A Study on the Estimation of Tension of Overhead Wire Using Acceleration Sensor Using Gradient Boosting Regression

This study proposes a novel method for estimating tension in overhead wires of distribution systems using acceleration sensors, crucial for ensuring reliable power supply and proactive asset management. Traditional tension sensors, which are costly and complex to install, are replaced by a more cost-effective and robust alternative. Pearson correlation analysis revealed significant correlations between acceleration sensor data and actual wire tension, enabling the use of Gradient Boosting Regression(GBR) for effective tension estimation. The model achieved a high R2 score of 0.95, demonstrating the potential of acceleration sensor-based systems in maintaining system integrity and enabling real-time monitoring for preemptive maintenance. This method promises enhanced operational efficiency, system longevity, and cost savings. Future research should integrate these findings into comprehensive monitoring systems for improved decision-making.

Authors

Publication Details

Journal
The Transactions of The Korean Institute of Electrical Engineers
Published
2024-10-31
DOI
https://doi.org/10.5370/kiee.2024.73.10.1757
Primary Topic
Engineering Applied Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Study on the Estimation of Tension of Overhead Wire Using Acceleration Sensor Using Gradient Boosting Regression

Jun-Hyeok Kim
The Transactions of The Korean Institute of Electrical Engineers
Engineering Applied Research
article

A Study on the Estimation of Tension of Overhead Wire Using Acceleration Sensor Using Gradient Boosting Regression

Jun-Hyeok Kim
article en

Abstract

This study proposes a novel method for estimating tension in overhead wires of distribution systems using acceleration sensors, crucial for ensuring reliable power supply and proactive asset management. Traditional tension sensors, which are costly and complex to install, are replaced by a more cost-effective and robust alternative. Pearson correlation analysis revealed significant correlations between acceleration sensor data and actual wire tension, enabling the use of Gradient Boosting Regression(GBR) for effective tension estimation. The model achieved a high R2 score of 0.95, demonstrating the potential of acceleration sensor-based systems in maintaining system integrity and enabling real-time monitoring for preemptive maintenance. This method promises enhanced operational efficiency, system longevity, and cost savings. Future research should integrate these findings into comprehensive monitoring systems for improved decision-making.

The Transactions of The Korean Institute of Electrical EngineersVol. 73(10)
Affordable and clean energy
Openalex Percentile: Top 76%
Engineering Applied Research
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.

A Study on the Estimation of Tension of Overhead Wire Using Acceleration Sensor Using Gradient Boosting Regression — Jun-Hyeok Kim · The Transactions of The Korean Institute of Electrical Engineers (2024) | TGRS Research Map | TGRS