An Electrical Insulator Defects Detection Method Combined Human Receptive Field Model

Joint Authors

Guo, Li
Wang, Manran
Chen, Jinhao
Liao, Yu
Yao, Hongying

Source

Journal of Control Science and Engineering

Issue

Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2018-07-03

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Electronic engineering
Information Technology and Computer Science

Abstract EN

Nondestructive inspection of electrical insulators subjected to the high electrical stress and environmental damage is fundamental for reliable operation of a transmission lines.

The breakage and defect of the insulator have great influence on the safe of transmission lines, and insulator defect detection with difference types is a complex work.

This paper proposed an insulator defect detection method inspired by human receptive field model, which meets the requirements for detecting defect insulator in a simple background.

In this method, the defect detection combined human receptive field model of human visual system is constructed and applied on the different insulators, so as to achieve accurate detection of the insulator defected parts.

Experimental results show that the method can accurately and robustly detect the defect (such as cracks and damage) of electrical insulator in case of noise affect.

American Psychological Association (APA)

Guo, Li& Liao, Yu& Yao, Hongying& Chen, Jinhao& Wang, Manran. 2018. An Electrical Insulator Defects Detection Method Combined Human Receptive Field Model. Journal of Control Science and Engineering،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1182914

Modern Language Association (MLA)

Guo, Li…[et al.]. An Electrical Insulator Defects Detection Method Combined Human Receptive Field Model. Journal of Control Science and Engineering No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1182914

American Medical Association (AMA)

Guo, Li& Liao, Yu& Yao, Hongying& Chen, Jinhao& Wang, Manran. An Electrical Insulator Defects Detection Method Combined Human Receptive Field Model. Journal of Control Science and Engineering. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1182914

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1182914