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In this paper research activities developed within the FutureCom project are presented. The project, funded by the European Metrology Programme for Innovation and Research (EMPIR), aims at evaluating and characterizing: (i) active devices, (ii) signal- and power integrity of field programmable gate array (FPGA) circuits, (iii) operational performance of electronic circuits in real-world and harsh environments (e.g. below and above ambient temperatures and at different levels of humidity), (iv) passive inter-modulation (PIM) in communication systems considering different values of temperature and humidity corresponding to the typical operating conditions that we can experience in real-world scenarios. An overview of the FutureCom project is provided here, then the research activities are described.
Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of water distribution systems (WDS), i.e. the enhancement of their capability to withstand and recover from disturbances, has been in particular focus recently. To assess the resilience of WDS, graph-theoretical metrics have been proposed. In this study, a promising approach is first physically derived analytically and then applied to assess the resilience of the WDS for a district in a major German City. The topology based resilience index computed for every consumer node takes into consideration the resistance of the best supply path as well as alternative supply paths. This resistance of a supply path is derived to be the dimensionless pressure loss in the pipes making up the path. The conducted analysis of a present WDS provides insight into the process of actively influencing the resilience of WDS locally and globally by adding pipes. The study shows that especially pipes added close to the reservoirs and main branching points in the WDS result in a high resilience enhancement of the overall WDS.
Many of today’s factors make software development more and more complex, such as time pressure, new technologies, IT security risks, et cetera. Thus, a good preparation of current as well as future software developers in terms of a good software engineering education becomes progressively important. As current research shows, Competence Developing Games (CDGs) and Serious Games can offer a potential solution.
This paper identifies the necessary requirements for CDGs to be conducive in principle, but especially in software engineering (SE) education. For this purpose, the current state of research was summarized in the context of a literature review. Afterwards, some of the identified requirements as well as some additional requirements were evaluated by a survey in terms of subjective relevance.
Communication via serial bus systems, like CAN, plays an important role for all kinds of embedded electronic and mechatronic systems. To cope up with the requirements for functional safety of safety-critical applications, there is a need to enhance the safety features of the communication systems. One measure to achieve a more robust communication is to add redundant data transmission path to the applications. In general, the communication of real-time embedded systems like automotive applications is tethered, and the redundant data transmission lines are also tethered, increasing the size of the wiring harness and the weight of the system. A radio link is preferred as a redundant transmission line as it uses a complementary transmission medium compared to the wired solution and in addition reduces wiring harness size and weight. Standard wireless links like Wi-Fi or Bluetooth cannot meet the requirements for real-time capability with regard to bus communication. Using the new dual-mode radio enables a redundant transmission line meeting all requirements with regard to real-time capability, robustness and transparency for the data bus. In addition, it provides a complementary transmission medium with regard to commonly used tethered links. A CAN bus system is used to demonstrate the redundant data transfer via tethered and wireless CAN.
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.
The initial idea of Robotic Process Automation (RPA) is the automation of business processes through a simple emulation of user input and output by software robots. Hence, it can be assumed that no changes of the used software systems and existing Enterprise Architecture (EA) is
required. In this short, practical paper we discuss this assumption based on a real-life implementation project. We show that a successful RPA implementation might require architectural work during analysis, implementation, and migration. As practical paper we focus on exemplary lessons-learned and new questions related to RPA and EA.
This article describes the functionality of a MATLAB® library that can be used to develop motion-logic applications in MATLAB programming language for industrial drive and control systems using the well known sercos automation bus. Therewith MATLAB's functionality is extended to designing automation applications from single axis machines up to multi-kinematic robots.
