Search results for: Electro Myo Graphic (EMG) signals

Authors: Oliver Commichau, Richard Krimm, Bernd-Arno Behrens

Abstract:

A growing demand on the production rate of modern presses leads to higher stroke rates. Commonly used material feeding devices for presses like grippers and roll-feeding systems can only achieve high stroke rates along with high gripper forces, to avoid stick-slip. These forces are limited by the sensibility of the surfaces of the workpieces. Stick-slip leads to scratches on the surface and false positioning of the workpiece. In this paper, a new contactless feeding device is presented, which develops higher feeding force without damaging the surface of the workpiece through gripping forces. It is based on the principle of the linear induction motor. A primary part creates a magnetic field and induces eddy currents in the electrically conductive material. A Lorentz-Force applies to the workpiece in feeding direction as a mutual reaction between the eddy-currents and the magnetic induction. In this study, the FEA model of this approach is shown. The calculation of this model was used to identify the influence of various design parameters on the performance of the feeder and thus showing the promising capabilities and limits of this technology. In order to validate the study, a prototype of the feeding device has been built. An experimental setup was used to measure pulling forces and placement accuracy of the experimental feeder in order to give an outlook of a potential industrial application of this approach.

Keywords: conductive material, contactless feeding, linear induction, Lorentz-Force

Procedia PDF Downloads 179

Authors: Maryam Abata, Moulhime El Bekkali, Said Mazer, Catherine Algani, Mahmoud Mehdi

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One major problem of most electronic systems operating in the millimeter wave band is the signal generation with a high purity and a stable carrier frequency. This problem is overcome by using the combination of a signal with a low frequency local oscillator (LO) and several stages of frequency multipliers. The use of these frequency multipliers to create millimeter-wave signals is an attractive alternative to direct generation signal. Therefore, the isolation problem of the local oscillator from the other stages is always present, which leads to have various mechanisms that can disturb the oscillator performance, thus a buffer amplifier is often included in oscillator outputs. In this paper, we present the study and design of a buffer amplifier in the mm-wave band using a 0.15μm pHEMT from UMS foundry. This amplifier will be used as a part of a frequency quadrupler at 60 GHz.

Keywords: Mm-wave band, local oscillator, frequency quadrupler, buffer amplifier

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Authors: Florin Leon, Silvia Curteanu

Abstract:

The Bacterial Foraging Optimization (BFO) algorithm is inspired by the behavior of bacteria such as Escherichia coli or Myxococcus xanthus when searching for food, more precisely the chemotaxis behavior. Bacteria perceive chemical gradients in the environment, such as nutrients, and also other individual bacteria, and move toward or in the opposite direction to those signals. The application example considered as a case study consists in establishing the dependency between the reaction yield of hydrogels based on polyacrylamide and the working conditions such as time, temperature, monomer, initiator, crosslinking agent and inclusion polymer concentrations, as well as type of the polymer added. This process is modeled with a neural network which is included in an optimization procedure based on BFO. An experimental study of BFO parameters is performed. The results show that the algorithm is quite robust and can obtain good results for diverse combinations of parameter values.

Keywords: bacterial foraging, hydrogels, modeling and optimization, neural networks

Procedia PDF Downloads 152

Authors: Hossein Ramezani Ali-Akbari

Abstract:

This paper presents an innovative method to control the rotational speed of a satellite solar panel during its deployment phase. A brushed DC motor has been utilized in the passive spring driven deployment mechanism to reduce the deployment speed. In order to use the DC motor as a damper, its connector terminals have been connected with an external resistance in a closed circuit. It means that, in this approach, there is no external power supply in the circuit. The working principle of this method is based on the back electromotive force (or back EMF) of the DC motor when an external torque (here the torque produced by the torsional springs) is coupled to the DC motor’s shaft. In fact, the DC motor converts to an electric generator and the current flows into the circuit and then produces the back EMF. Based on Lenz’s law, the generated current produced a torque which acts opposite to the applied external torque, and as a result, the deployment speed of the solar panel decreases. The main advantage of this method is to set an intended damping coefficient to the system via changing the external resistance. To produce the sufficient current, a gearbox has been assembled to the DC motor which magnifies the number of turns experienced by the DC motor. The coupled electro-mechanical equations of the system have been derived and solved, then, the obtained results have been presented. A full-scale prototype of the deployment mechanism has been built and tested. The potential application of brushed DC motors as a rotational speed damper has been successfully demonstrated.

