Fachbereich Ingenieur- und Naturwissenschaften
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Evaluation of medical images is of key importance in the work of medical staff today. Especially this problem pays important role in otolaryngology.
The aim of our work was to develop an automatic complex method for assessing the state of the human paranasal sinuses.
Our research included 10 people of different sex and age, who were divided into groups, taking into account the recommendations of the WHO for 2019-2021. The structure of the mucous membrane of the maxillary sinus were calculated and compared.
In the course of our research, an algorithm was developed for the automatic assessment of the state of the mucous membrane of the maxillary sinus and its bone walls according to the data of the spiral computed tomography. The difference between obtained data in the manual and automatic mode is minimal.
Periodic timetable optimization problems in public transport can be modeled as mixed-integer linear programs by means of the Periodic Event Scheduling Problem (PESP). In order to keep the branch-and-bound tree small, minimum integral cycle bases have been proven successful. We examine forward cycle bases, where no cycle is allowed to contain a backward arc. After reviewing the theory of these bases, we describe the construction of an integral forward cycle basis on a line-based event-activity network. Adding turnarounds to the instance R1L1 of the benchmark library PESPlib, we computationally evaluate three types of forward cycle bases in the Pareto sense, and come up with significant improvements concerning dual bounds.
Small and medium-sized companies increasingly turning their attention towards the fourth industrial revolution. In order to increase their own long-term competitiveness, there is a growing desire to make production smarter, more efficient, safer and more sustainable through new technologies. Often, however, existing plants cannot be easily replaced by modern equipment. The reasons for this can be high investment costs, excessive downtimes or the unavailability of an equivalent machine. An alternative solution to the purchase of new equipment is the modernisation or expansion of existing systems, also called retrofitting. Thus, this paper deals with the retrofit process of a machine tool, whereby the software architecture of the control unit is the primary concern of this work.
During the last decade production innovation was mainly focused on connectivity aspects. The vision of smart factories running on software, that uses collected machine data, has become true but foremost for leading industrial companies in highly developed countries. Apart from these, production can also be found in non-industrialized craft professions as well as in less developed countries. As digitalization does not necessarily require an industrial or developed setting the latter could possibly benefit from it as well. Socio-cyber-physical production systems have been used to describe the interdependencies of linked production systems but usually focus on highly developed regions as well as for industrial applications. This paper lines out similarities and differences for each case, introduces the concept of cyber-physical production systems (CPPS) and its extension to socio-CPPS (SCPPS), which emphasizes the role of human workers in the production environment. The relation between industrial, non-industrial production and innovations is examined. Furthermore, the widening of SCCPS concepts for non-industrial production is discussed.
Dermatological in vivo measurements are used for various purposes, e.g. health care, development and testing of skin care products or claim support in marketing. Especially for the last two purposes, in vivo measurements are extensive due to the quantity and repeatability of the measurement series. Furthermore, they are performed manually and therefore represent a nonnegligible time and cost factor. A solution to this is the implementation of collaborative robotics for the measurement execution. Due to various body shapes and surface conditions, common static control procedures are not applicable. To solve this problem, spatial information obtained from a stereoscopic camera can be integrated into the robot control process. However, the designated measurement area has to be detected and the spatial information processed. Therefore the authors propose a concept towards segmenting arm areas through a CNN-based object detector and their further processing to perform robot-based in vivo measurements. The paper gives an overview of the utilization of RGB-D images in 2D object detectors and describes the selection of a suitable model for the application. Furthermore the creation, annotation and augmentation of a custom dataset is presented.
Faults in industrial chiller systems can lead to higher energy consumption, increasing wear of system components and shorten equipment life. While they gradually cause anomalous system operating conditions, modern automatic fault detection models aim to detect them at low severity by using real-time sensor data. Many scientific contributions addressed this topic in the past and presented data-driven approaches to detect faulty system states. Although many promising results were presented to date, there is lack of suitable comparison studies that show the effectiveness of the proposed models by use of data stemming from different chiller systems. Therefore this study aims at detecting a suitable data-driven approach to detect faults reliable in different domains of industrial chillers. Thus, a unified procedure is developed, to train all algorithms in an identical way with same data-basis. Since most of the reviewed papers used only one dataset for training and testing, the selected approaches are trained and validated on two different datasets from real refrigeration systems. The data-driven approaches are evaluated based on their accuracy and true negative rate, from which the most suitable approach is derived as a conclusion.
