600 Technik, Medizin, angewandte Wissenschaften
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In this paper, low-loss Y-branch splitters up to 128 splitting ratio are designed, simulated, and optimized by using 2D beam propagation method in OptiBPM tool by Optiwave. For an optical waveguide, a silica-on-silicon material platform is used. The splitters were designed as a planar structure for a telecommunication operating wavelength of 1.55 m. According to the minimum insertion loss and minimum non-uniformity, the optimum length for each Y-branch is determined. The influence of the pre-defined S-Bend waveguide shapes (Arc, Cosine, Sine) and of the waveguide core size reduction on the splitter performance has been also studied. The obtained simulation results of all designed splitters with different S-Bend shape waveguides together with the different waveguide core sizes are discussed and compared with each other.
Eingebettete Systeme – wie zum Beispiel eine Multifunktions-Küchenmaschine, ein intelligenter Saugroboter oder Lautsprecher mit sprachgesteuerten Assistenten – sind für einige Menschen in der heutigen Zeit nicht mehr wegzudenken. Sie sind mittlerweile Bestandteil unseres täglichen Lebens. Doch hinter jedem System stehen auch eine Vielzahl von Anforderungen, die für die Kundinnen und Kunden, sowie Nutzerinnen und Nutzer relevant sind. Ob diese Anforderungen immer einen Mehrwert für die Kundinnen und Kunden bringen, ist dabei irrelevant. Doch wie kann gewährleistet werden, dass die zu Beginn definierten Anforderungen schlussendlich das gewünschte Ergebnis für die Kundinnen und Kunden oder Nutzerinnen und Nutzer bringt? Durch die Durchführung einer Validierung in verschiedenen Phasen der Systementwicklung können wichtige Erkenntnisse über das Produkt und dessen Funktionen vor der eigentlichen Marktfreigabe gewonnen und noch in den verschiedenen Entwicklungsphasen für Änderungen oder Verbesserungen eingeplant werden. Oft werden diese essentiellen Validierungsprozesse zu spät oder gar nicht durchgeführt, was zu unausgereiften Produktfreigaben führt, was wiederum unzufriedene Kundinnen und Kunden zur Folge haben kann.
Diese Masterarbeit bietet einen Einblick, wie eine solche Validierung in Systementwicklungen integriert werden kann. Unter anderem wird eine klassische Vorgehensweise, das V-Modell, und die agile Methode Scrum betrachtet und auf mögliche Validierungskonzepte hin untersucht. Anhand eines Praxisbeispiels einer bereits durchgeführten Systementwicklung im Elektronikbereich wird gezeigt, wie die Methoden des V-Modells und Scrum in Verbindung mit der Validierung umgesetzt wurden. Die Erkenntnisse aus diesen beiden Teilen, Theorie und Praxis, werden durch Handlungsempfehlungen für Entwicklungsprojekte abgerundet.
The purpose of an energy model is to predict the energy consumption of a real system and to use this information to address challenges such as rising energy costs, emission reduction or variable energy availability. Industrial robots account for an important share of electrical energy consumption in production, which makes the creating of energy models for industrial robots desirable. Currently, energy modeling methods for industrial robots are often based on physical modeling methods. However, due to the increased availability of data and improved computing capabilities, data-driven modeling methods are also increasingly used in areas such as modeling and system identification of dynamic systems. This work investigates the use of current data-driven modeling methods for the creation of energy models focusing on the energy consumption of industrial robots.
For this purpose, a robotic system is excited with various trajectories to obtain meaningful data about the system behavior. This data is used to train different artificial neural network (ANN) structures, where the structures used can be categorized into (i) Long Short Term Memory Neural Network (LSTM) with manual feature engineering, where meaningful features are extracted using deeper insights into the system under consideration, and (ii) LSTM with Convolutional layers for automatic feature extraction. The results show that models with automatic feature extraction are competitive with those using manually extracted features. In addition to the performance comparison, the learned filter kernels were further investigated, whereby similarities between the manually and automatically extracted features could be observed. Finally, to determine the usefulness of the derived models, the best-performing model was selected for demonstrating its performance on a real use case.
SysML Modellierung komplexer Systeme und automatische Erzeugung domänenspezifischer Ressourcen
(2021)
Moderne Technische Systeme und ihre Entwicklung werden zunehmend komplexer. Durch eine Vielzahl bei der Entwicklung beteiligter Modelle/Dokumente wird eine konsistente und rückverfolgbare Modellierung erschwert. Model-Based Systems Engineering (MBSE) ist ein Ansatz, welcher diese Problemstellung adressiert und bei der Systementwicklung formale Modelle anstelle von Dokumenten einsetzt/verwendet. Im Gegensatz zu Dokumenten sind Modelle formal definiert, können automatisiert überprüft werden und ermöglichen eine leichte maschinelle Verarbeitung der Informationen. Im Zentrum der Entwicklung steht ein Systemmodell, welches mit einer formalen Modellierungssprache erstellt wurde. Während der Entwicklung entstehende Informationen werden in das Systemmodell integriert, sodass eine konsistente Single Source of Truth entsteht. Aus dem Systemmodell können über automatisierte Modelltransformationen domänenspezifische Ressourcen, wie beispielsweise Digital Twins, generiert werden. Digital Twins und die damit verbundenen Simulationen können einen deutlichen Mehrwert in Bereichen, wie Optimierung, Wartung und Anomalieerkennung liefern. Allerdings ist die manuelle Erzeugung Aufwändig und Fehleranfällig sein, weshalb eine automatische Erzeugung aus den Informationen des Systemmodells eine Erleichterung darstellt.