Keywords: back electromotive force, brushed DC motor, rotational speed damper, satellite solar panel deployment mechanism

Procedia PDF Downloads 325

Authors: Mohamed. A. Saad

Abstract:

The paper represents a case study regarding the conversion of Electro-Static Precipitators (ESP`s) into Fabric Filters (FF). Seven cement production companies were established in Egypt during the period 1927 to 1980 and 6 new companies were established to cope with the increasing cement demand in 1980's. The cement production market shares in Egypt indicate that there are six multinational companies in the local market, they are interested in the environmental conditions improving and so decided to achieve emission reduction project. The experimental work in the present study is divided into two main parts: (I) Measuring Efficiency of Filter Fabrics with detailed description of a designed apparatus. The paper also reveals the factors that should be optimized in order to assist problem diagnosis, solving and increasing the life of bag filters. (II) Methods to mitigate dust emissions in Egyptian cement plants with a special focus on converting the Electrostatic Precipitators (ESP`s) into Fabric Filters (FF) using the same ESP casing, bottom hoppers, dust transportation system, and ESP ductwork. Only the fan system for the higher pressure drop with the fabric filter was replaced. The proper selection of bag material was a prime factor with regard to gas composition, temperature and particle size. Fiberglass with PTFE membrane coated bags was selected. This fabric is rated for a continuous temperature of 250 C and a surge temperature of 280C. The dust emission recorded was less than 20 mg/m3 from the production line fitted with fabric filters which is super compared with the ESP`s working lines stack.

Keywords: Engineering Electrostatic Precipitator, filtration, dust collectors, cement

Procedia PDF Downloads 253

Authors: Radhamanohar Aepuru, R. V. Mangalaraja

Abstract:

Flexible electronic devices have drawn potential interest and provide significant new insights to develop energy conversion and storage devices such as photodetectors and nanogenerators. Recently, self-powered electronic systems have captivated huge attention for next generation MEMS/NEMS devices that can operate independently by generating built-in field without any need of external bias voltage and have wide variety of applications in telecommunication, imaging, environmental and defence sectors. The basic physical process involved in these devices are charge generation, separation, and charge flow across the electrodes. Many inorganic nanostructures have been exploring to fabricate various optoelectronic and electromechanical devices. However, the interaction of nanostructures and their excited charge carrier dynamics, photoinduced charge separation, and fast carrier mobility are yet to be studied. The proposed research is to address one such area and to realize the self-powered electronic devices. In the present work, nanocomposites of inorganic nanostructures based on ZnO, metal halide perovskites; and polyvinylidene fluoride (PVDF) based nanocomposites are realized for photodetectors and nanogenerators. The characterization of the inorganic nanostructures is carried out through steady state optical absorption and luminescence spectroscopies as well as X-ray diffraction and high-resolution transmission electron microscopy (TEM) studies. The detailed carrier dynamics is investigated using various spectroscopic techniques. The developed composite nanostructures exhibit significant optical and electrical properties, which have wide potential applications in various MEMS/NEMS devices such as photodetectors and nanogenerators.

Keywords: dielectrics, nanocomposites, nanogenerators, photodetectors

Procedia PDF Downloads 129

Authors: Saeedeh Hajihosseini, Zahra Aghili, Navid Nasirizadeh

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An innovative method of a DNA electrochemical biosensor based on Oracet Blue (OB) as an electroactive label and gold electrode (AuE) for detection of Helicobacter pylori, was offered. A single–stranded DNA probe with a thiol modification was covalently immobilized on the surface of the AuE by forming an Au–S bond. Differential pulse voltammetry (DPV) was used to monitor DNA hybridization by measuring the electrochemical signals of reduction of the OB binding to double– stranded DNA (ds–DNA). Our results showed that OB–based DNA biosensor has a decent potential for detection of single–base mismatch in target DNA. Selectivity of the proposed DNA biosensor was further confirmed in the presence of non–complementary and complementary DNA strands. Under optimum conditions, the electrochemical signal had a linear relationship with the concentration of the target DNA ranging from 0.3 nmol L-1 to 240.0 nmol L-1, and the detection limit was 0.17 nmol L-1, whit a promising reproducibility and repeatability.

