Search results for: fault localization

Authors: Sungsik Jo, Hyeonwoo Kim, Iksu Choi, Hunmo Kim

Abstract:

In the SHP, LVDT sensor is for detecting the length changes of the EHA output, and the thrust of the EHA is controlled by the pressure sensor. Sensor is possible to cause hardware fault by internal problem or external disturbance. The EHA of SHP is able to be uncontrollable due to control by feedback from uncertain information, on this paper; the sliding mode observer algorithm estimates the original sensor output information in permanent sensor fault. The proposed algorithm shows performance to recovery fault of disconnection and short circuit basically, also the algorithm detect various of sensor fault mode.

Keywords: Smart Hybrid Powerpack (SHP), Electro Hydraulic Actuator (EHA), Permanent Sensor fault tolerance, Sliding mode observer (SMO), Graphic User Interface (GUI).

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Authors: Shrawan Kumar, D. K. Lobiyal

Abstract:

In this paper, we propose improved versions of DVHop algorithm as QDV-Hop algorithm and UDV-Hop algorithm for better localization without the need for additional range measurement hardware. The proposed algorithm focuses on third step of DV-Hop, first error terms from estimated distances between unknown node and anchor nodes is separated and then minimized. In the QDV-Hop algorithm, quadratic programming is used to minimize the error to obtain better localization. However, quadratic programming requires a special optimization tool box that increases computational complexity. On the other hand, UDV-Hop algorithm achieves localization accuracy similar to that of QDV-Hop by solving unconstrained optimization problem that results in solving a system of linear equations without much increase in computational complexity. Simulation results show that the performance of our proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop and DV-Hop based algorithms in all considered scenarios.

Keywords: Wireless sensor networks, Error term, DV-Hop algorithm, Localization.

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Authors: Madiha Tariq, Hena Rabbani

Abstract:

Recently, cavity-optomechanics becomes an extensive research field that has manipulated the mechanical effects of light for coupling of the optical field with other physical objects specifically with regards to dynamical localization. We investigate the dynamical localization (both in momentum and position space) for a vibrational mirror in a Fabry-Pérot cavity driven by a single mode optical field and a transverse probe field. The weak probe field phenomenon results in classical chaos in phase space and spatio temporal dynamics in position |ψ(x)²| and momentum space |ψ(p)²| versus time show quantum localization in both momentum and position space. Also, we discuss the parametric dependencies of dynamical localization for a designated set of parameters to be experimentally feasible. Our work opens an avenue to manipulate the other optical phenomena and applicability of proposed work can be prolonged to turn-able laser sources in the future.

Keywords: Dynamical localization, cavity optomechanics, hamiltonian chaos, probe field.

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Authors: R. Khadim, M. Erritali, A. Maaden

Abstract:

Localization of nodes is one of the key issues of Wireless Sensor Network (WSN) that gained a wide attention in recent years. The existing localization techniques can be generally categorized into two types: range-based and range-free. Compared with rang-based schemes, the range-free schemes are more costeffective, because no additional ranging devices are needed. As a result, we focus our research on the range-free schemes. In this paper we study three types of range-free location algorithms to compare the localization error and energy consumption of each one. Centroid algorithm requires a normal node has at least three neighbor anchors, while DV-hop algorithm doesn’t have this requirement. The third studied algorithm is the amorphous algorithm similar to DV-Hop algorithm, and the idea is to calculate the hop distance between two nodes instead of the linear distance between them. The simulation results show that the localization accuracy of the amorphous algorithm is higher than that of other algorithms and the energy consumption does not increase too much.

Keywords: Wireless Sensor Networks, Node Localization, Centroid Algorithm, DV–Hop Algorithm, Amorphous Algorithm.

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Authors: L.Tahmooresnejad, M.A.Shafia, R.Salami

Abstract:

Technology transfer is a common method for companies to acquire new technology and presents both challenges and substantial benefits. In some cases especially in developing countries, the mere possession of technology does not guarantee a competitive advantage if the appropriate infrastructure is not in place. In this paper, we identify the localization factors needed to provide a better understanding of the conditions necessary for localization in order to benefit from future technology developments. Our theoretical and empirical analyses allow us to identify several factors in the technology transfer process that affect localization and provide leverage in enhancing capabilities and absorptive capacity.The impact factors are categorized within different groups of government, firms, institutes and market, and are verified through the empirical survey of a technology transfer experience. Moreover, statistical analysis has allowed a deeper understanding of the importance of each factor and has enabled each group to prioritize their organizational policies to effectively localize their technology.

