Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1769

World Academy of Science, Engineering and Technology

[Electrical and Computer Engineering]

Online ISSN : 1307-6892

1769 Usage of Channel Coding Techniques for Peak-to-Average Power Ratio Reduction in Visible Light Communications Systems

Authors: P.L.D.N.M. de Silva, S.G. Edirisinghe, R. Weerasuriya

Abstract:

High Peak-to-Average Power Ratio (PAPR) is a concern of Orthogonal Frequency Division Multiplexing (OFDM) based Visible Light Communication (VLC) systems. Discrete Fourier Transform spread (DFT-s) OFDM is an alternative single carrier modulation scheme which would address this concern. Employing channel coding techniques is another mechanism to reduce the PAPR. In this study, the improvement which can be harnessed by hybridizing these two techniques for VLC system is being studied. Within the study, efficient techniques such as Hamming coding and Convolutional coding have been studied. Thus, we present the impact of the hybrid of DFT-s OFDM and Channel coding (Hamming coding and Convolutional coding) on PAPR in VLC systems, using MATLAB simulations.

Keywords: Convolutional Coding, Discrete Fourier Transform spread Orthogonal Frequency Division Multiplexing (DFT-s OFDM), Hamming Coding, Peak-to-Average Power Ratio (PAPR), Visible Light Communications (VLC).

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1768 Improvement of Ground Truth Data for Eye Location on Infrared Driver Recordings

Authors: Sorin Valcan, Mihail Găianu

Abstract:

Labeling is a very costly and time consuming process which aims to generate datasets for training neural networks in several functionalities and projects. For driver monitoring system projects, the need of labeled images has a significant impact on the budget and distribution of effort. This paper presents the modifications done to a ground truth data generation algorithm for 2D eyes location on infrared images with drivers in order to improve the quality of the data and performance of the trained neural networks. The algorithm restrictions become tougher which makes it more accurate but also less constant. The resulting dataset becomes smaller and shall not be altered by any kind of manual labels adjustment before being used in the neural networks training process. These changes resulted in a much better performance of the trained neural networks.

Keywords: Labeling automation, infrared camera, driver monitoring, eye detection, Convolutional Neural Networks.

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1767 Supervisory Control for Induction Machine with a Modified Star/Delta Switch in Fluid Transportation

Authors: O. S. Ebrahim, K. O. Shawky, M. A. Badr, P. K. Jain

Abstract:

This paper proposes an intelligent, supervisory, hysteresis liquid-level control with three-state energy saving mode (ESM) for induction motor (IM) in fluid transportation system (FTS) including storage tank. The IM pump drive comprises a modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to the computer’s ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. Considering the motor’s thermal capacity used (TCU) and grid-compatible tariff structure, a logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction. Fuzzy-logic (FL) based availability assessment is designed and deployed on cloud, in order to provide mobilized service for the star/delta switch and highly reliable contactors. Moreover, an artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and computer simulations are performed to demonstrate the validity and effectiveness of the proposed control system in terms of reliability, power quality and operational cost reduction with a motivation of power factor correction.

Keywords: Artificial Neural Network, ANN, Contactor Health Assessment, Energy Saving Mode, Induction Machine, IM, Supervisory Control, Fluid Transportation, Fuzzy Logic, FL, cloud computing, pumped storage.

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1766 Multi-Robotic Partial Disassembly Line Balancing with Robotic Efficiency Difference via HNSGA-II

Authors: Tao Yin, Zeqiang Zhang, Wei Liang, Yanqing Zeng, Yu Zhang

Abstract:

To accelerate the remanufacturing process of electronic waste products, this study designs a partial disassembly line with the multi-robotic station to effectively dispose of excessive wastes. The multi-robotic partial disassembly line is a technical upgrade to the existing manual disassembly line. Balancing optimization can make the disassembly line smoother and more efficient. For partial disassembly line balancing with the multi-robotic station (PDLBMRS), a mixed-integer programming model (MIPM) considering the robotic efficiency differences is established to minimize cycle time, energy consumption and hazard index and to calculate their optimal global values. Besides, an enhanced NSGA-II algorithm (HNSGA-II) is proposed to optimize PDLBMRS efficiently. Finally, MIPM and HNSGA-II are applied to an actual mixed disassembly case of two types of computers, the comparison of the results solved by GUROBI and HNSGA-II verifies the correctness of the model and excellent performance of the algorithm, and the obtained Pareto solution set provides multiple options for decision-makers.