Keywords: DNA biosensor, oracet blue, Helicobacter pylori, electrode (AuE)

Procedia PDF Downloads 266

Authors: Olesya Bolkhovskaya, Alexey Davydov, Alexander Maltsev

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In this paper two approaches to joint signal detection, time of arrival (ToA) and angle of arrival (AoA) estimation in multi-element antenna array are investigated. Two scenarios were considered: first one, when the waveform of the useful signal is known a priori and, second one, when the waveform of the desired signal is unknown. For first scenario, the antenna array signal processing based on multi-element matched filtering (MF) with the following non-coherent detection scheme and maximum likelihood (ML) parameter estimation blocks is exploited. For second scenario, the signal processing based on the antenna array elements covariance matrix estimation with the following eigenvector analysis and ML parameter estimation blocks is applied. The performance characteristics of both signal processing schemes are thoroughly investigated and compared for different useful signals and noise parameters.

Keywords: antenna array, signal detection, ToA, AoA estimation

Procedia PDF Downloads 496

Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

Procedia PDF Downloads 262

Authors: K. N. Umesh, K. S. Srinivasan

Abstract:

The influence of rotor rub was studied with respect to light rub and heavy rub conditions. The investigations were carried out for both below and above critical speeds. The time domain waveform has revealed truncation of the waveform during rubbing conditions. The quantum of rubbing has been indicated by the quantum of truncation. The orbits for light rub have indicated a single loop whereas for heavy rub multi looped orbits have been observed. In the heavy rub condition above critical speed both sub harmonics and super harmonics are exhibited. The orbit precess in a direction opposite to the direction of the rotation of the rotor. When the rubbing was created above the critical speed the orbit shape was of '8' shape indicating the rotor instability. Super-harmonics and sub-harmonics of vibration signals have been observed for light rub and heavy rub conditions and for speeds above critical.

Keywords: rotor rub, orbital analysis, frequency analysis, vibration signatures

Procedia PDF Downloads 313

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 42

Authors: Goodarz Sabetian, Sajjad Moshfe

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Control system for hi-tech industries could be realized generally and deeply by a special document. Vast heavy industries such as power plants with a large number of I/O signals are controlled by a distributed control system (DCS). This system comprises of so many parts from field level to high control level, and junior instrument engineers may be confused by this enormous information. The key document which can solve this problem is “control configuration system diagram” for each type of DCS. This is a road map that covers all of activities respect to control system in each industrial plant and inevitable to be studied by whom corresponded. It plays an important role from designing control system start point until the end; deliver the system to operate. This should be inserted in bid documents, contracts, purchasing specification and used in different periods of project EPC (engineering, procurement, and construction). Separate parts of DCS are categorized here in order of importance and a brief description and some practical plan is offered. This article could be useful for all instrument and control engineers who worked is EPC projects.

Keywords: control, configuration, DCS, power plant, bus

Procedia PDF Downloads 491

Authors: Zeki Oralhan, Mahmut Tokmakçı

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SSVEP based brain computer interface (BCI) systems have been preferred, because of high information transfer rate (ITR) and practical use. ITR is the parameter of BCI overall performance. For high ITR value, one of specification BCI system is that has high accuracy. In this study, we investigated to recognize SSVEP with shorter time and lower error rate. In the experiment, there were 8 flickers on light crystal display (LCD). Participants gazed to flicker which had 12 Hz frequency and 50% duty cycle ratio on the LCD during 10 seconds. During the experiment, EEG signals were acquired via EEG device. The EEG data was filtered in preprocessing session. After that Canonical Correlation Analysis (CCA), Multiset CCA (MsetCCA), phase constrained CCA (PCCA), and Multiway CCA (MwayCCA) methods were applied on data. The highest average accuracy value was reached when MsetCCA was applied.

