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Die vorliegende Masterarbeit befasst sich mit der Analyse von Unterstützungsverfahren, um mithilfe eines Roboters einen Fügeprozess kombiniert mit einer Fügeachse durchführen zu können. Durch das Führen der Bauteile durch den Roboter während des Fügevorgangs entsteht eine Überbestimmung zwischen Fügeachse und Roboter. Die auftretenden Kräfte und Momente, die dadurch auf den Roboter wirken, sind zu untersuchen. Mithilfe der Analysen soll ermittelt werden, ob der Roboter während der Fügeprozesse innerhalb seiner Leistungsgrenzen betrieben wird und ob eine ausreichend genaue Kompensation der Kräfte möglich ist. Ein dazu erstellter Versuchsaufbau soll diese Analysen ermöglichen. Nach dem Erarbeiten von Grundlagen der Roboterregelung wird speziell auf die, bei diesem Versuchsaufbau zu Verfügung stehenden, Unterstützungsverfahren des Roboters eingegangen. Die Eigenschaften und Anwendung des jeweiligen Verfahrens werden beleuchtet und dargestellt. Dem folgt eine Übersicht der geplanten Fügeversuche, um das Verhalten des Roboters während der Fügeprozesse zu analysieren. Die Auswertung einer durchgeführten Messsystemanalyse und der Fügeversuche stellt die Verwendbarkeit und die erreichbaren Toleranzen sowie die Stärken und Schwächen der Unterstützungsverfahren dar.
This master’s thesis provides an overview of a more efficient, future-oriented living concept in Dornbirn, Austria. The use of a combined heat and power unit (CHP), in combination with a thermal storage, as a heating system is specifically investigated. In order to make this heating system more attractive for the consumer, the sale of the generated electricity from the CHP is considered. The more efficient use of energy for heating increases the attractiveness by a minimisation of the living space. This master’s thesis aims to draw attention to the issue and to achieve a rethinking in the planning of future living space. For the research and elaboration of this thesis, statistics and trustworthy literature were used, and physical modelling was applied. This Master’s thesis can be assigned to the fields of energy technology, mechatronics, architecture and civil engineering. It contributes for students, researchers, and other interested person in these sectors.
In recent years, much research has been done on medical laser applications inside the human body, as they are minimally invasive and therefore have fewer side effects and are less expensive than conventional therapies. In order to bring the laser light into the human body, a glass fibre with a diffuser is needed. The goal of this master thesis is the characterization and production of fibre optic diffusers that can be used for the three therapeutic applications: photodynamic therapy, laser-induced thermotherapy and endovenous laser therapy. For this purpose the following goals have to be achieved:
- Optimization of the efficiency and homogeneity of internally structured diffusers
- Examine damage thresholds of the diffusers in the tissue using a crash test
- Achieving a better understanding of the decouple mechanism with a simulation
Using an ultra-short pulse laser, modifications could be introduced into the fibre in this way that the radiation profile is homogeneous and the decoupling efficiency is 68.3 %. It was discovered that the radiation profile depends on the wavelength. Attempts have been made to improve the decoupling efficiency by mirroring the distal end of the fibre. The mirror reflects the remaining light back into the fibre, so that it is also decoupled lateral on the modifications. Vapor-deposited aluminum with physical vapor deposition is a promising approach. However, the adhesion of the coating must be improved or the coating must be protected by a mechanical cover, otherwise it will flake off too quickly.
In a crash test, it was shown that the glass fibre diffusers can withstand 20 W laser power for 300 s without visible change. In an ex vivo test, the coagulation zone in the tissue was examined and it was showed that the diffusers radiate radially homogeneously. Using a ray trace simulation, the course of the light rays in the fibre was examined and the correlation of modification width and length with the decoupling efficiency was investigated. It was discovered that there are helical light rays in the fibre, which cannot be decoupled by modifications in the fibre centre.
This master thesis investigates a Computational Intelligence-based method for solving PDEs. The proposed strategy formulates the residual of a PDE as a fitness function. The solution is approximated by a finite sum of Gauss kernels. An appropriate optimisation technique, in this case JADE, is deployed that searches for the best fitting parameters for these kernels. This field is fairly young, a comprehensive literature research reveals several past papers that investigate similar techniques.
