Computer model of a two-stage diagnostic system for power transmission lines with tree topology

A computer model of a two-stage system for locating faults by analyzing reflected signals was developed. The simulation results for power transmission lines with varying numbers of branches extending from the main line were discussed. The relationship between fault location efficiency and the network bit error rate was analyzed. The dependence of diagnostic reliability on the number of branches and fault types was examined.

Authors

Institutions

Publication Details

Journal
Učenye zapiski Kazanskogo gosudarstvennogo universiteta. Seriâ Fiziko-matematičeskie nauki/Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki
Published
2024-12-22
DOI
https://doi.org/10.26907/2541-7746.2024.4.518-531
Primary Topic
Power Systems Fault Detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Computer model of a two-stage diagnostic system for power transmission lines with tree topology

С. В. Карпов, D.V. Sarychev
Učenye zapiski Kazanskogo gosudarstvennogo universiteta. Seriâ Fiziko-matematičeskie nauki/Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki
Power Systems Fault Detection
article

Computer model of a two-stage diagnostic system for power transmission lines with tree topology

С. В. Карпов, D.V. Sarychev
article en

Abstract

A computer model of a two-stage system for locating faults by analyzing reflected signals was developed. The simulation results for power transmission lines with varying numbers of branches extending from the main line were discussed. The relationship between fault location efficiency and the network bit error rate was analyzed. The dependence of diagnostic reliability on the number of branches and fault types was examined.

Učenye zapiski Kazanskogo gosudarstvennogo universiteta. Seriâ Fiziko-matematičeskie nauki/Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie naukiVol. 166(4)
Kazan Federal University (RU)
Openalex Percentile: Top 72%
Power Systems Fault Detection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.