Refine
Year of publication
- 2017 (262) (remove)
Institute
- Fachbereich Medizintechnik und Technomathematik (67)
- Fachbereich Elektrotechnik und Informationstechnik (37)
- IfB - Institut für Bioengineering (34)
- Fachbereich Luft- und Raumfahrttechnik (33)
- Fachbereich Wirtschaftswissenschaften (32)
- Fachbereich Energietechnik (27)
- INB - Institut für Nano- und Biotechnologien (27)
- Fachbereich Maschinenbau und Mechatronik (24)
- Fachbereich Bauingenieurwesen (14)
- Fachbereich Architektur (13)
Document Type
- Article (109)
- Conference Proceeding (87)
- Part of a Book (34)
- Book (14)
- Other (11)
- Part of a Periodical (2)
- Report (2)
- Contribution to a Periodical (1)
- Doctoral Thesis (1)
- Patent (1)
Keywords
- Autonomous mobile robots (2)
- Gamification (2)
- Industry 4.0 (2)
- MASCOT (2)
- Multi-robot systems (2)
- Smart factory (2)
- 3D nonlinear finite element model (1)
- Acceptance tests (1)
- Ausfachungsmauerwerk (1)
- Automated Optimization (1)
Is part of the Bibliography
- no (262)
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.
Implikationen der Digitalisierung für den Finanzbereich der Unternehmung und das Rollenbild des CFO
(2017)
The immobilization of NAD+-dependent dehydrogenases, in combination with a diaphorase, enables the facile development of multiparametric sensing devices. In this work, an amperometric biosensor array for simultaneous determination of ethanol, formate, d- and l-lactate is presented. Enzyme immobilization on platinum thin-film electrodes was realized by chemical cross-linking with glutaraldehyde. The optimization of the sensor performance was investigated with regard to enzyme loading, glutaraldehyde concentration, pH, cofactor concentration and temperature. Under optimal working conditions (potassium phosphate buffer with pH 7.5, 2.5 mmol L-1 NAD+, 2.0 mmol L-1 ferricyanide, 25 °C and 0.4% glutaraldehyde) the linear working range and sensitivity of the four sensor elements was improved. Simultaneous and cross-talk free measurements of four different metabolic parameters were performed successfully. The reliable analytical performance of the biosensor array was demonstrated by application in a clarified sample of inoculum sludge. Thereby, a promising approach for on-site monitoring of fermentation processes is provided.
Three amperometric biosensors have been developed for the detection of L-malic acid, fumaric acid, and L -aspartic acid, all based on the combination of a malate-specific dehydrogenase (MDH, EC 1.1.1.37) and diaphorase (DIA, EC 1.8.1.4). The stepwise expansion of the malate platform with the enzymes fumarate hydratase (FH, EC 4.2.1.2) and aspartate ammonia-lyase (ASPA, EC 4.3.1.1) resulted in multi-enzyme reaction cascades and, thus, augmentation of the substrate spectrum of the sensors. Electrochemical measurements were carried out in presence of the cofactor β-nicotinamide adenine dinucleotide (NAD+) and the redox mediator hexacyanoferrate (III) (HCFIII). The amperometric detection is mediated by oxidation of hexacyanoferrate (II) (HCFII) at an applied potential of + 0.3 V vs. Ag/AgCl. For each biosensor, optimum working conditions were defined by adjustment of cofactor concentrations, buffer pH, and immobilization procedure. Under these improved conditions, amperometric responses were linear up to 3.0 mM for L-malate and fumarate, respectively, with a corresponding sensitivity of 0.7 μA mM−1 (L-malate biosensor) and 0.4 μA mM−1 (fumarate biosensor). The L-aspartate detection system displayed a linear range of 1.0–10.0 mM with a sensitivity of 0.09 μA mM−1. The sensor characteristics suggest that the developed platform provides a promising method for the detection and differentiation of the three substrates.
An enzyme-based reversible Controlled NOT (CNOT) logic gate operating on a semiconductor transducer
(2017)
An enzyme-based biocatalytic system mimicking operation of a logically reversible Controlled NOT (CNOT) gate has been interfaced with semiconductor electronic transducers. Electrolyte–insulator–semiconductor (EIS) structures have been used to transduce chemical changes produced by the enzyme system to an electronically readable capacitive output signal using field-effect features of the EIS device. Two enzymes, urease and esterase, were immobilized on the insulating interface of EIS structure producing local pH changes performing XOR logic operation controlled by various combinations of the input signals represented by urea and ethyl butyrate. Another EIS transducer was functionalized with esterase only, thus performing Identity (ID) logic operation for the ethyl butyrate input. Both semiconductor devices assembled in parallel operated as a logically reversible CNOT gate. The present system, despite its simplicity, demonstrated for the first time logically reversible function of the enzyme system transduced electronically with the semiconductor devices. The biomolecular realization of a CNOT gate interfaced with semiconductors is promising for integration into complex biomolecular networks and future biosensor/biomedical applications.
Die Steiff Spielwarenfabrik in Giengen / Brenz : Ein unbekanntes Meisterwerk der frühen Moderne
(2017)
Die Verbindung der Welten dressierter Elektronen und grenzenloser Kreativität bietet ein großes Potential; zum Beispiel bei modernen Skulpturen, deren Form sich durch Motoren verändern kann. An der FH Aachen wurde ein solches Projekt verwirklicht: Eine Matrix aus Holzkugeln kann Piktogramme anzeigen, aber auch mathematische Funktionen visualisieren. In diesem Artikel beschreiben wir die clevere Ansteuerung der Motoren.
In this paper we propose a stochastic programming method to analyse limit and shakedown of structures under uncertainty condition of strength. Based on the duality theory, the shakedown load multiplier formulated by the kinematic theorem is proved actually to be the dual form of the shakedown load multiplier formulated by static theorem. In this investigation a dual chance constrained programming algorithm is developed to calculate simultaneously both the upper and lower bounds of the plastic collapse limit and the shakedown limit. The edge-based smoothed finite element method (ES-FEM) with three-node linear triangular elements is used for structural analysis.