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Appl. Sci. 2015, 5(3), 307-319; doi:10.3390/app5030307

Research on the Fault Coefficient in Complex Electrical Engineering

1,†
,
2,3,†,* and 3,†
1
Hebei Electric Power Research Institute, Shijiazhuang, Hebei 050022, China
2
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
3
Interdisciplinary Mathematics Institute, University of South Carolina, Columbia, SC 29208, USA
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Hung-Yu Wang
Received: 13 April 2015 / Accepted: 3 August 2015 / Published: 7 August 2015
View Full-Text   |   Download PDF [722 KB, uploaded 7 August 2015]   |  

Abstract

Fault detection and isolation in a complex system are research hotspots and frontier problems in the reliability engineering field. Fault identification can be regarded as a procedure of excavating key characteristics from massive failure data, then classifying and identifying fault samples. In this paper, based on the fundamental of feature extraction about the fault coefficient, we will discuss the fault coefficient feature in complex electrical engineering in detail. For general fault types in a complex power system, even if there is a strong white Gaussian stochastic interference, the fault coefficient feature is still accurate and reliable. The results about comparative analysis of noise influence will also demonstrate the strong anti-interference ability and great redundancy of the fault coefficient feature in complex electrical engineering. View Full-Text
Keywords: fault coefficient; Gaussian interference; BPA; noise influence; PMU fault coefficient; Gaussian interference; BPA; noise influence; PMU
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Sun, Y.; Zhang, Y.; Wang, Y. Research on the Fault Coefficient in Complex Electrical Engineering. Appl. Sci. 2015, 5, 307-319.

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