Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1835

Search results for: analog faults diagnosis

1835 Time Parameter Based for the Detection of Catastrophic Faults in Analog Circuits

Authors: Arabi Abderrazak, Bourouba Nacerdine, Ayad Mouloud, Belaout Abdeslam

Abstract:

In this paper, a new test technique of analog circuits using time mode simulation is proposed for the single catastrophic faults detection in analog circuits. This test process is performed to overcome the problem of catastrophic faults being escaped in a DC mode test applied to the inverter amplifier in previous research works. The circuit under test is a second-order low pass filter constructed around this type of amplifier but performing a function that differs from that of the previous test. The test approach performed in this work is based on two key- elements where the first one concerns the unique square pulse signal selected as an input vector test signal to stimulate the fault effect at the circuit output response. The second element is the filter response conversion to a square pulses sequence obtained from an analog comparator. This signal conversion is achieved through a fixed reference threshold voltage of this comparison circuit. The measurement of the three first response signal pulses durations is regarded as fault effect detection parameter on one hand, and as a fault signature helping to hence fully establish an analog circuit fault diagnosis on another hand. The results obtained so far are very promising since the approach has lifted up the fault coverage ratio in both modes to over 90% and has revealed the harmful side of faults that has been masked in a DC mode test.

Keywords: analog circuits, analog faults diagnosis, catastrophic faults, fault detection

Procedia PDF Downloads 358
1834 Fault Diagnosis of Squirrel-Cage Induction Motor by a Neural Network Multi-Models

Authors: Yahia. Kourd, N. Guersi D. Lefebvre

Abstract:

In this paper we propose to study the faults diagnosis in squirrel-cage induction motor using MLP neural networks. We use neural healthy and faulty models of the behavior in order to detect and isolate some faults in machine. In the first part of this work, we have created a neural model for the healthy state using Matlab and a motor located in LGEB by acquirins data inputs and outputs of this engine. Then we detected the faults in the machine by residual generation. These residuals are not sufficient to isolate the existing faults. For this reason, we proposed additive neural networks to represent the faulty behaviors. From the analysis of these residuals and the choice of a threshold we propose a method capable of performing the detection and diagnosis of some faults in asynchronous machines with squirrel cage rotor.

Keywords: faults diagnosis, neural networks, multi-models, squirrel-cage induction motor

Procedia PDF Downloads 511
1833 Faults Diagnosis by Thresholding and Decision tree with Neuro-Fuzzy System

Authors: Y. Kourd, D. Lefebvre

Abstract:

The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. This paper proposes a method of fault diagnosis based on a neuro-fuzzy hybrid structure. This hybrid structure combines the selection of threshold and decision tree. The validation of this method is obtained with the DAMADICS benchmark. In the first phase of the method, a model will be constructed that represents the normal state of the system to fault detection. Signatures of the faults are obtained with residuals analysis and selection of appropriate thresholds. These signatures provide groups of non-separable faults. In the second phase, we build faulty models to see the flaws in the system that cannot be isolated in the first phase. In the latest phase we construct the tree that isolates these faults.

Keywords: decision tree, residuals analysis, ANFIS, fault diagnosis

Procedia PDF Downloads 517
1832 Observer-based Robust Diagnosis for Wind Turbine System

Authors: Sarah Odofin, Zhiwei Gao

Abstract:

Operations and maintenance of wind turbine have received much attention by researcher due to rapid expansion of wind farms. This paper explores a novel fault diagnosis that is designed and optimized to be very sensitive to faults and robust to disturbances. The faults considered are the sensor faults of which the augmented observer is considered to enlarge faults and to be robust to disturbance. A qualitative model based analysis is proposed for early fault diagnosis to minimize downtime mostly caused by components breakdown and exploit productivity. Simulation results are computed validating the models provided which demonstrates system performance using practical application of fault type examples. The results demonstrate the effectiveness of the developed techniques investigated in a Matlab/Simulink environment.

