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Found 6289 publications

Dynamic extension of vector Preisach model

Miklós Kuczmann

Publication Name: Physica B Condensed Matter

Publication Date: 2018-11-15

Volume: 549

Issue: Unknown

Page Range: 47-52

Description:

The objective of the present paper is to generalize the vector Preisach hysteresis model to take dynamic effects into account. A comprehensive analysis of the vector behavior has been performed by a single sheet tester with a specimen of round shape. The locus of the magnetic flux density vector has been controlled by a digital measurement set up at different frequency. An inverse vector Preisach hysteresis model has been built up by viscous-type scalar models and an identification procedure has been developed to follow the measured data. Finally, the model has been inserted into a finite element procedure through the fixed point technique to simulate electrical engineering problems.

Open Access: Yes

DOI: 10.1016/j.physb.2017.09.068

Issue on implementation Possibility of Bluetooth Mesh Capabilities into OmNET++

Laszlo Kajdocsi Janos Kovacs

Publication Name: Sisy 2018 IEEE 16th International Symposium on Intelligent Systems and Informatics Proceedings

Publication Date: 2018-11-05

Volume: Unknown

Issue: Unknown

Page Range: 203-207

Description:

Navigation was always important to humankind. Today, it is unimaginable to navigate in the world without the Global Positioning System. Although, the Global Positioning System operates very accurately outdoors but does not in indoor environments. Unfortunately, the indoor navigation is still in its infancy. However, several approaches have been proposed during the last decade but none of them is accurate and/or inexpensive enough for the consumer use. According to the authors' proposal, utilization of a hybrid mesh network might solve the inaccuracy. The mesh technology would offer an accurate, fast, adaptive, self-organizing, self-healing and inexpensive solution for the indoor positioning. A hybrid mesh network would involve some technologies like Wi-Fi, Bluetooth, RFID or IQRF. Fortunately, the Bluetooth Special Interest Group announced the mesh capability in the Bluetooth 5 standard in 2017. However, building up a physical network is always expensive experiment, thus simulations would be executed in a OmNET++. In this paper, the implementation possibility of the Bluetooth mesh capabilities will be analyzed.

Open Access: Yes

DOI: 10.1109/SISY.2018.8524830

Demonstrating the Options for Automated Advanced Selective Waste Gathering

István Lakatos Ádám Titrik János Hollósi

Publication Name: Sisy 2018 IEEE 16th International Symposium on Intelligent Systems and Informatics Proceedings

Publication Date: 2018-11-05

Volume: Unknown

Issue: Unknown

Page Range: 167-171

Description:

Due to continuous developments, the exhausting and unpleasant work done by humans is going to be partly or totally replaced by automated devices. Such developments can be found in the field of transport concerning autonomous and networked vehicles. Although we are at a quite early stage of development, it is highly practical to make plans for a more distant future, i.e. targeting a totally automated selective waste gathering. Apart from the application of smart containers, this study presents alternatives for networked automated selective waste gathering.

Open Access: Yes

DOI: 10.1109/SISY.2018.8524707

Evaluation of Neural Network-Based Sensing and Perception in Experimental Vehicles

Claudiu Radu Pozna Áron Ballagi Ernö Horváth

Publication Name: Ines 2018 IEEE 22nd International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2018-11-05

Volume: Unknown

Issue: Unknown

Page Range: 000113-000118

Description:

As increasing use of neural networks (NN) and deep-learning (DL) can be observed in various fields, such as voice and image recognition, control, translation, data processing, function approximation, etc. These technologies can also be applied in a specific domain of experimental vehicles. This paper presents and summarizes our recent practical experiences gained during the usage of neural network as sensing and perception subsystem in an experimental vehicle. The paper does not targets general NN problems, only focuses on the narrow subdomain. The current paper also reviews and evaluates the available hyper parameter tunings, optimizers and neural network architectures and proposes tested solutions for enhanced performance. All of the used datasets, source codes and additional materials is available online.

Open Access: Yes

DOI: 10.1109/INES.2018.8523952

Parameter Sensitivity Analysis Method for Speed Sensorless Induction Machine Drives Based on Unscented Kalman Filter

Krisztian Horvath Marton Kuslits

Publication Name: Proceedings 2018 IEEE 18th International Conference on Power Electronics and Motion Control Pemc 2018

Publication Date: 2018-11-03

Volume: Unknown

Issue: Unknown

Page Range: 744-749

Description:

This paper presents a new method for determining the steady-state machine parameter sensitivities of induction machine speed sensorless control algorithms, which are utilizing unscented Kalman filter (UKF) and direct rotor field oriented control (DRFOC). Sensitivity influence of the UKF is investigated by alternative noise parameters and pointed out that selection of noise parameters may influence the flux and torque sensitivities of the entire system with respect to stator resistance variations. In order to obtain a better picture, the sensitivities are calculated for various operating points resulting in sensitivity maps. For this, a computationally efficient calculation method is applied by using the steady-state system equations.