Keywords: Absorption Capacity, Adaptation, Technology Transfer, Technology Localization

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Authors: R. Rajeswari, N. Kamaraj

Abstract:

In this paper, Wavelet based ANFIS for finding inter turn fault of generator is proposed. The detector uniquely responds to the winding inter turn fault with remarkably high sensitivity. Discrimination of different percentage of winding affected by inter turn fault is provided via ANFIS having an Eight dimensional input vector. This input vector is obtained from features extracted from DWT of inter turn faulty current leaving the generator phase winding. Training data for ANFIS are generated via a simulation of generator with inter turn fault using MATLAB. The proposed algorithm using ANFIS is giving satisfied performance than ANN with selected statistical data of decomposed levels of faulty current.

Keywords: Winding InterTurn fault, ANN, ANFIS, and DWT.

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Authors: Marian Dragomir, Alin Dragomir

Abstract:

In the paper, two fault location algorithms are presented for transmission lines which use the line parameters to estimate the distance to the fault. The first algorithm uses only the measurements from one end of the line and the positive and zero sequence parameters of the line, while the second one uses the measurements from both ends of the line and only the positive sequence parameters of the line. The algorithms were tested using a transmission grid transposed in MATLAB. In a first stage it was established a fault location base line, where the algorithms mentioned above estimate the fault locations using the exact line parameters. After that, the positive and zero sequence resistance and reactance of the line were calculated again for different ground resistivity values and then the fault locations were estimated again in order to compare the results with the base line results. The results show that the algorithm which uses the zero sequence impedance of the line is the most sensitive to the line parameters modifications. The other algorithm is less sensitive to the line parameters modification.

Keywords: Estimation algorithms, fault location, line parameters, simulation tool.

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Authors: Gyumin Hwang, Jihong Lee

Abstract:

This paper studied the CSS-based indoor localization system which is easy to implement, inexpensive to compose the systems, additionally CSS-based indoor localization system covers larger area than other system. However, this system has problem which is affected by reflected distance data. This problem in localization is caused by the multi-path effect. Error caused by multi-path is difficult to be corrected because the indoor environment cannot be described. In this paper, in order to solve the problem by multi-path, we have supplemented the localization system by using pattern matching method based on extended database. Thereby, this method improves precision of estimated. Also this method is verified by experiments in gymnasium. Database was constructed by 1m intervals, and 16 sample data were collected from random position inside the region of DB points. As a result, this paper shows higher accuracy than existing method through graph and table.

Keywords: Chirp Spread Spectrum (CSS), Indoor Localization, Pattern-Matching, Time of Arrival (ToA), Multi-Path, Mahalanobis Distance, Reception Rate, Simultaneous Localization and Mapping (SLAM), Laser Range Finder (LRF).

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Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin

Abstract:

This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of singleparameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.

Keywords: Hybrid fault diagnosis, Dynamic neural networks, Nonlinear systems.

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Authors: Win Win Tun, Han Su Yin, Ohn Zin Lin

Abstract:

Transmission networks are an important part of an electric power system. The transmission lines not only have high power transmission capacity but also they are prone of larger magnitudes. Different types of faults occur in transmission lines such as single line to ground (L-G) fault, double line to ground (L-L-G) fault, line to line (L-L) fault and three phases (L-L-L) fault. These faults are needed to be cleared quickly in order to reduce damage caused to the system and they have high impact on the electrical power system equipment’s which are connected in transmission line. The main fault in transmission line is L-G fault. Therefore, protection relays are needed to protect transmission line. Overcurrent and earth fault relay is an important relay used to protect transmission lines, distribution feeders, transformers and bus couplers etc. Sometimes these relays can be used as main protection or backup protection. The modeling of protection relays is important to indicate the effects of network parameters and configurations on the operation of relays. Therefore, the modeling of overcurrent and earth fault relay is described in this paper. The overcurrent and earth fault relays with standard inverse definite minimum time are modeled and simulated by using MATLAB/Simulink software. The developed model was tested with L-G, L-L-G, L-L and L-L-L faults with various fault locations and fault resistance (0.001Ω). The simulation results are obtained by MATLAB software which shows the feasibility of analysis of transmission line protection with overcurrent and earth fault relay.