Keywords: brain computer interface, canonical correlation analysis, human computer interaction, SSVEP

Procedia PDF Downloads 266

Authors: Mahdiar Hosseighadiry, Farnaz Fotovatikhah, Razali Ismail, Mohsen Khaledian, Mehdi Saeidemanesh

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In this paper, a new low-power high-performance full adder is presented based on a new design method. The proposed method relies on pass gate design and provides full-swing circuits with minimum number of transistors. The method has been applied on SUM, COUT and XOR-XNOR modules resulting on rail-to-rail intermediate and output signals with no feedback transistors. The presented full adder cell has been simulated in 45 and 32 nm CMOS technologies using HSPICE considering parasitic capacitance and compared to several well-known designs from literature. In addition, the proposed cell has been extensively evaluated with different output loads, supply voltages, temperatures, threshold voltages, and operating frequencies. Results show that it functions properly under all mentioned conditions and exhibits less PDP compared to other design styles.

Keywords: full adders, low-power, high-performance, VLSI design

Procedia PDF Downloads 388

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 47

Authors: Byung Cheol Kim

Abstract:

This study explores a method for the signal-noise separation challenge in project control, focusing on the limitations of traditional deterministic approaches that use single-point performance metrics to predict project outcomes. We detail how traditional methods often overlook future uncertainties, resulting in tracking biases when reliance is placed solely on immediate data without adjustments for predictive accuracy. Our investigation led to the development of the Predictive Tracking Project Control (PTPC) framework, which incorporates network simulation and Bayesian control models to adapt more effectively to project dynamics. The PTPC introduces controlled disturbances to better identify and separate tracking biases from useful predictive signals. We will demonstrate the efficacy of the PTPC with examples, highlighting its potential to enhance real-time project monitoring and decision-making, marking a significant shift towards more accurate project management practices.

Keywords: predictive tracking, project control, signal-noise separation, Bayesian inference

Procedia PDF Downloads 18

Authors: Anésio de Leles Ferreira Filho, Wesley Rodrigues de Oliveira, Jéssica Santoro Gonçalves, Jorge Andrés Cormane Angarita

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The increase in electric power demand in face of environmental issues has intensified the participation of renewable energy sources such as photovoltaics, in the energy matrix of various countries. Due to their operational characteristics, they can generate time-varying harmonic and inter-harmonic distortions. For this reason, the application of methods of measurement based on traditional Fourier analysis, as proposed by IEC 61000-4-7, can provide inaccurate results. Considering the aspects mentioned herein, came the idea of the development of this work which aims to present the results of a comparative evaluation between a methodology arising from the combination of the Prony method with the Kalman filter and another method based on the IEC 61000-4-30 and IEC 61000-4-7 standards. Employed in this study were synthetic signals and data acquired through measurements in a 50kWp photovoltaic installation.

Keywords: harmonics, inter-harmonics, iec61000-4-7, parametric estimators, photovoltaic generation

Procedia PDF Downloads 487

Authors: Gamal Shiha, Waleed Samir, Zahid Azam, Premashis Kar, Saeed Hamid, Shiv Sarin

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A simple, rapid and non-invasive electromagnetic sensor (C-FAST device) was- patented; for diagnosis of HCV RNA. Aim: To test the validity of the device compared to standard HCV PCR. Subjects and Methods: The first phase was done as pilot in Egypt on 79 participants; the second phase was done in five centers: one center from Egypt, two centers from Pakistan and two centers from India (800, 92 and 113 subjects respectively). The third phase was done nationally as multicenter study on (1600) participants for ensuring its representativeness. Results: When compared to PCR technique, C-FAST device revealed sensitivity 95% to 100%, specificity 95.5% to 100%, PPV 89.5% to 100%, NPV 95% to 100% and positive likelihood ratios 21.8% to 38.5%. Conclusion: It is practical evidence that HCV nucleotides emit electromagnetic signals that can be used for its identification. As compared to PCR, C-FAST is an accurate, valid and non-invasive device.

