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Is part of the Bibliography
- no (258)
Für Auftragschweißaufgaben existiert eine Vielzahl an verfahrenstechnischen
Prozessvarianten, die je nach Charakteristik und Anwendungsfall
ausgewählt werden. Ein Nachteil der vorwiegend verwendeten Metall-
Schutzgasschweißprozesse (MSG) für das Auftragschweißen ist durch die
direkte Kopplung von Drahtvorschub zu Energieeintrag gegeben. Die vorgestellte
Zweidraht-Prozessvariante kann durch die Ausbildung eines übertragenen
und eines nicht-übertragenen Lichtbogens die elektrische Leistung
beider Lichtbögen variieren und damit einen direkten Einfluss auf
die Prozessgrößen Abschmelzleistung und Aufschmelzgrad nehmen. Im
Speziellen besteht über die Entkopplung von Drahtvorschub zu Schweißstromstärke
die Möglichkeit eines niederenergetischen Betriebs trotz hoher
Drahtvorschubgeschwindigkeit. Damit lassen sich Aufschmelzgrade
unter 2% umsetzen und Abschmelzleistungen bis zu 15 kg/h realisieren.
Analysis of Big Data Streams to obtain Braking Reliability Information for Train Protection systems
(2017)
Towards inclusion of the freight rail system in the industrial internet of things - Wagon 4.0
(2017)
Eigene positive Erfahrungen mit Onlinekursen sowie die geringen Studierendenzahlen in der Präsenzlehre gaben den Anstoß zu einem Experiment mit einem offenen Onlinekurs auf der Plattform Udemy. Die Erfahrungen sowohl bei der Erstellung und als auch im Lehrbetrieb waren positiv und führten zu einer neuen Beschäftigung mit Inhalten und Lernenden, getrieben durch die Anforderungen der Lernplattform.
In the future, we expect manufacturing companies to follow a new paradigm that mandates more automation and autonomy in production processes. Such smart factories will offer a variety of production technologies as services that can be combined ad hoc to produce a large number of different product types and variants cost-effectively even in small lot sizes. This is enabled by cyber-physical systems that feature flexible automated planning methods for production scheduling, execution control, and in-factory logistics.
During development, testbeds are required to determine the applicability of integrated systems in such scenarios. Furthermore, benchmarks are needed to quantify and compare system performance in these industry-inspired scenarios at a comprehensible and manageable size which is, at the same time, complex enough to yield meaningful results.
In this chapter, based on our experience in the RoboCup Logistics League (RCLL) as a specific example, we derive a generic blueprint for how a holistic benchmark can be developed, which combines a specific scenario with a set of key performance indicators as metrics to evaluate the overall integrated system and its components.
Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure.
Modulation of muscle-tendon interaction in the human triceps surae during an energy dissipation task
(2017)
This paper introduces a hardware setup to measure efficiency maps of low-power electric motors and their associated inverters. Here, the power of the device under test (DUT) ranges from some Watts to a few hundred Watts. The torque and speed of the DUT are measured independent of voltage and current in multiple load points. A Matlab-based software approach in combination with an open Texas-Instruments (TI) hardware setup ensures flexibility. Exemplarily, the efficiency field of a Permanent Magnet Synchronous Machine (PMSM) is measured to proof the concept. Brushless-DC (BLDC) motors can be tested as well. The nomenclature in this paper is based on the new European standard DIN EN 50598. Special attention is paid to the calculation of the measurement error.
Altered neurovascular coupling as measured by optical imaging: a biomarker for Alzheimer’s disease
(2017)
The Dry-Low-NOx (DLN) Micromix combustion technology has been developed originally as a low emission alternative for industrial gas turbine combustors fueled with hydrogen. Currently the ongoing research process targets flexible fuel operation with hydrogen and syngas fuel.
The non-premixed combustion process features jet-in-crossflow-mixing of fuel and oxidizer and combustion through multiple miniaturized flames. The miniaturization of the flames leads to a significant reduction of NOx emissions due to the very short residence time of reactants in the flame.
The paper presents the results of a numerical and experimental combustor test campaign. It is conducted as part of an integration study for a dual-fuel (H2 and H2/CO 90/10 Vol.%) Micromix combustion chamber prototype for application under full scale, pressurized gas turbine conditions in the auxiliary power unit Honeywell Garrett GTCP 36-300.
In the presented experimental studies, the integration-optimized dual-fuel Micromix combustor geometry is tested at atmospheric pressure over a range of gas turbine operating conditions with hydrogen and syngas fuel. The experimental investigations are supported by numerical combustion and flow simulations. For validation, the results of experimental exhaust gas analyses are applied.
Despite the significantly differing fuel characteristics between pure hydrogen and hydrogen-rich syngas the evaluated dual-fuel Micromix prototype shows a significant low NOx performance and high combustion efficiency. The combustor features an increased energy density that benefits manufacturing complexity and costs.