Detection of Faults in Power System Using Wavelet Transform and Independent Component Analysis
P. K. Ray, B. K. Panigrahi, P. K. Rout, A. Mohanty, H. Dubey

TL;DR
This paper introduces a novel fault detection method in power systems using Wavelet Transform and Independent Component Analysis, demonstrating robustness under various noise conditions and outperforming traditional Fourier-based methods.
Contribution
The paper presents a new combined WT and ICA approach for fault detection in power systems, improving detection accuracy and robustness over existing techniques.
Findings
Effective fault detection under noise and frequency variations
Wavelet transform accurately detects fault initiation instant
Proposed method outperforms FT and STFT in energy-based detection
Abstract
Uninterruptible power supply is the main motive of power utility companies that motivate them for identifying and locating the different types of faults as quickly as possible to protect the power system prevent complete power black outs using intelligent techniques. Thus, the present research work presents a novel method for detection of fault disturbances based on Wavelet Transform (WT) and Independent Component Analysis (ICA). The voltage signal is taken offline under fault conditions and is being processed through wavelet and ICA for detection. The time-frequency resolution from WT transform detects the fault initiation instant in the signal. Again, a performance index is calculated from independent component analysis under fault condition which is used to detect the fault disturbance in the voltage signal. The proposed approach is tested to be robust enough under various operating…
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