Research on Large Angle Climbing Intelligent Inspection Rail Robot Applied in Hydropower Station Corridors

This paper proposes a new type of corridor climbing inspection robot, aimed at solving the problems of insufficient power and poor stability of existing robots in complex terrain and steep slope environments. The robot adopts a design that combines ground rails with linear transmission bodies, optimizes the automatic walking drive device and multi axis displacement robotic arm, and achieves stable inspection with a maximum climbing angle of over 60°. The robot is equipped with a high-resolution image acquisition device and a supplementary light source, combined with image processing and machine learning algorithms, to automatically identify and classify defects and anomalies during inspection. The experimental results show that the robot does not derail or deviate when climbing a 60° slope, with a minimum turning radius of 1.5 meters, image resolution of 1080p, battery life of 8 hours, stable data transmission, automatic recognition accuracy of over 95%, and maintains stable performance after continuous operation for 1000 hours.

Authors

Institutions

Publication Details

Published
2024-12-27
DOI
https://doi.org/10.1109/auteee62881.2024.10869766
Primary Topic
Vehicle License Plate Recognition
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Large Angle Climbing Intelligent Inspection Rail Robot Applied in Hydropower Station Corridors

Chengtai Hu, Yong Tao, Xiaoqiang Hou, Tong Liu et al.
Vehicle License Plate Recognition
article

Research on Large Angle Climbing Intelligent Inspection Rail Robot Applied in Hydropower Station Corridors

Chengtai Hu, Yong Tao, Xiaoqiang Hou, Tong Liu, Yang Jin, Minseok Song, Yang Hu, Xu Yong
article en

Abstract

This paper proposes a new type of corridor climbing inspection robot, aimed at solving the problems of insufficient power and poor stability of existing robots in complex terrain and steep slope environments. The robot adopts a design that combines ground rails with linear transmission bodies, optimizes the automatic walking drive device and multi axis displacement robotic arm, and achieves stable inspection with a maximum climbing angle of over 60°. The robot is equipped with a high-resolution image acquisition device and a supplementary light source, combined with image processing and machine learning algorithms, to automatically identify and classify defects and anomalies during inspection. The experimental results show that the robot does not derail or deviate when climbing a 60° slope, with a minimum turning radius of 1.5 meters, image resolution of 1080p, battery life of 8 hours, stable data transmission, automatic recognition accuracy of over 95%, and maintains stable performance after continuous operation for 1000 hours.

State Grid Corporation of China (China) (CN), Yalong Hydro (China) (CN)
Openalex Percentile: Top 60%
Vehicle License Plate Recognition
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.