Search results for: Fault classification
1357 Fault Detection of Broken Rotor Bars Using Stator Current Spectrum for the Direct Torque Control Induction Motor
Authors: Ridha Kechida, Arezki Menacer, Abdelhamid Benakcha
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The numerous qualities of squirrel cage induction machines enhance their use in industry. However, various faults can occur, such as stator short-circuits and rotor failures. In this paper, we use a technique based on the spectral analysis of stator current in order to detect the fault in the machine: broken rotor bars. Thus, the number effect of the breaks has been highlighted. The effect is highlighted by considering the machine controlled by the Direct Torque Control (DTC). The key to fault detection is the development of a simplified dynamic model of a squirrel cage induction motor taking account the broken bars fault and the stator current spectrum analysis (FFT).Keywords: Rotor faults, diagnosis, induction motor, DTC, statorcurrent spectrum.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31121356 A Fault-Tolerant Full Adder in Double Pass CMOS Transistor
Authors: Abdelmonaem Ayachi, Belgacem Hamdi
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This paper presents a fault-tolerant implementation for adder schemes using the dual duplication code. To prove the efficiency of the proposed method, the circuit is simulated in double pass transistor CMOS 32nm technology and some transient faults are voluntary injected in the Layout of the circuit. This fully differential implementation requires only 20 transistors which mean that the proposed design involves 28.57% saving in transistor count compared to standard CMOS technology.
Keywords: Semiconductors, digital electronics, double pass transistor technology, Full adder, fault tolerance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20921355 Impact of GCSC on Measured Impedance by Distance Relay in the Presence of Single Phase to Earth Fault
Authors: M. Zellagui, A. Chaghi
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This paper presents the impact study of GTO Controlled Series Capacitor (GCSC) parameters on measured impedance (Zseen) by MHO distance relays for single transmission line high voltage 220 kV in the presence of single phase to earth fault with fault resistance (RF). The study deals with a 220 kV single electrical transmission line of Eastern Algerian transmission networks at Group Sonelgaz (Algerian Company of Electrical and Gas) compensated by series Flexible AC Transmission System (FACTS) i.e. GCSC connected at midpoint of the transmission line. The transmitted active and reactive powers are controlled by three GCSC-s. The effects of maximum reactive power injected as well as injected maximum voltage by GCSC on distance relays measured impedance is treated. The simulations results investigate the effects of GCSC injected parameters: variable reactance (XGCSC), variable voltage (VGCSC) and reactive power injected (QGCSC) on measured resistance and reactance in the presence of earth fault with resistance fault varied between 5 to 50 Ω for three cases study.
Keywords: GCSC Parameters, Transmission line, Earth fault, Symmetrical components, Distance protection, Measured impedance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19371354 Pose Normalization Network for Object Classification
Authors: Bingquan Shen
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Convolutional Neural Networks (CNN) have demonstrated their effectiveness in synthesizing 3D views of object instances at various viewpoints. Given the problem where one have limited viewpoints of a particular object for classification, we present a pose normalization architecture to transform the object to existing viewpoints in the training dataset before classification to yield better classification performance. We have demonstrated that this Pose Normalization Network (PNN) can capture the style of the target object and is able to re-render it to a desired viewpoint. Moreover, we have shown that the PNN improves the classification result for the 3D chairs dataset and ShapeNet airplanes dataset when given only images at limited viewpoint, as compared to a CNN baseline.Keywords: Convolutional neural networks, object classification, pose normalization, viewpoint invariant.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11081353 Transient Energy and its Impact on Transmission Line Faults
Authors: Mamta Patel, R. N. Patel
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Transmission and distribution lines are vital links between the generating unit and consumers. They are exposed to atmosphere, hence chances of occurrence of fault in transmission line is very high which has to be immediately taken care of in order to minimize damage caused by it. In this paper Discrete wavelet transform of voltage signals at the two ends of transmission lines have been analyzed. The transient energy of the detail information of level five is calculated for different fault conditions. It is observed that the variation of transient energy of healthy and faulted line can give important information which can be very useful in classifying and locating the fault.