Keywords: Transmission line, overcurrent and earth fault relay, standard inverse definite minimum time, various faults, MATLAB Software.

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Authors: Hsiang-Wen Hsieh, Chin-Chia Wu, Hung-Hsiu Yu, Shu-Fan Liu

Abstract:

Localization is one of the critical issues in the field of robot navigation. With an accurate estimate of the robot pose, robots will be capable of navigating in the environment autonomously and efficiently. In this paper, a hybrid Distributed Vision System (DVS) for robot localization is presented. The presented approach integrates odometry data from robot and images captured from overhead cameras installed in the environment to help reduce possibilities of fail localization due to effects of illumination, encoder accumulated errors, and low quality range data. An odometry-based motion model is applied to predict robot poses, and robot images captured by overhead cameras are then used to update pose estimates with HSV histogram-based measurement model. Experiment results show the presented approach could localize robots in a global world coordinate system with localization errors within 100mm.

Keywords: Distributed Vision System, Localization, Measurement model, Motion model

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Authors: Shin Je Lee, Go Bong Choi, Jeong Cheol Seo, Jong Min Lee, Gibaek Lee

Abstract:

Water pipe network is installed underground and once equipped, it is difficult to recognize the state of pipes when the leak or burst happens. Accordingly, post management is often delayed after the fault occurs. Therefore, the systematic fault management system of water pipe network is required to prevent the accident and minimize the loss. In this work, we develop online fault detection system of water pipe network using data of pipes such as flow rate or pressure. The transient model describing water flow in pipelines is presented and simulated using MATLAB. The fault situations such as the leak or burst can be also simulated and flow rate or pressure data when the fault happens are collected. Faults are detected using statistical methods of fast Fourier transform and discrete wavelet transform, and they are compared to find which method shows the better fault detection performance.

Keywords: fault detection, water pipeline model, fast Fourier transform, discrete wavelet transform.

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Authors: Yali Zheng, Peipei Luo, Shinan Chen, Jiasheng Hao, Hong Cheng

Abstract:

Most of traditional visual indoor navigation algorithms and methods only consider the localization in ordinary daytime, while we focus on the indoor re-localization in low light in the paper. As RGB images are degraded in low light, less discriminative infrared and depth image pairs are taken, as the input, by RGB-D cameras, the most similar candidates, as the output, are searched from databases which is built in the bag-of-word framework. Epipolar constraints can be used to relocalize the query infrared and depth image sequence. We evaluate our method in two datasets captured by Kinect2. The results demonstrate very promising re-localization results for indoor navigation system in low light environments.

Keywords: Indoor navigation, low light, RGB-D camera, vision based.

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Authors: M. Ovinis, D. Kerr, K. Bouazza-Marouf, M. Vloeberghs

Abstract:

The use of anatomical landmarks as a basis for image to patient registration is appealing because the registration may be performed retrospectively. We have previously proposed the use of two anatomical soft tissue landmarks of the head, the canthus (corner of the eye) and the tragus (a small, pointed, cartilaginous flap of the ear), as a registration basis for an automated CT image to patient registration system, and described their localization in patient space using close range photogrammetry. In this paper, the automatic localization of these landmarks in CT images, based on their curvature saliency and using a rule based system that incorporates prior knowledge of their characteristics, is described. Existing approaches to landmark localization in CT images are predominantly semi-automatic and primarily for localizing internal landmarks. To validate our approach, the positions of the landmarks localized automatically and manually in near isotropic CT images of 102 patients were compared. The average difference was 1.2mm (std = 0.9mm, max = 4.5mm) for the medial canthus and 0.8mm (std = 0.6mm, max = 2.6mm) for the tragus. The medial canthus and tragus can be automatically localized in CT images, with performance comparable to manual localization, based on the approach presented.

Keywords: Anatomical Landmarks, CT, Localization.

