bodies. This method relies on the comparison between vibrations of real beams and of those with discretized, section-wise uniform mass distribution. The objective function relying on the least squares method has been minimized by the SUMT method. Implementation of the computation method is illustrated on hand of analyzing a railway luggage truck body

Detection of stroboscopic effects in dependence of duty cycle, speed and illuminance level

Light-emitting diodes (LEDs) that are dimmed by pulse width modulation (PWM) may cause visually uncomfortable stroboscopic effects due to improper selection of operating parameters. Therefore, it is important to understand that the visibility of the stroboscopic effect depends on parameters such as duty cycle, speed, and illuminance level. These dependencies were analysed by using a LED light source illuminating a black-coated rotating disk with a white dot mounted on top of it. Modulating the light source with a square wave signal between 100 Hz and 4200 Hz and different duty cycles (10%, 30%, 50%, 70%, 80%), allowed us to determine the subject’s visibility of the stroboscopic effect for different rotation speeds (2m/s, 4m/s, 6m/s) and illuminance levels (100lx, 500lx, 1000lx). Based on the results of these experiments, objective models were developed, which can be used to increase the accuracy and validity of the stroboscopic visibility measure, and effectively reduce the stroboscopic effects

Sensor array for the analysis of the lighting situation in an intelligent industrial hall

In this paper, the possibility of using a multi-channel color sensor to identify artificial light and daylight for use in an intelligently illuminated industrial hall is investigated. First, an overview of intelligent lighting systems is given and the experimental setup is explained. Due to the large amount of data, the processing of large data sets is then highlighted. On the basis of the data collected, it will then be shown that it is possible to distinguish between daylight and artificial light using multi-channel colour sensors

Resolution Aspects for Near-Field Projections

This work intends to define the resolution requirements for near-field projections in a psycho-physical study design to evaluate the participants’ perception under the influence of different ambient lighting levels and various viewing distances. The variation in ambient lighting and viewing distances relates to various daytime and critical distances in urban environments. The application of near-field projections increases the popularity of communication- or safety-relevant projections, such as for automated vehicles. However, previous studies in the filming industry have shown that the resolution requirements differ depending on the application. In this work, a field study design presents an experimental approach to define a perceived resolution on the street surface in the near field around the vehicle. Furthermore, the study evaluates the influence of viewing distance, ambient lighting and projection content on the perceived resolution in detail. The results reveal a significant dependency on ambient lighting (p < 0.05). Furthermore, this work states that the symbol-based projection has lower resolution requirements, e.g., a viewing distance of 1 m and 3 m results in a 2 pixels per degree resolution compared to the text-based projection in the parking garage scenario. Nevertheless, in the dusk/dawn scenario, the perceived resolution can be grouped for viewing distances above 1 m for content-independent projections

Sensor array for the analysis of the lighting situation in an intelligent industrial hall

In this paper, the possibility of using a multi-channel color sensor to identify artificial light and daylight for use in an intelligently illuminated industrial hall is investigated. First, an overview of intelligent lighting systems is given and the experimental setup is explained. Due to the large amount of data, the processing of large data sets is then highlighted. On the basis of the data collected, it will then be shown that it is possible to distinguish between daylight and artificial light using multi-channel colour sensors

Impact of the adapted white point and the cultural background on memory color assessments

With their inherent ability of serving as an internal reference, memory colors provide a very powerful concept in the evaluation of color rendering properties of white light sources with respect to visual appreciation. Recent results for example suggest fairly good correlations between memory‐based color quality metrics and the observers' general color preferences. However, due to technical limitations in the design of the underlying psychophysical experiments, they generally lack the explicit inclusion of realistic viewing and adaptation conditions, which is supposed to have a nonnegligible impact on the model prediction performance. In addition, intercultural effects might play a crucial role in the context of memory colors. For these reasons, the current article investigates the impact of both the adapted white point and the observers' cultural background on memory color assessments in order to contribute to a better understanding of these dependencies and their interactions. For this purpose, the color appearance rating results of Chinese and German observers were collected for a selection of 12 different familiar test objects assessed under two different adaptation conditions at 3200 K and 5600 K, respectively. From the statistical analysis of the experimental data, it is shown, in accordance to previous studies, that the impact of the observed intercultural deviations is likely to be of no practical importance even though significance is found. Despite considerably larger effect sizes, the same must be concluded for the two tested adaptation conditions