Keywords: Waste disposal, disassembly line balancing, multi-robot station, robotic efficiency difference, HNSGA-II.

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1765 Face Recognition Using Principal Component Analysis, K-Means Clustering, and Convolutional Neural Network

Authors: Zukisa Nante, Wang Zenghui

Abstract:

Face recognition is the problem of identifying or recognizing individuals in an image. This paper investigates a possible method to bring a solution to this problem. The method proposes an amalgamation of Principal Component Analysis (PCA), K-Means clustering, and Convolutional Neural Network (CNN) for a face recognition system. It is trained and evaluated using the ORL dataset. This dataset consists of 400 different faces with 40 classes of 10 face images per class. Firstly, PCA enabled the usage of a smaller network. This reduces the training time of the CNN. Thus, we get rid of the redundancy and preserve the variance with a smaller number of coefficients. Secondly, the K-Means clustering model is trained using the compressed PCA obtained data which select the K-Means clustering centers with better characteristics. Lastly, the K-Means characteristics or features are an initial value of the CNN and act as input data. The accuracy and the performance of the proposed method were tested in comparison to other Face Recognition (FR) techniques namely PCA, Support Vector Machine (SVM), as well as K-Nearest Neighbour (kNN). During experimentation, the accuracy and the performance of our suggested method after 90 epochs achieved the highest performance: 99% accuracy F1-Score, 99% precision, and 99% recall in 463.934 seconds. It outperformed the PCA that obtained 97% and KNN with 84% during the conducted experiments. Therefore, this method proved to be efficient in identifying faces in the images.

Keywords: Face recognition, Principal Component Analysis, PCA, Convolutional Neural Network, CNN, Rectified Linear Unit, ReLU, feature extraction.

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1764 Dielectric Recovery Characteristics of High Voltage Gas Circuit Breakers Operating with CO2 Mixture

Authors: Peng Lu, Branimir Radisavljevic, Martin Seeger, Daniel Over, Torsten Votteler, Bernardo Galletti

Abstract:

CO₂-based gas mixtures exhibit huge potential as the interruption medium for replacing SF₆ in high voltage switchgears. In this paper, the recovery characteristics of dielectric strength of CO₂-O₂ mixture in the post arc phase after the current zero are presented. As representative examples, the dielectric recovery curves under conditions of different gas filling pressures and short-circuit current amplitudes are presented. A series of dielectric recovery measurements suggests that the dielectric recovery rate is proportional to the mass flux of the blowing gas, and the dielectric strength recovers faster in the case of lower short circuit currents.

Keywords: CO2 mixture, high voltage circuit breakers, dielectric recovery rate, short-circuit current, mass flux.

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1763 Applying Biosensors’ Electromyography Signals through an Artificial Neural Network to Control a Small Unmanned Aerial Vehicle

Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores, Valentin Soloiu

Abstract:

This work describes a system that uses electromyography (EMG) signals obtained from muscle sensors and an Artificial Neural Network (ANN) for signal classification and pattern recognition that is used to control a small unmanned aerial vehicle using specific arm movements. The main objective of this endeavor is the development of an intelligent interface that allows the user to control the flight of a drone beyond direct manual control. The sensor used were the MyoWare Muscle sensor which contains two EMG electrodes used to collect signals from the posterior (extensor) and anterior (flexor) forearm, and the bicep. The collection of the raw signals from each sensor was performed using an Arduino Uno. Data processing algorithms were developed with the purpose of classifying the signals generated by the arm’s muscles when performing specific movements, namely: flexing, resting, and motion of the arm. With these arm motions roll control of the drone was achieved. MATLAB software was utilized to condition the signals and prepare them for the classification. To generate the input vector for the ANN and perform the classification, the root mean square and the standard deviation were processed for the signals from each electrode. The neuromuscular information was trained using an ANN with a single 10 neurons hidden layer to categorize the four targets. The result of the classification shows that an accuracy of 97.5% was obtained. Afterwards, classification results are used to generate the appropriate control signals from the computer to the drone through a Wi-Fi network connection. These procedures were successfully tested, where the drone responded successfully in real time to the commanded inputs.

Keywords: Biosensors, electromyography, Artificial Neural Network, Arduino, drone flight control, machine learning.

