Title :
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
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;
Conference_Titel :
American Control Conference, 2006
Conference_Location :
Minneapolis, MN
Print_ISBN :
1-4244-0209-3
Electronic_ISBN :
1-4244-0209-3
DOI :
10.1109/ACC.2006.1657414