Keywords: Wavelet, Discrete wavelet transform, Multiresolution analysis, Transient energy
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24241352 Lean Models Classification: Towards a Holistic View
Authors: Y. Tiamaz, N. Souissi
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The purpose of this paper is to present a classification of Lean models which aims to capture all the concepts related to this approach and thus facilitate its implementation. This classification allows the identification of the most relevant models according to several dimensions. From this perspective, we present a review and an analysis of Lean models literature and we propose dimensions for the classification of the current proposals while respecting among others the axes of the Lean approach, the maturity of the models as well as their application domains. This classification allowed us to conclude that researchers essentially consider the Lean approach as a toolbox also they design their models to solve problems related to a specific environment. Since Lean approach is no longer intended only for the automotive sector where it was invented, but to all fields (IT, Hospital, ...), we consider that this approach requires a generic model that is capable of being implemented in all areas.
Keywords: Lean approach, lean models, classification, dimensions, holistic view.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12391351 A Neuro-Fuzzy Approach Based Voting Scheme for Fault Tolerant Systems Using Artificial Bee Colony Training
Authors: D. Uma Devi, P. Seetha Ramaiah
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Voting algorithms are extensively used to make decisions in fault tolerant systems where each redundant module gives inconsistent outputs. Popular voting algorithms include majority voting, weighted voting, and inexact majority voters. Each of these techniques suffers from scenarios where agreements do not exist for the given voter inputs. This has been successfully overcome in literature using fuzzy theory. Our previous work concentrated on a neuro-fuzzy algorithm where training using the neuro system substantially improved the prediction result of the voting system. Weight training of Neural Network is sub-optimal. This study proposes to optimize the weights of the Neural Network using Artificial Bee Colony algorithm. Experimental results show the proposed system improves the decision making of the voting algorithms.Keywords: Voting algorithms, Fault tolerance, Fault masking, Neuro-Fuzzy System (NFS), Artificial Bee Colony (ABC)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26461350 Design and Analysis of Fault Tolerate feature of n-Phase Induction Motor Drive
Authors: G. Renuka Devi
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This paper presents design and analysis of fault tolerate feature of n-phase induction motor drive. The n-phase induction motor (more than 3-phases) has a number of advantages over conventional 3-phase induction motor, it has low torque pulsation with increased torque density, more fault tolerant feature, low current ripple with increased efficiency. When increasing the number of phases, it has reduced current per phase without increasing per phase voltage, resulting in an increase in the total power rating of n-phase motors in the same volume machine. In this paper, the theory of operation of a multi-phase induction motor is discussed. The detailed study of d-q modeling of n-phase induction motors is elaborated. The d-q model of n-phase (5, 6, 7, 9 and 12) induction motors is developed in a MATLAB/Simulink environment. The steady state and dynamic performance of the multi-phase induction motor is studied under varying load conditions. Comparison of 5-phase induction is presented under normal and fault conditions.
Keywords: d-q model, dynamic Response, fault tolerant feature, matlab/simulink, multi-phase induction motor, transient response.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5601349 Obstacle Classification Method Based On 2D LIDAR Database
Authors: Moohyun Lee, Soojung Hur, Yongwan Park
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We propose obstacle classification method based on 2D LIDAR Database. The existing obstacle classification method based on 2D LIDAR, has an advantage in terms of accuracy and shorter calculation time. However, it was difficult to classifier the type of obstacle and therefore accurate path planning was not possible. In order to overcome this problem, a method of classifying obstacle type based on width data of obstacle was proposed. However, width data was not sufficient to improve accuracy. In this paper, database was established by width and intensity data; the first classification was processed by the width data; the second classification was processed by the intensity data; classification was processed by comparing to database; result of obstacle classification was determined by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that calculation time declined in comparison to 3D LIDAR and it was possible to classify obstacle using single 2D LIDAR.