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1762 Separation of Composites for Recycling: Measurement of Electrostatic Charge of Carbon and Glass Fiber Particles

Authors: J. Thirunavukkarasu, M. Poulet, T. Turner, S. Pickering

Abstract:

Composite waste from manufacturing can consist of different fiber materials, including blends of different fiber. Commercially, the recycling of composite waste is currently limited to carbon fiber waste and recycling glass fiber waste is currently not economically viable due to the low cost of virgin glass fiber and the reduced mechanical properties of the recovered fibers. For this reason, the recycling of hybrid fiber materials, where carbon fiber is blended with glass fibers, cannot be processed economically. Therefore, a separation method is required to remove the glass fiber materials during the recycling process. An electrostatic separation method is chosen for this work because of the significant difference between carbon and glass fiber electrical properties. In this study, an experimental rig has been developed to measure the electrostatic charge achievable as the materials are passed through a tube. A range of particle lengths (80-100 µm, 6 mm and 12 mm), surface state conditions (0%SA, 2%SA and 6%SA), and several tube wall materials have been studied. A polytetrafluoroethylene (PTFE) tube and recycled fiber without sizing agent were identified as the most suitable parameters for the electrical separation method. It was also found that shorter fiber lengths helped to encourage particle flow and attain higher charge values. These findings can be used to develop a separation process to enable the cost-effective recycling of hybrid fiber composite waste. 

Keywords: electrostatic charging, hybrid fiber composite, recycling, short fiber composites

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1761 Mobile Robot Control by Von Neumann Computer

Authors: E. V. Larkin, T. A. Akimenko, A. V. Bogomolov, A. N. Privalov

Abstract:

The digital control system of mobile robots (MR) control is considered. It is shown that sequential interpretation of control algorithm operators, unfolding in physical time, suggests the occurrence of time delays between inputting data from sensors and outputting data to actuators. Another destabilizing control factor is presence of backlash in the joints of an actuator with an executive unit. Complex model of control system, which takes into account the dynamics of the MR, the dynamics of the digital controller and backlash in actuators, is worked out. The digital controller model is divided into two parts: the first part describes the control law embedded in the controller in the form of a control program that realizes a polling procedure when organizing transactions to sensors and actuators. The second part of the model describes the time delays that occur in the Von Neumann-type controller when processing data. To estimate time intervals, the algorithm is represented in the form of an ergodic semi-Markov process. For an ergodic semi-Markov process of common form, a method is proposed for estimation a wandering time from one arbitrary state to another arbitrary state. Example shows how the backlash and time delays affect the quality characteristics of the MR control system functioning.

Keywords: Mobile robot, backlash, control algorithm, Von Neumann controller, semi-Markov process, time delay.

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1760 Development of a Smart Liquid Level Controller

Authors: Adamu Mudi, Fawole Wahab Ibrahim, Abubakar Abba Kolo

Abstract:

In this paper, we present a microcontroller-based liquid level controller which identifies the various levels of a liquid, carries out certain actions and is capable of communicating with the human being and other devices through the GSM network. This project is useful in ensuring that a liquid is not wasted. It also contributes to the internet of things paradigm, which is the future of the internet. The method used in this work includes designing the circuit and simulating it. The circuit is then implemented on a solderless breadboard after which it is implemented on a strip board. A C++ computer program is developed and uploaded into the microcontroller. This program instructs the microcontroller on how to carry out its actions. In other to determine levels of the liquid, an ultrasonic wave is sent to the surface of the liquid similar to radar or the method for detecting the level of sea bed. Message is sent to the phone of the user similar to the way computers send messages to phones of GSM users. It is concluded that the routine of observing the levels of a liquid in a tank, refilling the tank when the liquid level is too low can be entirely handled by a programmable device without wastage of the liquid or bothering a human being with such tasks.

Keywords: Arduino Uno, HC-SR04 ultrasonic sensor, Internet of Things, IoT, SIM900 GSM Module.

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1759 A Timed and Colored Petri Nets for Modeling and Verifying Cloud System Elasticity

Authors: W. Louhichi, M.Berrima, N. Ben Rajeb Robbana

Abstract:

Elasticity is the essential property of cloud computing. As the name suggests, it constitutes the ability of a cloud system to adjust resource provisioning in relation to fluctuating workloads. There are two types of elasticity operations, vertical and horizontal. In this work, we are interested in horizontal scaling, which is ensured by two mechanisms; scaling in and scaling out. Following the sizing of the system, we can adopt scaling in the event of over-supply and scaling out in the event of under-supply. In this paper, we propose a formal model, based on temporized and colored Petri nets (TdCPNs), for the modeling of the duplication and the removal of a virtual machine from a server. This model is based on formal Petri Nets (PNs) modeling language. The proposed models are edited, verified, and simulated with two examples implemented in colored Petri nets (CPNs)tools, which is a modeling tool for colored and timed PNs.

