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After a brief introduction of conventional laboratory structures, this work focuses on an innovative and universal approach for a setup of a training laboratory for electric machines and drive systems. The novel approach employs a central 48 V DC bus, which forms the backbone of the structure. Several sets of DC machine, asynchronous machine and synchronous machine are connected to this bus. The advantages of the novel system structure are manifold, both from a didactic and a technical point of view: Student groups can work on their own performance level in a highly parallelized and at the same time individualized way. Additional training setups (similar or different) can easily be added. Only the total power dissipation has to be provided, i.e. the DC bus balances the power flow between the student groups. Comparative results of course evaluations of several cohorts of students are shown.
Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations.
Digital twins are seen as one of the key technologies of Industry 4.0. Although many research groups focus on digital twins and create meaningful outputs, the technology has not yet reached a broad application in the industry. The main reasons for this imbalance are the complexity of the topic, the lack of specialists, and the unawareness of the twin opportunities. The project "Digital Twin Academy" aims to overcome these barriers by focusing on three actions: Building a digital twin community for discussion and exchange, offering multi-stage training for various knowledge levels, and implementing realworld use cases for deeper insights and guidance. In this work, we focus on creating a flexible learning platform that allows the user to select a training path adjusted to personal knowledge and needs. Therefore, a mix of basic and advanced modules is created and expanded by individual feedback options. The usage of personas supports the selection of the appropriate modules.
Der Wunsch nach Gesundheit und Individualisierung der eigenen Freizeit als Ausgleich zum Alltag ist heute in der Gesellschaft so ausgeprägt wie noch nie. Dabei sind die positiven Auswirkungen körperlicher Aktivität auf das Immunsystem, die Lebenserwartung und die Leistungsfähigkeit immer bekannter. Diese Abschlussarbeit greift die erkannte Entwicklung und den wachsenden Wunsch der Nutzenden nach individuellem Fitnesstraining im Freien auf. Das entstandene Outdoor-Trainingssystem „TREICK“ ermöglicht ein mobiles, orts- und zeitunabhängiges Training der eigenen Fitness. Durch „TREICK“ kann der Sportler physiologisch sinnvolle Eigengewichtsübungen in einer selbst gewählten Umgebung ausführen, wodurch das Wohlbefinden und damit die Gesundheit gefördert werden kann. Das System kann als Rucksack oder Fahrradtasche transportiert werden, wobei die Trainingsmatte als Verpackung dient.