Multiple Fiber Fault Location With Low-Frequency Sub-Carrier Tone Sweep

2017 ◽  
Vol 29 (13) ◽  
pp. 1116-1119 ◽  
Author(s):  
Gustavo C. Amaral ◽  
Joaquim D. Garcia ◽  
Bruno Fanzeres ◽  
Patryk J. Urban ◽  
Jean Pierre von der Weid
Keyword(s):  
Fault Location ◽  
Low Frequency

A Novel Fault-location Method for HVDC Transmission Lines Based on Concentric Relaxation Principle and Wavelet Packet

2020 ◽  
Vol 13 (5) ◽  
pp. 705-716
Author(s):  
Congshan Li ◽  
Ping He ◽  
Feng Wang ◽  
Cunxiang Yang ◽  
Yukun Tao ◽  
...  
Keyword(s):  
Transmission Lines ◽  
Traveling Wave ◽  
Fault Location ◽  
Wave Attenuation ◽  
Wavelet Packet ◽  
Low Frequency ◽  
Evaluation Process ◽  
Location Method ◽  
Hvdc Transmission ◽  
Instantaneous Energy

Background: A novel fault location method of HVDC transmission line based on a concentric relaxation principle is proposed in this paper. Methods: Due to the different position of fault, the instantaneous energy measured from rectifier and inverter are different, and the ratio k between them is the relationship to the fault location d. Through the analysis of amplitude-frequency characteristics, we found that the wave attenuation characteristic of low frequency in the traveling wave is stable, and the amplitude of energy is larger, so we get the instantaneous energy ratio by using the low-frequency data. By using the method of wavelet packet decomposition, the voltage traveling wave signal was decomposed. Results: Finally, calculate the value k. By using the data fitting, the relative function of k and d can be got, that is the fault location function. Conclusion: After an exhaustive evaluation process considering different fault locations, fault resistances, and noise on the unipolar DC transmission system, four-machine two-area AC/DC parallel system, and an actual complex grid, the method presented here showed a very accurate and robust behavior.

Fast Low Frequency Fault Location and Section Identification Scheme for VSC-Based Multi-Terminal HVDC Systems

2021 ◽  
pp. 1-1
Author(s):  
Habib Panahi ◽  
Majid Sanaye-Pasand ◽  
Seyed Hassan Ashrafi Niaki ◽  
Reza Zamani
Keyword(s):  
Fault Location ◽  
Low Frequency ◽  
Identification Scheme

scholarly journals A Low-Frequency Tone Sweep Method for In-Service Fault Location in Subcarrier Multiplexed Optical Fiber Networks

2017 ◽  
Vol 35 (10) ◽  
pp. 2017-2025 ◽  
Author(s):  
Gustavo C. Amaral ◽  
Andrea Baldivieso ◽  
Joaquim Dias Garcia ◽  
Diego C. Villafani ◽  
Renata G. Leibel ◽  
...  
Keyword(s):  
Optical Fiber ◽  
Fault Location ◽  
Low Frequency ◽  
Sweep Method ◽  
Fiber Networks ◽  
Frequency Tone ◽  
Optical Fiber Networks

scholarly journals A Novel Pix2Pix Enabled Traveling Wave-Based Fault Location Method

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1633
Author(s):  
Jinxian Zhang ◽  
Qingwu Gong ◽  
Haojie Zhang ◽  
Yubo Wang ◽  
Yilin Wang
Keyword(s):  
Traveling Wave ◽  
Fault Location ◽  
Arrival Time ◽  
Low Frequency ◽  
Recognition Algorithm ◽  
Estimation Accuracy ◽  
Test Results ◽  
Accuracy Test ◽  
Image Translation ◽  
Component Image

This paper proposes a new Image-to-Image Translation (Pix2Pix) enabled deep learning method for traveling wave-based fault location. Unlike the previous methods that require a high sampling frequency of the PMU, the proposed method can translate the scale 1 detail component image provided by the low frequency PMU data to higher frequency ones via the Pix2Pix. This allows us to significantly improve the fault location accuracy. Test results via the YOLO v3 object recognition algorithm show that the images generated by pix2pix can be accurately identified. This enables to improve the estimation accuracy of the arrival time of the traveling wave head, leading to better fault location outcomes.

