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Wechselwirkungen zwischen Druckluftspeichern und Netzengpässen in zukünftigen Energiesystemen
(2013)
Herr Schwarzweiß ist seit seiner Geburt nicht in der Lage Farben zu erkennen. Seine Welt ist schwarzweiß. Doch kann er sehr gut zwischen den verschiedenen Grautönen unterscheiden. Für ihn ist Weiß nicht gleich Weiß. Es gibt ein sehr helles Weiß, ein dunkleres Weiß, ein grau unterlegtes Weiß und viele andere Arten von Weiß. ...
Innerhalb dieser Dokumentation des im Labor für Informatik an der Fachhochschule Düsseldorf durchgeführten Parxisprojekt werden zunächst Grundlagen vermittelt, die nötig sind, um den Kontext des Projekts und das Kommunikationsprotokoll 6LoWPAN zu verstehen. Da das Ziel des Praxisprojekts die Untersuchung eines Kommunikationssystems mit 6LoWPAN-Stack hinsichtlich dessen Portierungsmöglichkeiten ist, werden hierauf verschiedene, bereits auf dem Markt befindliche Lösungen analysiert und verglichen, die entweder direkt den drahtlosen Datenaustausch mit Hilfe des 6LoWPAN-Protokolls oder aber die Erweiterung zu einem eigenen Stack ermöglichen und dargestellt, warum das Mikrocontroller-Betriebssystem Contiki als geeignetster Kandidat hierfür erscheint. Als Basis für die Analyse in Hinblick auf eine mögliche Portierung dient der Mikrocontroller ATmega128RFA1 des Herstellers Atmel, der über eine integrierte Transceiver-Einheit verfügt. Nach der Vermittlung der Grundlagen des Contiki-Betriebssystems, die insbesondere den schichtenartigen Aufbau der Verzeichnisse und das komplexe, über Makefiles organisierte Build-System betreffen, folgt die Beschreibung der Vorgehensweise bei der Portierung von Contiki und den dabei aufgetretenen Problemen. Da während der Arbeit an diesem Praxisprojekt eine neue Version des Contiki-Betriebssystems veröffentlicht wurde, wird zusätzlich auf diese Version und die vorhandenen Inkompatibilitäten zwischen den verschiedenen Contiki-Versionen eingegangen und eine Beispielanwendung für die neue Version implementiert. Die Performancemessungen verschiedener Kommunikationshardware runden diese Arbeit zusammen mit dem Fazit, das nocheinmal auf das Betriebssystem Contiki, den Mikrocontroller ATmega128RFA1 und mögliche Vertiefungsund Optimierungsmöglichkeiten eingeht, ab.
We present a novel metric Spatial Recall Index to assess the performance of machine-learning (ML) algorithms for automotive applications, focusing on where in the image which performance occurs. Typical metrics like intersection-over-union (IoU), precisionrecallcurves or average precision (AP) quantify the performance over a whole database of images, neglecting spatial performance variations. But as the optics of camera systems are spatially variable over the field of view, the performance of ML-based algorithms is also a function of space, which we show in simulation: A realistic objective lens based on a Cooke-triplet that exhibits typical optical aberrations like astigmatism and chromatic aberration, all variable over field, is modeled. The model is then applied to a subset of the BDD100k dataset with spatially-varying kernels. We then quantify local changes in the performance of the pre-trained Mask R-CNN algorithm. Our examples demonstrate the spatial dependence of the performance of ML-based algorithms from the optical quality over field, highlighting the need to take the spatial dimension into account when training ML-based algorithms, especially when looking forward to autonomous driving applications.
