Long distance fault location system for single-mode and multimode fibers with a 1.3-µm YAG laser

1982 ◽  
Author(s):  
Masataka Nakazawa ◽  
Masamitsu Tokuda ◽  
Naoya Uchida
Keyword(s):  
Fault Location ◽  
Single Mode ◽  
Long Distance ◽  
Yag Laser ◽  
Location System ◽  
Multimode Fibers

Long-distance submerged cable fault location technique

1986 ◽  
Vol 22 (3) ◽  
pp. 162 ◽  
Author(s):  
G.F. Lakey ◽  
E.A. Cottrell
Keyword(s):  
Fault Location ◽  
Long Distance

scholarly journals A Single-Terminal Fault Location Method for HVDC Transmission Lines Based on a Hybrid Deep Network

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 255
Author(s):  
Lei Wang ◽  
Yigang He ◽  
Lie Li
Keyword(s):  
Deep Learning ◽  
Transmission Lines ◽  
Fault Location ◽  
Short Term Memory ◽  
Engineering Application ◽  
Energy Operator ◽  
Sampling Frequency ◽  
Learning Technology ◽  
Long Distance ◽  
Hvdc Transmission

High voltage direct current (HVDC) transmission systems play an increasingly important role in long-distance power transmission. Realizing accurate and timely fault location of transmission lines is extremely important for the safe operation of power systems. With the development of modern data acquisition and deep learning technology, deep learning methods have the feasibility of engineering application in fault location. The traditional single-terminal traveling wave method is used for fault location in HVDC systems. However, many challenges exist when a high impedance fault occurs including high sampling frequency dependence and difficulty to determine wave velocity and identify wave heads. In order to resolve these problems, this work proposed a deep hybrid convolutional neural network (CNN) and long short-term memory (LSTM) network model for single-terminal fault location of an HVDC system containing mixed cables and overhead line segments. Simultaneously, a variational mode decomposition–Teager energy operator is used in feature engineering to improve the effect of model training. 2D-CNN was employed as a classifier to identify fault segments, and LSTM as a regressor integrated the fault segment information of the classifier to achieve precise fault location. The experimental results demonstrate that the proposed method has high accuracy of fault location, with the effects of fault types, noise, sampling frequency, and different HVDC topologies in consideration.

Fault location system in autotransformer feeding circuit of ac electric railways

1976 ◽  
Vol 96 (5) ◽  
pp. 96-105 ◽  
Author(s):  
Hirofumi Fujie ◽  
Azusa Miura
Keyword(s):  
Fault Location ◽  
Location System

Aircraft Cable Fault Location Based on Detection Model

2011 ◽  
Vol 55-57 ◽  
pp. 332-336 ◽  
Author(s):  
Xiao Lin Liu ◽  
Zhi Quan Li
Keyword(s):  
Fault Location ◽  
Reference Signal ◽  
Experimental Results ◽  
Civil Aviation ◽  
Location Method ◽  
Aviation Maintenance ◽  
Location System ◽  
Detection Model ◽  
Experimental Installation

An aircraft cable fault location method based on detection model is proposed to solve the problem of being difficult to inspect the fault for the civil aviation maintenance. In response to the condition of the experimental installation, the reference signal is designed. The fault of the cable can be located according to the reflected waveform. An aircraft cable fault location system is designed and the experimental results show that the method is rational and effective.

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