Research on Intelligent Accounting Method for Power Transmission Channel Clearing Engineering Based on Binocular Visual Perception

In order to solve the problem of complex engineering quantity accounting process and low standardization level in the clearance work of transmission channels, this paper proposes an intelligent accounting method for transmission channel clearance engineering based on binocular visual perception. Firstly, the RGB image and depth image features are extracted separately through convolutional networks, and the RGB image features and depth features are fused using cross modal feature fusion module(CMF) and compact pyramid module (CPM) to achieve automatic recognition and contour extraction of tree stumps on the job site; Subsequently, a tree diameter measurement module based on 3D information reconstruction was constructed to achieve automatic calculation of tree diameter. Experiments have shown that the mAP for identifying tree stumps in transmission channel clearing sites reaches 0.972, and the relative error of tree diameter measurement is less than 5%, verifying the effectiveness of the method proposed in this paper and providing technical support for intelligent engineering quantity accounting in transmission channel clearing sites.

Authors

Institutions

Publication Details

Published
2024-11-29
DOI
https://doi.org/10.1109/ei264398.2024.10991577
Primary Topic
Evaluation Methods in Various Fields
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Intelligent Accounting Method for Power Transmission Channel Clearing Engineering Based on Binocular Visual Perception

Jiahao Wang, Bo Wang, Jiaxin Zhang, Peng Luo
Evaluation Methods in Various Fields
article

Research on Intelligent Accounting Method for Power Transmission Channel Clearing Engineering Based on Binocular Visual Perception

Jiahao Wang, Bo Wang, Jiaxin Zhang, Peng Luo
article en

Abstract

In order to solve the problem of complex engineering quantity accounting process and low standardization level in the clearance work of transmission channels, this paper proposes an intelligent accounting method for transmission channel clearance engineering based on binocular visual perception. Firstly, the RGB image and depth image features are extracted separately through convolutional networks, and the RGB image features and depth features are fused using cross modal feature fusion module(CMF) and compact pyramid module (CPM) to achieve automatic recognition and contour extraction of tree stumps on the job site; Subsequently, a tree diameter measurement module based on 3D information reconstruction was constructed to achieve automatic calculation of tree diameter. Experiments have shown that the mAP for identifying tree stumps in transmission channel clearing sites reaches 0.972, and the relative error of tree diameter measurement is less than 5%, verifying the effectiveness of the method proposed in this paper and providing technical support for intelligent engineering quantity accounting in transmission channel clearing sites.

Wuhan University (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 93%
Evaluation Methods in Various Fields
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.