基于RPN和FCN的电力设备锈迹检测

doi:10.3969/j.issn.1006-2475.2018.12.018

计算机与现代化

基于RPN和FCN的电力设备锈迹检测

(1.国网山东省电力公司,山东济南250000；2.中国石油大学（华东）计算机与通信工程学院,山东青岛266580)

收稿日期:2018-09-25 出版日期:2019-01-03 发布日期:2019-01-04
作者简介:沈茂东(1978-),男,山东滕州人,国网山东省电力公司高级工程师,硕士,研究方向:电力安全管理；周伟(1984-),男,高级工程师,硕士,研究方向:电力信息科学与技术; 宋晓东(1977-),男,高级工程师,硕士,研究方向:电气工程及其自动化; 邓昊(1982-),男,工程师,本科,研究方向:电力信息化,电力项目管理;马超(1988-),男,助理工程师,本科,研究方向:电力信息化,电力项目管理; 薛冰(1994-),女,中国石油大学（华东）计算机与通信工程学院硕士研究生,研究方向:深度学习与大数据处理; 张卫山（1970-）,男,教授,研究方向:人工智能,大数据智能处理。
基金资助:
国家自然科学基金资助项目(61309024); 山东省重点研发计划项目(2017GGX0140)

Rust Detection of Power Equipment Based on RPN and FCN

(1. National Grid Shandong Power Company, Jinan 250000, China；
2. College of Computer and Communication Engineering, China University of Petroleum, Qingdao 266582, China)

Received:2018-09-25 Online:2019-01-03 Published:2019-01-04

摘要/Abstract

摘要： 针对电力设备在高温、高压、高流速条件下长期连续运行发生锈蚀隐患难以及时发现的问题，提出一种基于区域建议网络与全卷积神经网络相结合的对无规则锈迹进行检测的方法RPN-FCN。首先使用区域建议网络生成带锈迹的候选区域，然后对锈迹候选区域进行全卷积操作，从而在像素级别进行精确的分类定位。通过实验对比，结果表明本文提出的方法对于无规则的锈蚀检测更加准确有效。

关键词: 区域建议网络, 全卷积网络, 锈迹检测, 无规则

Abstract: As the rust risk of power equipment is difficult to be discovered in the long-term continuous operation under high temperature, high pressure and high flow rate conditions, this paper develops an irregular rust detection method RPN-FCN based on region proposal network and fully convolution network. First, region proposal network generates region proposals, then performs a fully convolution operation on region proposals to perform accurate classification and positioning at the pixel level. The experimental results show the method improves the accuracy and effect of irregular rust detection.

Key words: region proposal network, fully convolution network, rust detection, irregular

中图分类号:

TP391

沈茂东1，周伟1，宋晓东1，邓昊1，马超1，薛冰2，张卫山2. 基于RPN和FCN的电力设备锈迹检测[J]. 计算机与现代化, doi: 10.3969/j.issn.1006-2475.2018.12.018.

SHEN Mao-dong1, ZHOU Wei1, SONG Xiao-dong1, DENG Hao1, MA Chao1, XUE Bing2, ZHANG Wei-shan2. Rust Detection of Power Equipment Based on RPN and FCN[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2018.12.018.

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基于RPN和FCN的电力设备锈迹检测

Rust Detection of Power Equipment Based on RPN and FCN

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