Keywords: Cloud computing, elasticity, elasticity controller, petri nets, scaling in, scaling out.

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1758 Blockchain in Saudi e-Government: A Systematic Literature Review

Authors: Haitham Assiri, Majed Eljazzar, Priyadarsi Nanda

Abstract:

The world is gradually entering the fourth industrial revolution. E-Government services are scaling government operations across the globe. However, as promising as an e-Government system would be, it is also susceptible to malicious attacks if not properly secured. In our study, we found that in Saudi Arabia, the e-Government website, Yesser, is vulnerable to external attacks. Obviously, this can lead to a breach of data integrity and privacy. In this paper, a systematic literature review (SLR) was conducted to explore possible ways the Kingdom of Saudi Arabia can take necessary measures to strengthen its e-Government system using blockchain. Blockchain is one of the emerging technologies shaping the world through its applications in finance, elections, healthcare, etc. It secures systems and brings more transparency. A total of 28 papers were selected for this SLR, and 19 of the papers significantly showed that blockchain could enhance the security and privacy of Saudi’s e-Government system. Other papers also concluded that blockchain is effective, albeit with the integration of other technologies like IoT, AI and big data. These papers have been analyzed to sieve out the findings and set the stage for future research into the subject.

Keywords: blockchain, data integrity, e-Government, security threats

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1757 A Low Power and High-Speed Conditional-Precharge Sense Amplifier Based Flip-Flop Using Single Ended Latch

Authors: Guo-Ming Sung, Naga Raju Naik R.

Abstract:

Paper presents a low power, high speed, sense-amplifier based flip-flop (SAFF). The flip-flop’s power con-sumption and delay are greatly reduced by employing a new conditionally precharge sense-amplifier stage and a single-ended latch stage. Glitch-free and contention-free latch operation is achieved by using a conditional cut-off strategy. The design uses fewer transistors, has a lower clock load, and has a simple structure, all of which contribute to a near-zero setup time. When compared to previous flip-flop structures proposed for similar input/output conditions, this design’s performance and overall PDP have improved. The post layout simulation of the circuit uses 2.91µW of power and has a delay of 65.82 ps. Overall, the power-delay product has seen some enhancements. Cadence Virtuoso Designing tool with CMOS 90nm technology are used for all designs.

Keywords: high-speed, low-power, flip-flop, sense-amplifier

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1756 Smartphone-Based Human Activity Recognition by Machine Learning Methods

Authors: Yanting Cao, Kazumitsu Nawata

Abstract:

As smartphones are continually upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described more refined, complex and detailed. In this context, we analyzed a set of experimental data, obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model become extremely challenging. After a series of feature selection and parameters adjustments, a well-performed SVM classifier has been trained. 

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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1755 Energy Management System with Temperature Rise Prevention on Hybrid Ships

Authors: Asser S. Abdelwahab, Nabil H. Abbasy, Ragi A. Hamdy

Abstract:

Marine shipping has now become one of the major worldwide contributors to pollution and greenhouse gas emissions. Hybrid ships technology based on multiple energy sources has taken a great scope of research to get rid of ship emissions and cut down fuel expenses. Insufficiency between power generated and the demand load to withstand the transient behavior on ships during severe climate conditions will lead to a blackout. Thus, an efficient energy management system (EMS) is a mandatory scope for achieving higher system efficiency while enhancing the lifetime of the onboard storage systems is another salient EMS scope. Considering energy storage system conditions, both the battery state of charge (SOC) and temperature represent important parameters to prevent any malfunction of the storage system that eventually degrades the whole system. In this paper, a two battery packs ratio fuzzy logic control model is proposed. The overall aim is to control the charging/discharging current while including both the battery SOC and temperature in the energy management system. The full designs of the proposed controllers are described and simulated using Matlab. The results prove the successfulness of the proposed controller in stabilizing the system voltage during both loading and unloading while keeping the energy storage system in a healthy condition.