Keywords: Obstacle, Classification, LIDAR, Segmentation, Width, Intensity, Database.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34361348 An Efficient Obstacle Detection Algorithm Using Colour and Texture
Authors: Chau Nguyen Viet, Ian Marshall
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This paper presents a new classification algorithm using colour and texture for obstacle detection. Colour information is computationally cheap to learn and process. However in many cases, colour alone does not provide enough information for classification. Texture information can improve classification performance but usually comes at an expensive cost. Our algorithm uses both colour and texture features but texture is only needed when colour is unreliable. During the training stage, texture features are learned specifically to improve the performance of a colour classifier. The algorithm learns a set of simple texture features and only the most effective features are used in the classification stage. Therefore our algorithm has a very good classification rate while is still fast enough to run on a limited computer platform. The proposed algorithm was tested with a challenging outdoor image set. Test result shows the algorithm achieves a much better trade-off between classification performance and efficiency than a typical colour classifier.
Keywords: Colour, texture, classification, obstacle detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18021347 Round Addition Differential Fault Analysis on Lightweight Block Ciphers with On-the-Fly Key Scheduling
Authors: Hideki Yoshikawa, Masahiro Kaminaga, Arimitsu Shikoda, Toshinori Suzuki
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Round addition differential fault analysis using operation skipping for lightweight block ciphers with on-the-fly key scheduling is presented. For 64-bit KLEIN, it is shown that only a pair of correct and faulty ciphertexts can be used to derive the secret master key. For PRESENT, one correct ciphertext and two faulty ciphertexts are required to reconstruct the secret key. Furthermore, secret key extraction is demonstrated for the LBlock Feistel-type lightweight block cipher.Keywords: Differential Fault Analysis (DFA), round addition, block cipher, on-the-fly key schedule.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20041346 Ultra Fast Solid State Ground Fault Isolator
Authors: I Made Darmayuda, Zhou Jun, Krishna Mainali, Simon Ng Sheung Yan, Saisundar S, Eran Ofek
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Personnel protection devices are cardinal in safety hazard applications. They are widely used in home, office and in industry environments to reduce the risk of lethal shock to human being and equipment safety. This paper briefly reviews various personnel protection devices also describes the basic working principle of conventional ground fault circuit interrupter (GFCI) or ground fault isolator (GFI), its disadvantages and ways to overcome the disadvantages with solid-state relay (SSR) based GFI with ultrafast response up on fault implemented in printed circuit board. This solid state GFI comprises discrete MOSFET based alternating current (AC) switches, linear optical amplifier, photovoltaic isolator and sense resistor. In conventional GFI, current transformer is employed as a sensing element to detect the difference in current flow between live and neutral conductor. If there is no fault in equipment powered through GFI, due to insulation failure of internal wires and windings of motors, both live and neutral currents will be equal in magnitude and opposite in phase.
Keywords: current transformer, electrocution, GFCI, GFI
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23131345 Diagnosis of Induction Machine Faults by DWT
Authors: Hamidreza Akbari
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In this paper, for detection of inclined eccentricity in an induction motor, time–frequency analysis of the stator startup current is carried out. For this purpose, the discrete wavelet transform is used. Data are obtained from simulations, using winding function approach. The results show the validity of the approach for detecting the fault and discriminating with respect to other faults.
Keywords: Induction machine, Fault, DWT.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21251344 Neural Network Evaluation of FRP Strengthened RC Buildings Subjected to Near-Fault Ground Motions having Fling Step
Authors: Alireza Mortezaei, Kimia Mortezaei
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Recordings from recent earthquakes have provided evidence that ground motions in the near field of a rupturing fault differ from ordinary ground motions, as they can contain a large energy, or “directivity" pulse. This pulse can cause considerable damage during an earthquake, especially to structures with natural periods close to those of the pulse. Failures of modern engineered structures observed within the near-fault region in recent earthquakes have revealed the vulnerability of existing RC buildings against pulse-type ground motions. This may be due to the fact that these modern structures had been designed primarily using the design spectra of available standards, which have been developed using stochastic processes with relatively long duration that characterizes more distant ground motions. Many recently designed and constructed buildings may therefore require strengthening in order to perform well when subjected to near-fault ground motions. Fiber Reinforced Polymers are considered to be a viable alternative, due to their relatively easy and quick installation, low life cycle costs and zero maintenance requirements. The objective of this paper is to investigate the adequacy of Artificial Neural Networks (ANN) to determine the three dimensional dynamic response of FRP strengthened RC buildings under the near-fault ground motions. For this purpose, one ANN model is proposed to estimate the base shear force, base bending moments and roof displacement of buildings in two directions. A training set of 168 and a validation set of 21 buildings are produced from FEA analysis results of the dynamic response of RC buildings under the near-fault earthquakes. It is demonstrated that the neural network based approach is highly successful in determining the response.