Spatial precision and recall indices to assess the performance of instance segmentation algorithms
(2022)
We present an experimental technique that allows the simultaneous spatial imaging and spectral analysis of falling droplets that exhibit lasing. Single droplet investigations serve as, among other purposes, a preliminary study for spray and combustion researchers. The described setup provides a valuable tool for the evaluation of microdroplet investigations with laser-spectroscopic techniques that rely on laser-induced fluorescence (LIF) or similar spectroscopical phenomena. The emphasis is that both spatial and spectral information are obtained from single-shot images of a falling droplet. Furthermore, combining spatial imaging and a spatially resolving optical multichannel analyzer makes a pointwise rastering of the droplets spectrum possible. This allows for the (almost) unambiguous determination of sources of influence on the spectrum of these droplets-such as geometrical distortion and lasing, nondissolved tracer lumps, and similar phenomena. Although the focus is on the experimental technique itself, we supplement detailed studies of lasing in falling microdroplets. These results were obtained with the aim of developing a system for measuring temperature distributions in droplets and sprays. In the light of these results the practice of calibrating a droplets spectrum by use of a bulk liquid sample needs to be critically reviewed.
We had already demonstrated a numerical model for the point spread function (PSF) of an optical system that can efficiently model both the experimental measurements and the lens design simulations of the PSF. The novelty lies in the portability and the parameterization of this model, which allow for completely new ways to validate optical systems, which is especially interesting not only for mass production optics such as in the automotive industry but also for ophthalmology. The numerical basis for this model is a nonlinear regression of the PSF with an artificial neural network (ANN). After briefly describing both the principle and the applications of the model, we then discuss two optically important aspects: the spatial resolution and the accuracy of the model. Using mean squared error (MSE) as a metric, we vary the topology of the neural network, both in the number of neurons and in the number of hidden layers. Measurement and simulation of a PSF can have a much higher spatial resolution than the typical pixel size used in current camera sensors. We discuss the influence this has on the topology of the ANN. The relative accuracy of the averaged pixel MSE is below 10 − 4, thus giving confidence that the regression does indeed model the measurement data with good accuracy. This article is only the starting point, and we propose several research avenues for future work.
In a previous work we have demonstrated a novel numerical model for the point spread function (PSF) of an optical system that can efficiently model both experimental measurements and lens design simulations of the PSF. The novelty lies in the portability and the parameterization of this model, which allows for completely new ways to validate optical systems, which is especially interesting for mass production optics like in the automotive industry, but also for ophtalmology. The numerical basis for this model is a non-linear regression of the PSF with an artificial neural network (ANN). In this work we examine two important aspects of this model: the spatial resolution and the accuracy of the model. Measurement and simulation of a PSF can have a much higher resolution then the typical pixel size used in current camera sensors, especially those for the automotive industry. We discuss the influence this has on on the topology of the ANN and the final application where the modeled PSF is actually used. Another important influence on the accuracy of the trained ANN is the error metric which is used during training. The PSF is a distinctly non-linear function, which varies strongly over field and defocus, but nonetheless exhibits strong symmetries and spatial relations. Therefore we examine different distance and similarity measures and discuss its influence on the modeling performance of the ANN.
The importance of high data quality is increasing with the growing impact and distribution of ML systems and big data. Also, the planned AI Act from the European commission defines challenging legal requirements for data quality especially for the market introduction of safety relevant ML systems. In this paper, we introduce a novel approach that supports the data quality assurance process of multiple data quality aspects. This approach enables the verification of quantitative data quality requirements. The concept and benefits are introduced and explained on small example data sets. How the method is applied is demonstrated on the well-known MNIST data set based an handwritten digits.
The importance of high data quality is increasing with the growing impact and distribution of ML systems and big data. Also the planned AI Act from the European commission defines challenging legal requirements for data quality especially for the market introduction of safety relevant ML systems. In this paper we introduce a novel approach that supports the data quality assurance process of multiple data quality aspects. This approach enables the verification of quantitative data quality requirements. The concept and benefits are introduced and explained on small example data sets. How the method is applied is demonstrated on the well known MNIST data set based an handwritten digits.
