Multi-core Cable Fault Diagnosis using Cluster Time-Frequency Domain Reflectometry

被引:0
|
作者
Lee, Chun-Kwon [1 ]
Shin, Yong-June [1 ]
机构
[1] Yonsei Univ, Sch Elect & Elect Engn, 50 Yonsei-Ro, Seoul, South Korea
来源
2018 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC): DISCOVERING NEW HORIZONS IN INSTRUMENTATION AND MEASUREMENT | 2018年
关键词
control and instrumentation cable; fault diagnosis; reflectometry; time-frequency analysis; crosstalk; K-means clustering;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Guaranteeing the integrity and functionality of the control and instrumentation (C &I) cable system is essential in ensuring safe nuclear power plant (NPP) operation. When a fault occurs in a multi-core cable, it not only affects the signals of faulty lines but in fact, disturbs the rest as well due to crosstalk and noise interference. Therefore, this results in C&I signal errors in NPP operation and further leads to a rise in concern regarding the NPP operation. Thus, it is necessary for diagnostic technologies of multi-core C&I cables to classify the faulty line and detect the fault to assure the safety and reliability of NPP operation. We propose a diagnostic method that detects the fault location and faulty line in multi-core C&I cable using a clustering algorithm based on TFDR results. The faulty line detection clustering algorithm uses TFDR cross-correlation and phase synchrony results as input feature data altogether which can detect the faulty line and identify the fault point successfully. The proposed clustering algorithm is verified by experiments with two possible fault scenarios in NPP operation.
引用
收藏
页码:499 / 504
页数:6
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