Keywords: wind turbine, condition monitoring, genetic algorithm, fault diagnosis, augmented observer, disturbance robustness, fault estimation, sensor monitoring

Procedia PDF Downloads 427
1831 Multiple Fault Detection and Classification in a Coupled Motor with Rotor Using Artificial Neural Network

Authors: Mehrdad Nouri Khajavi, Gollamhassan Payganeh, Mohsen Fallah Tafti

Abstract:

Fault diagnosis is an important aspect of maintaining rotating machinery health and increasing productivity. Many researches has been done in this regards. Many faults such as unbalance, misalignment, looseness, bearing faults, etc. have been considered and diagnosed with different techniques. Most of the researches in fault diagnosis of rotating machinery deal with single fault. Where as in reality faults usually occur simultaneously and it is, therefore, necessary to recognize them at the same time. In this research, two of the most common faults namely unbalance and misalignment have been considered simultaneously with different intensity and then identified and classified with the use of Multi-Layer Perception Neural Network (MLPNN). Processed Vibration signals are used as the input to the MLPNN, and the class of mixed unbalancy, and misalignment is the output of the NN.

Keywords: unbalance, parallel misalignment, combined faults, vibration signals

Procedia PDF Downloads 266
1830 Multivariate Statistical Process Monitoring of Base Metal Flotation Plant Using Dissimilarity Scale-Based Singular Spectrum Analysis

Authors: Syamala Krishnannair

Abstract:

A multivariate statistical process monitoring methodology using dissimilarity scale-based singular spectrum analysis (SSA) is proposed for the detection and diagnosis of process faults in the base metal flotation plant. Process faults are detected based on the multi-level decomposition of process signals by SSA using the dissimilarity structure of the process data and the subsequent monitoring of the multiscale signals using the unified monitoring index which combines T² with SPE. Contribution plots are used to identify the root causes of the process faults. The overall results indicated that the proposed technique outperformed the conventional multivariate techniques in the detection and diagnosis of the process faults in the flotation plant.

Keywords: fault detection, fault diagnosis, process monitoring, dissimilarity scale

Procedia PDF Downloads 125
1829 Fault Diagnosis in Induction Motors Using the Discrete Wavelet Transform

Authors: Khaled Yahia

Abstract:

This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: induction motors (IMs), inter-turn short-circuits diagnosis, discrete wavelet transform (DWT), current park’s vector modulus (CPVM)

Procedia PDF Downloads 490
1828 Fault Diagnosis in Induction Motors Using Discrete Wavelet Transform

Authors: K. Yahia, A. Titaouine, A. Ghoggal, S. E. Zouzou, F. Benchabane

Abstract:

This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: Induction Motors (IMs), inter-turn short-circuits diagnosis, Discrete Wavelet Transform (DWT), Current Park’s Vector Modulus (CPVM)

Procedia PDF Downloads 472
1827 Stator Short-Circuits Fault Diagnosis in Induction Motors

Authors: K. Yahia, M. Sahraoui, A. Guettaf

Abstract:

This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental results, show the effectiveness of the used method.

Keywords: induction motors (IMs), inter-turn short-circuits diagnosis, discrete wavelet transform (DWT), Current Park’s Vector Modulus (CPVM)

Procedia PDF Downloads 374
1826 Online Electric Current Based Diagnosis of Stator Faults on Squirrel Cage Induction Motors

Authors: Alejandro Paz Parra, Jose Luis Oslinger Gutierrez, Javier Olaya Ochoa

Abstract:

In the present paper, five electric current based methods to analyze electric faults on the stator of induction motors (IM) are used and compared. The analysis tries to extend the application of the multiple reference frames diagnosis technique. An eccentricity indicator is presented to improve the application of the Park’s Vector Approach technique. Most of the fault indicators are validated and some others revised, agree with the technical literatures and published results. A tri-phase 3hp squirrel cage IM, especially modified to establish different fault levels, is used for validation purposes.

Keywords: motor fault diagnosis, induction motor, MCSA, ESA, Extended Park´s vector approach, multiparameter analysis

Procedia PDF Downloads 262
1825 Diagnosis of Induction Machine Faults by DWT

Authors: Hamidreza Akbari

Abstract:

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, electric

Procedia PDF Downloads 268
1824 Identification of Soft Faults in Branched Wire Networks by Distributed Reflectometry and Multi-Objective Genetic Algorithm

Authors: Soumaya Sallem, Marc Olivas

Abstract:

This contribution presents a method for detecting, locating, and characterizing soft faults in a complex wired network. The proposed method is based on multi-carrier reflectometry MCTDR (Multi-Carrier Time Domain Reflectometry) combined with a multi-objective genetic algorithm. In order to ensure complete network coverage and eliminate diagnosis ambiguities, the MCTDR test signal is injected at several points on the network, and the data is merged between different reflectometers (sensors) distributed on the network. An adapted multi-objective genetic algorithm is used to merge data in order to obtain more accurate faults location and characterization. The proposed method performances are evaluated from numerical and experimental results.