Production and distribution of personalized information services employing mass customization
(2003)
During the Covid-19 pandemic, vocational colleges, universities of applied science and technical universities often had to cancel laboratory sessions requiring students’ attendance. These above of all are of decisive importance in order to give learners an understanding of theory through practical work.This paper is a contribution to the implementation of distance learning for laboratory work applicable for several upper secondary educational facilities. Its aim is to provide a paradigm for hybrid teaching to analyze and control a non-linear system depicted by a tank model. For this reason, we redesign a full series of laboratory sessions on the basis of various challenges. Thus, it is suitable to serve different reference levels of the European Qualifications Framework (EQF).We present problem-based learning through online platforms to compensate the lack of a laboratory learning environment. With a task deduced from their future profession, we give students the opportunity to develop own solutions in self-defined time intervals. A requirements specification provides the framework conditions in terms of time and content for students having to deal with the challenges of the project in a self-organized manner with regard to inhomogeneous previous knowledge. If the concept of Complete Action is introduced in classes before, they will automatically apply it while executing the project.The goal is to combine students’ scientific understanding with a procedural knowledge. We suggest a series of remote laboratory sessions that combine a problem formulation from the subject area of Measurement, Control and Automation Technology with a project assignment that is common in industry by providing extracts from a requirements specification.
The problem of fair and privacy-preserving ordered set reconciliation arises in a variety of applications like auctions, e-voting, and appointment reconciliation. While several multi-party protocols have been proposed that solve this problem in the semi-honest model, there are no multi-party protocols that are secure in the malicious model so far. In this paper, we close this gap. Our newly proposed protocols are shown to be secure in the malicious model based on a variety of novel non-interactive zero-knowledge-proofs. We describe the implementation of our protocols and evaluate their performance in comparison to protocols solving the problem in the semi-honest case.
This paper addresses the pixel based recognition of 3D objects with bidirectional associative memories. Computational power and memory requirements for this approach are identified and compared to the performance of current computer architectures by benchmarking different processors. It is shown, that the performance of special purpose hardware, like neurocomputers, is between one and two orders of magnitude higher than the performance of mainstream hardware. On the other hand, the calculation of small neural networks is performed more efficiently on mainstream processors. Based on these results a novel concept is developed, which is tailored for the efficient calculation of bidirectional associative memories. The computational efficiency is further enhanced by the application of algorithms and storage techniques which are matched to characteristics of the application at hand.
Physical layer specification of the L-band Digital Aeronautical Communications System (L-DACS1)
(2009)
Phase Repeatable Synthesizers as a New Harmonic Phase Standard for Nonlinear Network Analysis
(2018)
To increase pressure to supply all floors of high buildings with water, booster stations, normally consisting of several parallel pumps in the basement, are used. In this work, we demonstrate the potential of a decentralized pump topology regarding energy savings in water supply systems of skyscrapers. We present an approach, based on Mixed-Integer Nonlinear Programming, that allows to choose an optimal network topology and optimal pumps from a predefined construction kit comprising different pump types. Using domain-specific scaling laws and Latin Hypercube Sampling, we generate different input sets of pump types and compare their impact on the efficiency and cost of the total system design. As a realistic application example, we consider a hotel building with 325 rooms, 12 floors and up to four pressure zones.
Successful optimization requires an appropriate model of the system under consideration. When selecting a suitable level of detail, one has to consider solution quality as well as the computational and implementation effort. In this paper, we present a MINLP for a pumping system for the drinking water supply of high-rise buildings. We investigate the influence of the granularity of the underlying physical models on the solution quality. Therefore, we model the system with a varying level of detail regarding the friction losses, and conduct an experimental validation of our model on a modular test rig. Furthermore, we investigate the computational effort and show that it can be reduced by the integration of domain-specific knowledge.
In order to allow an autonomous robot to perform non-trivial tasks like to explore a foreign planet the robot has to have deliberative capabilities like reasoning or planning. Logic-based approaches like the programming and planing language Golog and it successors has been successfully used for such decision-making problems. A drawback of this particular programing language is that their interpreter usually are written in Prolog and run on a Prolog back-end. Such back-ends are usually not available or feasible on resource-limited robot systems. In this paper we present our ideas and first results of a re-implementation of the interpreter based on the Lua scripting language which is available on a wide range of systems including small embedded systems.
