Wyniki wyszukiwania - BazTech

1

Design of instrumented wheelset for measuring wheel-rail interaction forces

Bižić Milan, Petrović Dragan

Metrology and Measurement Systems

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2023

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Vol. 30, nr 3

563--579

EN

The paper presents the design of a specific type of instrumented wheelset intended for continuous measuring of lateral and vertical wheel-rail interaction forces 𝑌 and 𝑄, in accordance with regulations EN 14363 and UIC 518. The platform is a standard heavy wheelset BA314 with an axle-load of 25 tons. The key problems of smart instrumentalization are solved by the use of the wheel’s numerical FEM model, which provides a significant cost reduction in the initial stage of development of the instrumented wheelset. The main goal is to ensure high measuring accuracy. The results of the FEM calculations in ANSYS are basis for identification of the distribution of strains on the internal and external side of the wheel disc. Consequently, the most convenient radial distances for installation of strain gauges of Wheatstone measuring bridges are determined. In the next stage, the disposition, number and ways of interconnection of strain gauges in the measuring bridges are defined. Ultimately, an algorithm for inverse determination of parameters 𝑌 and 𝑄 based on mixed signals from the measuring bridges is developed. The developed solution is validated through tests on specific examples, using a created numerical FEM model. A high accuracy of estimation of unknown parameters 𝑌 and 𝑄 is obtained with an error of less than 4.5%, while the error of estimation of their ratio 𝑌 𝑄 is less than 2%. Therefore, the proposed solution can be efficiently used in the instrumentalization of the considered wheelset, while the problems of its practical implementation will be the subject of further research.

2

ICA based on Split Generalized Gaussian

Spurek Przemysław, Rola Przemysław, Tabor Jacek, Czechowski Aleksander, Bedychaj Andrzej

Schedae Informaticae

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2019

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Vol. 28

25--47

EN

Independent Component Analysis (ICA) is a method for searching the linear transformation that minimizes the statistical dependence between its components. Most popular ICA methods use kurtosis as a metric of independence (non-Gaussianity) to maximize, such as FastICA and JADE. However, their assumption of fourth-order moment (kurtosis) may not always be satisfied in practice. One of the possible solution is to use third-order moment (skewness) instead of kurtosis, which was applied in ICASG and EcoICA. In this paper we present a competitive approach to ICA based on the Split Generalized Gaussian distribution (SGGD), which is well adapted to heavy-tailed as well as asymmetric data. Consequently, we obtain a method which works better than the classical approaches, in both cases: heavy tails and non-symmetric data.

3

Road profile identification using estimation techniques: comparison between independent component analysis and Kalman filter

Chaabane Mariem Miladi, Ben Hassen Dorra, Abbes Mohamed Slim, Baslamisli Selahattin Caglar, Chaari Fakher, Haddar Mohamed

Journal of Theoretical and Applied Mechanics

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2019

|

Vol. 57 nr 2

397--409

EN

This paper focuses on the identification of a road profile disturbance acting on vehicles. Vehicles are subjected to many kinds of excitation sources such as road profile irregularities, which constitute a major area of interest when designing suspension systems. Indeed, determining the road profile is important for passive suspension design on the one hand and for determining an appropriate control law for active suspensions on the other. Direct measurement techniques of the road profile are expensive, so solutions based on estimation theory are needed. The aim of this paper is to characterize the road excitation using the Independent Component Analysis (ICA). This proposed method can reconstruct original excitation sources by using physically measurable signals of the system under study. Here, the estimation of road disturbances is considered as output sources and identified from dynamic responses of the vehicle. These responses can be measured via sensors or can be numerically computed. In our case, they are numerically simulated using the Newmark method and consider different types of road profiles. The obtained results are validated after using a comparison with the Kalman filtering. The robustness of the ICA is confirmed via parametric study.