Keywords: wired network, reflectometry, network distributed diagnosis, multi-objective genetic algorithm

Procedia PDF Downloads 111
1823 Robust Diagnosability of PEMFC Based on Bond Graph LFT

Authors: Ould Bouamama, M. Bressel, D. Hissel, M. Hilairet

Abstract:

Fuel cell (FC) is one of the best alternatives of fossil energy. Recently, the research community of fuel cell has shown a considerable interest for diagnosis in view to ensure safety, security, and availability when faults occur in the process. The problematic for model based FC diagnosis consists in that the model is complex because of coupling of several kind of energies and the numerical values of parameters are not always known or are uncertain. The present paper deals with use of one tool: the Linear Fractional Transformation bond graph tool not only for uncertain modelling but also for monitorability (ability to detect and isolate faults) analysis and formal generation of robust fault indicators with respect to parameter uncertainties.The developed theory applied to a nonlinear FC system has proved its efficiency.

Keywords: bond graph, fuel cell, fault detection and isolation (FDI), robust diagnosis, structural analysis

Procedia PDF Downloads 300
1822 Characteristic Matrix Faults for Flight Control System

Authors: Thanh Nga Thai

Abstract:

A major issue in air transportation is in flight safety. Recent developments in control engineering have an attractive potential for resolving new issues related to guidance, navigation, and control of flying vehicles. Many future atmospheric missions will require increased on board autonomy including fault diagnosis and the subsequent control and guidance recovery actions. To improve designing system diagnostic, an efficient FDI- fault detection and identification- methodology is necessary to achieve. Contribute to characteristic of different faults in sensor and actuator in the view of mathematics brings a lot of profit in some condition changes in the system. This research finds some profit to reduce a trade-off to achieve between fault detection and performance of the closed loop system and cost and calculated in simulation.

Keywords: fault detection and identification, sensor faults, actuator faults, flight control system

Procedia PDF Downloads 340
1821 Stator Short-Circuits Fault Diagnosis in Induction Motors Using Extended Park’s Vector Approach through the Discrete Wavelet Transform

Authors: K. Yahia, A. Ghoggal, A. Titaouine, S. E. Zouzou, F. Benchabane

Abstract:

This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: Induction Motors (IMs), Inter-turn Short-Circuits Diagnosis, Discrete Wavelet Transform (DWT), Current Park’s Vector Modulus (CPVM)

Procedia PDF Downloads 482
1820 Asynchronous Sequential Machines with Fault Detectors

Authors: Seong Woo Kwak, Jung-Min Yang

Abstract:

A strategy of fault diagnosis and tolerance for asynchronous sequential machines is discussed in this paper. With no synchronizing clock, it is difficult to diagnose an occurrence of permanent or stuck-in faults in the operation of asynchronous machines. In this paper, we present a fault detector comprised of a timer and a set of static functions to determine the occurrence of faults. In order to realize immediate fault tolerance, corrective control theory is applied to designing a dynamic feedback controller. Existence conditions for an appropriate controller and its construction algorithm are presented in terms of reachability of the machine and the feature of fault occurrences.

Keywords: asynchronous sequential machines, corrective control, fault diagnosis and tolerance, fault detector

Procedia PDF Downloads 276
1819 Robust Fault Diagnosis for Wind Turbine Systems Subjected to Multi-Faults

Authors: Sarah Odofin, Zhiwei Gao, Sun Kai

Abstract:

Operations, maintenance and reliability of wind turbines have received much attention over the years due to rapid expansion of wind farms. This paper explores early fault diagnosis scale technique based on a unique scheme of a 5MW wind turbine system that is optimized by genetic algorithm to be very sensitive to faults and resilient to disturbances. A quantitative model based analysis is pragmatic for primary fault diagnosis monitoring assessment to minimize downtime mostly caused by components breakdown and exploit productivity consistency. Simulation results are computed validating the wind turbine model which demonstrates system performance in a practical application of fault type examples. The results show the satisfactory effectiveness of the applied performance investigated in a Matlab/Simulink/Gatool environment.