Das Projekt „Programmiere Dich fit: Koslar“ geht aus der Idee von Herrn Prof. Lux, Lehrender an der Hochschule Düsseldorf, hervor. Er hat bereits in einer unterrichtsähnlichen Form mit Kindern in programmiertechnischer Richtung gearbeitet und möchte diese Arbeit gerne um eine Projektarbeit an der Hochschule Düsseldorf ergänzen.
Der Kern des Projektes zielt dabei auf die Vermittlung von Programmierkenntnissen an Kinder im Alter zwischen 6 und 10 Jahren ab. Zwar soll das Programmieren an erster Stelle stehen, aber insbesondere für eine kindergerechte Vermittlung sollen körperliche Aktivitäten und Bewegungen berücksichtigt werden. In diesem Sinne erfolgt eine Verbindung der beiden zuvor genannten Themenfelder in einer Projektarbeit, die aktiv mit Schülerinnen und Schülern einer Grundschule durchgeführt werden soll. Um den sportlichen Aspekt besser bewerten und betreuen zu können, wird die Ausführung in Zusammenarbeit mit Herr Schmitz als Geschäftsführer des Kreissportbund Düren (KSB Düren e.V.) ablaufen. Herr Schmitz wird in dieser Projektarbeit von Herrn Sebastian Lieberth, der für den Bereich des betrieblichen Gesundheitsmanagement im KSB Düren zuständig ist, unterstützt.
Herr Lux arbeitet an der Hochschule Düsseldorf mit Herrn Prof. Michels aus dem Fachbereich Sozial- und Kulturwissenschaften zusammen, um in Bezug auf die kindergerechte Vermittlung einen Vertreter zu haben. Zur Abrundung der Fachkenntnisse nehmen zusätzlich zwei Studentinnen der Hochschule Düsseldorf am Projekt teil. Unterstützung finden beide Professoren durch jeweils einen Studierenden Ihrer Themengebiete. Herr Prof. Michels wird von Frau Preissegger aus dem Fachbereich Sozial- und Kulturwissenschaften unterstützt. Frau Preissegger befindet sich im sechsten Semester und möchte auf dieses Projekt aufbauend ihre Thesis im Wintersemester schreiben. Herr Prof. Lux erhält Unterstützung durch Frau Gramsch aus dem Fachbereich Maschinenbau und Verfahrenstechnik. Sie befindet sich ebenfalls im sechsten Semester und führt dieses Projekt im Rahmen eines Wahlfaches durch.
Poincaré gauge theory of gravity: Friedman cosmology with even and odd parity modes: Analytic part
(2011)
Beschrieben wird eine optoelektronische Sensoreinrichtung für ein Kraftfahrzeug zur unterscheidenden Detektion von Feuchtigkeit und Salzlösungen auf einer Fahrzeugscheibe, mit einer Beleuchtungseinheit zur Einstrahlung von Licht in eine Fahrzeugscheibe und mit einem Lichtempfänger, welcher von der Fahrzeugscheibe reflektiertes Licht erfasst, sowie mit einem Koppelelement zur Ein- und Auskopplung von Licht in bzw. aus der Fahrzeugscheibe, wobei die Beleuchtungseinrichtung Licht über einen Einfallswinkelbereich in die Fahrzeugscheibe einstrahlt, der sich über mehrere Winkelgrade erstreckt, wobei der Lichtempfänger eine Vielzahl von Empfangselementen aufweist, wobei ein optisches System das von der Fahrzeugscheibe in einen Ausfallswinkelbereich reflektierte Licht auf Empfangselemente des Lichtempfängers abbildet und wobei der Lichtempfänger ein Signal generiert, aus dem eine Auswertevorrichtung den Grenzwinkel der Totalreflexion an der Fahrzeugscheibe ermittelt.