To evaluate the performance of the solver, a comprehensive testbed is defined. It consists of 11 different Poisson equations. The solving time, the memory consumption and the approximation quality are compared to the state of the art open-source Finite Element solver NGSolve. The first experiment tests a serial JADE. The results are not as good as comparable work in the literature. Further, a strange behaviour is observed, where the fitness and the quality do not match. The second experiment implements a parallel JADE, which allows to make use of parallel hardware. This significantly speeds up the solving time. The third experiment implements a parallel JADE with adaptive kernels. It starts with one kernel and introduce more kernels along the solving process. A significant improvement is observed on one PDE, that is purposely built to be solvable. On all other testbed PDEs the quality-difference is not conclusive. The last experiment investigates the discrepancy between the fitness and the quality. Therefore, a new kernel is defined. This kernel inherits all features of the Gauss kernel and extends it with a sine function. As a result, the observed inconsistency between fitness and quality is mitigated.
The thesis closes with a proposal for further investigations. The concepts here should be reconsidered by using better performing optimisation algorithms from the literature, like CMA-ES. Beyond that, an adaptive scheme for the collocation points could be tested. Finally, the fitness function should be further examined.
Many test drives are carried out in the automotive environment. During these test drives many signals are recorded. The task of the test engineers is to find certain patterns (e.g. an emergency stop) in these long time series. Finding these interesting patterns is currently done with rule based processing. This procedure is very time consuming and requires a test engineer with expertise. In this thesis it is examined if the emerging field of machine learning can be used to support the engineers in this task. Active Learning, a subarea of machine learning, is used to train a classifier during the labeling process. Thereby it proposes similar windows to the already labeled ones. This saves the annotator time for searching or formulating rules for the problem. A data generator is worked out to replace the missing labeled data for tests. The custom performance measure “proportion of seen samples” is developed to make the success measurable. A modular software architecture is designed. With that, several combinations of Time Series Classification algorithms and query strategies are compared on artificial data. The results are verified on real datasets, which are open source available. The best performing, but computational intensive solution is an adapted RandOm Convolutional KErnel Transform (ROCKET). The custom query strategy “certainty sampling” shows the best results for highly imbalanced datasets.
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.
Development of a low pressure syringe pump for detecting cannabinoids through liquid chromatography
(2022)
The following thesis covers the miniaturization and characterization of a pneumatic syringe pump, which is used for applications in low-pressure liquid chromatography. For this purpose, the components of the prototype are dealt with in the first section. These include the membrane pump and the cylinder for pressure and force generation, the syringe used for sample preparation and the construction of the test column. Furthermore, the pressure preparation on the cylinder, the friction losses of the syringe and then the behavior of the syringe in various application scenarios are considered. In the second section, the focus is on the different behaviors when using water and ethanol as a solvent. Tests in normal applications, as well as with air pockets or leaking seals, show the different behavior and the resulting deviations in the test pressure of the column. In addition, the maximum forces that can be applied to the syringe are worked out in several tests and the different maximum pressures, which depend on the solvent contained, are evaluated. These different maximum pressures, which are due to the different sealing behavior in connection with the surface tension of the liquid, will be discussed in conclusion. An outlook follows, up to which test pressures the system can be used and how these can be achieved.
The detection of glucose is an essential part of diabetes management and can help to prevent secondary diseases, that can occur as a result of diabetes. For this reason, it is important to improve the current glucose monitoring by developing novel sensors with high efficiency, low cost and compact design. The use of microelectrodes with interdigitated array (IDA) structures reduces the total detector size while providing benefits such as large currents, high sensitivity, and fast response. The aim of this thesis is to develop a novel sensor based on platinum interdigitated array (IDA) electrodes and to investigate which method is most effective for the detection of glucose. This work is divided into two parts. The first part is focused on the design and the fabrication of the sensor chips. The second part is concerned with the electrochemical characterisation of the sensors. Two distinct sensor designs are created, each consisting of a four-electrode system arranged as an interdigitated array. For the fabrication of the sensors, two different manufacturing processes are used. A lift-off process is used to fabricate the 2 μm-Gap sensor chips, whereas a lift-off free process is applied to produce the nanogap sensor chips. The electrochemical characterisation of both sensor chips is achieved by the immobilisation of the enzyme glucose oxidase (GOx) on the electrode surface. This thesis investigates the immobilisation of GOx by reduction of diazonium salts and the direct immobilisation of GOx by cyclic voltammetry. As a result of this work, it has been demonstrated that glucose detection by reduction of diazonium salts is error-prone due to modification with a multi-step procedure and is not suitable for our sensors based on platinum IDA electrodes. The direct immobilisation of GOx by cyclic voltammetry, by contrast, demonstrates the successful detection of glucose. In glucose solutions ranging from 5 mM to 20 mM, a direct correlation between the glucose concentration and the measured current is obtained. The reproducibility of direct immobilization is demonstrated by repeated performance with various sensors.
