Advanced monitoring system for integrity assessment of electric power transmission lines

Author

Lim, Sun-Wook ; Shoureshi, Rahmat A.

Author_Institution

Sch. of Eng. & Comput. Sci., Denver Univ., CO

fYear

2006

fDate

14-16 June 2006

Abstract

An advanced monitoring system, composed of an electromagnetic acoustic transducer (EMAT), and a neural-based classifier has been developed. The fault detection is achieved by analyzing the reflected displacement waves from broken strands of the transmission line. This monitoring system can assess the state of an energized electric transmission lines in real-time. For pattern analysis of reflected signals and extracting important features from the raw data, signal processing and feature extraction techniques are employed. In addition, this paper presents a technique for synthesizing signatures using neural-fuzzy inference engine for enhancing the robustness of the classifier. Experimental results verifying performance of this new monitoring system are presented

Keywords

acoustic transducers; fuzzy neural nets; inference mechanisms; pattern classification; power distribution faults; power transmission control; power transmission faults; signal processing; advanced monitoring system; classifier robustness; electric power transmission line; electromagnetic acoustic transducer; fault detection; feature extraction; integrity assessment; neural-based classifier; neural-fuzzy inference engine; pattern analysis; reflected displacement wave; reflected signal; signal processing; Acoustic transducers; Data mining; Electrical fault detection; Feature extraction; Monitoring; Pattern analysis; Power transmission lines; Real time systems; Signal processing; Signal synthesis;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2006

Conference_Location

Minneapolis, MN

Print_ISBN

1-4244-0209-3

Electronic_ISBN

1-4244-0209-3

Type

conf

DOI

10.1109/ACC.2006.1657414

Filename

1657414