4

Impulse Noise Suppression Based on Power Iterative ICA in Power Line Communication

Zhang Wei, Luo Zhongqiang, Xiong Xingzhong

International Journal of Electronics and Telecommunications

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2019

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Vol. 65, No. 4

651--656

EN

To overcome the detrimental influence of impulse noise in power line communication and the trap of scarce prior information in traditional noise suppression schemes , a power iteration based fast independent component analysis (PowerICA) based noise suppression scheme is designed in this paper. Firstly, the pseudo-observation signal is constructed by weighted processing so that single-channel blind separation model is transformed into the multi-channel observed model. Then the proposed blind separation algorithm is used to separate noise and source signals. Finally, the effectiveness of the proposed algorithm is verified by experiment simulation. Experiment results show that the proposed algorithm has better separation effect, more stable separation and less implementation time than that of FastICA algorithm, which also improves the real-time performance of communication signal processing.

5

Development of Data Processing Tools for the Analysis of Radargrams in Utility Detection Using Ground Penetrating Radar

Sagnard F.

Journal of Telecommunications and Information Technology

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2017

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nr 3

55--68

EN

The extraction of quantitative information from Ground Penetrating Radar (GPR) data sets (radargrams) to detect and map underground utility pipelines is a challenging task. This study proposes several algorithms included in the main stages of a data processing chain associated with radargrams. It comprises preprocessing, hyperbola enhancing, hyperbola detection and localization, and parameter extraction. Additional parameters related to the GPR system such as the frequency band and the polarization bring data sets additional information that need to be exploited. Presently, the algorithms have been applied step by step on synthetic and experimental data. The results help to guide future developments in signal processing for quantitative parameter estimation.

6

Stochastic risk and reliability assessments of energy management system in grid of microgrids under uncertainty

Nikmehr N., Najafi-Ravadanegh S.

Journal of Power Technologies

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2017

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Vol. 97, nr 3

179--189

EN

As various renewable energy resources (RERs) are exploited within microgrids (MGs), some important challenges have arisen as regards coping with generation fluctuations. This paper proposes a probabilistic method aimed at achieving optimal coordinated operation in a grid of microgrids under uncertainties of RERs and variable load demand. In the supposed structure based on networked microgrids (NMGs), a two-level strategy is required for guaranteeing efficient coordination between the MGs and distribution network operator (DNO). Another contribution of the paper deals with the flexibility of NMGs in improving the reliability of the whole system. Additionally, the value at risk (VaR) calculations for output results are carried out for different confidence levels with two important methods. In sum, the aim of the paper is to minimize total energy costs considering the environmental effects. To achieve this purpose, the Imperialist Competitive Algorithm (ICA) as a heuristic algorithm is applied to solve the optimal power dispatch problem and the obtained results are compared using the Monte Carlo Simulation (MCS) method. As the input data are modeled under uncertainties, the output results are described with probability distribution function (PDF).

7

Definition of Mass Spring Parameters for Knitted Fabric Simulation Using the Imperialist Competitive Algorithm

Mozafary V., Payvandy P.

Fibres & Textiles in Eastern Europe

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2017

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Vol. 25, no. 1 (121)

65--74

EN

The 3D simulation of fabrics is an interesting issue in many fields, such as computer engineering, textile engineering, cloth design and so on. Several methods have been presented for fabric simulation. The mass spring model, a typical physically-based method, is one of the methods for fabric simulation which is widely considered by researchers due to rapid simulation and being more consistent with reality. The aim of this paper is the optimization of mass spring parameters in the simulation of the drape behaviour of knitted fabric using the Imperialist Competitive Algorithm. First a mass spring model is proposed to simulate the drape behavior of knitted fabric. Then in order to reduce the error value between the simulated and actual result (reducing the simulation error value), parameters of the mass spring model such as the stiffness coefficient, damping coefficient, elongation rate, topology and natural length of the spring are optimized using the Imperialist Competitive Algorithm (ICA). The ICA parameters are specified using the Taguchi Design of Experiment. Finally fabrics drape shapes are simulated in other situations and compared with their actual results to validate the model parameters. Results show that the optimized model is able to predict the drape behavior of knitted fabric with an error value of 2.4 percent.