In today’s world, fiber optic networks for data transmission are an essential technology. This technology provides multiple advantages compared to conventional electrical data transmission. The simultaneous transmission of multiple optical signals in a single fiber is one of the main benefits of fiber optic cable. This is accomplished by directing the different optical signals into a single fibre and splitting them up after the transmission in order to obtain the individual signals. Arrayed Waveguide Gratings (AWGs) are used for this purpose in modern optical networks. Design and evaluation process are two components of AWG development. During the evaluation of several simulated and already manufactured AWGs for telecommunication applications, it was discovered that the channel spacing parameter does not conform telecommunication standards. The correct shift of the geometric parameter ”separation of the output waveguides” leads to the standard-conform channel spacing.
According to the current state of the art, no commercial tool is available which calculates the shift of this parameter correctly. The aim of this thesis is the development of a software tool to calculate the accurate shifting of the geometric parameter ”separation of the output waveguides” of an AWG. This tool operates as an interface between the design and evaluation processes and must be able to import the data format of the evaluation process and returns the data in a suitable data format for the design process. The Vorarlberg University of Applied Sciences uses three different methods for the shifting of the geometric parameter ”separation of the output waveguides”. These methods are evaluated and optimised as part of this thesis. Additionally, it has been determined that the shift of the geometric parameter ”separation of the output waveguides” has no significant impact on the performance of the AWG.
Power cables play an important role in power grids. Insulation faults in cables can have adverse effects on the operating behaviour. These effects can be assessed through an AC withstand test by using a very-low frequency high voltage generator. This generator produces a sinusoidal voltage waveform at 0.1Hz with high voltage levels up to 65kV peak. During the quality assessment, the power cable is repeatedly charged and discharged. The discharging process is done by a discharging circuit where the energy is dissipated thermally. But to reuse the dissipated energy a novel extension in form of an energy storage system is presented. This thesis, therefore, describes the design process of an energy storage system that allows the temporary storage of the discharge energy. The developed system is composed of a bidirectional DC/DC converter and an aluminium electrolytic capacitor as storage type. Based on the maximum VLF system ratings the energy storage unit is dimensioned and sized. The effective power flow control between the storage system and the available discharge energy is done by a synchronous buck-boost converter. This bidirectional converter works in continuous conduction mode over the complete charging phase. Together with a theoretical analysis of the underlying problem and the use of converter analysis methods the selected synchronous buck-boost converter is dimensioned and sized. In addition, a state space AC modeling of the converter with its electrical uncertainties is conducted. With the converters AC model, the controller is designed. A closed-loop input converter current control scheme based on a proportional-integral controller is implemented. The system assessment is done by a model-based hardware implementation in Matlab Simulink and Plecs Blockset. The system is rated to store discharge energies up to 4.3kJ in a short charging period of 2.5s. The maximum peak power during the charging phase is 2.7kW. The digital proportional-integral controller is implemented through an emulation process of the designed analog controller. Based on a C-code implementation of the digital controller the gap between the real hardware is reduced. During the design process theoretical calculations are made and reveal that designing a capacitor storage unit has a direct impact on the peak system currents and also impose also limitations on permissible DC voltage ranges on electrical components. The developed energy storage system and its power flow control strategy were investigated through simulation studies. The results show proper charging of the energy storage medium. In addition, also a statement of the final technical feasibility is made. In total, this work summarizes a detailed design process of the energy storage system. This proof of concept is intended to further advance the system integration.