《机电工程》杂志社科技期刊核心期刊论文投稿机电一体化机械、仪表电工自动化、计算机浙江大学主办

International Standard Serial Number:

ISSN 1001-4551

Sponsor:

Zhejiang University;

Zhejiang Machinery and Electrical Group

Edited by:

Editorial of Journal of Mechanical & Electrical Engineering

Chief Editor:

ZHAO Qun

Vice Chief Editor:

TANG ren-zhong,

LUO Xiang-yang

Tel:

86-571-87041360,87239525

Fax:

86-571-87239571

Add:

No.9 Gaoguannong,Daxue Road,Hangzhou,China

P.C:

310009

E-mail:

meem_contribute@163.com

Recognition and fault diagnosis of insulator string in aerial images

Published:2015-04-08 author:JIANG Hao-ran1，2，JIN Lin-jun1，2，YAN Shu-jia1 Browse: 3568 Check PDF documents

Recognition and fault diagnosis of insulator string in aerial images

JIANG Hao-ran1，2，JIN Lin-jun1，2，YAN Shu-jia1

（1. College of Electronics and Information Engineering，Tongji University，Shanghai 201804，China；

2. State Key Laboratory of Electrical Insulation and Power Equipment，Xi'an Jiaotong University，

Xi'an 710049，China）

Abstract：Aiming at the insulator sheds' dropping off，study on image threshold segmentation，edge detection，insulator recognition and

fault diagnosis were carried out，characteristics of insulator and the background area were summarized，a new method to recognize and

diagnose fault insulator was proposed. The OTSU was applied for image segmentation，and wavelet modulus maximum method for edge

detection，Hough transform was improved to detect ellipsis quickly，ellipse parameters were used to design the classification standards and

accurately recognize the insulator. Finally，fault diagnosis was realized based on location information. The method was verified using aerial

images. The results indicate that ellipse parameters can be calculated，functions such as edge detection，insulator recognition，and fault

diagnosis can be realized，and the algorithm responds quickly and accurately.

Key words：insulator；hough transform；image recognition；fault diagnose

Advanced Search

Online Office System