Dieses Bachelorprojekt wurde im Labor für Informatik an der Fachhochschule Düsseldorf durchgeführt und steht im Zusammenhang mit einem Forschungsprojekt zu dem Themengebiet Ambient Assisted Living. Hauptziele des Bachelorprojektes waren die Optimierung der Kommunikation über das 6LoWPAN-Protokoll hinsichtlich der Aspekte Datendurchsatz, Energieeffizienz und der Sicherheit der Datenübertragung. Um diese Ziele zu erreichen, wurden innerhalb des Projektes ein Kommunikationsmodul und eine entsprechenden Entwicklungsplatine realisiert. Zudem wurden softwaretechnische Funktionen entwickelt, die der Anpassung des Mikrocontroller-Betriebssystems Contiki 2.5 für die Nutzung der Stromsparfunktionen des verwendeten Mikrocontrollers ATmega128RFA1 und der Verwendung des Verschlüsselungsmoduls dienen. Durch die am Ende des Projektes durchgeführten Gerätetests konnte die Erreichung der wesentlichen Projektziele verifiziert werden. Innerhalb dieser Thesis wird dem Leser neben dem Grundlagenwissen zu dem verwendeten Mikrocontroller die Vorgehensweise bei der Erstellung der Hard- und Software näher gebracht werden.
Image restoration is a process used to remove blur (from different sources like object motion or aberrations) from images by either non-blind or blind-deconvolution. The metrics commonly used to quantify the restoration process are peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM). Often only a small sample of test images are used (like Lena or the camera guy). In optical design research PSNR and SSIM are not normally used, here image quality metrics based on linear system theory (e.g. modulation transfer function, MTF) are used to quantify optical errors like spherical or chromatic aberration. In this article we investigate how different image restoration algorithms can be quantified by applying image quality metrics. We start with synthetic image data that is used in camera test stands (e.g. Siemens star etc.), apply two different spatially variant degradation algorithms, and restore the original image by a direct method (Wiener filtering within sub-images), and by an iterative method (alternating direction method of multipliers, ADMM). Afterwards we compare the quality metrics (like MTF curves) for the original, the degraded and the restored image. As a first result we show that restoration algorithms sometimes fail in dealing with non-natural scenes, e.g. slanted-edge targets. Further, these first results indicate a correlation between degradation and restoration, i.e. the restoration algorithms are not capable of removing the optically relevant errors introduced by the degradation, a fact neither visible nor available from the PSNR values. We discuss the relevance in the context of the automotive industry, where image restoration may yield distinct advantages for camera-based applications, but testing methods rely on the used image quality metrics.
The decarbonization of for example the energy or heat sector leads to the transformation of distribution grids. The expansion of decentralized energy resources and the integration of new consumers due to sector coupling (e.g. heat pumps or electric vehicles) into low voltage grids increases the need for grid expansion and usage of flexibilities in the grid. A high observability of the current grid status is needed to perform these tasks efficiently and effectively. Therefore, there is a need to increase the observability of low voltage grids by installing measurement technologies (e.g. smart meters). Multiple different measurement technologies are available for low voltage grids which can vary in their benefit to observation quality and their installation costs. Therefore, Bayernwerk Netz GmbH and E.DIS AG in cooperation with E-Bridge Consulting GmbH and the Institute for High Voltage Equipment and Grids, Digitalization and Energy Economics (IAEW) investigated the effectiveness of different strategies for the smartification of low voltage grids. This paper presents the methodology used for the investigation and exemplary results focusing on the impact of intelligent cable distribution cabinets and smart meters on the quality of the state estimation.