Chiller systems are used in many different applications in both the industrial and the commercial sector. They are considered major energy consumers and thus contribute a non-negligible factor to environmental pollution as well as to the overall operating cost. In addition, chillers, especially in industrial applications, are often associated with high reliability requirements, as unplanned system downtimes are usually costly. As many studies over the past decades have shown, the presence of faults can lead to significant performance degradation and thus higher energy consumption of these systems. Thus, data-driven fault detection plays an ever-increasing role in terms of energy efficient control strategies. However, labelled data to train associated algorithms are often only available to a limited extent, which consequently inhibits the broad application of such technologies. Therefore, this paper presents an approach that exploits only a small amount of labelled and large amounts of unlabelled data in the training phase in order to detect fault related anomalies. For this, the model utilizes the residual space of the data transformed through principal component analyses in conjunction with a biased support vector machine, which can be ascribed to the concept of semi-supervised learning, or more specifically, positive-unlabelled learning.
To achieve climate goals and contain further global warming, it is inevitable to reduce CO2 emissions especially in energy consumption. A way to do so is by integrating renewable energy sources (RES) into an energy system’s power generation. However, there is no standard procedure to decarbonise a locally restricted system. Therefore, the various local conditions have to be analysed and taken into consideration.
The authors propose a model-based approach to decarbonise the energy system of the island Föhr, Germany. This includes various collected data sets on local conditions such as climate data and heat and power demand. The data is used to represent the island’s energy system and design a model-based solution in a simulation software.
The authors identify potentials by comparing costs and revenues by addressing the deployment of different RES technologies. One finding is that heat generation causes 91 % of CO2 emissions making it the major producer. However, with the designed solution, emissions could be reduced to a third.
The fossil fuels used to provide energy, such as coal, crude oil and natural gas, are largely responsible for carbon dioxide emissions and other so-called greenhouse gases. Hydrogen gas (H2) can make a key contribution to decarbonization. It can be produced using various processes. Several processes are available to produce hydrogen, such as (i) steam reforming, (ii) cracking process or (iii) electrolysis. Depending on the source of origin, there is a distinction made between different “colours”. Gray, blue, turquoise, yellow and green hydrogen is available, the latter made using Renewable Energies. However, items such as (i) possible variants of hydrogen, (ii) leading export countries or (iii) provision paths to be preferred in the future will be discussed in this paper.
Science, technology and politics agree: hydrogen will be the energy carrier of the future. It will replace fossil fuels based on a sufficient supply from sustainable energy. Since the possibilities of storing and transporting hydrogen play a decisive role here, the so-called LOHC (Liquid Organic Hydrogen Carriers) can be used as carrier materials. LOHC carrier materials can reversibly absorb hydrogen, store it without loss and release it again when needed. Since little or no pressure is required, normal containers or tanks can be used. The volume or mass-related energy densities can reach around a quarter of liquid fossil fuels.
This paper is to give an introduction to the field of hydrogen storage and usage of those LOHC, in particular. The developments of the last ten years have been related to the storage and transport of hydrogen with LOHC. These are crucial to meet the future demand for energy carriers e.g. for mobile applications. For this purpose, all transport systems are under consideration as well as the decentralized supply of rural areas with low technological penetration, e.g. regions of Western Africa which are often characterized by a lack of energy supply. Hydrogen bound in LOHC can provide a hazard-free alternative for distribution. The paper provides an overview of the conversion forms as well as the chemical carrier materials. Dibenzyltoluene as well as N-ethylcarbazole - as examples for LOHC - are discussed as well as chemical hydrogen storage materials like ammonia boranes as alternatives to LOHC.