Journal articles on the topic 'Fault location (engineering)'
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Forouzesh, Alireza, Mohammad S. Golsorkhi, Mehdi Savaghebi, and Mehdi Baharizadeh. "Support Vector Machine Based Fault Location Identification in Microgrids Using Interharmonic Injection." Energies 14, no. 8 (April 20, 2021): 2317. http://dx.doi.org/10.3390/en14082317.
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This paper proposes an algorithm for detection and identification of the location of short circuit faults in islanded AC microgrids (MGs) with meshed topology. Considering the low level of fault current and dependency of the current angle on the control strategies, the legacy overcurrent protection schemes are not effective in in islanded MGs. To overcome this issue, the proposed algorithm detects faults based on the rms voltages of the distributed energy resources (DERs) by means of support vector machine classifiers. Upon detection of a fault, the DER which is electrically closest to the fault injects three interharmonic currents. The faulty zone is identified by comparing the magnitude of the interharmonic currents flowing through each zone. Then, the second DER connected to the faulty zone injects distinctive interharmonic currents and the resulting interharmonic voltages are measured at the terminal of each of these DERs. Using the interharmonic voltages as its features, a multi-class support vector machine identifies the fault location within the faulty zone. Simulations are conducted on a test MG to obtain a dataset comprising scenarios with different fault locations, varying fault impedances, and changing loads. The test results show that the proposed algorithm reliably detects the faults and the precision of fault location identification is above 90%.
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Ling, Jie, Qiu Ping Zhang, and Wan Min Huang. "Research and Implementation of Network Fault Location System Based on Event Correlation." Advanced Materials Research 756-759 (September 2013): 2410–15. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.2410.
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Network fault location is the premise of fault repair. Event correlation technique is an important fault location strategy which has its own advantages, but this technique also has some defects. Automatic fault location has not been realized and it worthy further study. This paper proposes a fault location method based on event correlation and realizes a network fault location system, which uses the relationship of topological structure of network node to generate fault correlation graph and the adjacency matrix, and through the fault correlation algorithm to locate the sources of faults. At the same time, the fault data is stored in case retrieval library for next network fault location, the system improves network fault locating speed and reduces workload of network management.
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Gururajapathy, Sophi Shilpa, Hazlie Mokhlis, and Hazlee Azil Illias. "Fault location using mathematical analysis and database approach." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 38, no. 1 (January 7, 2019): 415–30. http://dx.doi.org/10.1108/compel-02-2018-0077.
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PurposeThe purpose of this paper is to identify faults in distribution systems which are unavoidable because of adverse weather conditions and unexpected accidents. Hence, quick fault location is vital for continuous power supply. However, most fault location methods depend on the stored database for locating fault. The database is created by simulation, which is time consuming. Therefore, in this work, a comprehensive fault location method to detect faulty section and fault distance from one-ended bus using limited simulated data is proposed.Design/methodology/approachThe work uses voltage sag data measured at a primary substation. Support vector machine estimates the data which are not simulated. The possible faulty section is determined using matching approach and fault distance using mathematical analysis.FindingsThis work proposed a ranking analysis for multiple possible faulty sections, and the fault distance is calculated using Euclidean distance approach.Practical implicationsThe research work uses Malaysian distribution system as it represents a practical distribution system with multiple branches and limited measurement at primary substation. The work requires only metering devices to identify fault which is cost effective. In addition, the distribution system is simulated using real-time PSCAD by which the capability of proposed method can be fully tested.Originality/valueThe paper presents a new method for fault analysis. It reduces simulation time and storage space of database. The work identifies faulty section and ranks the prior faulty section. It also identifies fault distance using a mathematical approach.
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Martin, K. F., and M. Moavenian. "Failure Detection and Location Using Residual Difference Generation Detection Filters." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 210, no. 4 (November 1996): 283–90. http://dx.doi.org/10.1243/pime_proc_1996_210_467_02.
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The paper describes a theoretical investigation of failure detection using a new type of filter. The latter, called a residual difference generation detection filter, is based upon using (a) a main detection filter and (b) a faulty parameter modifier. Both of these use a reference model of the system; this is a mathematical model of the system without faults. In (a) the reference model is used in parallel with the real system in order to generate residuals (functions of differences between the real system and the reference model); in (b) the reference model is used in parallel with another mathematical model of the system which contains a known fault which again generates residuals that are a function of the known fault. By analysing these residuals while changing the known fault in (b) it is possible to detect which fault is occurring. The technique is applied to faults in a servo-motor, faults being assumed to occur singly. Tests were carried out using a mathematical model of the real system which incorporated an ‘unknown’ fault.
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FENG, Yunwen, Weihuang PAN, Cheng LU, and Jiaqi LIU. "Fault diagnosis and location of hydraulic system of domestic civil aircraft based on logic data." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 40, no. 4 (August 2022): 732–38. http://dx.doi.org/10.1051/jnwpu/20224040732.
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To study the typical fault diagnosis and fault location technology of the hydraulic system of the domestic civil aircraft, the logic data of the typical fault is constructed according to the formation conditions of the fault. The operation data of the typical fault is collected, and the Bayesian network is used to realize the fault diagnosis and fault components position. First, according to the fault formation conditions in the unit operation manual of a certain type of domestic civil aircraft, referring to the construction method of the logic data, taking the typical fault of the hydraulic system as an example, the fault logic data of the domestic civil aircraft is established to intuitively reflect the logical relationship of the fault formation; secondly, based on the constructed logic data, considering the formation conditions of the fault, a Bayesian network corresponding to the logic data is established, and the logical relationship formed by the fault is represented by the value of the conditional probability distribution; obtain quick access recorder (QAR) data and its parameter information according to the input information of the logic data; finally, according to the established Bayesian network and the obtained QAR data, apply forward reasoning to realize the diagnosis of typical faults of the hydraulic system. Under the condition of partial information, reverse reasoning is applied to locate the faulty components of hydraulic system. The research shows that the proposed method can accurately diagnose faults, and can accurately locate faulty components in complete information, and give the probability of occurrence of potentially faulty components under partial information, which can effectively assist in the location of faulty components. The research work has certain reference significance for improving the fault diagnosis function of the airborne health management system and the ground health management system of domestic civil aircraft.
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Tariq, Rizwan, Ibrahim Alhamrouni, Ateeq Ur Rehman, Rao Muhammad Asif, and Zimran Rafique. "A new algorithm for fault location in multi-end underground cables using traveling waves." International Journal of Power Electronics and Drive Systems (IJPEDS) 14, no. 2 (June 1, 2023): 1280. http://dx.doi.org/10.11591/ijpeds.v14.i2.pp1280-1289.
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<p>A quick, reliable, and accurate fault location approach is essential in underground power systems protection. Being the most optimistic research topic of electrical power systems, this article presents an optimized algorithm for fault location in multi-end underground cables using travelling waves. Existing algorithms based on wavelet theory have fewer reliability and accuracy issues that raise an error to the power systems in fault location. The proposed layout presents a multiterminal underground cables system where the entire system is segregated into several fault identification sections where this model identifies the faulty section and the faulty half. Voltage and current wave transient at the mid-point of each fault locator are taken into account to eliminate the time-synchronous error. Traveling waves models are modelled using Bewley diagrams. Detecting the first and second traveling wave transient at both ends of each cable keeps the system reliable. Extensive simulations are simulated using the alternative transient program (ATP) to discriminate, identify, and locate several faults, while the system can also validate the faults near the busbar. The model is developed in MATLAB, and the obtained results depict the proposed algorithm's higher accuracy in fault location.</p>
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Chu, Kenny Sau Kang, Kuew Wai Chew, Yoong Choon Chang, and Stella Morris. "An Open-Circuit Fault Diagnosis System Based on Neural Networks in the Inverter of Three-Phase Permanent Magnet Synchronous Motor (PMSM)." World Electric Vehicle Journal 15, no. 2 (February 16, 2024): 71. http://dx.doi.org/10.3390/wevj15020071.