A Line Fault Analysis Algorithm Based on the TDR Test Algorithm

2014 ◽  
Vol 686 ◽  
pp. 371-376
Author(s):  
Hai Ye Qiao ◽  
Guang Ling Liang
Keyword(s):  
Fault Location ◽  
Low Frequency ◽  
Comprehensive Analysis ◽  
Fault Analysis ◽  
Analysis Algorithm ◽  
Fault Type ◽  
Time Period ◽  
Test Circuit ◽  
Test Algorithm ◽  
Communication Lines

The use of TDR for a single test to analyze the state of communication lines is not accurate to fault location, It also can cause the confusion of fault type and other drawbacks. This paper proposes a analysis algorithm. It can comprehensive analysis TDR test circuit fault pattern and low-frequency circuit parameters of tested line, then it determines the type and position of faults. During a time period, It tests the circuit impedance with 5-element DC model, records the values of line impedance at different times. Combining Curves of the line impedance and TDR waveforms, It accurately determines fault type of the line through the TDR test and Position of fault. By the trying It can increase the accuracy of judging failure , reduce time of repairing.

scholarly journals Hybrid Pattern Recognition and Multi-resolution Analysis (MRA) Based Fault Location in Power Transmission Lines

2019 ◽  
pp. 1-14
Author(s):  
Jude I. Aneke ◽  
O. A. Ezechukwu ◽  
P. I. Tagboh
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Transmission Lines ◽  
High Frequency ◽  
Fault Location ◽  
Power Transmission ◽  
Low Frequency ◽  
Power Transmission Lines ◽  
Multi Resolution Analysis ◽  
Resolution Analysis

This paper proposes a fault (line-to-line) location on Ikeja West – Benin 330kV electric power transmission lines using wavelet multi-resolution analysis and neural networks pattern recognition abilities. Three-phase line-to-line current and voltage waveforms measured during the occurrence of a fault in the power transmission-line were pre-processed first and then decomposed using wavelet multi-resolution analysis to obtain the high-frequency details and low-frequency approximations. The patterns formed based on high-frequency signal components were arranged as inputs of the neural network, whose task is to indicate the occurrence of a fault on the lines. The patterns formed using low-frequency approximations were arranged as inputs of the second neural network, whose task is to indicate the exact fault type. The new method uses both low and high-frequency information of the fault signal to achieve an exact location of the fault. The neural network was trained to recognize patterns, classify data and forecast future events. Feed forward networks have been employed along with back propagation algorithm for each of the three phases in the Fault location process. An analysis of the learning and generalization characteristics of elements in power system was carried using Neural Network toolbox in MATLAB/SIMULINK environment. Simulation results obtained demonstrate that neural network pattern recognition and wavelet multi-resolution analysis approach are efficient in identifying and locating faults on transmission lines as the average percentage error in fault location was just 0.1386%. This showed that satisfactory performance was achieved especially when compared to the conventional methods such as impedance and travelling wave methods.

Fault Diagnosis Research of TWERD Frequency Converter Based on Wavelet Transform

2011 ◽  
Vol 55-57 ◽  
pp. 596-601
Author(s):  
Xin Sheng Wang ◽  
Hua Qiang Zhang ◽  
Tian Min Zhang
Keyword(s):  
Wavelet Transform ◽  
Fault Location ◽  
Frequency Converter ◽  
Low Frequency ◽  
Normal Operation ◽  
Output Line ◽  
Voltage Waveform ◽  
Line Voltage ◽  
Diagnosis Accuracy ◽  
Working Principle

Taking TWERD frequency converter as research object, the working principle and fault types of three-phase SPWM inverter are analyzed. Its output line voltage waveform in normal operation and fault condition is studied. According to the fault information and the different data of input and load changes, the frequency converter output line voltage waveform is decomposed by wavelet transform. The low frequency energy value is picked-up and regards it as eigenvector. The mapping relationship between eigenvector and fault types are established by BP neural network, the fault bridge and fault location of frequency converter are found. Simulation results show that the diagnosis accuracy is 96.5% after training 46 times. Fast convergence speed and high precision is obtained.

Research on Indirect Fault Diagnosis Method of Top Gearbox on Blast Furnace

2013 ◽  
Vol 823 ◽  
pp. 9-12 ◽  
Author(s):  
Xiang Li Zhao ◽  
Li Xin Gao ◽  
Jian Feng Li
Keyword(s):  
Fault Diagnosis ◽  
Characteristic Frequency ◽  
High Speed ◽  
Fault Location ◽  
Low Frequency ◽  
Vibration Signal ◽  
Heavy Duty ◽  
Low Speed ◽  
Transmission Chain ◽  
Diagnosis Method

Aiming at the difficulties in diagnosis for low speed and heavy duty components of furnace top gearbox, an indirect diagnosis method for vibration signal is proposed in this subject, through which the vibration features of high speed rotating parts that near input end of gearbox is effectively utilized and analyzed for fault judgment of low speed components and a useful methodology is also given for fault diagnosis of both furnace top gearbox and low speed and heavy duty equipments. Since the identification for all faults and accurate fault location cannot be realized by using the existing diagnosis methods, a method of vibration analysis for fault diagnosis to furnace top gearbox is presented to realize accurate judgment and fault location. It can be found out that if near the basic frequency and double frequency of characteristic frequency of high speed components of upper gearbox, there were frequency spacing of fault characteristic frequency of low speed components of subordinate transmission chain apparently showing up, which also happened in low frequency range after demodulation, then the fault location can be determined to the low speed parts of subordinate transmission chain.

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