Time-of-flight (ToF) sensors have become an alternative to conventional distance sensing techniques like laser scanners or image based stereo. ToF sensors provide full range distance information at high frame-rates and thus have a significant impact onto current research in areas like online object recognition, collision prevention or scene reconstruction. However, ToF cameras like the photonic mixer device (PMD) still exhibit a number of challenges regarding static and dynamic effects, e.g. systematic distance errors and motion artefacts, respectively. Sensor calibration techniques reducing static system errors have been proposed and show promising results. However, current calibration techniques in general need a large set of reference data in order to determine the corresponding parameters for the calibration model. This paper introduces a new calibration approach which combines different demodulation techniques for the ToF- camera 's reference signal. Examples show, that the resulting combined demodulation technique yields improved distance values based on only two required reference data sets.
In times of planned obsolescence the demand for sustainability keeps growing. Ideally, a technical system is highly reliable, without failures and down times due to fast wear of single components. At the same time, maintenance should preferably be limited to pre-defined time intervals. Dispersion of load between multiple components can increase a system’s reliability and thus its availability inbetween maintenance points. However, this also results in higher investment costs and additional efforts due to higher complexity. Given a specific load profile and resulting wear of components, it is often unclear which system structure is the optimal one. Technical Operations Research (TOR) finds an optimal structure balancing availability and effort. We present our approach by designing a hydrostatic transmission system.
The paper industry is the industry with the third highest energy consumption in the European Union. Using recycled paper instead of fresh fibers for papermaking is less energy consuming and saves resources. However, adhesive contaminants in recycled paper are particularly problematic since they reduce the quality of the resulting paper-product. To remove as many contaminants and at the same time obtain as many valuable fibres as possible, fine screening systems, consisting of multiple interconnected pressure screens, are used. Choosing the best configuration is a non-trivial task: The screens can be interconnected in several ways, and suitable screen designs as well as operational parameters have to be selected. Additionally, one has to face conflicting objectives. In this paper, we present an approach for the multi-criteria optimization of pressure screen systems based on Mixed-Integer Nonlinear Programming. We specifically focus on a clear representation of the trade-off between different objectives.
Motivation-based Learning: Teaching Fundamentals of Electrical Engineering with an LED Spinning Top
(2018)
The work in modern open-pit and underground mines requires the transportation of large amounts of resources between fixed points. The navigation to these fixed points is a repetitive task that can be automated. The challenge in automating the navigation of vehicles commonly used in mines is the systemic properties of such vehicles. Many mining vehicles, such as the one we have used in the research for this paper, use steering systems with an articulated joint bending the vehicle’s drive axis to change its course and a hydraulic drive system to actuate axial drive components or the movements of tippers if available. To address the difficulties of controlling such a vehicle, we present a model-predictive approach for controlling the vehicle. While the control optimisation based on a parallel error minimisation of the predicted state has already been established in the past, we provide insight into the design and implementation of an MPC for an articulated mining vehicle and show the results of real-world experiments in an open-pit mine environment.
MedicVR : Acceleration and Enhancement Techniques for Direct Volume Rendering in Virtual Reality
(2019)
Market changes have forced telecommunication companies to transform their business. Increased competition, short innovation cycles, changed usage patterns, increased customer expectations and cost reduction are the main drivers. Our objective is to analyze to what extend transformation projects have improved the orientation towards the end-customers. Therefore, we selected 38 real-life case studies that are dealing with customer orientation. Our analysis is based on a telecommunication-specific framework that aligns strategy, business processes and information systems. The result of our analysis shows the following: transformation projects that aim to improve the customer orientation are combined with clear goals on costs and revenue of the enterprise. These projects are usually directly linked to the customer touch points, but also to the development and provisioning of products. Furthermore, the analysis shows that customer orientation is not the sole trigger for transformation. There is no one-fits-all solution; rather, improved customer orientation needs aligned changes of business processes as well as information systems related to different parts of the company.
In steps of the production chain of carbide inserts, such as unloading or packaging, the conformity test of the insert type is done manually, which causes a statistic increase of errors due to monotony and fatigue of the worker and the wide variety of the insert types. A machine vision system is introduced that captures digital frames of the inserts in the production line, analyses inspects automatically and measures four quality features: coating colour, edge radius, plate shape and chip-former geometry. This new method has been tested on several inserts of different types and has shown that the prevalent insert types can be inspected and robustly classified in real production environment and therefore improves the manufacturing automation.
In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine.
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.