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Three-phase motors find extensive applications in various industries. Open-circuit faults are a common occurrence in inverters, and the open-circuit fault diagnosis system plays a crucial role in identifying and addressing these faults to enhance the safety of motor operations. Nevertheless, the current open-circuit fault diagnosis system faces challenges in precisely detecting specific faulty switches. The proposed work presents a neural network-based open-circuit fault diagnosis system for identifying faulty power switches in inverter-driven motor systems. The system leverages trained phase-to-phase voltage data from the motor to recognize the type and location of faults in each phase with high accuracy. Employing separate neural networks for each of the three phases in a three-phase permanent magnet synchronous motor, the system achieves an outstanding overall fault detection accuracy of approximately 99.8%, with CNN and CNN-LSTM architectures demonstrating superior performance. This work makes two key contributions: (1) implementing neural networks to significantly improve the accuracy of locating faulty switches in open-circuit fault scenarios, and (2) identifying the optimal neural network architecture for effective fault diagnosis within the proposed system.
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Swetapadma, Aleena, Shobha Agarwal, Satarupa Chakrabarti, Soham Chakrabarti, Adel El-Shahat, and Almoataz Y. Abdelaziz. "Locating Faults in Thyristor-Based LCC-HVDC Transmission Lines Using Single End Measurements and Boosting Ensemble." Electronics 11, no. 2 (January 7, 2022): 186. http://dx.doi.org/10.3390/electronics11020186.
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Most of the fault location methods in high voltage direct current (HVDC) transmission lines usemethods which require signals from both ends. It will be difficult to estimate fault location if the signal recorded is not correct due to communication problems.Hence a robust method is required which can locate fault with minimum error. In this work, faults are located using boosting ensembles in HVDC transmission lines based on single terminal direct current (DC) signals. The signals are processed to obtain input features that vary with the fault distance. These input features are obtained by taking maximum of half cycle current signals after fault and minimum of half cycle voltage signals after fault from the root mean square of DC signals. The input features are input to a boosting ensemble for estimating the location of fault. Boosting ensemble method attempts to correct the errors from the previous models and find outputs by combining all models. The boosting ensemble method has been also compared with the decision tree method and thebagging-based ensemble method. Fault locations are estimated using three methods and compared to obtain an optimal method. The boosting ensemble method has better performance than all the other methods in locating the faults. It also validated varying fault resistance, smoothing reactors, boundary faults, pole to ground faults and pole to pole faults. The advantage of the method is that no communication link is needed. Another advantage is that it allowsreach setting up to 99.9% and does not exhibitthe problem of over-fitting. Another advantage is that the percentage error in locating faults is within 1% and has a low realization cost. The proposed method can be implemented in HVDC transmission lines effectively as an alternative to overcome the drawbacks of traveling wave methods.
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Tariq, Rizwan, Ibrahim Alhamrouni, Ateeq Ur Rehman, Elsayed Tag Eldin, Muhammad Shafiq, Nivin A. Ghamry, and Habib Hamam. "An Optimized Solution for Fault Detection and Location in Underground Cables Based on Traveling Waves." Energies 15, no. 17 (September 5, 2022): 6468. http://dx.doi.org/10.3390/en15176468.
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Faults in the power system affect the reliability, safety, and stability. Power-distribution systems are familiar with the different faults that can damage the overall performance of the entire system, from which they need to be effectively cleared. Underground power systems are more complex and require extra accuracy in fault detection and location for optimum fault management. Slow processing and the unavailability of a protection zone for relay coordination are concerns in fault detection and location, as these reduce the performance of power-protection systems. In this regard, this article proposes an optimized solution for a fault detection and location framework for underground cables based on a discrete wavelet transform (DWT). The proposed model supports area detection, the identification of faulty sections, and fault location. To overcome the abovementioned facts, we optimize the relay coordination for the overcurrent and timing relays. The proposed protection zone has two sequential stages for the current and time at which it optimizes the current and time settings of the connected relays through Newton–Raphson analysis (NRA). Moreover, the traveling times for the DWT are modeled, which relate to the protection zone provided by the relay coordination, and the faulty line that is identified as the relay protection is not overlapped. The model was tested for 132 kV/11 kV and 16-node networks for underground cables, and the obtained results show that the proposed model can detect and locate the cable’s faults speedily, as it detects the fault in 0.01 s, and at the accurate location. MATLAB/Simulink (DigSILENT Toolbox) is used to establish the underground network for fault location and detection.
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Gupta, Kapil. "Fault Detection System for GSS." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 2934–36. http://dx.doi.org/10.22214/ijraset.2022.44483.
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Abstract: The efficiency of power systems is largely determined by the effectiveness of the inbuilt power equipment. Monitoring transmission parameters for faults and quick isolation of the system from faults helps to improve the efficiency of the power systems reliability. Current conventional method has its own limitations due to the reliance on technical team to carrying out visual inspection in order to identify any fault. The functions of the protective systems are to detect, then classify and finally determine the location of the faulty. This project presents some techniques that helps to find, determine and diagnosing faults in GSS. This project will review the type of fault that possibly occurs in an electric power system, the type of fault detection and location technique that are available together with the protection device that can be utilized in the power system to protect the equipment from electric fault.
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Xiu, Wanjing, and Yuan Liao. "Fault Location Methods for Ungrounded Distribution Systems Using Local Measurements." International Journal of Emerging Electric Power Systems 14, no. 5 (August 27, 2013): 467–76. http://dx.doi.org/10.1515/ijeeps-2013-0079.
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Abstract This article presents novel fault location algorithms for ungrounded distribution systems. The proposed methods are capable of locating faults by using obtained voltage and current measurements at the local substation. Two types of fault location algorithms, using line to neutral and line to line measurements, are presented. The network structure and parameters are assumed to be known. The network structure needs to be updated based on information obtained from utility telemetry system. With the help of bus impedance matrix, local voltage changes due to the fault can be expressed as a function of fault currents. Since the bus impedance matrix contains information about fault location, superimposed voltages at local substation can be expressed as a function of fault location, through which fault location can be solved. Simulation studies have been carried out based on a sample distribution power system. From the evaluation study, it is evinced that very accurate fault location estimates are obtained from both types of methods.
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Idris, Muhd Hafizi, Mohd Rafi Adzman, Hazlie Mokhlis, Lilik Jamilatul Awalin, and Mohammad Faridun Naim Tajuddin. "Enhanced two-terminal impedance-based fault location using sequence values." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 2 (April 1, 2023): 1291. http://dx.doi.org/10.11591/ijece.v13i2.pp1291-1305.
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<span lang="EN-US">Fault at transmission line system may lead to major impacts such as power quality problems and cascading failure in the grid system. Thus, it is very important to locate it fast so that suitable solution can be taken to ensure power system stability can be retained. The complexity of the transmission line however makes the fault point identification a challenging task. This paper proposes an enhanced fault detection and location method using positive and negative-sequence values of current and voltage, taken at both local and remote terminals. The fault detection is based on comparison between the total fault current with currents combination during the pre-fault time. While the fault location algorithm was developed using an impedance-based method and the estimated fault location was taken at two cycles after fault detection. Various fault types, fault resistances and fault locations have been tested in order to verify the performance of the proposed method. The developed algorithms have successfully detected all faults within high accuracy. Based on the obtained results, the estimated fault locations are not affected by fault resistance and line charging current. Furthermore, the proposed method able to detect fault location without the needs to know the fault type.</span>
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Dashtdar, Masoud, Arif Hussain, Hassan Z. Al Garni, Abdullahi Abubakar Mas’ud, Waseem Haider, Kareem M. AboRas, and Hossam Kotb. "Fault Location in Distribution Network by Solving the Optimization Problem Based on Power System Status Estimation Using the PMU." Machines 11, no. 1 (January 13, 2023): 109. http://dx.doi.org/10.3390/machines11010109.