Diese Arbeit beschäftigt sich mit dieser Problemstellung und der Modellierung komplexer Systeme. Es wird ein Systemmodell mit der Modellierungssprache Systems Modeling Language (SysML) erstellt, welches durch domänenspezifische Profile erweitert wird um Modellierung/Integration der Domänen zu ermöglichen. Mittels einer Modelltransformation in Acceleo werden Informationen aus dem Systemmodell in ein Simulationsmodell der Simulationssoftware twin, welche zur Simulation von Digital Twins geeignet ist, transformiert. Der in der Arbeit präsentierte Ansatz wird anhand er Modellfabrik des Forschungszentrums Digital Factory Vorarlberg veranschaulicht.
In this work, the simulation possibilities of transient magnetic fields are investigated. For this purpose, an experimental setup is established to compare the simulation results with actual measurement data.
The experimental set-up consists of two coils, which are placed on two U-shaped iron cores. These cores are then brought together to form two air-gaps. These two gaps are used for measurement and the optional insertion of samples. The simulations are carried out with the finite element method (FEM) program ANSYS Maxwell 19R3.
In the first experiments, static simulations and measurements are compared to verify the validity of the available material data and the simulation techniques, especially the symmetry considerations, excitations of the coils, and boundary conditions. The static simulations show two main sources of uncertainty. The B-H curve of the core material used in the simulations and the air-gap distance uncertainty.
After validating the simulations with the static measurements, transient experiments are performed. In these experiments, the qualitative agreement of the simulation and measurement, as well as the characteristic rise times are compared. The experiments show a decisive influence of the considered loss mechanisms on the agreement of the simulation results with the measurements. Therefore, several simulations with different loss mechanisms are performed.
Finally, also the simulation capability including a material sample in the upper gap is investigated. Therefore, the conformity of the relative change of the measurement and the simulation is compared.
In the experiments a good simulation capability within a 5% error bar is seen. The main difficulty of this work represents the uncertainty due to the available material data. It is assumed, that with more accurate material data the error can be reduced significantly.
This paper analyses an electrical test tower of the OMCIRON electronics GmbH and evaluates whether a Predictive Maintenance (PdM) strategy can be implemented for the test towers. The company OMICRON electronics GmbH performs unit tests for its devices on test towers. Those tests consist of a multitude of subtests which all return a measurement value. Those results are tracked and stored in a database. The goal is to analyze the data of the test towers subtests and evaluate the possibility of implementing a predictive maintenance system in order to be able to predict the RUL and quantify the degradation of the test tower.
By assuming that the main degradation source are the relays of the test tower, a reliability modelling is performed which is the model-driven approach. The data-driven modelling process of the test tower consists of multiple steps. Firstly, the data is cleaned and compromised by removing redundances and optimizing for the best subtests where a subtest is rated as good if the trendability and monotonicity metric values are above a specific threshold. In a second step, the trend behaviours of the subtests are analyzed and ranked which illustrates that none of the subtests contained usable trend behaviour thus making an implementation of a PdM system impossible.
By using the ranking, the data-driven model is compared with the reliability model which shows that the assumption of the relays being the main error source is inaccurate.
An analysis of a possible anomaly detection model for a PdM is evaluated which shows that an anomaly detection is not possible for the test towers as well. The implementability of PdM for test towers and other OMICRON devices is discussed and followed up with proposals for future PdM implementations as well as additional analytical analyses that can be performed for the test towers.
To create a map of an unknown area, autonomous robots must follow a strategy to explore the area without knowing the optimal paths to reduce the time needed to map the whole area. To reduce the time to accomplish this task, multiple robots can work together to create a map in a more efficient way. However, without proper coordination, the time a team of autonomous robots needs to explore the unknown area can exceed the time needed by a single robot. To counteract the challenges, a shared infrastructure is needed which extracts useful information for the individual robots out of the shared information of all robots so the exploration can be coordinated. These measures introduce new challenges to the system, concerning the load of the communication infrastructure as well as the overall task of exploring and mapping becoming dependent on the correct communication and robustness of the shared team infrastructure. Therefore, the amount of communication and dependency of each individual robot of the rest of the other robots of the team must be reduced to ensure that the robots can continue working even if the communication with the shared infrastructure fails.