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To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.
Design and Development of a Hot S-Parameter Measurement System for Plasma and Magnetron Applications
(2020)
This paper presents the design, development and calibration procedures of a novel hot S-parameter measurement system for plasma and magnetron applications with power level up to 6 kW. Based on a vector network analyzer, a power amplifier and two directional couplers, the input matching hotS 11 and transmission hotS 21 of the device under test are measured at 2.45 GHz center frequency and 300MHz bandwidth, while the device is driven by the magnetron. This measurement system opens a new horizon to develop many new industrial applications such as microwave plasma jets, dryer systems, dryers and so forth. Furthermore, the developing, controlling and monitoring a 2kW 2.45GHz plasma jet and a dryer system using the measurement system are presented and explained.
In this paper we report on an architecture for a self-driving car that is based on ROS2. Self-driving cars have to take decisions based on their sensory input in real-time, providing high reliability with a strong demand in functional safety. In principle, self-driving cars are robots. However, typical robot software, in general, and the previous version of the Robot Operating System (ROS), in particular, does not always meet these requirements. With the successor ROS2 the situation has changed and it might be considered as a solution for automated and autonomous driving. Existing robotic software based on ROS was not ready for safety critical applications like self-driving cars. We propose an architecture for using ROS2 for a self-driving car that enables safe and reliable real-time behaviour, but keeping the advantages of ROS such as a distributed architecture and standardised message types. First experiments with an automated real passenger car at lower and higher speed-levels show that our approach seems feasible for autonomous driving under the necessary real-time conditions.
With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs.
Magnetic nanoparticles (MNPs) are used as therapeutic and diagnostic agents for local delivery of heat and image contrast enhancement in diseased tissue. Besides magnetization, the most important parameter that determines their performance for these applications is their magnetic relaxation, which can be affected when MNPs immobilize and agglomerate inside tissues. In this letter, we investigate different MNP agglomeration states for their magnetic relaxation properties under excitation in alternating fields and relate this to their heating efficiency and imaging properties. With focus on magnetic fluid hyperthermia, two different trends in MNP heating efficiency are measured: an increase by up to 23% for agglomerated MNP in suspension and a decrease by up to 28% for mixed states of agglomerated and immobilized MNP, which indicates that immobilization is the dominant effect. The same comparatively moderate effects are obtained for the signal amplitude in magnetic particle spectroscopy.
Thermal and Optical Study on the Frequency Dependence of an Atmospheric Microwave Argon Plasma Jet
(2019)
This paper describes the development of a capacitively coupled high-pressure lamp with input power between 20 and 43 W at 2.45 GHz, using a coaxial line network. Compared with other electrodeless lamp systems, no cavity has to be used and a reduction in the input power is achieved. Therefore, this lamp is an alternative to the halogen incandescent lamp for domestic lighting. To serve the demands of domestic lighting, the filling of the lamp is optimized over all other resulting requirements, such as high efficacy at low induced powers and fast startups. A workflow to develop RF-driven plasma applications is presented, which makes use of the hot S-parameter technique. Descriptions of the fitting process inside a circuit and FEM simulator are given. Results of the combined ignition and operation network from simulations and measurements are compared. An initial prototype is built and measurements of the lamp's lighting properties are presented along with an investigation of the efficacy optimizations using large signal amplitude modulation. With this lamp, an efficacy of 135 lmW -1 is achieved.
High gradient magnetic separation (HGMS) has been established since the early 1970s. A more recent application of these systems is the use in bioprocesses. To integrate the HGMS in a fermentation process, it is necessary to optimize the separation matrix with regard to the magnetic separation characteristics and permeability of the non-magnetizable components of the fermentation broth. As part of the work presented here, a combined fluidic and magnetic force finite element model simulation was created using the software COMSOL Multiphysics and compared with separation experiments. Finally, as optimal lattice orientation of the separation matrix, a transversal rhombohedral arrangement was defined. The high suitability of the new filter matrix has been verified by separation experiments.
The capacitive electrolyte–insulator–semiconductor (EIS) structure is a typical device based on a field-effect sensor platform. With a simple silicon-based structure, EIS have been useful for several sensing applications, especially with incorporation of nanostructured films to modulate the ionic transport and the flat-band potential. In this paper, we report on ion transport and changes in flat-band potential in EIS sensors made with layer-by-layer films containing poly(amidoamine) (PAMAM) dendrimer and single-walled carbon nanotubes (SWNTs) adsorbed on p-Si/SiO 2 /Ta 2 O 5 chips with an Al ohmic contact. The impedance spectra were fitted using an equivalent circuit model, from which we could determine parameters such as the double-layer capacitance. This capacitance decreased with the number of bilayers owing to space charge accumulated at the electrolyte–insulator interface, up to three PAMAM/SWNTs bilayers, after which it stabilized. The charge-transfer resistance was also minimum for three bilayers, thus indicating that this is the ideal architecture for an optimized EIS performance. The understanding of the influence of nanostructures and the fine control of operation parameters pave the way for optimizing the design and performance of new EIS sensors.
