Detection and Fault Diagnosis of Power Transmission Line in Infrared Image

被引：0

作者：

He, Siyuan ^{[1
,2
,3
]}

Yang, Dawei ^{[1
,2
]}

Li, Wentao ^{[1
]}

Xia, Yong ^{[4
]}

Tang, Yandong ^{[1
]}

机构：

[1] Chinese Acad Sci, Shenyang Inst Automat, State Key Lab Robot, Shenyang 110016, Liaoning, Peoples R China

[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

[3] Shenyang Inst Engn, Sch Automat, Shenyang 110136, Liaoning, Peoples R China

[4] Liaoning Elect Power Co Ltd, Benxi Power Supply Co, Benxi 117000, Liaoning, Peoples R China

来源：

2015 IEEE INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (CYBER) | 2015年

关键词：

power transmission line; infrared image; object detection; fault diagnosis;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With surface aging and natural disasters, power transmission line often has broken strand fault which presents partial discharge and temperature rising. Infrared thermography is a new method to detect the temperature rising fault. Aiming at the temperature rising fault, a method based on infrared image for power transmission line detection and fault diagnosis is proposed. First, we convert infrared image into gray image, enhance the contrast, and eliminate the interference and noise. Next, cellular automaton method is used to segment the target and background in preprocessed image. Then, power transmission line is recognized and detected by using Hessian matrix. Finally, the fault is diagnosed based on temperature, and fault location is also determined. Experimental results indicate that this method can diagnose the temperature rising fault, and its accuracy is more than 90%. It has better robustness, accuracy and validity.

引用

页码：431 / 435

页数：5

共 50 条

[41] Fault detection system for ICRF transmission line in LHD
Saito, K.
Seki, T.
Kasahara, H.
Seki, R.
Kamio, S.
Nomura, G.
Mutoh, T.
FUSION ENGINEERING AND DESIGN, 2017, 123 : 444 - 447
[42] Support vector machine for fault detection in transmission line
Malathi, V.
Marimuthu, N.S.
Engineering Intelligent Systems, 2009, 17 (01): : 13 - 18
[43] Autonomous Transmission Line Inspection and Fault Detection System
Ranaweera, P. S.
Alahakoon, D. C.
Prabhashwara, K. S. S.
Lakmal, A. M. G. V., I
2018 MORATUWA ENGINEERING RESEARCH CONFERENCE (MERCON) 4TH INTERNATIONAL MULTIDISCIPLINARY ENGINEERING RESEARCH CONFERENCE, 2018, : 402 - 407
[44] Transmission Line Fault Detection Based on Multilayer Perceptron
Yang, Hengyu
2022 INTERNATIONAL CONFERENCE ON BIG DATA, INFORMATION AND COMPUTER NETWORK (BDICN 2022), 2022, : 778 - 781
[45] Support vector machine for fault detection in transmission line
Malathi, V.
Marimuthu, N. S.
ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, 2009, 17 (01): : 13 - 18
[46] An algorithm for power transmission line fault detection based on improved YOLOv4 model
Yan, Su
Gao, Lisha
Wang, Wendi
Cao, Gang
Han, Shuo
Wang, Shufan
SCIENTIFIC REPORTS, 2024, 14 (01)
[47] An algorithm for power transmission line fault detection based on improved YOLOv4 model
Su Yan
Lisha Gao
Wendi Wang
Gang Cao
Shuo Han
Shufan Wang
Scientific Reports, 14
[48] Transmission Line Fault Detection and Identification in an Interconnected Power Network using Phasor Measurement Units
Khan, Abdul Qayyum
Ullah, Qudrat
Sarwar, Muhammad
Gul, Sufi Tabassum
Iqbal, Naeem
IFAC PAPERSONLINE, 2018, 51 (24): : 1356 - 1363
[49] Linear regression index-based method for fault detection and classification in power transmission line
Musa, Mohammed H. H.
He, Zhengyou
Fu, Ling
Deng, Yujia
IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, 2018, 13 (07) : 979 - 987
[50] Accurate Fault Detection and Location in Power Transmission Line Using Concurrent Neuro Fuzzy Technique
Eboule, Patrick S. Pouabe
Hasan, An N.
PRZEGLAD ELEKTROTECHNICZNY, 2021, 97 (01): : 37 - 45

← 1 2 3 4 5 →