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Fault location is one of the main challenges in the distribution network due to its expanse and complexity. Today, with the advent of phasor measurement units (PMU), various techniques for fault location using these devices have been proposed. In this research, distribution network fault location is defined as an optimization problem, and the network fault location is determined by solving it. This is done by combining PMU data before and after the fault with the power system status estimation (PSSE) problem. Two new objective functions are designed to identify the faulty section and fault location based on calculating the voltage difference between the two ends of the grid lines. In the proposed algorithm, the purpose of combining the PMU in the PSSE problem is to estimate the voltage and current quantities at the branch point and the total network nodes after the fault occurs. Branch point quantities are calculated using the PMU and the governing equations of the π line model for each network section, and the faulty section is identified based on a comparison of the resulting values. The advantages of the proposed algorithm include simplicity, step-by-step implementation, efficiency in conditions of different branch specifications, application for various types of faults including short-circuit and series, and its optimal accuracy compared to other methods. Finally, the proposed algorithm has been implemented on the IEEE 123-node distribution feeder and its performance has been evaluated for changes in various factors including fault resistance, type of fault, angle of occurrence of a fault, uncertainty in loading states, and PMU measurement error. The results show the appropriate accuracy of the proposed algorithm showing that it was able to determine the location of the fault with a maximum error of 1.21% at a maximum time of 23.87 s.
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Li, Zhenhua, Junjie Cheng, and A. Abu-Siada. "Classification and Location of Transformer Winding Deformations using Genetic Algorithm and Support Vector Machine." (Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 14, no. 8 (December 23, 2021): 837–45. http://dx.doi.org/10.2174/2352096514666211026142216.
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Background: Winding deformation is one of the most common faults an operating power transformer experiences over its operational life. Thus, it is essential to detect and rectify such faults at early stages to avoid potential catastrophic consequences to the transformer. At present, methods published in the literature for transformer winding fault diagnosis are mainly focused on identifying fault type and quantifying its extent without giving much attention to the identification of fault location. Methods: This paper presents a method based on a genetic algorithm and support vector machine (GA-SVM) to improve the faults’ classification of power transformers in terms of type and location. In this regard, a sinusoidal sweep signal in the frequency range of 600 kHz to 1MHz is applied to one terminal of the transformer winding. : A mathematical index of the induced current at the head and end of the transformer winding under various fault conditions is used to extract unique features that are fed to a Support Vector Machine (SVM) model for training. Parameters of the SVM model are optimized using a Genetic Algorithm (GA). Results : The effectiveness of mathematical indicators to extract fault type characteristics and the proposed fault classification model for fault diagnosis is demonstrated through extensive simulation analysis for various transformer winding faults at different locations. Conclusion : The proposed model can effectively identify different fault types and determine their location within the transformer winding, and the diagnostic rates of the fault type and fault location are 100% and 90%, respectively.
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Wang, Jinxin, Zhongwei Wang, Xiuzhen Ma, Guojin Feng, and Chi Zhang. "Locating Sensors in Complex Engineering Systems for Fault Isolation Using Population-Based Incremental Learning." Energies 13, no. 2 (January 8, 2020): 310. http://dx.doi.org/10.3390/en13020310.
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Fault diagnostics aims to locate the origin of an abnormity if it presents and therefore maximize the system performance during its full life-cycle. Many studies have been devoted to the feature extraction and isolation mechanisms of various faults. However, limited efforts have been spent on the optimization of sensor location in a complex engineering system, which is expected to be a critical step for the successful application of fault diagnostics. In this paper, a novel sensor location approach is proposed for the purpose of fault isolation using population-based incremental learning (PBIL). A directed graph is used to model the fault propagation of a complex engineering system. The multidimensional causal relationships of faults and symptoms were obtained via traversing the directed path in the directed graph. To locate the minimal quantity of sensors for desired fault isolatability, the problem of sensor location was firstly formulated as an optimization problem and then handled using PBIL. Two classical cases, including a diesel engine and a fluid catalytic cracking unit (FCCU), were taken as examples to demonstrate the effectiveness of the proposed approach. Results show that the proposed method can minimize the quantity of sensors while keeping the capacity of fault isolation unchanged.
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Mirshekali, Hamid, Rahman Dashti, Karsten Handrup, and Hamid Reza Shaker. "Real Fault Location in a Distribution Network Using Smart Feeder Meter Data." Energies 14, no. 11 (June 1, 2021): 3242. http://dx.doi.org/10.3390/en14113242.
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Distribution networks transmit electrical energy from an upstream network to customers. Undesirable circumstances such as faults in the distribution networks can cause hazardous conditions, equipment failure, and power outages. Therefore, to avoid financial loss, to maintain customer satisfaction, and network reliability, it is vital to restore the network as fast as possible. In this paper, a new fault location (FL) algorithm that uses the recorded data of smart meters (SMs) and smart feeder meters (SFMs) to locate the actual point of fault, is introduced. The method does not require high-resolution measurements, which is among the main advantages of the method. An impedance-based technique is utilized to detect all possible FL candidates in the distribution network. After the fault occurrence, the protection relay sends a signal to all SFMs, to collect the recorded active power of all connected lines after the fault. The higher value of active power represents the real faulty section due to the high-fault current. The effectiveness of the proposed method was investigated on an IEEE 11-node test feeder in MATLAB SIMULINK 2020b, under several situations, such as different fault resistances, distances, inception angles, and types. In some cases, the algorithm found two or three candidates for FL. In these cases, the section estimation helped to identify the real fault among all candidates. Section estimation method performs well for all simulated cases. The results showed that the proposed method was accurate and was able to precisely detect the real faulty section. To experimentally evaluate the proposed method’s powerfulness, a laboratory test and its simulation were carried out. The algorithm was precisely able to distinguish the real faulty section among all candidates in the experiment. The results revealed the robustness and effectiveness of the proposed method.
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Al Kazzaz, Sa’ad Ahmed S., Ibrahim Ismaeel, and Karam Khairullah Mohammed. "Fault detection and location of power transmission lines using intelligent distance relay." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 2 (June 1, 2020): 726. http://dx.doi.org/10.11591/ijpeds.v11.i2.pp726-734.
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The aim of this paper is to design a three-phase distance relay using an adaptive neuro-fuzzy inference system algorithm (ANFIS). The proposed relay is used to protect the power transmission lines where they are subjected to faults continuously. These faults may produce a high electric current which leads to high damage in power system equipment. The relay is used to detect the transmission line faults by measuring the voltage and current values for each phase. The line impedance is then calculated to detect the faults and issue instantaneous trip signal to circuit breaker, to separate the fault zone of the transmission line without affecting the work of other relays. To isolate the faulty line without affecting the other lines within the network the relays were trained using adaptive neuro-fuzzy inference system (ANFIS). The obtained results through this work show that the designated distance relay with (ANFIS) algorithm has the ability to detect the faults occurrence, recognize it from the cases of the disturbance and to isolate only the fault zone without affecting the work of other relays in system.
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Xia, Bing Yang, and Jing Ma. "A Wide-Area Backup Protection Algorithm for Multi-Fault Location in Complex Large Power Grid." Advanced Materials Research 960-961 (June 2014): 836–40. http://dx.doi.org/10.4028/www.scientific.net/amr.960-961.836.
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This paper presents a fitting degree-based multi-fault location algorithm for complex large power grid utilizing wide-area information. Firstly, fault injection current of the equivalent fault points is used in the equivalent model. Then the correlation matrix is formed by the network topology and associated nodal injection current and a network is formed to determine the location of faults. When multiple faults occur, the addition of the current of each two fault lines is calculated and the real-time current is measured. Then by calculating the minimum of fitting degree between two current values, fault line and virtual fault location can be determined. The simulation results of 10-generator 39-bus system verify the validity and feasibility of this algorithm.
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Zhao, Qiao, Zengping Wang, Guomin Li, Xuanjun Liu, and Yuxuan Wang. "A Fault Section Location Method for Distribution Networks Based on Divide-and-Conquer." Applied Sciences 13, no. 10 (May 12, 2023): 5974. http://dx.doi.org/10.3390/app13105974.