Der Weg zur effizienten Belichtungsregelung in Algen-Photobioreaktoren

Zur effizienten Belichtungsregelung in Algen-Photobioreaktoren müssen viele Regelparameter aufeinander abgestimmt werden. Neben den aktuellen Lichtbedingungen sorgen Vorhersagen der zu erwartenden Tageslichtmenge sowie der Energiepreise für langfristig energieeffiziente Regelstrategien im Algenanbau. Maßgebende Messgröße für das Tageslicht ist hierbei die photosynthetische Photonenflussdichte (PPFD). In diesem Paper werden drei Methoden zur Bestimmung der PPFD von Tageslichtspektren mit kostengünstigen Spektralsensoren vorgestellt. Die erste Methode schätzt die PPFD anhand der Kanalempfindlichkeitskurven. Bei der zweiten Methode wird die PPFD auf der Grundlage der berechneten ähnlichsten Farbtemperatur (CCT) und einer spektralen Rekonstruktion unter Verwendung des CIE-Tageslichtmodells berechnet. Und die dritte Methode basiert auf einem Regressionsmodell zur Berechnung der PPFD. Es wird gezeigt, dass die tatsächlichen Tageslichtspektren zu stark vom CIE-Tageslichtmodell abweichen, um eine hinreichende Aussage zur PPFD zu treffen. Abschließend erfolgt ein Test der Robustheit dieser Methoden anhand von realen Messdaten, die mit den Sensoren im Freien bei verschiedenen Tageslichtverhältnissen erzeugt wurden

Deep learning-based pupil model predicts time and spectral dependent light responses

Although research has made significant findings in the neurophysiological process behind the pupillary light reflex, the temporal prediction of the pupil diameter triggered by polychromatic or chromatic stimulus spectra is still not possible. State of the art pupil models rested in estimating a static diameter at the equilibrium-state for spectra along the Planckian locus. Neither the temporal receptor-weighting nor the spectral-dependent adaptation behaviour of the afferent pupil control path is mapped in such functions. Here we propose a deep learning-driven concept of a pupil model, which reconstructs the pupil’s time course either from photometric and colourimetric or receptor-based stimulus quantities. By merging feed-forward neural networks with a biomechanical differential equation, we predict the temporal pupil light response with a mean absolute error below 0.1 mm from polychromatic (2007 ± 1 K, 4983 ± 3 K, 10,138 ± 22 K) and chromatic spectra (450 nm, 530 nm, 610 nm, 660 nm) at 100.01 ± 0.25 cd/m². This non-parametric and self-learning concept could open the door to a generalized description of the pupil behaviour

Evaluating colour preference by using multidimensional approaches

Colour preference is a key factor in the design and evaluation of lighting systems, particularly with the emergence of multichannel LED systems which allow for greater control over the spectrum of light emitted and therefore the colour appearance of the illuminated objects. To more accurately and objectively measure colour preference, there has been a growing interest in the development of multidimensional evaluation algorithms that consider multiple dimensions of colour rendering, such as chroma and hue shift. The purpose of this study was to compare and evaluate the performance of different multidimensional evaluation algorithms for colour preference in lighting applications. Using computer-generated images of a coloured object displayed on a computer monitor under a fixed white point, we simulated the colour shifts of the object under different light sources and test subjects evaluated the results using a range of multidimensional methods. Our analysis revealed that there are significant differences in the performance of these algorithms, with some providing more accurate and reliable measures of colour preference than others. Considering all relevant criteria, genetic algorithms seem to provide the most promising approach, as they lead to a result quickly and reliably. These findings have important implications for the selection and use of multidimensional algorithms for evaluating colour preference in lighting, particularly in the context of multichannel LED systems, and can inform future research in this area