Condition Assessment of High Voltage Circuit Breaker Operating Mechanism Based on Coil Current Waveform

DOI

10.2991/epee-16.2016.46How to use a DOI?

Keywords

coil current waveform; condition assessment; finite element method; feature and inflection extraction; high voltage circuit breaker; neural network; operating mechanism of circuit breaker; Pearson correlation coefficient; slope method; waveform recognition

Abstract

In order to evaluate the condition of the high voltage circuit breaker (HVCB) operating mechanism, a method based on the coil current (CC) waveform of the operating mechanism has been studied in this paper. A finite element method (FEM) with high accuracy has been used to establish an electromagnetic system model of the operating mechanism. The effects of the mechanical parameter variations and mechanism faults on the CC waveform have been studied by simulation and experimental studies, and the features and inflections of the CC waveform are determined as the evaluation indices of the mechanism. Then the slope method has been used to extract features and inflections of the CC waveform after filtering, and the CC features are optimized by Pearson correlation coefficient method. Finally, the condition of the HVCB operating mechanism has been evaluated by the combination of the waveform recognition and neural network analysis. It has been concluded that the evaluation results can accurately reflect the operation condition of the HVCB operating mechanism.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaoli Duan
AU  - Hongcai Lei
AU  - Min Fan
AU  - Lihua Zhao
AU  - Rongrong Fu
AU  - Qiang Rong
AU  - Hao Zhang
AU  - Zhong Wang
PY  - 2016/10
DA  - 2016/10
TI  - Condition Assessment of High Voltage Circuit Breaker Operating Mechanism Based on Coil Current Waveform
BT  - Proceedings of the 2016 International Conference on Energy, Power and Electrical Engineering
PB  - Atlantis Press
SP  - 207
EP  - 212
SN  - 2352-5401
UR  - https://doi.org/10.2991/epee-16.2016.46
DO  - 10.2991/epee-16.2016.46
ID  - Duan2016/10
ER  -