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

Procedia PDF Downloads 307
1818 Sensor Validation Using Bottleneck Neural Network and Variable Reconstruction

Authors: Somia Bouzid, Messaoud Ramdani

Abstract:

The success of any diagnosis strategy critically depends on the sensors measuring process variables. This paper presents a detection and diagnosis sensor faults method based on a Bottleneck Neural Network (BNN). The BNN approach is used as a statistical process control tool for drinking water distribution (DWD) systems to detect and isolate the sensor faults. Variable reconstruction approach is very useful for sensor fault isolation, this method is validated in simulation on a nonlinear system: actual drinking water distribution system. Several results are presented.

Keywords: fault detection, localization, PCA, NLPCA, auto-associative neural network

Procedia PDF Downloads 314
1817 Development of Fault Diagnosis Technology for Power System Based on Smart Meter

Authors: Chih-Chieh Yang, Chung-Neng Huang

Abstract:

In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

Procedia PDF Downloads 76
1816 Application of Support Vector Machines in Fault Detection and Diagnosis of Power Transmission Lines

Authors: I. A. Farhat, M. Bin Hasan

Abstract:

A developed approach for the protection of power transmission lines using Support Vector Machines (SVM) technique is presented. In this paper, the SVM technique is utilized for the classification and isolation of faults in power transmission lines. Accurate fault classification and location results are obtained for all possible types of short circuit faults. As in distance protection, the approach utilizes the voltage and current post-fault samples as inputs. The main advantage of the method introduced here is that the method could easily be extended to any power transmission line.

Keywords: fault detection, classification, diagnosis, power transmission line protection, support vector machines (SVM)

Procedia PDF Downloads 455
1815 The Complexity of Testing Cryptographic Devices on Input Faults

Authors: Alisher Ikramov, Gayrat Juraev

Abstract:

The production of logic devices faces the occurrence of faults during manufacturing. This work analyses the complexity of testing a special type of logic device on inverse, adhesion, and constant input faults. The focus of this work is on devices that implement cryptographic functions. The complexity values for the general case faults and for some frequently occurring subsets were determined and proved in this work. For a special case, when the length of the text block is equal to the length of the key block, the complexity of testing is proven to be asymptotically half the complexity of testing all logic devices on the same types of input faults.

Keywords: complexity, cryptographic devices, input faults, testing

Procedia PDF Downloads 141
1814 Root Mean Square-Based Method for Fault Diagnosis and Fault Detection and Isolation of Current Fault Sensor in an Induction Machine

Authors: Ahmad Akrad, Rabia Sehab, Fadi Alyoussef

Abstract:

Nowadays, induction machines are widely used in industry thankful to their advantages comparing to other technologies. Indeed, there is a big demand because of their reliability, robustness and cost. The objective of this paper is to deal with diagnosis, detection and isolation of faults in a three-phase induction machine. Among the faults, Inter-turn short-circuit fault (ITSC), current sensors fault and single-phase open circuit fault are selected to deal with. However, a fault detection method is suggested using residual errors generated by the root mean square (RMS) of phase currents. The application of this method is based on an asymmetric nonlinear model of Induction Machine considering the winding fault of the three axes frame state space. In addition, current sensor redundancy and sensor fault detection and isolation (FDI) are adopted to ensure safety operation of induction machine drive. Finally, a validation is carried out by simulation in healthy and faulty operation modes to show the benefit of the proposed method to detect and to locate with, a high reliability, the three types of faults.

Keywords: induction machine, asymmetric nonlinear model, fault diagnosis, inter-turn short-circuit fault, root mean square, current sensor fault, fault detection and isolation

Procedia PDF Downloads 73
1813 Current-Based Multiple Faults Detection in Electrical Motors

Authors: Moftah BinHasan

Abstract:

Induction motors (IM) are vital components in industrial processes whose failure may yield to an unexpected interruption at the industrial plant, with highly incurred consequences in costs, product quality, and safety. Among different detection approaches proposed in the literature, that based on stator current monitoring termed as Motor Current Signature Analysis (MCSA) is the most preferred. MCSA is advantageous due to its non-invasive properties. The popularity of motor current signature analysis comes from being that the current consists of motor harmonics, around the supply frequency, which show some properties related to different situations of healthy and faulty conditions. One of the techniques used with machine line current resorts to spectrum analysis. Besides discussing the fundamentals of MCSA and its applications in the condition monitoring arena, this paper shows a summary of the most frequent faults and their consequence signatures on the stator current spectrum of an induction motor. In addition, this article presents different case studies of induction motor fault diagnosis. These faults were seeded in the machine which was run for more than an hour for each test before the results were recorded for the faulty situations. These results are then compared with those for the healthy cases that were recorded earlier.