Keywords: C-FAST- a valid and reliable device, distant cellular interaction, electromagnetic signal detection, non-invasive diagnosis of HCV

Procedia PDF Downloads 432

Authors: Bhaveek Maini, Sanjay Dhanka, Surita Maini

Abstract:

Electroencephalography (EEG) is used to classify several epileptic seizures worldwide. It is a very crucial task for the neurologist to identify the epileptic seizure with manual EEG analysis, as it takes lots of effort and time. Human error is always at high risk in EEG, as acquiring signals needs manual intervention. Disease diagnosis using machine learning (ML) has continuously been explored since its inception. Moreover, where a large number of datasets have to be analyzed, ML is acting as a boon for doctors. In this research paper, authors proposed two different ML models, i.e., logistic regression (LR) and Naïve Bayes (NB), to predict epileptic seizures based on general parameters. These two techniques are applied to the epileptic seizures recognition dataset, available on the UCI ML repository. The algorithms are implemented on an 80:20 train test ratio (80% for training and 20% for testing), and the performance of the model was validated by 10-fold cross-validation. The proposed study has claimed accuracy of 81.87% and 95.49% for LR and NB, respectively.

Keywords: epileptic seizure recognition, logistic regression, Naïve Bayes, machine learning

Procedia PDF Downloads 61

Authors: Sudhina H. K, Ravi M. Yadahalli, N. M. Shetti

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Reconfigurable antennas represent a recent innovation in antenna design that changes from classical fixed-form, Fixed function antennas to modifiable structures that can be adapted to fit the requirements of a time varying system. The ability to control the operating band of an antenna system can have many useful applications. Systems that operate in an acquire-and-track configuration would see a benefit from active bandwidth control. In such systems a wide band search mode is first employed to find a desired signal, Then a narrow band track mode is used to follow only that signal. Utilizing active antenna bandwidth control, A single antenna would function for both the wide band and narrow band configurations providing the rejection of unwanted signals with the antenna hardware. This ability to move a portion of the RF filtering out of the receiver and onto the antenna itself will also aid in reducing the complexity of the often expensive RF processing subsystems.

Keywords: designing methods, mems, stack, reconfigurable elements

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Authors: L. Lakhdari, B. Bouchiba, M. Bechar

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The multi-level inverters present an important novelty in the field of energy control with high voltage and power. The major advantage of all multi-level inverters is the improvement and spectral quality of its generated output signals. In recent years, various pulse width modulation techniques have been developed. From these technics we have: Sinusoidal Pulse Width Modulation (SPWM) and Space Vector Pulse Width Modulation (SVPWM). This work presents a detailed analysis of the comparative advantage of space vector pulse width modulation (SVPWM) and the standard SPWM technique for Three Level Diode Clamped Inverter fed Induction Motor. The comparison is based on the evaluation of harmonic distortion THD.

Keywords: induction motor, multilevel inverters, SVPWM, SPWM, THD

Procedia PDF Downloads 338

Authors: Nadia Chagtmi, Nejla Rejab, Noureddine Boulejfen

Abstract:

This paper presents a calibration approach based on artificial neural networks (ANN) to determine the envelop signal (I+jQ) of a six-port based receiver (SPR). The memory effects called also dynamic behavior and the nonlinearity brought by diode based power detector have been taken into consideration by the ANN. Experimental set-up has been performed to validate the efficiency of this method. The efficiency of this approach has been confirmed by the obtained results in terms of waveforms. Moreover, the obtained error vector magnitude (EVM) and the mean absolute error (MAE) have been calculated in order to confirm and to test the ANN’s performance to achieve I/Q recovery using the output voltage detected by the power based detector. The baseband signal has been recovered using ANN with EVMs no higher than 1 % and an MAE no higher than 17, 26 for the SPR excited different type of signals such QAM (quadrature amplitude modulation) and LTE (Long Term Evolution).

