Mobile QR Code QR CODE : The Transactions of the Korean Institute of Electrical Engineers
Title Anomaly Data Analysis of Electric Railway Facility using Data Mining Method
Authors 신승권(Seung-Kwon Shin) ; 김재원(Jae-Won Kim) ; 조규정(Gyu-Jung Cho) ; 정호성(Ho-Sung Jung) ; 김형철(Hyung-Chul Kim)
DOI https://doi.org/10.5370/KIEE.2020.69.11.1795
Page pp.1795-1800
ISSN 1975-8359
Keywords TEO; STFT; Clustering
Abstract It is necessary to develop a novel technology for predicting and diagnosing anomaly conditions of the railway power system, such as voltage drop and distortion so as to prevent a fault due to a power outage of the railway power system during railroad operation.
Therefore, for intelligent management and maintenance of electric power equipment for railway system, an algorithm for an anomaly condition monitoring system based on real time TEO information was developed, and field installation for performance verification of the developed module was completed. In this paper, we describe the data mining process of a real-time monitoring system for anomaly conditions of the railway power system and the process of verifying the operation of the monitoring system.