Page 48 - IJEEE-2022-Vol18-ISSUE-1
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44 | Saeed, Abdulhassan & Khudair
Fig.10: Series arc fault FFT simulation model.
By least average of error, Daubechies wavelets db2
were determined to be capable of extracting arc-fault
information. The coefficients of the LPF and HPF FIR filters
were then determined and utilized in the method. The results
of its series and parallel arc fault operations are shown in
Fig.12 and 13.
Fig.11: Parallel arc fault FFT simulation model. Fault location
VI. SIMULATION RESULT Fig .12: Simulation result of series arc fault using DWT
and db2.
This section presents simulation results for wavelet
and FFT methods of series and parallel arc fault detection.
A. Simulation result with discrete wavelet detection.
The simulation result with wavelet detection model of
series and parallel arc fault with MATLAB/Simulink and
use dyadic filter bank block to build the wavelet detection.
These models are online simulation by using buffer as
shown in Fig.8 and 9.
MATLAB/Simulink wavelet transform and simulation
results of Arc current waveforms can be used to identify
where an arc fault happened. The Daubechies Wavelets are
an orthogonal wavelet family with compact support. This
enables high-quality extraction of localized signal
disruptions (ignoring fundamental components).