Refractive power measurements serve as the primary quality standard in the automotive glazing industry. In the light of autonomous driving new optical metrics are becoming more and more popular for specifying optical quality requirements for the windshield. Nevertheless, the link between those quantities and the refractive power needs to be established in order to ensure a holistic requirement profile for the windshield. As a consequence, traceable high-resolution refractive power measurements are still required for the glass quality assessment. Standard measurement systems using Moiré patterns for refractive power monitoring in the automotive industry are highly resolution limited, wherefore they are insufficient for evaluating the camera window area. Consequently, there is a need for more sophisticated refractive power measurement systems that provide a higher spatial resolution. In addition, a calibration procedure has to be developed in order to guarantee for comparability of the measurement results. For increasing the resolution, a measurement setup based on an auto-correlation algorithm is tested in this paper. Furthermore, a calibration procedure is established by using a single reference lens with a nominal refractive power of 100 km-1. For the calibration of the entire measurement range of the system, the lens is tilted by an inclination angle orthogonal to the optical axis. The effective refractive power is then given by the Kerkhof model. By adopting the measurement and calibration procedure presented in this paper, glass suppliers in the automotive industry will be able to detect relevant manufacturing defects within the camera window area more accurately paving the way for a holistic quality assurance of the windshield for future advanced driver-assistance system (ADAS) functionalities. Concurrently, the traceability of the measurement results is ensured by establishing a calibration chain based on a single reference lens, which is traced back to international standards.
Abstract The modulation-transfer function (MTF) is a fundamental optical metric to measure the optical quality of an imaging system. In the automotive industry it is used to qualify camera systems for ADAS/AD. Each modern ADAS/AD system includes evaluation algorithms for environment perception and decision making that are based on AI/ML methods and neural networks. The performance of these AI algorithms is measured by established metrics like Average Precision (AP) or precision-recall-curves. In this article we research the robustness of the link between the optical quality metric and the AI performance metric. A series of numerical experiments were performed with object detection and instance segmentation algorithms (cars, pedestrians) evaluated on image databases with varying optical quality. We demonstrate with these that for strong optical aberrations a distinct performance loss is apparent, but that for subtle optical quality differences – as might arise during production tolerances – this link does not exhibit a satisfactory correlation. This calls into question how reliable the current industry practice is where a produced camera is tested end-of-line (EOL) with the MTF, and fixed MTF thresholds are used to qualify the performance of the camera-under-test.
Training autonomous vehicles requires lots of driving sequences in all situations. Collecting and labeling these drive scenes is a very time-consuming and expensive process. Currently, it is not possible to reuse these drive scenes with different optical properties, because there exists no numerically efficient model for the transfer function of the optical system. We present a numerical model for the point spread function (PSF) of an optical system that can efficiently model both experimental measurements and lens design simulations of the PSF. The numerical basis for this model is a nonlinear regression of the PSF with an artificial neural network. The novelty lies in the portability and the parameterization of this model. We present a lens measurement series, yielding a numerical function for the PSF that depends only on the parameters defocus, field, and azimuth. By convolving existing images and videos with this PSF, we generate images as if seen through the measured lens. The methodology applies to any optical scenario, but we focus on the context of autonomous driving, where the quality of the detection algorithms depends directly on the optical quality of the used camera system. With this model, it is possible to reuse existing recordings, with the potential to avoid millions of test drive miles. The parameterization of the optical model allows for a method to validate the functional and safety limits of camera-based advanced driver assistance systems based on the real, measured lens actually used in the product.
Im Rahmen dieser Bachelorthesis sollen die Möglichkeiten für eine Migration des Nutzerwelten Programmcodes in die neuen Eclipse 4 Versionen ermittelt und anhand von Beispielen schrittweise erklärt werden. Hierbei werden zunächst die neuen Möglichkeiten erläutert die eine Eclipse 4 Entwicklung bietet und welche Vorteile durch die Einführung von Dependency Injections und dem Application Model entstanden sind. Anschließend werden die möglichen Wege zur Durchführung einer Migration aufgezeigt und auf ihre Vorteile und Nachteile überprüft. Im letzten Abschnitt werden schließlich die Migrationswege anhand von Beispielen schrittweise an einem Bundle der Nutzerwelten RCP durchgeführt und auf ihren Nutzen für eine Migration des gesamten Programms bewertet.