PL

Celem niniejszej pracy jest optymalizacja parametrów masowo-sprężystych w symulacji układalności struktur dzianych przy wykorzystaniu imperialistycznego algorytmu konkurencji. Zaproponowano model mas i sprężyn symulujących zachowanie dzianin. Następnie, dla polepszenia korelacji pomiędzy strukturami teoretycznymi a rzeczywistymi, określone parametry modelu, takie jak: współczynnik sztywności, współczynnik tłumienia, wydłużenie, topologia i naturalna długości sprężyny zoptymalizowano posługując się imperialistycznym algorytmem konkurencji (ICA). Parametry określono przy użyciu planowania eksperymentu metodą Taguchi. Przedstawiono i porównano symulacje układalności z rzeczywistą układalnością dzianin. Stwierdzono, że opracowany model pozwala na przewidywanie układalności dzianin z dokładnością do 2,4%.

8

Volcanic ash cloud detection from MODIS image based on CPIWS method

Liu L., Li Ch., Lei Y., Yin J., Zhao J.

Acta Geophysica

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2017

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Vol. 65, no. 1

151--163

EN

Volcanic ash cloud detection has been a difficult problem in moderate-resolution imaging spectroradiometer (MODIS) multispectral remote sensing application. Principal component analysis (PCA) and independent component analysis (ICA) are effective feature extraction methods based on second-order and higher order statistical analysis, and the support vector machine (SVM) can realize the nonlinear classification in low-dimensional space. Based on the characteristics of MODIS multispectral remote sensing image, via presenting a new volcanic ash cloud detection method, named combined PCA-ICA-weighted and SVM (CPIWS), the current study tested the real volcanic ash cloud detection cases, i.e., Sangeang Api volcanic ash cloud of 30 May 2014. Our experiments suggest that the overall accuracy and Kappa coefficient of the proposed CPIWS method reach 87.20 and 0.7958%, respectively, under certain conditions with the suitable weighted values; this has certain feasibility and practical significance.

9

Modelowanie oporu skrzyżowań w modelach makroskopowych

Kucharski R., Drabicki A., Szarata A.

Transport Miejski i Regionalny

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2016

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nr 8

14--19

PL

Artykuł prezentuje metodę obliczania oporu relacji skrętnych na skrzyżowaniach dla makroskopowych miejskich modeli ruchu. Pokazano, jak na podstawie dostępnej bazy danych o warszawskiej sieci drogowej można zbudować model sieciowy wraz z określeniem przepustowości i czasów traconych na relacjach skrętnych. Wykorzystano w nim podstawowe formuły inżynierii ruchu (Gaca i in., 2008) pozwalające obliczyć przepustowość (poprzez oszacowanie natężenia nasycenia, udziału efektywnego sygnału zielonego, potoku nadrzędnego) oraz czasy przejazdu (swobodny oraz tracony) dla skrzyżowań sygnalizowanych, niesygnalizowanych i rond. Proponowana metoda jest uogólnieniem dostosowanym do dostępnej bazy danych i potrzeb makroskopowego modelu ruchu dużego obszaru (np. Aglomeracja Warszawska). Nie uwzględnia wszystkich czynników wpływających na przepustowość, jednak pozwala zbudować model sieciowy, w którym, tak jak w rzeczywistości, o czasie przejazdu i powstawaniu kolejek decyduje ograniczona przepustowość skrzyżowań, a nie odcinków. Metoda może być zastosowana w budowie modelu sieciowego dla dużego miasta przy użyciu dostępnej bazy danych bez znacznego zwiększenia czasów obliczeń. Wyniki metody ilustrują przykłady dla wybranych skrzyżowań w Warszawie.

EN

In the article we propose method to model a junction impedance in the static macroscopic traffic network graphs. The available network database is used to parameterize the Warsaw road’ network. We use the generic data for the urban network: link types, node types, turn types and traffic signs. Thanks to this we are able to apply fundamental Intersection Capacity Analysis formulas (Gaca, et al. 2008) and compute the capacities and travel times for the turns in the network of Warsaw. The methods are proposed both for signalized, uncontrolled intersections and roundabouts. We propose heuristics for effective green, saturation flow, main flow and number of lanes, which can be practically applied in the urban macroscopic models. We apply and parameterize the Akcelik (1981) delay formulas to calculate the total travel time in the congested network. The paper is illustrated with both signalized and uncontrolled junctions in Warsaw. The results are plausible and the model can be further tested in practical applications.

10

EEG of game players - detecting involvement with and without ICA preprocessing

Górski P., Rejer I.