Open Access: Yes

DOI: 10.1109/EPEPEMC.2018.8521843

Development of an ion beam detector for the atomic beam probe diagnostic

M. Berta G. Anda D. Dunai P. Hacek D. Réfy M. Aradi J. Krbec R. Pánek S. Zoletnik A. Bencze V. Weinzettl J. Stöckel

Publication Name: Review of Scientific Instruments

Publication Date: 2018-11-01

Volume: 89

Issue: 11

Page Range: Unknown

Description:

The atomic beam probe diagnostic concept aims at measuring the edge magnetic field and through that edge current distribution in fusion plasmas by observing trajectories of an ion beam stemming from a diagnostic neutral beam. The diagnostic potentially has microsecond scale time resolution and can thus prove to be a powerful option to study fast changes in the edge plasma. A test detector has been installed on the COMPASS tokamak as an extension of the existing lithium beam diagnostic system. It employs a relatively simple concept of an array of conductive detection plates measuring the incident ion current, which is then amplified and converted to a voltage signal. The aim of the test detector is to experimentally examine the idea of the diagnostic and provide background data for design and installation of a final detector. Also, a numerical code based on the CUDA parallel computing platform has been developed for modeling lithium ion trajectories in the given COMPASS plasma discharges. We present the developments of the detector design and test measurements of the diagnostic performed both in a laboratory beam system and on the COMPASS tokamak.

Open Access: Yes

DOI: 10.1063/1.5044529

Improve the Accuracy of Neural Networks using Capsule Layers

Claudiu Radu Pozna János Hollósi

Publication Name: 18th IEEE International Symposium on Computational Intelligence and Informatics Cinti 2018 Proceedings

Publication Date: 2018-11-01

Volume: Unknown

Issue: Unknown

Page Range: 15-18

Description:

Neural networks are a powerful and widely used tools for various classification and segmentation tasks. Nowadays, in the field of computer vision the convolutional neural networks (CNNs) are the most popular solution for many problems. The CNNs performance is looks like exceptionally great when the test images are very close to the training dataset. However if the input images are transformed, such as rotating or tilting, the efficiency of the neural network may be greatly reduced. A new kind of neural network, is called capsule network, is trying to solve this problem. In this paper we examines the efficiency of the capsule network, by trying to increase the accuracy of different networks with capsule layers.

Open Access: Yes

DOI: 10.1109/CINTI.2018.8928194

Fast density reconstruction of Li-BES signal on the COMPASS tokamak

M. Berta J. Seidl P. Hacek J. Krbec M. Hron R. Pánek

Publication Name: Review of Scientific Instruments

Publication Date: 2018-11-01

Volume: 89

Issue: 11

Page Range: Unknown

Description:

This article describes a fast and automatic reconstruction of the edge plasma electron density from the radiation of energetic Li atoms of the diagnostic beam on the COMPASS tokamak. Radiation is detected by using a CCD camera and by using an avalanche photo-diode system with a temporal resolution of 20 ms and 2 μs, respectively. Both systems are equipped with a 670.8 nm optical filter which corresponds to the lithium 1s22s1-1s22p1 transition. A theoretical model and a data processing procedure of a raw signal to obtain the density profile are described. The reconstruction algorithm provides the absolutely calibrated electron density profiles together with the measurement error estimated from relatively calibrated light profiles; the implementation is performed in Python. Time demanding operations of the code were optimized to provide reconstruction of a single profile within less than 10 ms which makes the code applicable for processing of a large amount of data. Thanks to this calculation speed, it is possible to reconstruct electron density profiles between two consecutive shots on the COMPASS tokamak with 2 μs time resolution.

Open Access: Yes

DOI: 10.1063/1.5049894

High Precision Test System for the Investigation of the Condition of Lithium-ion Batteries

Adrienn Dineva Krisztian Ferko Miklos Szekely Gyula Gyoker Istvan Vajda

Publication Name: 2018 International Symposium on Fundamentals of Electrical Engineering Isfee 2018

Publication Date: 2018-11-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Modern electric drive systems require more sophisticated monitoring and diagnosis methods for determining the expected life-Time and reliability. Recently, continuous assessment of the electrical condition of electrical machines has become increasingly important. Investigations to predict battery life are of the utmost importance for Electric Vehicles (EVs). The evaluation of the instantaneous State-of-Health (SoH) of the battery cell packs requires a precise measurement system that encompasses the especially important specifications related to the operating conditions. In addition modern Battery Management Systems (BMS) rely on empirical battery models whose parametrization is crucial from the reliability's point of view. The model parameters are necessary to be indentified via the appropriate measurement data. To address these considerations, this paper presents a new test system for Li-ion batteries and control software based on LabView, which is capable of conducting high quality and completely automated battery cell measurements defined by user input test vectors and test suites. The test system allows conducting also real time condition monitoring in Li-ion batteries by discharge impulse responses. Finally several measurements on the experimental setup are performed. Analysis of the measured data validate that the designed device ensures high performance testing and post-processing.

Open Access: Yes

DOI: 10.1109/ISFEE.2018.8742422