Keywords: Seismic evaluation, FRP, neural network, near-fault ground motion
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17291343 An Enhanced Fault-Tolerant Conference Key Agreement Protocol
Authors: Cheng-Chi Lee, Chun-Ta Li, Chia-Ying Wu, Shiow-Yuan Huang
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Establishing a secure communication of Internet conferences for participants is very important. Before starting the conference, all the participants establish a common conference key to encrypt/decrypt communicated messages. It enables participants to exchange the secure messages. Nevertheless, in the conference, if there are any malicious participants who may try to upset the key generation process causing other legal participants to obtain a different conference key. In this article, we propose an improved conference key agreement with fault-tolerant capability. The proposed scheme can filter malicious participants at the beginning of the conference to ensure that all participants obtain the same conference key. Compare with other schemes, our scheme is more secure and efficient than others.Keywords: Conference key, Diffie-Hellman protocol, key agreement, fault tolerance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13301342 A Performance Evaluation of Oscillation Based Test in Continuous Time Filters
Authors: Eduardo Romero, Marcelo Costamagna, Gabriela Peretti, Carlos Marqués
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This work evaluates the ability of OBT for detecting parametric faults in continuous-time filters. To this end, we adopt two filters with quite different topologies as cases of study and a previously reported statistical fault model. In addition, we explore the behavior of the test schemes when a particular test condition is changed. The new data reported here, obtained from a fault simulation process, reveal a lower performance of OBT not observed in previous work using single-deviation faults, even under the change in the test condition.
Keywords: Testing, analog fault simulation, analog filter test, oscillation based test.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14331341 A Comparison of Inverse Simulation-Based Fault Detection in a Simple Robotic Rover with a Traditional Model-Based Method
Authors: Murray L. Ireland, Kevin J. Worrall, Rebecca Mackenzie, Thaleia Flessa, Euan McGookin, Douglas Thomson
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Robotic rovers which are designed to work in extra-terrestrial environments present a unique challenge in terms of the reliability and availability of systems throughout the mission. Should some fault occur, with the nearest human potentially millions of kilometres away, detection and identification of the fault must be performed solely by the robot and its subsystems. Faults in the system sensors are relatively straightforward to detect, through the residuals produced by comparison of the system output with that of a simple model. However, faults in the input, that is, the actuators of the system, are harder to detect. A step change in the input signal, caused potentially by the loss of an actuator, can propagate through the system, resulting in complex residuals in multiple outputs. These residuals can be difficult to isolate or distinguish from residuals caused by environmental disturbances. While a more complex fault detection method or additional sensors could be used to solve these issues, an alternative is presented here. Using inverse simulation (InvSim), the inputs and outputs of the mathematical model of the rover system are reversed. Thus, for a desired trajectory, the corresponding actuator inputs are obtained. A step fault near the input then manifests itself as a step change in the residual between the system inputs and the input trajectory obtained through inverse simulation. This approach avoids the need for additional hardware on a mass- and power-critical system such as the rover. The InvSim fault detection method is applied to a simple four-wheeled rover in simulation. Additive system faults and an external disturbance force and are applied to the vehicle in turn, such that the dynamic response and sensor output of the rover are impacted. Basic model-based fault detection is then employed to provide output residuals which may be analysed to provide information on the fault/disturbance. InvSim-based fault detection is then employed, similarly providing input residuals which provide further information on the fault/disturbance. The input residuals are shown to provide clearer information on the location and magnitude of an input fault than the output residuals. Additionally, they can allow faults to be more clearly discriminated from environmental disturbances.Keywords: Fault detection, inverse simulation, rover, ground robot.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9391340 Centralized Monitoring and Self-protected against Fiber Fault in FTTH Access Network
Authors: Mohammad Syuhaimi Ab-Rahman, Boonchuan Ng, Kasmiran Jumari