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In this paper, a fault location method based on divide-and-conquer (DAC) is proposed to solve the inadequacy problem that arises when using the traditional fault section location method based on the optimization model of logic operation. The problem is that it is difficult to balance speed and accuracy after the scale of the distribution network is expanded. First, the causal link between fault information and the faulty device was described using the road vector, the equivalent transformation of the logical operations in the traditional model was implemented with the properties of the road vector, and the numerical computational model of the fault location was constructed. Based on this, the optimization-seeking variable “approximation gain” was introduced to prove that the proposed model conforms to the recursive structure of DAC, and the method of applying DAC to locate faults is proposed. The method applies the “Divide-Conquer-Combine” recursive mode to locate faults, and each level of recursion contains only linear-time “approximation gain” operations and constant-time decomposition and combination operations. The efficiency analysis and simulation results show that the proposed method has linear-time complexity and can accurately locate faults in milliseconds, providing a reference for solving the fault location problem in large distribution networks.
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Kumar, Anup, Himanshu Sharma, Ram Niwash Mahia, Om Prakash Mahela, and Baseem Khan. "Design and Implementation of Hybrid Transmission Line Protection Scheme Using Signal Processing Techniques." International Transactions on Electrical Energy Systems 2022 (May 10, 2022): 1–20. http://dx.doi.org/10.1155/2022/7209553.
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A hybrid scheme for transmission line protection (HSTLP) using the Stockwell transform (ST), Wigner distribution function (WDF), and alienation coefficient (ACF) is designed. Current signals are analyzed using the ST, WDF, and ACF to compute the Stockwell fault index (SFI), Wigner fault index (WFI), and alienation coefficient fault index (ACFI), respectively. These fault indexes are used to derive a hybrid signal processing fault index (HSPFI), which is implemented for the detection of transmission line fault events. The peak magnitude of HSPFI is compared with a preset threshold magnitude (TH) to identify the fault. The statistical formulation is proposed for fault location on the power transmission line. Fault classification is achieved using the number of faulty phases. A hybrid ground fault index (HGFI) is used to recognize the involvement of the ground during the fault event. This HGFI is determined by processing zero sequence current using ST and WDF. The performance of algorithm is tested by various case studies for fault impedance variation, variable sampling frequency, fault incidence angle variation, reverse power flow on transmission line, highly loaded line, different fault locations online, and noisy conditions. The algorithm is also validated to detect a fault on a practical transmission line of large area utility grid of Rajasthan Rajya Vidyut Prasaran Nigam Limited (RVPN) in India. The algorithm performs better than the Hilbert–Huang transform (HHT)-based protection scheme and wavelet transform (WT)-based protection scheme available in the literature in terms of mean error of fault location, fault location accuracy, and noise level. The proposed protection scheme efficiently detected, classified, and located the faulty events such as single-phase-to-ground fault (SPGF), two-phase fault (TPF), two-phase-to-ground fault (TPGF), three-line fault (TLF), and three-line-to-ground fault (TLGF). Transmission line fault location accuracy of 99.031% is achieved. The algorithm performs well even with a high noise level of 10 dB SNR.
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Liu, Fuqiang, Yan Long, Jun Luo, Huayan Pu, Chaoqun Duan, and Songyi Zhong. "Active Fault Localization of Actuators on Torpedo-Shaped Autonomous Underwater Vehicles." Sensors 21, no. 2 (January 11, 2021): 476. http://dx.doi.org/10.3390/s21020476.
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To ensure the mission implementation of Autonomous Underwater Vehicles (AUVs), faults occurring on actuators should be detected and located promptly; therefore, reliable control strategies and inputs can be effectively provided. In this paper, faults occurring on the propulsion and attitude control systems of a torpedo-shaped AUV are analyzed and located while fault features may induce confusions for conventional fault localization (FL). Selective features of defined fault parameters are assorted as necessary conditions against different faulty actuators and synthesized in a fault tree subsequently to state the sufficiency towards possible abnormal parts. By matching fault features with those of estimated fault parameters, suspected faulty sections are located. Thereafter, active FL strategies that analyze the related fault parameters after executing purposive actuator control are proposed to provide precise fault location. Moreover, the generality of the proposed methods is analyzed to support extensive implementations. Simulations based on finite element analysis against a torpedo-shaped AUV with actuator faults are carried out to illustrate the effectiveness of the proposed methods.
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Sushkov, Valery V., Ilya S. Sukhachev, and Sergey V. Sidorov. "DEVELOPMENT OF A COMPREHENSIVE APPROACH TO DIAGNOSING THE OVERHEAD LINE FAULTS LOCATION IN SINGLE-PHASE GROUND FAULTS BASED ON A DIGITAL SUBSTATION DATA PROCESSING ALGORITHM." Bulletin of the Tomsk Polytechnic University Geo Assets Engineering 334, no. 7 (July 28, 2023): 66–77. http://dx.doi.org/10.18799/24131830/2023/7/4332.
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Link for citation: Sushkov V.V., Sukhachev I.S., Sidorov S.V. Development of a comprehensive approach to diagnosing the overhead line faults location in single-phase ground faults based on a digital substation data processing algorithm. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 7, рр. 66-77. In Rus. Relevance. Emergency of electric complex of outgoing transmission lines is associated with the occurrence of damage to the line isolation and the resulting transients, marked by the presence of higher harmonic components of currents and voltage, which reduce the reliability and energy efficiency of electrical equipment of oil and gas companies: degrade the mechanical characteristics and efficiency of electric motors, accelerate aging of their isolation, disrupt the operation of control systems and emergency automatics, fault diagnostics systems. One of the reasons of high-level emergency situations, outages and emergency repairs in electric complexes of outgoing transmission lines of oil and gas companies is appearance of phase-to-ground faults. A large number of changing factors are known to influence the reliability of phase-to-ground fault location methods: parameters of transmission line operating mode, its structural and electrical parameters, fault type, transient resistance value, ground resistance and others. Inclusion in the transmission line fault location algorithms of averaged values of a number of the factors listed above independent of changes of humidity of soil and air, its temperature and other factors causes an error of methods of fault location up to 30 %. Accordingly, the research to develop a fault location method for overhead transmission lines with isolated neutral points during phase-to-ground faults based on a digital substation data processing algorithm, accounting for tower parameters and natural-climatic factors, is relevant. Objective: improving the reliability of power grids and providing consumers with power of the required standard by applying a digital fault location system to the outgoing transmission lines electrical complex. Methods: mathematical analysis of a power transmission line, taking into account its design features and natural-climatic factors on the basis of the method of mirror images; mathematical analysis of steady-state and transient modes of transmission line operation considering self and mutual parameters terms of wires; transmission line currents and voltages Fourier analysis; validation of developed method of phase-to-ground fault location in power grid of Tyumen region energy company. Results. The authors have developed the phase-to-ground faults location method for transmission lines in power grids with isolated neutral points, which differs in the following – first the faulty overhead line feeder branch is identified by correspondences between the negative sequence voltage values of the phase voltages at the transformer substation inputs, and then the distance to the location of the single-phase ground fault is determined along the branch line based on the resonant frequencies of the line taking into account its design features and natural and climatic factors.
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Liu, Fuqiang, Yan Long, Jun Luo, Huayan Pu, Chaoqun Duan, and Songyi Zhong. "Active Fault Localization of Actuators on Torpedo-Shaped Autonomous Underwater Vehicles." Sensors 21, no. 2 (January 11, 2021): 476. http://dx.doi.org/10.3390/s21020476.
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To ensure the mission implementation of Autonomous Underwater Vehicles (AUVs), faults occurring on actuators should be detected and located promptly; therefore, reliable control strategies and inputs can be effectively provided. In this paper, faults occurring on the propulsion and attitude control systems of a torpedo-shaped AUV are analyzed and located while fault features may induce confusions for conventional fault localization (FL). Selective features of defined fault parameters are assorted as necessary conditions against different faulty actuators and synthesized in a fault tree subsequently to state the sufficiency towards possible abnormal parts. By matching fault features with those of estimated fault parameters, suspected faulty sections are located. Thereafter, active FL strategies that analyze the related fault parameters after executing purposive actuator control are proposed to provide precise fault location. Moreover, the generality of the proposed methods is analyzed to support extensive implementations. Simulations based on finite element analysis against a torpedo-shaped AUV with actuator faults are carried out to illustrate the effectiveness of the proposed methods.