Keywords: energy storage system, fuzzy logic control, hybrid ship, thermal runaway

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1754 Design and Construction of an Impulse Current Generator for Lightning Strike Experiments

Authors: Kamran Yousefpour, Mojtaba Rostaghi-Chalaki, Jason Warden, David Wallace, Chanyeop Park

Abstract:

There has been a rising trend in using impulse current generators to investigate the lightning strike protection of materials including aluminum and composites in structures such as wind turbine blade and aircraft body. The focus of this research is to present an impulse current generator built in the High Voltage Lab at Mississippi State University. The generator is capable of producing component A and D of the natural lightning discharges in accordance with the Society of Automotive Engineers (SAE) standard, which is widely used in the aerospace industry. The generator can supply lightning impulse energy up to 400 kJ with the capability of producing impulse currents with magnitudes greater than 200 kA. The electrical circuit and physical components of an improved impulse current generator are described and several lightning strike waveforms with different amplitudes is presented for comparing with the standard waveform. The results of this study contribute to the fundamental understanding the functionality of the impulse current generators and present an impulse current generator developed at the High Voltage Lab of Mississippi State University.

Keywords: impulse current generator, lightning, society of automotive engineers, capacitor

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1753 Slime Mould Optimization Algorithms for Optimal Distributed Generation Integration in Distribution Electrical Network

Authors: F. Fissou Amigue, S. Ndjakomo Essiane, S. Pérabi Ngoffé, G. Abessolo Ondoa, G. Mengata Mengounou, T. P. Nna Nna

Abstract:

This document proposes a method for determining the optimal point of integration of distributed generation (DG) in distribution grid. Slime mould optimization is applied to determine best node in case of one and two injection point. Problem has been modeled as an optimization problem where the objective is to minimize joule loses and main constraint is to regulate voltage in each point. The proposed method has been implemented in MATLAB and applied in IEEE network 33 and 69 nodes. Comparing results obtained with other algorithms showed that slime mould optimization algorithms (SMOA) have the best reduction of power losses and good amelioration of voltage profile.

Keywords: Optimization, distributed generation, integration, slime mould algorithm.

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1752 A Convolutional Deep Neural Network Approach for Skin Cancer Detection Using Skin Lesion Images

Authors: Firas Gerges, Frank Y. Shih

Abstract:

Malignant Melanoma, known simply as Melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient death. When detected early, Melanoma is curable. In this paper we propose a deep learning model (Convolutional Neural Networks) in order to automatically classify skin lesion images as Malignant or Benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.

Keywords: Deep learning, skin cancer, image processing, melanoma.

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1751 Study of Compatibility and Oxidation Stability of Vegetable Insulating Oils

Authors: Helena M. Wilhelm, Paulo O. Fernandes, Laís P. Dill, Kethlyn G. Moscon

Abstract:

The use of vegetable oil (or natural ester) as an insulating fluid in electrical transformers is a trend that aims to contribute to environmental preservation since it is biodegradable and non-toxic. Besides, vegetable oil has high flash and combustion points, being considered a fire safety fluid. However, vegetable oil is usually less stable towards oxidation than mineral oil. Both insulating fluids, mineral and vegetable oils, need to be tested periodically according to specific standards. Oxidation stability can be determined by the induction period measured by conductivity method (Rancimat) by monitoring the effectivity of oil’s antioxidant additives, a methodology already developed for food application and biodiesel but still not standardized for insulating fluids. Besides adequate oxidation stability, fluids must be compatible with transformer's construction materials under normal operating conditions to ensure that damage to the oil and parts of the transformer does not occur. ASTM standard and Brazilian normative differ in parameters evaluated, which reveals the need to regulate tests for each oil type. The aim of this study was to assess oxidation stability and compatibility of vegetable oils to suggest the best way to assure a viable performance of vegetable oil as transformer insulating fluid. The determination of the induction period for several vegetable insulating oils from the local market by using Rancimat was carried out according to BS EN 14112 standard, at different temperatures (110, 120, and 130 °C). Also, the compatibility of vegetable oil was assessed according to ASTM and ABNT NBR standards. The main results showed that the best temperature for use in the Rancimat test is 130 °C, which allows a better observation of conductivity change. The compatibility test results presented differences between vegetable and mineral oil standards that should be taken into account in oil testing since materials compatibility and oxidation stability are essential for equipment reliability.

Keywords: Compatibility, Rancimat, natural ester, vegetable oil.