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This paper presented a new approach for centralized monitoring and self-protected against fiber fault in fiber-to-the-home (FTTH) access network by using Smart Access Network Testing, Analyzing and Database (SANTAD). SANTAD will be installed with optical line terminal (OLT) at central office (CO) for in-service transmission surveillance and fiber fault localization within FTTH with point-to-multipoint (P2MP) configuration downwardly from CO towards customer residential locations based on the graphical user interface (GUI) processing capabilities of MATLAB software. SANTAD is able to detect any fiber fault as well as identify the failure location in the network system. SANTAD enable the status of each optical network unit (ONU) connected line is displayed onto one screen with capability to configure the attenuation and detect the failure simultaneously. The analysis results and information will be delivered to the field engineer for promptly actions, meanwhile the failure line will be diverted to protection line to ensure the traffic flow continuously. This approach has a bright prospect to improve the survivability and reliability as well as increase the efficiency and monitoring capabilities in FTTH.Keywords: Fiber fault, FTTH, SANTAD, transmission surveillance, MATLAB.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25391339 Seismic Hazard Assessment of Offshore Platforms
Authors: F. D. Konstandakopoulou, G. A. Papagiannopoulos, N. G. Pnevmatikos, G. D. Hatzigeorgiou
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This paper examines the effects of pile-soil-structure interaction on the dynamic response of offshore platforms under the action of near-fault earthquakes. Two offshore platforms models are investigated, one with completely fixed supports and one with piles which are clamped into deformable layered soil. The soil deformability for the second model is simulated using non-linear springs. These platform models are subjected to near-fault seismic ground motions. The role of fault mechanism on platforms’ response is additionally investigated, while the study also examines the effects of different angles of incidence of seismic records on the maximum response of each platform.
Keywords: Hazard analysis, offshore platforms, earthquakes, safety.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10021338 A Proposed Technique for Software Development Risks Identification by using FTA Model
Authors: Hatem A. Khater, A. Baith Mohamed, Sara M. Kamel
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Software Development Risks Identification (SDRI), using Fault Tree Analysis (FTA), is a proposed technique to identify not only the risk factors but also the causes of the appearance of the risk factors in software development life cycle. The method is based on analyzing the probable causes of software development failures before they become problems and adversely affect a project. It uses Fault tree analysis (FTA) to determine the probability of a particular system level failures that are defined by A Taxonomy for Sources of Software Development Risk to deduce failure analysis in which an undesired state of a system by using Boolean logic to combine a series of lower-level events. The major purpose of this paper is to use the probabilistic calculations of Fault Tree Analysis approach to determine all possible causes that lead to software development risk occurrenceKeywords: Software Development Risks Identification (SDRI), Fault Tree Analysis (FTA), Taxonomy for Software Development Risks (TSDR), Probabilistic Risk Assessment (PRA).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22011337 Access Control System: Monitoring Tool for Fiber to the Home Passive Optical Network
Authors: Aswir Premadi, Mohammad Syuhaimi Ab. Rahman, Mohamad Najib Moh. Saupe, KasmiranJumari
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An optical fault monitoring in FTTH-PON using ACS is demonstrated. This device can achieve real-time fault monitoring for protection feeder fiber. In addition, the ACS can distinguish optical fiber fault from the transmission services to other customers in the FTTH-PON. It is essential to use a wavelength different from the triple-play services operating wavelengths for failure detection. ACS is using the operating wavelength 1625 nm for monitoring and failure detection control. Our solution works on a standard local area network (LAN) using a specially designed hardware interfaced with a microcontroller integrated Ethernet.Keywords: ACS, monitoring tool, FTTH-PON.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26821336 A New Performance Characterization of Transient Analysis Method
Authors: José Peralta, Gabriela Peretti, Eduardo Romero, Carlos Marqués
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This paper proposes a new performance characterization for the test strategy intended for second order filters denominated Transient Analysis Method (TRAM). We evaluate the ability of the addressed test strategy for detecting deviation faults under simultaneous statistical fluctuation of the non-faulty parameters. For this purpose, we use Monte Carlo simulations and a fault model that considers as faulty only one component of the filter under test while the others components adopt random values (within their tolerance band) obtained from their statistical distributions. The new data reported here show (for the filters under study) the presence of hard-to-test components and relatively low fault coverage values for small deviation faults. These results suggest that the fault coverage value obtained using only nominal values for the non-faulty components (the traditional evaluation of TRAM) seem to be a poor predictor of the test performance.