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Idris, Muhd Hafizi, Mohd Rafi Adzman, Hazlie Mokhlis, Mohammad Faridun Naim Tajuddin, Haziah Hamid, and Melaty Amirruddin. "Two-terminal fault detection and location for hybrid transmission circuit." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 2 (August 1, 2021): 639. http://dx.doi.org/10.11591/ijeecs.v23.i2.pp639-649.
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This paper presents the algorithms developed to detect and locate the faults ata hybrid circuit. First, the fault detection algorithm was developed using the comparison of total positive-sequence fault current between pre-fault and fault times to detect the occurrence of a fault. Then, the voltage check method was used to decide whether the fault occurred at overhead line (OHL) or cable section. Finally, the fault location algorithm using the impedance-based method and negative-sequence measurements from both terminals of the circuit were used to estimate the fault point from local terminal. From the tests of various fault conditions including different fault types, fault resistance and fault locations, the proposed method successfully detected all fault cases at around 1 cycle from fault initiation and with correct faulted section identification. Besides that, the fault location algorithm also has very accurate results of fault estimation with average error less than 1 km and 1%.<br /><div> </div>
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Hosseini Dolatabadi, Sayed Hamid, and Mohammad Esmail Hamedani Golshan. "Fault location observability rules for impedance-based fault location algorithms." Electric Power Systems Research 224 (November 2023): 109771. http://dx.doi.org/10.1016/j.epsr.2023.109771.
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Bayati, Navid, Lasse Kappel Mortensen, Mehdi Savaghebi, and Hamid Reza Shaker. "A Localized Transient-Based Fault Location Scheme for Distribution Systems." Sensors 22, no. 7 (April 1, 2022): 2723. http://dx.doi.org/10.3390/s22072723.
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Many distribution systems have several branches with only one protection system at the upstream system. This characteristic degrades the performance of traditional fault location schemes. In this paper, a localized fault location method based on the transient behavior of fault currents by using local data is proposed. The proposed scheme uses only local current and the voltage of the upstream overcurrent relay as input data of the fault location scheme. The formulation considers fault resistance, loads, and different fault locations. Furthermore, due to the usage of transient fault current data, the proposed method locates the fault within several milliseconds with a suitable range of error. To validate the effectiveness of this method, field measurement data, obtained from a real distribution system in East Jutland, Denmark operated by Dinel A/S, are used, and extensive real-time simulations are performed. The results prove that the proposed method locates different types of faults within an appropriate time and error, which can improve the maintenance and reliability of distribution systems.
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Dowalla, Krzysztof, Piotr Bilski, Robert Łukaszewski, Augustyn Wójcik, and Ryszard Kowalik. "A Novel Method for Detection and Location of Series Arc Fault for Non-Intrusive Load Monitoring." Energies 16, no. 1 (December 23, 2022): 171. http://dx.doi.org/10.3390/en16010171.
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Series arc faults cause the majority of household fires involving electrical failures or malfunctions. Low-fault current amplitude is the reason for the difficulties faced in implementing effective arc detection systems. The paper presents a novel arc detection and faulty line identification method. It can be easily used in the low-voltage Alternate Current (AC) household network for arc detection in the Non-Intrusive Load Monitoring (NILM). Unlike existing methods, the proposed approach exploits both current and voltage signal time domain analysis. Experiments have been conducted with up to six devices operating simultaneously in the same circuit with an arc fault generator based on the IEC 62606:2013 standard. Sixteen time-domain features were used to maximize the arc-fault detection accuracy for particular appliances. Performance of the random forest classifier for arc fault detection was evaluated for 28 sets of features with five different sampling rates. For the single period analysis arc, detection accuracy was 98.38%, with F-score of 0.9870, while in terms of the IEC 62606:2013 standard, it was 99.07%, with F-score of 0.9925. Location of a series arc fault (line selection) was realized by identifying devices powered by the faulty line. The line selection was based on the Mean Values of Changes feature vector (MVC50), calculated for absolute values of differences between adjacent current signal periods during the arc fault. The fault location accuracy was 93.20% for all cases and 98.20% for cases where the arc fault affected a single device.
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Guo, Liang, Yingqi Huang, Hongli Gao, and Li Zhang. "Ball Screw Fault Detection and Location Based on Outlier and Instantaneous Rotational Frequency Estimation." Shock and Vibration 2019 (July 10, 2019): 1–12. http://dx.doi.org/10.1155/2019/7497363.
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Ball screw, as a crucial component, is widely used in various rotating machines. Its health condition significantly influences the efficiency and position precision of rotating machines. Therefore, it is important to accurately detect faults and estimate fault location in a ball screw system to make sure that the ball screw system runs safely and effectively. However, there are few research studies concerning the topic. The aim of this paper is to fill the gap. In this paper, we propose a method to automatically detect and locate faults in a ball screw system. The proposed method mainly consists of two steps: fault time estimation and instantaneous rotational frequency extraction. In the first step, a statistics-based outlier detection method is proposed to involve the fault information mixing in vibration signals and estimate the fault time. In the second step, a parameterized time-frequency analysis method is utilized to extract the instantaneous rotational frequency of the ball screw system. Once the fault time and instantaneous rotational frequency are estimated, the fault location in a ball screw system is calculated through an integral operation. In order to verify the effectiveness of the proposed method, two fault location experiments under the constant and varying speed conditions are conducted in a ball screw failure simulation testbed. The results demonstrate that the proposed method is able to accurately detect the faults in a ball screw system and estimate the fault location within an error of 22%.
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Lei, Lai, Cong Wang, Jie Gao, Jinjin Zhao, and Xiaowei Wang. "A Protection Method Based on Feature Cosine and Differential Scheme for Microgrid." Mathematical Problems in Engineering 2019 (March 10, 2019): 1–17. http://dx.doi.org/10.1155/2019/7248072.
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The fault current level of microgrid is different between islanded mode and grid connected mode. This situation degrades the performance of traditional overcurrent protection schemes. Hence, this paper proposes a protection method based on feature cosine and differential scheme. Firstly, feature cosine is proposed; it employs ellipse equation and minimum least squares to quantify the united behavior about voltage and current. Secondly, fault current direction and feature cosine are analyzed when fault occurs at different locations of a typical microgrid, and then the difference of feature cosine between faulty and healthy section locations is obtained. Thirdly, based on feature cosine and differential scheme, the differential direction is defined and utilized to detect faulty section location. Lastly, various time domain simulation case studies, including different microgrid operation modes, grounding resistances, faulty types, faulty section locations, and noise influence, are conducted and demonstrate that the proposed protection has high accuracy.
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Liao, Yuan. "A Novel Fault Location Method for Radial Distribution Systems." International Journal of Emerging Electric Power Systems 16, no. 3 (June 1, 2015): 225–32. http://dx.doi.org/10.1515/ijeeps-2014-0036.
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Abstract This paper presents a new method for locating faults on radial distribution systems utilizing local voltage and current measurements. The method considers feeder shunt capacitances, is applicable to any type of faults, is suitable for unbalanced networks and does not require fault type information. The method is also independent of source impedance. Analytical analysis is utilized to obtain a generic performance equation for any type of faults, which reduces or eliminates iterative steps to reach the fault location. A process to trim down multiple estimates due to laterals is discussed. Evaluation studies based on simulated data have demonstrated the effectiveness of the proposed solution.
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Pragati, Abha, Debadatta Amaresh Gadanayak, Tanmoy Parida, and Manohar Mishra. "Data-Mining Techniques Based Relaying Support for Symmetric-Monopolar-Multi-Terminal VSC-HVDC System." Applied System Innovation 6, no. 1 (February 5, 2023): 24. http://dx.doi.org/10.3390/asi6010024.