Przegląd Elektrotechniczny

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2016

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R. 92, nr 12

237--240

EN

The aim of this paper is to analyze the differences in the classification accuracy obtained with raw EEG data and with data preprocessed with Independent Components Analysis (ICA). Our main research question is whether ICA is able to improve the classification accuracy not only in the case of a multichannel recording but also when EEG data are recorded only from a few channels. In order to answer this question we performed an experiment with 6 game players and gathered EEG data during Dota 2 game session. We analyzed the EEG data separately for 19, 7, and 3 channels with and without ICA preprocessing. With all three number of channels and for each of the six players we obtained more precise classifiers, classifying the seconds of the game as involving or boring, after applying ICA (mean accuracy averaged over subjects: 19 channels - 0.87 (raw signals), 0.91 (after ICA); 7 channels - 0.8 (raw signals), 0.85 (after ICA); 3 channels - 0.75 (raw signals), 0.8 (after ICA)).

PL

Celem artykułu jest analiza różnic w dokładności klasyfikacji otrzymanej przy wykorzystaniu surowego sygnału EEG oraz sygnału poddanego preprocessingowi z wykorzystaniem analizy składowych niezależnych (ICA). Naszym głównym pytaniem badawczym jest to, czy ICA jest w stanie zwiększyć dokładność klasyfikacji nie tylko w przypadku wielokanałowego EEG, ale również wtedy, kiedy dane EEG są nagrywane tylko z kilku kanałów. W celu udzielenia odpowiedzi na to pytanie przeprowadziliśmy eksperyment z sześcioma graczami i zgromadziliśmy dane EEG podczas gry w grę Dota 2. Przeanalizowaliśmy dane oddzielnie dla 19, 7 i 3 kanałów z oraz bez zastosowania algorytmu ICA. Dla wszystkich trzech liczb kanałów i dla każdego z sześciu graczy otrzymaliśmy bardziej dokładne klasyfikatory, dokonujące klasyfikacji poszczególnych sekund gry jako angażujących i nudnych, po przeprowadzeniu preprocessingu z wykorzystaniem ICA (średnia dokładność dla wszystkich podmiotów: 19 kanałów - 0.87 (surowe sygnały), 0.91 (po ICA); 7 kanałów - 0.8 (surowe sygnały), 0.85 (po ICA); 3 kanały - 0.75 (surowe sygnały), 0.8 (po ICA)).

11

A framework for optimal clustering of a greenfield distribution network area into multiple autonomous microgrids

Mojtahedzadeh S., Najafi Ravadanegh S., Haghifan M. R.

Journal of Power Technologies

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2016

|

Vol. 96, nr 4

219--228

EN

Microgrids (MGs) are recognized as cores and clusters of smart distribution networks. The optimal planning and clustering of smart low-voltage distribution networks into autonomous MGs within a greenfield area is modeled and discussed in this paper. In order to form and determine the electrical boundary of MGs set, some predefined criteria such as power mismatch, supply security and load density are defined. The network includes an external grid as backup and both dispatchable and non-dispatchable Distributed Energy Resources (DERs) as MGs resources. The proposed strategy offers optimum sizing and siting of DERs and MV substations for the autonomous operation of multiple MGs simultaneously. The imperialist competitive algorithm (ICA) is used to optimize the cost function to determine the optimal linked MG clustering boundary. To evaluate the algorithm the proposed method is applied to a greenfield area which is planned to become a mixed residential and commercial town. The MGs’ optimal border, DERs location, size and type within each MG and LV feeders route are illustrated in both graphical and tabular form.

12

Independent component analysis of EEG data for EGI system

Gajos A., Wójcik G. M.

Bio-Algorithms and Med-Systems

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2016

|

Vol. 12, no. 2

67--72

EN

Component analysis is one of the most important methods used for electroencephalographic (EEG) signal decomposition, and the so-called independent component analysis (ICA) is commonly used. The main function of the ICA algorithm is to find a linear representation of non-Gaussian data whose elements are statistically independent or at least as independent as possible. There are many commercial solutions for EEG signal acquisition. Usually, together with the EEG, one gets a dedicated software to handle the signal. However, quite often, the software does not provide researchers with all necessary functions. A high-performance, dense-array EGI-EEG system is distributed with the NetStation software. Although NetStation is a powerful tool, it does not have any implementation of the ICA algorithm. This causes many problems for researchers who want to export raw data from the amplifier and then work on it using some other tools such as EEGLAB for MATLAB, as these data are not fully compatible with the EGI format. We will present the C++ implementation of ICA that can handle filtered data from the EGI with better affordability. Our tool offers visualization of raw signal and ICA algorithm results and will be distributed under Freeware license.