Keywords: induction motor, condition monitoring, fault diagnosis, MCSA, rotor, stator, bearing, eccentricity

Procedia PDF Downloads 394
1812 A New Method for Fault Detection

Authors: Mehmet Hakan Karaata, Ali Hamdan, Omer Yusuf Adam Mohamed

Abstract:

Consider a distributed system that delivers messages from a process to another. Such a system is often required to deliver each message to its destination regardless of whether or not the system components experience arbitrary forms of faults. In addition, each message received by the destination must be a message sent by a system process. In this paper, we first identify the necessary and sufficient conditions to detect some restricted form of Byzantine faults referred to as modifying Byzantine faults. An observable form of a Byzantine fault whose effect is limited to the modification of a message metadata or content, timing and omission faults, and message replay is referred to as a modifying Byzantine fault. We then present a distributed protocol to detect modifying Byzantine faults using optimal number of messages over node-disjoint paths.

Keywords: Byzantine faults, distributed systems, fault detection, network protocols, node-disjoint paths

Procedia PDF Downloads 321
1811 Intelligent Fault Diagnosis for the Connection Elements of Modular Offshore Platforms

Authors: Jixiang Lei, Alexander Fuchs, Franz Pernkopf, Katrin Ellermann

Abstract:

Within the [email protected] project, funded by the Horizon 2020 program, an island consisting of multiple platforms was designed. The platforms are connected by ropes and fenders. The connection is critical with respect to the safety of the whole system. Therefore, fault detection systems are investigated, which could detect early warning signs for a possible failure in the connection elements. Previously, a model-based method called Extended Kalman Filter was developed to detect the reduction of rope stiffness. This method detected several types of faults reliably, but some types of faults were much more difficult to detect. Furthermore, the model-based method is sensitive to environmental noise. When the wave height is low, a long time is needed to detect a fault and the accuracy is not always satisfactory. In this sense, it is necessary to develop a more accurate and robust technique that can detect all rope faults under a wide range of operational conditions. Inspired by this work on the Space at Sea design, we introduce a fault diagnosis method based on deep neural networks. Our method cannot only detect rope degradation by using the acceleration data from each platform but also estimate the contributions of the specific acceleration sensors using methods from explainable AI. In order to adapt to different operational conditions, the domain adaptation technique DANN is applied. The proposed model can accurately estimate rope degradation under a wide range of environmental conditions and help users understand the relationship between the output and the contributions of each acceleration sensor.

Keywords: fault diagnosis, deep learning, domain adaptation, explainable AI

Procedia PDF Downloads 75
1810 Fault Tolerant Control System Using a Multiple Time Scale SMC Technique and a Geometric Approach

Authors: Ghodbane Azeddine, Saad Maarouf, Boland Jean-Francois, Thibeault Claude

Abstract:

This paper proposes a new design of an active fault-tolerant flight control system against abrupt actuator faults. This overall system combines a multiple time scale sliding mode controller for fault compensation and a geometric approach for fault detection and diagnosis. The proposed control system is able to accommodate several kinds of partial and total actuator failures, by using available healthy redundancy actuators. The overall system first estimates the correct fault information using the geometric approach. Then, and based on that, a new reconfigurable control law is designed based on the multiple time scale sliding mode technique for on-line compensating the effect of such faults. This approach takes advantages of the fact that there are significant difference between the time scales of aircraft states that have a slow dynamics and those that have a fast dynamics. The closed-loop stability of the overall system is proved using Lyapunov technique. A case study of the non-linear model of the F16 fighter, subject to the rudder total loss of control confirms the effectiveness of the proposed approach.