This contribution discusses the utilization of RF power in an MRI system with RF mode shimming which enables the superposition of circularly polarized modes of a transmit RF coil array driven by a Butler matrix. Since the required power for the individual modes can vary widely, mode-shimming can result in a significant underutilization of the total available RF power. A variable power combiner (VPC) is proposed to improve the power utilization: it can be realized as a reconfiguration of the MRI transmit system by the inclusion of one additional matrix network which receives the power from all transmit amplifiers at its input ports and provides any desired (combined) power distribution at its output ports by controlling the phase and amplitude of the amplifiers’ input signals. The power distribution at the output ports of the VPC is then fed into the “mode” ports of the coil array Butler matrix in order to superimpose the spatial modes at the highest achievable power utilization. The VPC configuration is compared to the standard configuration of the transmit chain of our MRI system with 8 transmit channels and 16 coils. In realistic scenarios, improved power utilization was achieved from 17% to 60% and from 14% to 55% for an elliptical phantom and a region of interest in the abdomen, respectively, and an increase of the power utilization of 1 dB for a region of interest in the upper leg. In general, it is found that the VPC allows significant improvement in power utilization when the shimming solution demands only a few modes to be energized, while the technique can yield loss in power utilization in cases with many modes required at high power level.
This paper presents the latest prototype of the integrated emitter turn-off thyristor concept, which potentially ranks among thyristor high-power devices like the gate turn-off thyristor and the integrated gate-commutated thyristor (IGCT). Due to modifications of the external driver stage and mechanical press-pack design optimization, this prototype allows for full device characterization. The turn-off capability was increased to 1600 A with an active silicon area of 823mm2 . This leads to a transient peak power of 672.1kW/cm² . Within this paper, measurements and concept assessment are presented and a comparison to state-of-the-art IGCT devices is provided.
The continuously growing amount of renewable sources starts compromising the stability of electrical grids. Contradictory to fossil fuel power plants, energy production of wind and photovoltaic (PV) energy is fluctuating. Although predictions have significantly improved, an outage of multi-MW offshore wind farms poses a challenging problem. One solution could be the integration of storage systems in the grid. After a short overview, this paper focuses on two exemplary battery storage systems, including the required power electronics. The grid integration, as well as the optimal usage of volatile energy reserves, is presented for a 5- kW PV system for home application, as well as for a 100- MW medium-voltage system, intended for wind farm usage. The efficiency and cost of topologies are investigated as a key parameter for large-scale integration of renewable power at medium- and low-voltage.
High-intensity discharge lamps can be driven by radio-frequency signals in the ISM frequency band at 2.45 GHz, using a matching network to transform the impedance of the plasma to the source impedance. To achieve an optimal operating condition, a good characterization of the lamp in terms of radio frequency equivalent circuits under operating conditions is necessary, enabling the design of an efficient matching network. This paper presents the characterization technique for such lamps and presents the design of the required matching network. For the characterization, a high-intensity discharge lamp was driven by a monofrequent large signal at 2.45 GHz, whereas a frequency sweep over 300 MHz was performed across this signal to measure so-called small-signal hot S-parameters using a vector network analyzer. These parameters are then used as an equivalent load in a circuit simulator to design an appropriate matching network. Using the measured data as a black-box model in the simulation results in a quick and efficient method to simulate and design efficient matching networks in spite of the complex plasma behavior. Furthermore, photometric analysis of high-intensity discharge lamps are carried out, comparing microwave operation to conventional operation.
The interest in PET detectors with monolithic block scintillators is growing. In order to obtain high spatial resolutions dedicated positioning algorithms are required. But even an ideal algorithm can only deliver information which is provided by the detector. In this simulation study we investigated the light distribution on one surface of cuboid LSO scintillators of different size. Scintillators with a large aspect ratio (small footprint and large height) showed significant position information only for a minimum interaction depth of the gamma particle. The results allow a quantitative estimate for a useful aspect ratio.
In our case the double-side-method is used to minimize the complexity of a matrix-readout. Here the number of channels is reduced to 2√N̅. It is also possible to benefit from the method in a single pixel readout system. One signal can be used to measure position and energy of the event, the other one can be applied to a fast trigger-circuit at the same time. In a next step we will investigate timing behavior and electrical crosstalk of the circuit.
The readout of gamma detectors is considerably simplified when the event intensity is encoded as a pulse width (Pulse Width Modulation, PWM). Time-to-Digital-Converters (TDC) replace the conventional ADCs and multiple TDCs can be realized easily in one PLD chip (Programmable Logic Device). The output of a PWM stage is only one digital signal per channel which is well suited for transport so that further processing can be performed apart from the detector. This is particularly interesting for large systems with high channel density (e.g. high resolution scanners). In this work we present a circuit with a linear transfer function that requires a minimum of components by performing the PWM already in the preamp stage. This allows a very compact and also cost-efficient implementation of the front-end electronics.