13

Inverse method for a one-stage spur gear diagnosis

Akrout A., Tounsi D., Taktak M., Abbes M. S., Haddar M.

Journal of Theoretical and Applied Mechanics

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2015

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Vol. 53 nr 3

617--628

EN

In this paper, a source separation approach based on the Blind Source Separation (BSS) is presented. In fact, the Independent Component Analysis (ICA), which is the main technique of BSS, consists in extracting different source signals from several observed mixtures. This inverse method is very useful in many fields such as telecommunication, signal processing and biomedicine. It is also very attractive for diagnosis of mechanical systems such as rotating machines. Generally, dynamic responses of a given mechanical system (displacements, accelerations and speeds) measured through sensors are used as inputs for the identification of internal defaults. In this study, the ICA concept is applied to the diagnosis of a one-stage gear mechanism in which two types of defects (the eccentricity error and the localized tooth defect)are introduced. The finite element method allows determination of the signals corresponding to the acceleration in some locations of the system, and those signals may be used also in the ICA algorithm. Hence, the vibratory signatures of each defect can be identified by the ICA concept. Thus, a good agreement is obtained by comparing the expected default signatures to those achieved by the developed inverse method.

14

Feature vector or time-series – comparison of gestures representations in automatic gesture recognition systems

Barczewska K., Wójtowicz W., Moszkowski T.

Challenges of Modern Technology

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2015

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Vol. 6, no. 1

1--5

EN

In this paper, we performed recognition of isolated sign language gestures - obtained from Australian Sign Language Database (AUSLAN) – using statistics to reduce dimensionality and neural networks to recognize patterns. We designated a set of 70 signal features to represent each gesture as a feature vector instead of a time series, used principal component analysis (PCA) and independent component analysis (ICA) to reduce dimensionality and indicate the features most relevant for gesture detection. To classify the vectors a feedforward neural network was used. The resulting accuracy of detection ranged between 61 to 87%.

15

Vibro-acoustic analysis of laminated double glazing using the force identification method

Ben Jdidia M, Akrout A, Tounsi D, Fakhfakh T., Haddar M.

Journal of Theoretical and Applied Mechanics

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2014

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Vol. 52 nr 4

895--904

EN

This paper presents a procedure for identifying wave forms and excitation frequencies of some forces applied on a given complex fluid-structure coupled system by using only its vibro-acoustic response. The considered concept is called the Independent Component Analysis (ICA) which is based on the Blind Source Separation (BSS). In this work, the ICA method is exploited in order to determine the excitation force applied to a thin-film laminated double glazing system enclosing a thin fluid cavity and limited by an elastic joint. The dynamic response of the studied fluid-structure coupled system is determined by finite element discretization and minimization of the homogenized energy functional of the coupled problem. This response will serve as the input for the ICA algorithm in order to extract the applied excitation.

16

Noise identification for ICA ensemble predictors

Szupiluk R., Ząbkowski T.

Przegląd Elektrotechniczny

|

2013

|

R. 89, nr 6

307--309

EN

In this paper we present a novel method for integration the prediction results by finding common latent components via independent component analysis. The latent components can have constructive or destructive influence on particular prediction results. After the elimination of the deconstructive signals we rebuilt the improved predictions. We check the method validity on the electricity load prediction task.

PL

W artykule przedstawiono nową metodę pozwalającą na łączenie wyników predykcji poprzez poszukiwanie ukrytych wspólnych składowych przy zastosowaniu procedury analizy składowych niezależnych. Składowe ukryte mogą mieć pozytywny lub negatywny wpływ na wyniki predykcji. Po wyeliminowaniu składowych niekorzystnych poprawione zostały wyniki predykcji. Poprawność metody sprawdzono na przykładzie predykcji zapotrzebowania na energię elektryczną.