Keywords: six-port based receiver; calibration, nonlinearity, memory effect, artificial neural network

Procedia PDF Downloads 76

Authors: Javad Yarmahmoudi, Alireza Mirzaee

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Many active and passive structural health monitoring (SHM) techniques have been developed for detection of the defects of plates. Generally, riveted joints hold the plates together and their failure may create accidents. In this study, well known active and passive methods were modified for the evaluation of the health of the riveted joints between the plates. The active method generated Lamb waves and monitored their propagation by using lead zirconate titanate (PZT) disks. The signal was analyzed by using the wavelet transformations. The passive method used the Fiber Bragg Grating (FBG) sensors and evaluated the spectral characteristics of the signals by using Fast Fourier Transformation (FFT). The results indicated that the existing methods designed for the evaluation of the health of individual plates may be used for inspection of riveted joints with software modifications.

Keywords: structural health monitoring, SHM, active SHM, passive SHM, fiber bragg grating sensor, lead zirconate titanate, PZT

Procedia PDF Downloads 327

Authors: Kamel Laidi, Khelifa Benmansour, Ouahid Bouchhida

Abstract:

Neural networks-based approach for 2-cells serial converter has been developed and implemented. The approach is based on a behavioural description of the different operating modes of the converter. Each operating mode represents a well-defined configuration, and for which is matched an operating zone satisfying given invariance conditions, depending on the capacitors' voltages and the load current of the converter. For each mode, a control vector whose components are the control signals to be applied to the converter switches has been associated. Therefore, the problem is reduced to a classification task of the different operating modes of the converter. The artificial neural nets-based approach, which constitutes a powerful tool for this kind of task, has been adopted and implemented. The application to a 2-cells chopper has allowed ensuring efficient and robust control of the load current and a high capacitors voltages balancing.

Keywords: neural nets, control, multicellular converters, 2-cells chopper

Procedia PDF Downloads 834

Authors: Geetanjali Sharma

Abstract:

Guillain Barre’ syndrome (GBS) is an auto-immune mediated demyelination poly-radiculo-neuropathy. Clinical features include progressive symmetrical ascending muscle weakness of more than two limbs, areflexia with or without sensory, autonomic and brainstem abnormalities, the purpose of this study was to determine subclinical neurological changes of CNS with GBS and to establish the presence of central demyelination in GBS. The study was prospective and conducted in the Department of Physiology, Pt. B. D. Sharma Post-graduate Institute of Medical Sciences, University of Health Sciences, Rohtak, Haryana, India to find out early central demyelination in clinically diagnosed patients of GBS. These patients were referred from the department of Medicine of our Institute to our department for electro-diagnostic evaluation. The study group comprised of 40 subjects (20 clinically diagnosed GBS patients and 20 healthy individuals as controls) aged between 6-65 years. Brain Stem evoked Potential (BAEP) were done in both groups using RMS EMG EP mark II machine. BAEP parameters included the latencies of waves I to IV, inter peak latencies I-III, III-IV & I-V. Statistically significant increase in absolute peak and inter peak latencies in the GBS group as compared with control group was noted. Results of evoked potential reflect impairment of auditory pathways probably due to focal demyelination in Schwann cell derived myelin sheaths that cover the extramedullary portion of auditory nerves. Early detection of the sub-clinical abnormalities is important as timely intervention reduces morbidity.

Keywords: brainstem, demyelination, evoked potential, Guillain Barre’

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Authors: Nor Asrina Binti Ramlee

Abstract:

Voltage sag, voltage swell, high-frequency noise and voltage transients are kinds of disturbances in power quality. They are also known as power quality events. Equipment used in the industry nowadays has become more sensitive to these events with the increasing complexity of equipment. This leads to the importance of distributing clean power quality to the consumer. To provide better service, the best analysis on power quality is very vital. Thus, this paper presents the events detection focusing on voltage sag and swell. The method is developed by applying time domain signal analysis using wavelet transform approach in MATLAB. Four types of mother wavelet namely Haar, Dmey, Daubechies, and Symlet are used to detect the events. This project analyzed real interrupted signal obtained from 22 kV transmission line in Skudai, Johor Bahru, Malaysia. The signals will be decomposed through the wavelet mothers. The best mother is the one that is capable to detect the time location of the event accurately.