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1750 Modelling of Multi-Agent Systems for the Scheduling of Multi-EV Charging from Power Limited Sources

Authors: Manan’Iarivo Rasolonjanahary, Chris Bingham, Nigel Schofield, Masoud Bazargan

Abstract:

This paper presents the research and application of model predictive scheduled charging of electric vehicles (EV) subject to limited available power resource. To focus on algorithm and operational characteristics, the EV interface to the source is modelled as a battery state equation during the charging operation. The researched methods allow for the priority scheduling of EV charging in a multi-vehicle regime and when subject to limited source power availability. Priority attribution for each connected EV is described. The validity of the developed methodology is shown through the simulation of different scenarios of charging operation of multiple connected EVs including non-scheduled and scheduled operation with various numbers of vehicles. Performance of the developed algorithms is also reported with the recommendation of the choice of suitable parameters.

Keywords: Model predictive control, non-scheduled, power limited sources, scheduled and stop-start battery charging.

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1749 Identification of Configuration Space Singularities with Local Real Algebraic Geometry

Authors: Marc Diesse, Hochschule Heilbronn

Abstract:

We address the question of identifying the configuration space singularities of linkages, i.e., points where the configuration space is not locally a submanifold of Euclidean space. Because the configuration space cannot be smoothly parameterized at such points, these singularity types have a significantly negative impact on the kinematics of the linkage. It is known that Jacobian methods do not provide sufficient conditions for the existence of CS-singularities. Herein, we present several additional algebraic criteria that provide the sufficient conditions. Further, we use those criteria to analyze certain classes of planar linkages. These examples will also show how the presented criteria can be checked using algorithmic methods.

Keywords: Linkages, configuration space singularities, real algebraic geometry, analytic geometry, computer algebra.

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1748 An Investigation to Study the Moisture Dependency of Ground Enhancement Compound

Authors: Arunima Shukla, Vikas Almadi, Devesh Jaiswal, Sunil Saini, Bhusan S. Patil

Abstract:

Lightning protection consists of three main parts; mainly air termination system, down conductor, and earth termination system. Earth termination system is the most important part as earth is the sink and source of charges. Therefore, even when the charges are captured and delivered to the ground, and an easy path is not provided to the charges, earth termination system would lead to problems. Soil has significantly different resistivities ranging from 10 Ωm for wet organic soil to 10000 Ωm for bedrock. Different methods have been discussed and used conventionally such as deep-ground-well method and altering the length of the rod. Those methods are not considered economical. Therefore, it was a general practice to use charcoal along with salt to reduce the soil resistivity. Bentonite is worldwide acceptable material, that had led our interest towards study of bentonite at first. It was concluded that bentonite is a clay which is non-corrosive, environment friendly. Whereas bentonite is suitable only when there is moisture present in the soil, as in the absence of moisture, cracks will appear on the surface which will provide an open passage to the air, resulting into increase in the resistivity. Furthermore, bentonite without moisture does not have enough bonding property, moisture retention, conductivity, and non-leachability. Therefore, bentonite was used along with the other backfill material to overcome the dependency of bentonite on moisture. Different experiments were performed to get the best ratio of bentonite and carbon backfill. It was concluded that properties will highly depend on the quantity of bentonite and carbon-based backfill material.

Keywords: Backfill material, bentonite, conducting soil, grounding material, low resistivity.

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1747 Effect of Different Contaminants on Mineral Insulating Oil Characteristics

Authors: H. M. Wilhelm, P. O. Fernandes, L. P. Dill, C. Steffens, K. G. Moscon, S. M. Peres, V. Bender, T. Marchesan, J. B. Ferreira Neto

Abstract:

Deterioration of insulating oil is a natural process that occurs during transformers operation. However, this process can be accelerated by some factors, such as oxygen, high temperatures, metals and, moisture, which rapidly reduce oil insulating capacity and favor transformer faults. Parts of building materials of a transformer can be degraded and yield soluble compounds and insoluble particles that shorten the equipment life. Physicochemical tests, dissolved gas analysis (including propane, propylene and, butane), volatile and furanic compounds determination, besides quantitative and morphological analyses of particulate are proposed in this study in order to correlate transformers building materials degradation with insulating oil characteristics. The present investigation involves tests of medium temperature overheating simulation by means of an electric resistance wrapped with the following materials immersed in mineral insulating oil: test I) copper, tin, lead and, paper (heated at 350-400 °C for 8 h); test II) only copper (at 250 °C for 11 h); and test III) only paper (at 250 °C for 8 h and at 350 °C for 8 h). A different experiment is the simulation of electric arc involving copper, using an electric welding machine at two distinct energy sets (low and high). Analysis results showed that dielectric loss was higher in the sample of test I, higher neutralization index and higher values of hydrogen and hydrocarbons, including propane and butane, were also observed. Test III oil presented higher particle count, in addition, ferrographic analysis revealed contamination with fibers and carbonized paper. However, these particles had little influence on the oil physicochemical parameters (dielectric loss and neutralization index) and on the gas production, which was very low. Test II oil showed high levels of methane, ethane, and propylene, indicating the effect of metal on oil degradation. CO2 and CO gases were formed in the highest concentration in test III, as expected. Regarding volatile compounds, in test I acetone, benzene and toluene were detected, which are oil oxidation products. Regarding test III, methanol was identified due to cellulose degradation, as expected. Electric arc simulation test showed the highest oil oxidation in presence of copper and at high temperature, since these samples had huge concentration of hydrogen, ethylene, and acetylene. Particle count was also very high, showing the highest release of copper in such conditions. When comparing high and low energy, the first presented more hydrogen, ethylene, and acetylene. This sample had more similar results to test I, pointing out that the generation of different particles can be the cause for faults such as electric arc. Ferrography showed more evident copper and exfoliation particles than in other samples. Therefore, in this study, by using different combined analytical techniques, it was possible to correlate insulating oil characteristics with possible contaminants, which can lead to transformers failure.

Keywords: Ferrography, gas analysis, insulating mineral oil, particle contamination, transformer failures.

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1746 Matrix-Based Linear Analysis of Switched Reluctance Generator with Optimum Pole Angles Determination

Authors: Walid A. M. Ghoneim, Hamdy A. Ashour, Asmaa E. Abdo

Abstract:

In this paper, linear analysis of a Switched Reluctance Generator (SRG) model is applied on the most common configurations (4/2, 6/4 and 8/6) for both conventional short-pitched and fully-pitched designs, in order to determine the optimum stator/rotor pole angles at which the maximum output voltage is generated per unit excitation current. This study is focused on SRG analysis and design as a proposed solution for renewable energy applications, such as wind energy conversion systems. The world’s potential to develop the renewable energy technologies through dedicated scientific researches was the motive behind this study due to its positive impact on economy and environment. In addition, the problem of rare earth metals (Permanent magnet) caused by mining limitations, banned export by top producers and environment restrictions leads to the unavailability of materials used for rotating machines manufacturing. This challenge gave authors the opportunity to study, analyze and determine the optimum design of the SRG that has the benefit to be free from permanent magnets, rotor windings, with flexible control system and compatible with any application that requires variable-speed operation. In addition, SRG has been proved to be very efficient and reliable in both low-speed or high-speed applications. Linear analysis was performed using MATLAB simulations based on the (Modified generalized matrix approach) of Switched Reluctance Machine (SRM). About 90 different pole angles combinations and excitation patterns were simulated through this study, and the optimum output results for each case were recorded and presented in detail. This procedure has been proved to be applicable for any SRG configuration, dimension and excitation pattern. The delivered results of this study provide evidence for using the 4-phase 8/6 fully pitched SRG as the main optimum configuration for the same machine dimensions at the same angular speed.

Keywords: Generalized matrix approach, linear analysis, renewable applications, switched reluctance generator, SRG.

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1745 A Review in Advanced Digital Signal Processing Systems

Authors: Roza Dastres, Mohsen Soori

Abstract:

Digital Signal Processing (DSP) is the use of digital processing systems by computers in order to perform a variety of signal processing operations. It is the mathematical manipulation of a digital signal's numerical values in order to increase quality as well as effects of signals. DSP can include linear or nonlinear operators in order to process and analyze the input signals. The nonlinear DSP processing is closely related to nonlinear system detection and can be implemented in time, frequency and space-time domains. Applications of the DSP can be presented as control systems, digital image processing, biomedical engineering, speech recognition systems, industrial engineering, health care systems, radar signal processing and telecommunication systems. In this study, advanced methods and different applications of DSP are reviewed in order to move forward the interesting research filed.

Keywords: Digital signal processing, advanced telecommunication, nonlinear signal processing, speech recognition systems.

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1744 Artificial Neural Network-Based Short-Term Load Forecasting for Mymensingh Area of Bangladesh

Authors: S. M. Anowarul Haque, Md. Asiful Islam

Abstract:

Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: Load forecasting, artificial neural network, particle swarm optimization.