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Considering the advantage of the ability of data-mining techniques (DMTs) to detect and classify patterns, this paper explores their applicability for the protection of voltage source converter-based high voltage direct current (VSC-HVDC) transmission systems. In spite of the location of fault occurring points such as external/internal, rectifier-substation/inverter-substation, and positive/negative pole of the DC line, the stated approach is capable of accurate fault detection, classification, and location. Initially, the local voltage and current measurements at one end of the HVDC system are used in this work to extract the feature vector. Once the feature vector is retrieved, the DMTs are trained and tested to identify the fault types (internal DC faults, external AC faults, and external DC faults) and fault location in the particular feeder. In the data-mining framework, several state-of-the-art machine learning (ML) models along with one advanced deep learning (DL) model are used for training and testing. The proposed VSC-HVDC relaying system is comprehensively tested on a symmetric-monopolar-multi-terminal VSC-HVDC system and presents heartening results in diverse operating conditions. The results show that the studied deep belief network (DBN) based DL model performs better compared with other ML models in both fault classification and location. The accuracy of fault classification of the DBN is found to be 98.9% in the noiseless condition and 91.8% in the 20 dB noisy condition. Similarly, the DBN-based DMT is found to be effective in fault locations in the HVDC system with a smaller percentage of errors as MSE: 2.116, RMSE: 1.4531, and MAPE: 2.7047. This approach can be used as an effective low-cost relaying support tool for the VSC-HVDC system, as it does not necessitate a communication channel.
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Nabwani, Moneer, Michael Suleymanov, Yosef Pinhasi, and Asher Yahalom. "Real-Time Fault Location Using the Retardation Method." Electronics 11, no. 7 (March 22, 2022): 980. http://dx.doi.org/10.3390/electronics11070980.
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A new method for short-circuit fault location is proposed. The method is based on instantaneous signal measurement and its first and second derivatives, which are the novel elements of the current approach. The derivatives allow associating a precise time stamp to the occurrence of the fault. Due to retardation phenomena, the difference between the times in which a signal is registered in two detectors can be used to locate the fault. We offer several mathematical models to describe the fault. Although a description of faults in terms of a lumped circuit is useful for elucidating the methods for detecting the fault, this description will not suffice to describe the fault signal propagation; hence, a distributed models is needed, which is given in terms of the telegraph equations. Those equations were used to derive a transmission line transfer function, and an exact analytical description of the fault signal propagating in the transmission line was obtained. The analytical solution was verified both by numerical simulations and experimentally.
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Zabihi-Hesari, Alireza, Saeed Ansari-Rad, Farzad A. Shirazi, and Moosa Ayati. "Fault detection and diagnosis of a 12-cylinder trainset diesel engine based on vibration signature analysis and neural network." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, no. 6 (June 3, 2018): 1910–23. http://dx.doi.org/10.1177/0954406218778313.
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This paper presents a condition monitoring and combustion fault detection technique for a 12-cylinder 588 kW trainset diesel engine based on vibration signature analysis using fast Fourier transform, discrete wavelet transform, and artificial neural network. Most of the conventional fault diagnosis techniques in diesel engines are mainly based on analyzing the difference of vibration signals amplitude in the time domain or frequency spectrum. Unfortunately, for complex engines, the time- or frequency-domain approaches do not provide appropriate features solely. In the present study, vibration signals are captured from both intake manifold and cylinder heads of the engine and were analyzed in time-, frequency-, and time–frequency domains. In addition, experimental data of a 12-cylinder 588 kW diesel engine (of a trainset) are captured and the proposed method is verified via these data. Results show that power spectra of vibration signals in the low-frequency range reliably distinguish between normal and faulty conditions. However, they cannot identify the fault location. Hence, a feature extraction method based on discrete wavelet transform and energy spectrum is proposed. The extracted features from discrete wavelet transform are used as inputs in a neural network for classification purposes according to the location of sensors and faults. The experimental results verified that vibration signals acquired from intake manifold have more potential in fault detection. In addition, the capacity of discrete wavelet transform and artificial neural network in detection and diagnosis of faulty cylinders subjected to the abnormal fuel injection was revealed in a complex diesel engine. Beside condition monitoring of the engine, a two-step fault detection method is proposed, which is more reliable than other one-step methods for complex engines. The average condition monitoring performance is from 93.89% up to 99.17%, based on fault location and sensor placement, and the minimum classification performance is 98.34%.
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Bayati, Navid, and Mehdi Savaghebi. "Protection Systems for DC Shipboard Microgrids." Energies 14, no. 17 (August 27, 2021): 5319. http://dx.doi.org/10.3390/en14175319.
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In recent years, shipboard microgrids (MGs) have become more flexible, efficient, and reliable. The next generations of future shipboards are required to be equipped with more focuses on energy storage systems to provide all-electric shipboards. Therefore, the shipboards must be very reliable to ensure the operation of all parts of the system. A reliable shipboard MG should be protected from system faults through protection selectivity to minimize the impact of faults and facilitate detection and location of faulty zones with the highest accuracy and speed. It is necessary to have an across-the-board overview of the protection systems in DC shipboards. This paper provides a comprehensive review of the issues and challenges faced in the protection of shipboard MGs. Furthermore, given the different types of components utilized in shipboard MGs, the fault behavior analysis of these components is provided to highlight the requirements for their protection. The protection system of DC shipboards is divided into three sub-systems, namely, fault detection, location, and isolation. Therefore, a comprehensive comparison of different existing fault detection, location, and isolation schemes, from traditional to modern techniques, on shipboard MGs is presented to highlight the advantages and disadvantages of each scheme.
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Wu, Yanhui, Guowei Zhu, Wei Wang, Mengbo Zhang, and Zhen Gao. "Quantitative Evaluation of Faults by Combined Channel Wave Seismic Transmission-Reflection Detection Method." Minerals 12, no. 8 (August 14, 2022): 1022. http://dx.doi.org/10.3390/min12081022.
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The quantitative detection of faults using the channel wave seismic method has been a major but challenging area of interest. In this study, we adopted an effective technical process to evaluate fault attribution. First, we use integrated transmission and reflection channel wave information to improve the accuracy of extraction velocity. Then, the location of the fault is determined by the elliptical tangent offset method, and feature extraction and fault location extension determination are achieved through logistic regression and a neural network. This is combined with the prior geological information, the fractional dimension D to the quantitative analysis of the fault throw. Data regarding the 4203 working face of a mine in Shanxi, China, are considered as an example. Two groups of faults were predicted, with the location error in the f30 fault position as 6.7 m. In addition, the f29 fault throw first increased, and then gradually decreased from the return airway to the haulage gateway. These predicted results have been drill-verified and were used to modify the original design. The proposed method has good stability and promising application prospects for fault evaluation.
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Mirshekali, Hamid, Rahman Dashti, Ahmad Keshavarz, and Hamid Reza Shaker. "Machine Learning-Based Fault Location for Smart Distribution Networks Equipped with Micro-PMU." Sensors 22, no. 3 (January 26, 2022): 945. http://dx.doi.org/10.3390/s22030945.
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Faults in distribution networks occur unpredictably, causing a threat to public safety and resulting in power outages. Automated, efficient, and precise detection of faulty sections could be a major element in immediately restoring networks and avoiding further financial losses. Distributed generations (DGs) are used in smart distribution networks and have varied current levels and internal impedances. However, fault characteristics are completely unknown because of their stochastic nature. Therefore, in these circumstances, locating the fault might be difficult. However, as technology advances, micro-phasor measurement units (micro-PMU) are becoming more extensively employed in smart distribution networks, and might be a useful tool for reducing protection uncertainties. In this paper, a new machine learning-based fault location method is proposed for use regardless of fault characteristics and DG performance using recorded data of micro-PMUs during a fault. This method only uses the recorded voltage at the sub-station and DGs. The frequency component of the voltage signals is selected as a feature vector. The neighborhood component feature selection (NCFS) algorithm is utilized to extract more informative features and lower the feature vector dimension. A support vector machine (SVM) classifier is then applied to the decreased dimension training data. The simulations of various fault types are performed on the 11-node IEEE standard feeder equipped with three DGs. Results reveal that the accuracy of the proposed fault section identification algorithm is notable.