Keywords: power quality, voltage sag, voltage swell, wavelet transform

Procedia PDF Downloads 372

Authors: Haggag H. Mohamed, Ghatass F. Zekry, Shalaby A. Elsayed

Abstract:

Most sources of air pollution in Egypt are of anthropogenic origin. Alexandria Governorate is located at north of Egypt. The main contributing sectors of air pollution in Alexandria are industry, transportation and area source due to human activities. Alexandria includes more than 40% of the industrial activities in Egypt. Cement manufacture contributes a significant amount to the particulate pollution load. Alexandria Portland Cement Company (APCC) surrounding was selected to be the study area. APCC main kiln stack Total Suspended Particulate (TSP) continuous monitoring data was collected for assessment of dust emission control technology. Electro Static Precipitator (ESP) was fixed on the cement kiln since 2002. The collected data of TSP for first quarter of 2012 was compared to that one in first quarter of 2013 after installation of new bag house filter. In the present study, based on these monitoring data and metrological data a detailed air dispersion modeling investigation was carried out using the Industrial Source Complex Short Term model (ISC3-ST) to find out the impact of applying new bag house filter control technology on the neighborhood ambient air quality. The model results show a drastic reduction of the ambient TSP hourly average concentration from 44.94μg/m3 to 5.78μg/m3 which assures the huge positive impact on the ambient air quality by applying bag house filter technology on APCC cement kiln

Keywords: air pollution modeling, ambient air quality, baghouse filter, cement industry

Procedia PDF Downloads 269

Authors: Sergio Saponara, Luca Fanucci, Riccardo Cassettari, Ruggero Piernicola, Marco Righetto

Abstract:

The paper presents an innovative networked radar system for detection of obstacles in a railway level crossing scenario. This Monitoring System (MS) is able to detect moving or still obstacles within the railway level crossing area automatically, avoiding the need of human presence for surveillance. The MS is also connected to the National Railway Information and Signaling System to communicate in real-time the level crossing status. The architecture is compliant with the highest Safety Integrity Level (SIL4) of the CENELEC standard. The number of radar sensors used is configurable at set-up time and depends on how large the level crossing area can be. At least two sensors are expected and up four can be used for larger areas. The whole processing chain that elaborates the output sensor signals, as well as the communication interface, is fully-digital, was designed in VHDL code and implemented onto a Xilinx Virtex 6.

Keywords: radar for safe mobility, railroad crossing, railway, transport safety

Procedia PDF Downloads 480

Authors: Tine Cencič, Marko Hočevar, Brane Širok

Abstract:

An experimental investigation has been made to detect cavitation in pump–storage hydro power plant prototype suffering from cavitation in pump mode. Vibrations and acoustic emission on the housing of turbine bearing and pressure fluctuations in the draft tube were measured and the corresponding signals have been recorded and analyzed. The analysis was based on the analysis of high-frequency content of measured variables. The pump-storage hydro power plant prototype has been operated at various input loads and Thoma numbers. Several estimators of cavitation were evaluated according to coefficient of determination between Thoma number and cavitation estimators. The best results were achieved with a compound discharge coefficient cavitation estimator. Cavitation estimators were evaluated in several intervals of frequencies. Also, a prediction of cavitation erosion was made in order to choose the appropriate maintenance and repair periods.

Keywords: cavitation erosion, turbine, cavitation measurement, fluid dynamics

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Authors: M. Rezki, A. Belaidi

Abstract:

This paper deals with a method of learning to solve a real problem in biomedical engineering from a technical study of muscle fatigue. Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles (viewpoint: anatomical and physiological). EMG is used as a diagnostics tool for identifying neuromuscular diseases, assessing low-back pain and muscle fatigue in general. In order to study the EMG signal for detecting fatigue in a muscle, we have taken a real problem which touches the tramway conductor the handle bar. For the study, we have used a typical autonomous platform in order to get signals at real time. In our case study, we were confronted with complex problem to do our experiments in a tram. This type of problem is recurring among students. To teach our students the method to solve this kind of problem, we built a similar system. Through this study, we realized a lot of objectives such as making the equipment for simulation, the study of detection of muscle fatigue and especially how to manage a study of biomedical looking.

Keywords: EMG, health platform, conductor’s tram, muscle fatigue

Procedia PDF Downloads 313