Energy and Power Engineering, 2013, 5, 1425-1428
doi:10.4236/epe.2013.54B270 Published Online July 2013 (http://www.scirp.org/journal/epe)
The Discrimination of Inrush Current from Internal
Fault of Power Transformer based on EMD
Fanyuan Zeng, Qianjin Liu, Chao Shi
School of Electric Power, South China University of Technology,Guangzhou, China
Email: zeng_fanyuan@163.com
Received March, 2013
ABSTRACT
The method is based on that the waveform of the inrush distorts seriously, while the fault current nearly keeps sinusoid.
The complicated signal can be decomposed into a finite intrinsic mode functions (IMF) by the EMD, then define and
compute the projection area on X-axis of each IMF—, the specific gravity of SIMF—
ci
Sci
, and the maximum of
ci
—max
. We can get a new scheme of transformer-protection based on comparing the difference between inrush and
fault current. Theoretical analysis show that the method can precisely discriminate inrush and fault current, fault clear-
ance time is about 20ms. Moreover, it is convenient to achieve and hardly be affect by not-periodic component.
Keywords: Inrush Current; Transformer Protection; HHT; EMD; IMF
1. Introduction
At present, the domestic transformer primary protection
in power system configuration mainly uses second har-
monic restraint principle and longitudinal differential
protection based on current discontinuous corner braking
principle. The long-term operating experience shows that
the differential protection can not accurately distinguish
the difference between the transformer internal faults and
external faults, so the main contradiction is still focused
on the identification of magnetizing inrush and internal
fault.
2. Empirical Mode Decomposition
Empirical Mode Decomposition (EMD) can effectively
identify magnetizing inrush and internal fault. EMD is
suitable for the analysis of non-linear, non-stationary
signal sequence with a high signal-to-noise ratio. The
center of this technology is empirical mode decomposi-
tion, which can decompose complex signals into a finite
number of intrinsic mode functions (IMF).The decom-
posed IMF component contains the local features signal
of the different time scales of the original signal. The
empirical mode decomposition method can make the
non- stationary data become smooth and get the Hilbert
transform spectrogram and the frequency of physical
significance. Compared with the short-time Fourier
transform and wavelet decomposition methods, this
method is intuitive, direct, posterior and adaptive.
Basic principles of empirical mode decomposition:
In order to obtain th e intrinsic mode fun ction s , the d ata
signal must be decomposed with EMD. So it is necessary
to introduce the definition of the basic concepts of EMD
decomposition process: IMF. This is the basis of the
master of EMD method.
The intrinsic mode function must satisfy the following
two conditions:
1) In the entire time range, the number of lo cal extreme
points and zero-crossing points of the function must be
equal to, or up to a diffe rence of one;
2) At any time, the average of the local maximum of
the envelope (upper envelope) and the local minimum of
the envelope (the envelope line) must be zero.
The first condition obviously has the similar require-
ments with traditional narrowband stationary Gaussian
signal. For the second condition, it is a new concept
which is the classic global requirements modifies local-
ized requirements, so that the instantaneous frequency is
no longer subject to the asymmetric waveform with un-
necessary fluctuations. In fact, this condition should be
“the local mean of the data is zero”. However, for non-
stationary data calculating the local mean involves the
concept of the local time scale, which is difficult to de-
fine. Therefore, in the second condition, the envelope
flocal maxima and local minimum values of the average
envelope are instead of zero, which make the wave form
of a signal locally symmetric. Huang et al study shows
that, under normal circumstances, to use this instead of
the physical significance of the instantaneous frequency
is in line with the system studied. Intrinsic mode func-
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