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Hung, Truong Ngoc. "Methods for Fault Location in High Voltage Power Transmission Lines: A Comparative Analysis." International Journal of Renewable Energy Development 11, no. 4 (August 15, 2022): 1134–41. http://dx.doi.org/10.14710/ijred.2022.46501.
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Power transmission system stability can be significantly affected due to faults. The fault location accuracy in the transmission lines can make many benefits such as acceleration of the line restoration, reduction in cost, breakdown time, maintenance, and time searching. The methods based on the impedance, including the simple reactance, Takagi, modified Takagi, and double-end, are very much appreciated for locating the fault in transmission lines and especially by estimating the fault distance. This study proposes a comparative case study between these methods. The theoretical basis and the analysis, calculation, and estimation of each method are specifically re-established. To observe the performance of each method, a practical 220kV Quy Nhon - Tuy Hoa transmission line in Vietnam is used to simulate, calculate, evaluate, and compare under the various fault types and resistances. The power system is modeled and simulated in the MATLAB/Simulink software via the time domain. The voltage and current measurements at two ends of the line are used to determine the fault location on the Quy Nhon - Tuy Hoa transmission line. The simulation results show clearly the effectiveness of each fault location method.
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Wang, Chenqing, Peng Li, Xiao Xu, and Hui Gao. "A DC Fault Location Method of Multiterminal Flexible DC Distribution Network." Mathematical Problems in Engineering 2022 (February 24, 2022): 1–12. http://dx.doi.org/10.1155/2022/8120857.
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Multiterminal flexible DC distribution network is a complex system made up of many power-electronic devices. Its diversified and comprehensive fault characteristics are featured by multiperiod and strong transient. This paper starts with investigating the mechanisms of typical DC short circuit faults of the MMC-based system. Then, a typical flexible DC distribution network is built in PSCAD to analyse the characteristics of its pole-to-pole short-circuit fault and pole-to-ground fault. With the aid of the above findings, a fault detection and location method is proposed with its effectiveness evaluated through simulations.
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Yang, Haizhu, Xiangyang Liu, Yiming Guo, and Peng Zhang. "Fault Location of Active Distribution Networks Based on the Golden Section Method." Mathematical Problems in Engineering 2020 (February 8, 2020): 1–9. http://dx.doi.org/10.1155/2020/6937319.
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Aiming at the problem of fault location in distribution networks with distributed energy resources (DERs), a fault location method based on the concepts of minimum fault reactance and golden section is proposed in this paper. Considering the influence of distributed energy resource supply on fault point current in distribution networks, an improved trapezoidal iteration method is proposed for load flow analysis and fault current calculation. This method only needs to measure the synchronous current of the distributed energy resource and does not need to measure the voltage information. Therefore, the investment in equipment is reduced. Validation is made using the IEEE 34-node test feeder. The simulation results show that the method is suitable for fault location of distribution networks with multiple distributed generators. This method can accurately locate the faults of the active distribution network under different conditions.
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Abasi-obot, I. E., A. B. Kunya, G. S. Shehu, and Y. Jibril. "High Impedance Fault Detection and Localization Using Fully-Connected Convolutional Neural Network: A Deep Learning Approach." Nigerian Journal of Technological Development 20, no. 4 (February 26, 2024): 62–71. http://dx.doi.org/10.4314/njtd.v20i4.2143.
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The detection and localization of high impedance faults (HIF) in power systems are challenging due to the low fault current magnitude, which often falls below the detection threshold of conventional devices. HIF events introduce harmonics into the network, posing risks to the safety of connected equipment, including the potential for igniting fire which endangers lives and properties. In this study, Emanuel's HIF model was used to generate HIF signatures resembling real HIF events. Model parameters were adjusted to mimic various contact surface impedances. Two datasets were created: 'no-fault' data, simulating the network without HIF, and 'fault' data, incorporating HIF waveforms by simulating single and multiple lines with the HIF model. The faulted line was divided into five segments along the 33 kV line to capture fault signatures at different locations. The generated data, including current waveforms and magnitudes, were processed and divided into an 80:20 ratio for training, validation, and testing using a deep fully connected Convolutional Neural Network for HIF detection and location. The results showed an impressive accuracy rate of 99.44% and 99.78% for detection and location respectively, representing a significant advancement in HIF detection and location, and offering practical applications for enhancing power line safety.
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Balladka, Dhananjaya. "Unmanned Fault Detection in Distribution Lines." European Journal of Electrical Engineering 23, no. 1 (February 28, 2021): 37–43. http://dx.doi.org/10.18280/ejee.230105.
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The companies supplying electric power round the globe are facing various issues related due to the occurrence of fault in the distribution lines. Most of them are investing on the research and development of state-of-art technologies to boost continuous supply of energy to the users. The consumers can be guaranteed of flawless power if it is possible to identify and rectify the faults at the shorter time span than usual. The usual way to identify the fault and fault location is with the aid of man power. This work deals with the design and fabrication of an intelligent system based on the GSM. This system helps in efficient identification of the fault and location of the fault, initiating a message to the respective crew members and the control station and ensures that the technical crew will be able to reach the location very accurately in shorter time and recapitulate power at the earliest. The setup includes a current sensor, Arduino and a GSM module. The system identifies the location of fault and the data regarding the location of fault is efficiently conveyed to the control personnel or monitoring system over GSM. The location of the fault thus obtained is very fine and accurate, and the time needed to identify the location of flaw is greatly reduced.
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Gómez, Roberto, Diego Cabrera, and Pablo Robles. "Study for localization of fault in the electrical distribution systems." Ingenius, no. 30 (July 1, 2023): 64–78. http://dx.doi.org/10.17163/ings.n30.2023.06.
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This article studies the location of faults in the electrical distribution system based on processing short-circuit signals. For this analysis, the simulation of cases using the CYME software is proposed, using the Wavelet transform to study the signal obtained and decomposed. The minimum spanning tree method is proposed so that fault location is optimal and reconnection time is minimal. This analysis considers the reclosers’ location in the distribution system that will serve as information repositories. In this investigation, a fault location algorithm was developed to analyse transient phenomena, achieving good precision in time frequency. Applying the proposed method, the signal is broken down into different levels, obtaining the necessary parameters to determine the distance of the fault.
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Nazerian, Vahdat, Mohammad Esmail Zakerifar, Mahmoud Zadehbagheri, Mohammad Javad Kiani, and Tole Sutikno. "Comparative detection and fault location in underground cables using Fourier and modal transforms." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (December 1, 2022): 5821. http://dx.doi.org/10.11591/ijece.v12i6.pp5821-5839.
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<span>In this research, we create a single-phase to ground synthetic fault by the simulation of a three-phase cable system and identify the location using mathematical techniques of Fourier and modal transforms. Current and voltage signals are measured and analyzed for fault location by the reflection of the waves between the measured point and the fault location. By simulating the network and line modeling using alternative transient programs (ATP) and MATLAB software, two single-phase to ground faults are generated at different points of the line at times of 0.3 and 0.305 s. First, the fault waveforms are displayed in the ATP software, and then this waveform is transmitted to MATLAB and presented along with its phasor view over time. In addition to the waveforms, the detection and fault location indicators are presented in different states of fault. Fault resistances of 1, 100, and 1,000 ohms are considered for fault creation and modeling with low arch strength. The results show that the proposed method has an average fault of less than 0.25% to determine the fault location, which is perfectly correct. It is varied due to changing the conditions of time, resistance, location, and type of error but does not exceed the above value.</span>
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Yang, Yongsheng, Qi Zhang, Minzhen Wang, Xinheng Wang, and Entie Qi. "Fault Location Method of Multi-Terminal Transmission Line Based on Fault Branch Judgment Matrix." Applied Sciences 13, no. 2 (January 15, 2023): 1174. http://dx.doi.org/10.3390/app13021174.