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Authors: V. Malathi, N.S.Marimuthu

Abstract:

This paper presents a wavelet transform and Support Vector Machine (SVM) based algorithm for estimating fault location on transmission lines. The Discrete wavelet transform (DWT) is used for data pre-processing and this data are used for training and testing SVM. Five types of mother wavelet are used for signal processing to identify a suitable wavelet family that is more appropriate for use in estimating fault location. The results demonstrated the ability of SVM to generalize the situation from the provided patterns and to accurately estimate the location of faults with varying fault resistance.

Keywords: Fault location, support vector machine, supportvector regression, transmission lines, wavelet transform.

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Authors: Magdy B. Eteiba, Wael Ismael Wahba, Shimaa Barakat

Abstract:

This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system.

Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location.

Keywords: ANFIS, Fault location, Underground Cable, Wavelet Transform.

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Authors: C. Kalamani, V. Abishek Karthick, S. Anitha, K. Kavin Kumar

Abstract:

The fault tolerant system plays a crucial role in the critical applications which are being used in the present scenario. A fault may change the functionality of circuits. Aim of this paper is to design multiplier using fault tolerant hybrid full adder. Fault tolerant hybrid full adder is designed to check and repair any fault in the circuit using self-checking circuit and the self-repairing circuit. Further, the use of conventional logic circuits may result in more area, delay as well as power consumption. In order to reduce these parameters of the circuit, GDI (Gate Diffusion Input) techniques with less number of transistors are used compared to conventional full adder circuit. This reduces the area, delay and power consumption. The proposed method solves the major problems occurring in the most crucial and critical applications.

Keywords: Gate diffusion input, hybrid full adder, self-checking, fault tolerant.

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Authors: Sallem F., Dahhou B., Kamoun A.

Abstract:

In this work, the main problem considered is the  detection and the isolation of the actuator fault. A new formulation of  the linear system is generated to obtain the conditions of the actuator  fault diagnosis. The proposed method is based on the representation  of the actuator as a subsystem connected with the process system in  cascade manner. The designed formulation is generated to obtain the  conditions of the actuator fault detection and isolation. Detectability  conditions are expressed in terms of the invertibility notions. An  example and a comparative analysis with the classic formulation  illustrate the performances of such approach for simple actuator fault  diagnosis by using the linear model of nuclear reactor.

 

Keywords: Actuator fault, Fault detection, left invertibility, nuclear reactor, observability, parameter intervals, system inversion.

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Authors: Xing Xiong, Byung-Jae Choi

Abstract:

It is important for an autonomous mobile robot to know where it is in any time in an indoor environment. In this paper, we design a relative self-localization algorithm. The algorithm compare the interest point in two images and compute the relative displacement and orientation to determent the posture. Firstly, we use the SURF algorithm to extract the interest points of the ceiling. Second, in order to reduce amount of calculation, a replacement SURF is used to extract orientation and description of the interest points. At last, according to the transformation of the interest points in two images, the relative self-localization of the mobile robot will be estimated greatly.

Keywords: Relative Self-Localization Posture, SURF, Natural Landmark, Interest Point.

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Authors: Parvinder S. Sandhu, Satish Kumar Dhiman, Anmol Goyal

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Fault-proneness of a software module is the probability that the module contains faults. A correlation exists between the fault-proneness of the software and the measurable attributes of the code (i.e. the static metrics) and of the testing (i.e. the dynamic metrics). Early detection of fault-prone software components enables verification experts to concentrate their time and resources on the problem areas of the software system under development. This paper introduces Genetic Algorithm based software fault prediction models with Object-Oriented metrics. The contribution of this paper is that it has used Metric values of JEdit open source software for generation of the rules for the classification of software modules in the categories of Faulty and non faulty modules and thereafter empirically validation is performed. The results shows that Genetic algorithm approach can be used for finding the fault proneness in object oriented software components.

Keywords: Genetic Algorithms, Software Fault, Classification, Object Oriented Metrics.