Keywords: testing, fault analysis, analog filter test, parametric faults detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14511335 Improving Classification in Bayesian Networks using Structural Learning
Authors: Hong Choon Ong
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Naïve Bayes classifiers are simple probabilistic classifiers. Classification extracts patterns by using data file with a set of labeled training examples and is currently one of the most significant areas in data mining. However, Naïve Bayes assumes the independence among the features. Structural learning among the features thus helps in the classification problem. In this study, the use of structural learning in Bayesian Network is proposed to be applied where there are relationships between the features when using the Naïve Bayes. The improvement in the classification using structural learning is shown if there exist relationship between the features or when they are not independent.Keywords: Bayesian Network, Classification, Naïve Bayes, Structural Learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25881334 Conditions for Fault Recovery of Interconnected Asynchronous Sequential Machines with State Feedback
Authors: Jung–Min Yang
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In this paper, fault recovery for parallel interconnected asynchronous sequential machines is studied. An adversarial input can infiltrate into one of two submachines comprising parallel composition of the considered asynchronous sequential machine, causing an unauthorized state transition. The control objective is to elucidate the condition for the existence of a corrective controller that makes the closed-loop system immune against any occurrence of adversarial inputs. In particular, an efficient existence condition is presented that does not need the complete modeling of the interconnected asynchronous sequential machine.Keywords: Asynchronous sequential machines, parallel composition, corrective control, fault tolerance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8321333 An Intelligent Combined Method Based on Power Spectral Density, Decision Trees and Fuzzy Logic for Hydraulic Pumps Fault Diagnosis
Authors: Kaveh Mollazade, Hojat Ahmadi, Mahmoud Omid, Reza Alimardani
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Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. The aim of this work is to investigate the effectiveness of a new fault diagnosis method based on power spectral density (PSD) of vibration signals in combination with decision trees and fuzzy inference system (FIS). To this end, a series of studies was conducted on an external gear hydraulic pump. After a test under normal condition, a number of different machine defect conditions were introduced for three working levels of pump speed (1000, 1500, and 2000 rpm), corresponding to (i) Journal-bearing with inner face wear (BIFW), (ii) Gear with tooth face wear (GTFW), and (iii) Journal-bearing with inner face wear plus Gear with tooth face wear (B&GW). The features of PSD values of vibration signal were extracted using descriptive statistical parameters. J48 algorithm is used as a feature selection procedure to select pertinent features from data set. The output of J48 algorithm was employed to produce the crisp if-then rule and membership function sets. The structure of FIS classifier was then defined based on the crisp sets. In order to evaluate the proposed PSD-J48-FIS model, the data sets obtained from vibration signals of the pump were used. Results showed that the total classification accuracy for 1000, 1500, and 2000 rpm conditions were 96.42%, 100%, and 96.42% respectively. The results indicate that the combined PSD-J48-FIS model has the potential for fault diagnosis of hydraulic pumps.Keywords: Power Spectral Density, Machine ConditionMonitoring, Hydraulic Pump, Fuzzy Logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26911332 Hierarchical Checkpoint Protocol in Data Grids
Authors: Rahma Souli-Jbali, Minyar Sassi Hidri, Rahma Ben Ayed
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Grid of computing nodes has emerged as a representative means of connecting distributed computers or resources scattered all over the world for the purpose of computing and distributed storage. Since fault tolerance becomes complex due to the availability of resources in decentralized grid environment, it can be used in connection with replication in data grids. The objective of our work is to present fault tolerance in data grids with data replication-driven model based on clustering. The performance of the protocol is evaluated with Omnet++ simulator. The computational results show the efficiency of our protocol in terms of recovery time and the number of process in rollbacks.Keywords: Data grids, fault tolerance, chandy-lamport, clustering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9361331 A Novel Approach for Protein Classification Using Fourier Transform
Authors: A. F. Ali, D. M. Shawky
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Discovering new biological knowledge from the highthroughput biological data is a major challenge to bioinformatics today. To address this challenge, we developed a new approach for protein classification. Proteins that are evolutionarily- and thereby functionally- related are said to belong to the same classification. Identifying protein classification is of fundamental importance to document the diversity of the known protein universe. It also provides a means to determine the functional roles of newly discovered protein sequences. Our goal is to predict the functional classification of novel protein sequences based on a set of features extracted from each protein sequence. The proposed technique used datasets extracted from the Structural Classification of Proteins (SCOP) database. A set of spectral domain features based on Fast Fourier Transform (FFT) is used. The proposed classifier uses multilayer back propagation (MLBP) neural network for protein classification. The maximum classification accuracy is about 91% when applying the classifier to the full four levels of the SCOP database. However, it reaches a maximum of 96% when limiting the classification to the family level. The classification results reveal that spectral domain contains information that can be used for classification with high accuracy. In addition, the results emphasize that sequence similarity measures are of great importance especially at the family level.