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Aiming at the difficulty of fault location of multi-source transmission lines, this paper proposes a fault location method for multi-terminal transmission lines based on a fault branch judgment matrix. The fault traveling wave signal is decomposed by Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and the IMFs sensitive components that can characterize the fault characteristics of the target signals are selected by constructing a correlation-rearrangement entropy function. The arrival time of fault signals at the endpoint has been accurately calibrated by combining them with the Teager Energy Operator (TEO). To eliminate the influence of wave velocity and fault time on the location results, this paper proposes a two-terminal location method based on the line mode component to improve the location accuracy. On this basis, combined with the fault branch judgment matrix, the accurate location of multi-terminal transmission line faults is realized. This method has been shown to have high accuracy in detecting traveling wave heads, accurately judging fault branches, and producing a small error in fault location results. Compared with the existing multi-terminal transmission line fault location algorithm, it has obvious advantages and meets the needs of actual working conditions.
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Hamdouche, Tarek, Omar Bendjeghaba, Brakta Noureddine, and Ahriche Aimad. "A novel fault location approach for radial power distribution systems." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (June 1, 2022): 2242. http://dx.doi.org/10.11591/ijece.v12i3.pp2242-2255.
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Power distribution systems (PDS) are increasingly complex and spread over long distances and in different locations. Given their radial configuration, the loads could be inserted at the same distances from the substation. This leads to multiple estimation of fault location (FL) and yields time consuming for iterative FL algorithms. In this article, we provide a novel practical approach to fault localization in order to defeat these limitations. The central idea of the proposed approach is to divide the multilateral distribution system into a possible number of mono-lateral sub systems (MLS) using a proposed communicating sensor. Next, we apply two different fault locator algorithms only to the defective MLS. The first variant of the approach is based on the impedance method, while the second variant is non-parametric used only when there is lack in the line data. To test the proposed technique in practice, we used the IEEE 13 Node test feeder, and a real Algerian PDS. The results obtained clearly show the contribution of the dedicated method for locating faults in the PDS.
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FANG, ZIJUN, GUANSHUI XU, and DAVID D. OGLESBY. "GEOMETRIC EFFECTS ON EARTHQUAKE NUCLEATION ON BENT DIP-SLIP FAULTS." International Journal of Applied Mechanics 03, no. 01 (March 2011): 99–117. http://dx.doi.org/10.1142/s1758825111000890.
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The geometric effects on earthquake nucleation processes on bent dip-slip faults are studied using a slip strengthening and weakening friction law implemented in a two-dimensional quasi-static boundary integral model. The results show that the bend causes normal stress variations under tectonic loading on both the upper and lower segments. These stress variations differ from those on planar faults, leading to significant effects on earthquake nucleation location and time. Earthquakes tend to nucleate at shallower locations on thrust faults and at deeper locations on normal faults for steeper dipping angles on the lower fault segments. The elapsed time until nucleation on both thrust and normal faults is increased considerably as the bend angle becomes larger. For a thrust fault with a nearly horizontal lower segment, the time until nucleation can be more than 10 times larger than that for a corresponding planar fault. These findings may provide important insights for earthquake hazard analysis by taking the fault geometry effect into account when estimating hypocenter positions and time to instability.
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Xiao, Yang, Jinxin Ouyang, and Xiaofu Xiong. "A New Locating Method of Break Faults in an Active Distribution Network Based on Distributed Generator Monitoring." International Transactions on Electrical Energy Systems 2022 (January 31, 2022): 1–12. http://dx.doi.org/10.1155/2022/4176869.
Full textAbstract:
Traditional distribution networks are transforming into active distribution networks (ADNs) with the advancement of distributed generators (DGs). Break faults that lead to voltage and current imbalances and fluctuations threat the safety of sensitive power electronic equipment in ADNs. However, locating break faults in ADNs remains a challenge under the influence of DG fault polymorphism. This paper proposes a new method to locate break faults by monitoring information of DG current based on the observability of ADNs. The DG equivalent model is established based on the DG output characteristics under the presence of a single-phase break fault. The characteristics of the fault current contributed by DG are analyzed. An identification method of break faults is proposed based on the variations in DG current. Thus, a fault-locating matrix algorithm is proposed combined with current information and location information of DGs. The simulation results demonstrate that the proposed method can locate break faults quickly and accurately. The method is not affected by topology and changes of DG output and load.
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Okoli, Chinweike, Boniface Anyaka, Chidiogo Nwokedi, and Victor Anya. "Application of Composite Method for Determining Fault Location on Electrical Power Distribution Lines." Journal of Electrical and Computer Engineering 2020 (September 1, 2020): 1–9. http://dx.doi.org/10.1155/2020/2836940.
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Distribution line is one of the most important components of the distribution system. Troubleshooting faults on these lines are often a tedious task requiring service vehicles and personnel moving from one place to another in order to locate the fault and fix the problem. The study, therefore, is on how a composite fault location technique can be applied to predict the location of faults on the distribution lines. The calculations for the estimation of the fault location are performed using one terminal voltage and current data of the distribution line. A composite method that combines the impedance-based method and the fuzzy inference system method is used in the fault location algorithm. The presented algorithm has been extensively tested using the MATLAB-Simulink model of a 33 KV 40-kilometer distribution line. The simulation result demonstrates good accuracy and robustness of the algorithm.
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Liu, Junqiao, Yanfang Lv, Ye Wang, Yunshuang Kang, Xinlei Hu, and Jijian Shi. "Prediction of Favourable Hydrocarbon Transport Pathways of the Jiuzhou Fault in Langgu Sag, Bohai Bay Basin." Processes 11, no. 6 (May 30, 2023): 1666. http://dx.doi.org/10.3390/pr11061666.
Full textAbstract:
The Jiuzhou fault in the Langgu Sag of the Bohai Bay Basin is a significant oil-source fault that connects source rocks and reservoirs, and thus it can transport oil and gas during the hydrocarbon accumulation period. The hydrocarbon distribution characteristics along the strike of the Jiuzhou fault differ distinctly, indicating that the transport capacity in different fault segments is also different. In this study, we focused on analyzing the fault development characteristics to accurately predict the location of favorable hydrocarbon transport pathways on the Jiuzhou fault. We found that the zones superimposed by paleo relay ramps developed before hydrocarbon accumulation, active faulting areas during hydrocarbon accumulation, and transport ridges of the fault are favourable along-fault locations for transporting hydrocarbons. Based on this idea and 3D seismic data, we investigated the distribution of the paleo relay ramps of the Jiuzhou fault and the fault activity rate during hydrocarbon accumulation using the maximum throw subtraction method. Then, the burial depth contour was employed to search hydrocarbon transport ridges of the fault and therefore predict the location of favourable hydrocarbon transport pathways of the Jiuzhou fault. The prediction results show that there are totally 4 favorable hydrocarbon transport pathways, where hydrocarbons are more likely to migrate vertically and finally accumulate in the overlying formations. In addition, the pathway locations of the Jiuzhou fault are consistent with the hydrocarbon distribution in the study area, demonstrating that this method is reliable and feasible for predicting the favorable hydrocarbon transport pathways of oil-source faults.
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Murugan, N., J. S. Senthil Kumar, T. Thandapani, S. Jaganathan, and N. Ameer. "Underground Cable Fault Detection Using Internet of Things (IoT)." Journal of Computational and Theoretical Nanoscience 17, no. 8 (August 1, 2020): 3684–88. http://dx.doi.org/10.1166/jctn.2020.9261.
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A fault in electrical equipment is defined as defect in the system where the current is diverted or blocked from its original path. Faults occur due to cheap materials and improper sheath in the cables. Also, whenever a fault occurs in underground cable it is very difficult to detect the exact location of the fault and for repairing the same cable. The proposed system helps to find the exact location of the fault and determines the fault using an Arduino microcontroller. It also detects the leakage current using a relay driver to avoid faults occurring repeatedly. The concept is based on ohm’s law, due to variation in current the voltage drop can vary on counting on the length of the fault in cable. The fault data are stored in cloud for future reference to the base station. The exact location is displayed in the LCD screen connected with the microcontroller.