The growing need for bidirectional mobile satellite communications in the Ka-band necessitates development of dedicated antenna systems. In this article, we describe two different solutions user-terminal antennas intended an operation emergency scenarios. first solution, a high-gain antenna, consists Cassegrain reflector, fed from multimode monopulse tracking system circular polarization at downlink frequency 20 GHz. structure is operational 30 GHz to cover uplink range. mounted on...

Fault detection at rotating machinery with the help of vibration sensors offers possibility to detect damage machines an early stage and prevent production downtimes by taking appropriate measures. The analysis data using methods machine learning promises a significant reduction in associated effort further improvement diagnostic accuracy. Here we publish dataset which is used as basis for development evaluation algorithms unbalance detection. For this purpose, unbalances various sizes were...

Functional Digital Mock-up (FDMU) and Interface (FMI) are two keywords arising in the last years simulation technology.In this paper, we would like to show that both principles, aiming at a comprehensive investigation of heterogeneous systems, e.g. from mechatronics, not necessarily competing with each other but may be combined benefit ideas behind.The approaches based on different cover aspects interaction modern tools.For reason constraints have considered, which do make things easier.Both...

Systems for process automation become increasingly complex and also tend to be composed of autonomous subsystems, which is strongly driven by the progress made in information technology. An active field research implementation monitoring control at sub-system level using cognitive approaches. In this paper we present a method sensorless condition an electric drive train. Based on experiment design measured phase currents physical demonstrator device including mechanical defects extracted...

Early damage detection and classification by condition monitoring systems is crucial to enable predictive maintenance of manufacturing industrial facilities. Data analysis can be improved applying machine learning algorithms fusion data from heterogenous sensors. This paper presents an approach for a step-wise integration classifications gained vibration acoustic emission sensors in order combine the information signals acquired low high frequency ranges. A test rig comprising drive train...

This paper presents the development of a diagnostic method which uses measurement motor currents in order to detect defects electromechanical systems. It focusses on two main topics: acquisition experimental data, and method. The data was crucial for successful dedicated signal analysis For this purpose, test rig generating training created. provides ability simulate wide range experimentally. Different types artificial defects, such as bearing damage or misalignments, were used; these are...

Modern buildings have complex technical equipment that is hard to operate efficiently from a user's point of view. Users and building managers therefore need guidance in terms finding the most efficient operational strategies monitoring plans avoid faults energy wastes. Current support systems can do that, but they must usually be adapted each manually. In this study, an expert system proposed provides complementary analysis layer with semantic modeling knowledge reuse. During configuration...

Using hourly energy consumption data recorded by smart meters, retailers can estimate the day-ahead of their customer portfolio. Deep neural networks are especially suited for this task as a huge amount historical is available from meter recordings to be used model training. Probabilistic layers further enable estimation uncertainty forecasts. Here, we propose method calculate forecasts which include an aleatoric uncertainty. To consider statistical properties values, modeled using lognormal...

Reliability of machines and facilities has played an important role since many years.Nowadays, attention is also paid to maintenance times.Maintenance standstills are be reduced as far possible.On the other hand, technical systems subject signs wear tear which in general growing slowly imperceptibly.The gradual abrasion applied tools may lead poor production tolerances or a component's standstill.Hence, condition-based strategy will increasing importance.Such requires permanent condition...

Digitalization in facility management has become an active field of research for many reasons. Among others, it can provide high support by saving energy and cost the building sector as well optimizing internal processes involved within a facility. To enable this, data about to be collected analyzed. Building systems already produce huge amounts that are analyzed supervising, controlling benchmarking buildings. However, even if numerous produced during operation there is no much use...

The digitalization process is steadily increasing in the building industry and promises new perspectives for better designing operating buildings throughout their life cycle. However, has not yet brought its greatest benefit tackling rising global energy demand even generally associated with more consumption. Instead, it become urgent to rationalize use decrease wastes. Indeed, are responsible about one third of consumption world [1], 30% this wasted through wrong or suboptimal operation,...

The dataset contains one csv file per measurement. All files are packed into one zip-file. can, for example, be read using Python and the modules zipfile pandas. An example code this is documented in README.md file.

Increasing reliability, availability and safety requirements as well an increasing amount of data acquisition systems have enabled condition-based maintenance in mobile industrial machinery. In this paper, we present a methodology to develop robust diagnostic approach. This includes the consideration variable operating conditions process versatile, non domain-specific feature extraction technique. By doing so, train anomaly detection models for different fault types intensities displacement...

Often; mathematical models with different levels of detail are used. In this contribution; a model drum motor is presented. This was designed for the description dynamic behaviour as well possible implementation several wearing phenomena. Using model; better understanding wear and tear phenomena has been achieved by carrying out considerable number simulation runs using operational conditions. information; important knowledge about detection wearout signs able to be gained.

Active condition monitoring of automation systems is a strongly emerging topic. In this paper purely data-driven approach presented which allows for detection wear-out or faulty situations in machine subsystems, each consisting servomotor driving different parts the machine. The based on empirical analysis motor's electric currents, but can be applied to tracking errors servo controller as well. features gained from spectra motor currents errors, respectively, are reduced by singular value...

Equation-based 1 modelling of hybrid systems has to consider dynamical consisting components with continuous and/or discrete behavior. The paper focuses on such under special consideration variable model structure. Some ideas are presented how a simulation and phenomena can be handled correctly. main process is continuing alternation between phases, where in the phase changeover performed new structure which valid during next phase. addresses problem finding as within This found time history...

Many developments and research have led in last decade to enhanced building automation systems embedding data analytics algorithms performing energy-optimized control. The presented approach aims at providing a complementary analysis layer compared such by the means of semantic modeling knowledge reuse. For that purpose, it relies on description energy system from which conservation measures can be derived. Starting an ontological system, expert is proposed provides monitoring plan operation...