Keywords: Bioinformatics, Artificial Neural Networks, Protein Sequence Analysis, Feature Extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23431330 Testing Loaded Programs Using Fault Injection Technique
Authors: S. Manaseer, F. A. Masooud, A. A. Sharieh
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Fault tolerance is critical in many of today's large computer systems. This paper focuses on improving fault tolerance through testing. Moreover, it concentrates on the memory faults: how to access the editable part of a process memory space and how this part is affected. A special Software Fault Injection Technique (SFIT) is proposed for this purpose. This is done by sequentially scanning the memory of the target process, and trying to edit maximum number of bytes inside that memory. The technique was implemented and tested on a group of programs in software packages such as jet-audio, Notepad, Microsoft Word, Microsoft Excel, and Microsoft Outlook. The results from the test sample process indicate that the size of the scanned area depends on several factors. These factors are: process size, process type, and virtual memory size of the machine under test. The results show that increasing the process size will increase the scanned memory space. They also show that input-output processes have more scanned area size than other processes. Increasing the virtual memory size will also affect the size of the scanned area but to a certain limit.Keywords: Complex software systems, Error detection, Fault tolerance, Injection and testing methodology, Memory faults, Process and virtual memory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18741329 Vehicle Type Classification with Geometric and Appearance Attributes
Authors: Ghada S. Moussa
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With the increase in population along with economic prosperity, an enormous increase in the number and types of vehicles on the roads occurred. This fact brings a growing need for efficiently yet effectively classifying vehicles into their corresponding categories, which play a crucial role in many areas of infrastructure planning and traffic management.
This paper presents two vehicle-type classification approaches; 1) geometric-based and 2) appearance-based. The two classification approaches are used for two tasks: multi-class and intra-class vehicle classifications. For the evaluation purpose of the proposed classification approaches’ performance and the identification of the most effective yet efficient one, 10-fold cross-validation technique is used with a large dataset. The proposed approaches are distinguishable from previous research on vehicle classification in which: i) they consider both geometric and appearance attributes of vehicles, and ii) they perform remarkably well in both multi-class and intra-class vehicle classification. Experimental results exhibit promising potentials implementations of the proposed vehicle classification approaches into real-world applications.
Keywords: Appearance attributes, Geometric attributes, Support vector machine, Vehicle classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42661328 Reducing Test Vectors Count Using Fault Based Optimization Schemes in VLSI Testing
Authors: Vinod Kumar Khera, R. K. Sharma, A. K. Gupta
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Power dissipation increases exponentially during test mode as compared to normal operation of the circuit. In extreme cases, test power is more than twice the power consumed during normal operation mode. Test vector generation scheme is key component in deciding the power hungriness of a circuit during testing. Test vector count and consequent leakage current are functions of test vector generation scheme. Fault based test vector count optimization has been presented in this work. It helps in reducing test vector count and the leakage current. In the presented scheme, test vectors have been reduced by extracting essential child vectors. The scheme has been tested experimentally using stuck at fault models and results ensure the reduction in test vector count.Keywords: Low power VLSI testing, independent fault, essential faults, test vector reduction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1411