17

Direct assessment of the fetal heart rate from abdominal composite recordings

Moslem B., Bazzi O., Khalaf J., Diab M.O.

Journal of Medical Informatics & Technologies

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2013

|

Vol. 22

143--149

EN

In respect to the main goal of our ongoing work for analyzing fetal electrocardiogram (FECG) signals for monitoring the health of the fetus, we investigate in this paper the possibility of extracting the fetal heart rate (FHR) directly from the abdominal composite recordings. Our proposed approach is based on a combination of Independent Component Analysis (ICA) and least mean square (LMS) adaptive filter. The FHR of the estimated FECG signal is finally compared to a reference value extracted from a FECG signal recorded by using a spiral electrode attached directly to the fetal scalp. The experimental results show that FHR can be successfully evaluated directly from the abdominal composite recordings without the need of using any external reference signal.

18

Rozpoznawanie twarzy: PCA czy ICA

Miziołek W., Sawicki D.

Przegląd Elektrotechniczny

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2012

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R. 88, nr 7a

286-288

PL

Praca jest opisem badań nad zastosowaniem metod ICA i PCA w rozpoznawaniu twarzy. Przeprowadzono szereg eksperymentów wykorzystując najczęściej stosowaną bazę obrazów twarzy FERET. Autorzy próbują analizować niezależnie wpływ różnych czynników na efektywność pracy metod ICA i PCA. Mimo że w obu metodach twarz jest analizowana holistycznie to jednak każdy z czynników inaczej wpływa na efektywność poszczególnych metod. Pokazuje to niezależną przydatność metod w różnych zadaniach testowych.

EN

The research on applying ICA and PCA methods in face recognition is described. Several experiments were conducted using FERET, the most often applied base of face images. Authors are trying to analyze the influence of different factors independently on the efficiency of the work of ICA and PCA. In both methods the face is being analyzed in holistic way; however each of factors influences differently the efficiency of individual methods. It shows the independent usefulness of methods to different recognition task.

19

Design Optimization of a Single-Phase Axial Flux Induction Motor with Low Torque Ripple

Nasiri-Gheidari Z., Lesani H.

Przegląd Elektrotechniczny

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2012

|

R. 88, nr 3b

168-172

EN

Beside distinct advantages of single phase axial flux induction motors, they suffer from high torque ripple. In this paper a new detailed model of motor considering saturation, anisotropy and harmonics is developed. Then design optimization is done regarding low torque ripple using a new evolutionary algorithm which is called imperialist competitive algorithm. Not only geometrical dimensions, but also the temperature of different parts of motor is considered as constrains. Optimization results have been validated using three dimensional time-stepping finite element methods.

PL

W artykule analizowano tętnienia momentu napędowego w silniku indukcyjnym osiowym, jednofazowym. Wzięto pod uwagę indukcję nasycenia, anizotropię i obecność harmonicznych. Analizowano wymiary silnika oraz rozkład temperatury.

20

Dostrajanie regulatora z pominięciem eksperymentu identyfikacji obiektu przy użyciu Imperialist Competitive Algorithm

Awtoniuk M.

Elektronika : konstrukcje, technologie, zastosowania

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2012

|

Vol. 53, nr 12

46-49

PL

Celem pracy jest przybliżenie sposobu dostrajania nastaw regulatora PI, który pozwala na pominięcie eksperymentu identyfikacji. Wykorzystanie tej metody pozwala na znalezienie optymalnych nastaw wykorzystując tylko dane zebrane z pracy zamkniętej pętli regulacji. Początkowo praca regulatora odbywała się z parametrami otrzymanymi w wyniku działania funkcji autotuningu. Wykonano szereg eksperymentów symulujących różne aspekty pracy układu regulacji, a następnie wykorzystano zebrane dane do ponownego sparametryzowania układu. Za pomocą wskaźników całkowych oceniono jakość regulacji przed i po zastosowaniu opisanej metody. Do dostrojenia regulatora wykorzystano algorytm ewolucyjny.

EN

The paper presents a method of retuning PI regulator which allows to omit object identification experiment. This method allows to find optimum regulator settings by use only data collected from working closed loop. The goal of this paper is to compare the effectiveness of control quality given by automatic tuning procedure with effects of retuning by means of Imperialist Competitive Algorithm.