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Authors: Wook-Won Kim, Sung-Yul Kim, Jin-O Kim

Abstract:

The fault current levels through the electric devices have a significant impact on failure probability. New fault current results in exceeding the rated capacity of circuit breaker and switching equipments and changes operation characteristic of overcurrent relay. In order to solve these problems, SFCL (Superconducting Fault Current Limiter) has rising as one of new alternatives so as to improve these problems. A fault current reduction differs depending on installed location. Therefore, a location of SFCL is very important. Also, SFCL decreases the fault current, and it prevents surrounding protective devices to be exposed to fault current, it then will bring a change of reliability. In this paper, we propose method which determines the optimal location when SFCL is installed in power system. In addition, the reliability about the power system which SFCL was installed is evaluated. The efficiency and effectiveness of this method are also shown by numerical examples and the reliability indices are evaluated in this study at each load points. These results show a reliability change of a system when SFCL was installed.

Keywords: Superconducting Fault Current Limiter, OptimalLocation, Reliability

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Authors: Mahanijah Md Kamal., Dingli Yu

Abstract:

This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC stack. One actuator fault, one component fault and three sensor faults have been introduced to the PEMFC systems experience faults between -7% to +10% of fault size in real-time operation. To validate the results, a benchmark model developed by Michigan University is used in the simulation to investigate the effect of these five faults. The developed independent RBF model is tested on MATLAB R2009a/Simulink environment. The simulation results confirm the effectiveness of the proposed method for FDI under an open-loop condition. By using this method, the RBF networks able to detect and isolate all five faults accordingly and accurately.

Keywords: Polymer electrolyte membrane fuel cell, radial basis function neural networks, fault detection, fault isolation.

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Authors: Sarah Odofin, Zhiwei Gao, Sun Kai

Abstract:

Operations, maintenance and reliability of wind turbines have received much attention over the years due to the rapid expansion of wind farms. This paper explores early fault diagnosis technique for a 5MW wind turbine system subjected to multiple faults, where genetic optimization algorithm is employed to make the residual sensitive to the faults, but robust against disturbances. The proposed technique has a potential to reduce the downtime mostly caused by the breakdown of components and exploit the productivity consistency by providing timely fault alarms. Simulation results show the effectiveness of the robust fault detection methods used under Matlab/Simulink/Gatool environment.

Keywords: Disturbance robustness, fault monitoring and detection, genetic algorithm and observer technique.

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Authors: Junyou Shi, Weiwei Cui

Abstract:

Testability modeling is a commonly used method in testability design and analysis of system. A dependency matrix will be obtained from testability modeling, and we will give a quantitative evaluation about fault detection and isolation. Based on the dependency matrix, we can obtain the diagnosis tree. The tree provides the procedures of the fault detection and isolation. But the dependency matrix usually includes built-in test (BIT) and manual test in fact. BIT runs the test automatically and is not limited by the procedures. The method above cannot give a more efficient diagnosis and use the advantages of the BIT. A Comprehensive method of fault detection and isolation is proposed. This method combines the advantages of the BIT and Manual test by splitting the matrix. The result of the case study shows that the method is effective.

Keywords: BIT, fault detection, fault isolation, testability modeling.

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Authors: Amany M. El-Zonkoly, Hussein Desouki

Abstract:

Distance protection of transmission lines including advanced flexible AC transmission system (FACTS) devices has been a very challenging task. FACTS devices of interest in this paper are static synchronous series compensators (SSSC) and unified power flow controller (UPFC). In this paper, a new algorithm is proposed to detect and classify the fault and identify the fault position in a transmission line with respect to a FACTS device placed in the midpoint of the transmission line. Discrete wavelet transformation and wavelet entropy calculations are used to analyze during fault current and voltage signals of the compensated transmission line. The proposed algorithm is very simple and accurate in fault detection and classification. A variety of fault cases and simulation results are introduced to show the effectiveness of such algorithm.

Keywords: Entropy calculation, FACTS, SSSC, UPFC, wavelet transform.

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Authors: Nurbanu Guzey, S. Jagannathan

Abstract:

Locating Radio Controlled (RC) devices using their unintended emissions has a great interest considering security concerns. Weak nature of these emissions requires near field localization approach since it is hard to detect these signals in far field region of array. Instead of only angle estimation, near field localization also requires range estimation of the source which makes this method more complicated than far field models. Challenges of locating such devices in a near field region and real time environment are analyzed in this paper. An ESPRIT like near field localization scheme is utilized for both angle and range estimation. 1-D search with symmetric subarrays is provided. Two 7 element uniform linear antenna arrays (ULA) are employed for locating RC source. Experiment results of location estimation for one unintended emitting walkie-talkie for different positions are given.