Keywords: actuator faults, fault detection and diagnosis, fault tolerant flight control, sliding mode control, multiple time scale approximation, geometric approach for fault reconstruction, lyapunov stability

Procedia PDF Downloads 297
1809 Applied Actuator Fault Accommodation in Flight Control Systems Using Fault Reconstruction Based FDD and SMC Reconfiguration

Authors: A. Ghodbane, M. Saad, J. F. Boland, C. Thibeault

Abstract:

Historically, actuators’ redundancy was used to deal with faults occurring suddenly in flight systems. This technique was generally expensive, time consuming and involves increased weight and space in the system. Therefore, nowadays, the on-line fault diagnosis of actuators and accommodation plays a major role in the design of avionic systems. These approaches, known as Fault Tolerant Flight Control systems (FTFCs) are able to adapt to such sudden faults while keeping avionics systems lighter and less expensive. In this paper, a (FTFC) system based on the Geometric Approach and a Reconfigurable Flight Control (RFC) are presented. The Geometric approach is used for cosmic ray fault reconstruction, while Sliding Mode Control (SMC) based on Lyapunov stability theory is designed for the reconfiguration of the controller in order to compensate the fault effect. Matlab®/Simulink® simulations are performed to illustrate the effectiveness and robustness of the proposed flight control system against actuators’ faulty signal caused by cosmic rays. The results demonstrate the successful real-time implementation of the proposed FTFC system on a non-linear 6 DOF aircraft model.

Keywords: actuators’ faults, fault detection and diagnosis, fault tolerant flight control, sliding mode control, geometric approach for fault reconstruction, Lyapunov stability

Procedia PDF Downloads 312
1808 Modifying Byzantine Fault Detection Using Disjoint Paths

Authors: Mehmet Hakan Karaata, Ali Hamdan, Omer Yusuf Adam Mohamed

Abstract:

Consider a distributed system that delivers messages from a process to another. Such a system is often required to deliver each message to its destination regardless of whether or not the system components experience arbitrary forms of faults. In addition, each message received by the destination must be a message sent by a system process. In this paper, we first identify the necessary and sufficient conditions to detect some restricted form of Byzantine faults referred to as modifying Byzantine faults. An observable form of a Byzantine fault whose effect is limited to the modification of a message metadata or content, timing and omission faults, and message replay is referred to as a modifying Byzantine fault. We then present a distributed protocol to detect modifying Byzantine faults using optimal number of messages over node-disjoint paths.

Keywords: Byzantine faults, distributed systems, fault detection, network pro- tocols, node-disjoint paths

Procedia PDF Downloads 426
1807 Presentation of HVA Faults in SONELGAZ Underground Network and Methods of Faults Diagnostic and Faults Location

Authors: I. Touaїbia, E. Azzag, O. Narjes

Abstract:

Power supply networks are growing continuously and their reliability is getting more important than ever. The complexity of the whole network comprises numerous components that can fail and interrupt the power supply for the end user. Underground distribution systems are normally exposed to permanent faults, due to specific construction characteristics. In these systems, visual inspection cannot be performed. In order to enhance service restoration, accurate fault location techniques must be applied. This paper describes the different faults that affect the underground distribution system of SONELGAZ (National Society of Electricity and Gas of Algeria), and cable fault location procedure with impulse reflection method (TDR), based in the analyses of the cable response of the electromagnetic impulse, allows cable fault prelocation. The results are obtained from real test in the underground distribution feeder from electrical network of energy distribution company of Souk-Ahras, in order to know the influence of cable characteristics in the types and frequency of faults.

Keywords: distribution networks, fault location, TDR, underground cable

Procedia PDF Downloads 406
1806 Study of Harmonics Estimation on Analog kWh Meter Using Fast Fourier Transform Method

Authors: Amien Rahardjo, Faiz Husnayain, Iwa Garniwa

Abstract:

PLN used the kWh meter to determine the amount of energy consumed by the household customers. High precision of kWh meter is needed in order to give accuracy results as the accuracy can be decreased due to the presence of harmonic. In this study, an estimation of active power consumed was developed. Based on the first year study results, the largest deviation due to harmonics can reach up to 9.8% in 2200VA and 12.29% in 3500VA with kWh meter analog. In the second year of study, deviation of digital customer meter reaches 2.01% and analog meter up to 9.45% for 3500VA household customers. The aim of this research is to produce an estimation system to calculate the total energy consumed by household customer using analog meter so the losses due to irregularities PLN recording of energy consumption based on the measurement used Analog kWh-meter installed is avoided.

Keywords: harmonics estimation, harmonic distortion, kWh meters analog and digital, THD, household customers

Procedia PDF Downloads 419