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1743 Understanding the Behavior of Superconductors by Analyzing Permittivity

Authors: Fred Lacy

Abstract:

A superconductor has the ability to conduct electricity perfectly and exclude magnetic fields from its interior. In order to understand electromagnetic characteristics of superconductors, their material properties need to be examined. To facilitate this understanding, a theoretical model based on concepts of electromagnetics is presented to explain the electrical and magnetic properties of superconductors. The permittivity response is the key aspect of the model and it describes the electrical resistance response and why it vanishes at the material’s critical temperature. The model also explains the behavior of magnetic fields and why they cannot exist inside superconducting materials. The theoretical concepts and equations associated with this model are used to demonstrate that they are sufficient in describing the behavior of both type I and type II (or high temperature) superconductors. This model is also able to explain why superconductors behave differently than perfect conductors. As a result, examining the permittivity response and understanding electromagnetic field theory provides insight into the major aspects associated with superconducting materials.

Keywords: Ampere’s law, permittivity, permeability, resistivity, Schrödinger wave equation.

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1742 Grid-Connected Photovoltaic System: System Overview and Sizing Principles

Authors: Najiya Omar, Hamed Aly, Timothy Little

Abstract:

The optimal size of a photovoltaic (PV) array is considered a critical factor in designing an efficient PV system due to the dependence of the PV cell performance on temperature. A high temperature can lead to voltage losses of solar panels, whereas a low temperature can cause voltage overproduction. There are two possible scenarios of the inverter’s operation in which they are associated with the erroneous calculations of the number of PV panels: 1) If the number of the panels is scant and the temperature is high, the minimum voltage required to operate the inverter will not be reached. As a result, the inverter will shut down. 2) Comparably, if the number of panels is excessive and the temperature is low, the produced voltage will be more than the maximum limit of the inverter which can cause the inverter to get disconnected or even damaged. This article aims to assess theoretical and practical methodologies to calculate size and determine the topology of a PV array. The results are validated by applying an experimental evaluation for a 100 kW Grid-connected PV system for a location in Halifax, Nova Scotia and achieving a satisfactory system performance compared to the previous work done.

Keywords: Sizing PV panels, grid-connected PV, topology of PV array, theoretical and practical methodologies.

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1741 Design and Characterization of a CMOS Process Sensor Utilizing Vth Extractor Circuit

Authors: Rohana Musa, Yuzman Yusoff, Chia Chieu Yin, Hanif Che Lah

Abstract:

This paper presents the design and characterization of a low power Complementary Metal Oxide Semiconductor (CMOS) process sensor. The design is targeted for implementation using Silterra’s 180 nm CMOS process technology. The proposed process sensor employs a voltage threshold (Vth) extractor architecture for detection of variations in the fabrication process. The process sensor generates output voltages in the range of 401 mV (fast-fast corner) to 443 mV (slow-slow corner) at nominal condition. The power dissipation for this process sensor is 6.3 µW with a supply voltage of 1.8V with a silicon area of 190 µm X 60 µm. The preliminary result of this process sensor that was fabricated indicates a close resemblance between test and simulated results.

Keywords: CMOS Process sensor, Process, Voltage and Temperature (PVT) sensor, threshold extractor circuit, Vth extractor circuit.

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1740 A Socio-Technical Approach to Cyber-Risk Assessment

Authors: Kitty Kioskli, Nineta Polemi

Abstract:

Evaluating the levels of cyber-security risks within an enterprise is most important in protecting its information system, services and all its digital assets against security incidents (e.g. accidents, malicious acts, massive cyber-attacks). The existing risk assessment methodologies (e.g. eBIOS, OCTAVE, CRAMM, NIST-800) adopt a technical approach considering as attack factors only the capability, intention and target of the attacker, and not paying attention to the attacker’s psychological profile and personality traits. In this paper, a socio-technical approach is proposed in cyber risk assessment, in order to achieve more realistic risk estimates by considering the personality traits of the attackers. In particular, based upon principles from investigative psychology and behavioural science, a multi-dimensional, extended, quantifiable model for an attacker’s profile is developed, which becomes an additional factor in the cyber risk level calculation.

Keywords: Attacker, behavioural models, cyber risk assessment, cyber-security, human factors, investigative psychology, ISO27001, ISO27005.

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