Keywords: Localization, angle of arrival (AoA), range estimation, array signal processing, ESPRIT, uniform linear array (ULA).

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Authors: Victor Krebss

Abstract:

Task of object localization is one of the major challenges in creating intelligent transportation. Unfortunately, in densely built-up urban areas, localization based on GPS only produces a large error, or simply becomes impossible. New opportunities arise for the localization due to the rapidly emerging concept of a wireless ad-hoc network. Such network, allows estimating potential distance between these objects measuring received signal level and construct a graph of distances in which nodes are the localization objects, and edges - estimates of the distances between pairs of nodes. Due to the known coordinates of individual nodes (anchors), it is possible to determine the location of all (or part) of the remaining nodes of the graph. Moreover, road map, available in digital format can provide localization routines with valuable additional information to narrow node location search. However, despite abundance of well-known algorithms for solving the problem of localization and significant research efforts, there are still many issues that currently are addressed only partially. In this paper, we propose localization approach based on the graph mapped distances on the digital road map data basis. In fact, problem is reduced to distance graph embedding into the graph representing area geo location data. It makes possible to localize objects, in some cases even if only one reference point is available. We propose simple embedding algorithm and sample implementation as spatial queries over sensor network data stored in spatial database, allowing employing effectively spatial indexing, optimized spatial search routines and geometry functions.

Keywords: Intelligent Transportation System, Sensor Network, Localization, Spatial Query, GIS, Graph Embedding.

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Authors: Adeniran Ademuwagun, Alastair Allen

Abstract:

The relationship dependence between RSS and distance in an enclosed environment is an important consideration because it is a factor that can influence the reliability of any localization algorithm founded on RSS. Several algorithms effectively reduce the variance of RSS to improve localization or accuracy performance. Our proposed algorithm essentially avoids this pitfall and consequently, its high adaptability in the face of erratic radio signal. Using 3 anchors in close proximity of each other, we are able to establish that RSS can be used as reliable indicator for localization with an acceptable degree of accuracy. Inherent in this concept, is the ability for each prospective anchor to validate (guarantee) the position or the proximity of the other 2 anchors involved in the localization and vice versa. This procedure ensures that the uncertainties of radio signals due to multipath effects in enclosed environments are minimized. A major driver of this idea is the implicit topological relationship among sensors due to raw radio signal strength. The algorithm is an area based algorithm; however, it does not trade accuracy for precision (i.e the size of the returned area).

Keywords: Anchor nodes, centroid algorithm, communication graph, received signal strength (RSS).

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Authors: A. H. Akhaveissy

Abstract:

Nonlinear finite element method with eight noded isoparametric quadrilateral element is used for prediction of loaddeformation behavior including bearing capacity of foundations. Modified generalized plasticity model with non-associated flow rule is applied for analysis of soil-footing system. Also Von Mises and Tresca criterions are used for simulation of soil behavior. Modified generalized plasticity model is able to simulate load-deformation including softening behavior. Localization phenomena are considered by different meshes. Localization phenomena have not been seen in the examples. Predictions by modified generalized plasticity model show good agreement with laboratory data and theoretical prediction in comparison the other models.

Keywords: Localization phenomena, Generalized plasticity, Non-associated Flow Rule

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Authors: Pushkar Tripathi, Abhishek Sharma, G. N. Pillai, Indira Gupta

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This paper presents a new approach for the protection of Thyristor-Controlled Series Compensator (TCSC) line using Support Vector Machine (SVM). One SVM is trained for fault classification and another for section identification. This method use three phase current measurement that results in better speed and accuracy than other SVM based methods which used single phase current measurement. This makes it suitable for real-time protection. The method was tested on 10,000 data instances with a very wide variation in system conditions such as compensation level, source impedance, location of fault, fault inception angle, load angle at source bus and fault resistance. The proposed method requires only local current measurement.

Keywords: Fault Classification, Section Identification, Feature Selection, Support Vector Machine (SVM), Thyristor-Controlled Series Compensator (TCSC)

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