Date of Award


Document Type


Degree Name

Master of Electrical Engineering

Degree Discipline



This work aimed to improve fault detection accuracy in three-phase power systems, addressing a critical need for reliable and uninterrupted electrical power supply. Existing approaches often fluctuate in accuracy. The study explored the gaps in current literature, emphasizing the need for precise fault detection strategies. The technique to enhance fault detection is an innovative methodology combining MATLAB simulation with Wavelet analysis. This study explored the application of Wavelet transforms, including Daubechies 4, Haar, Symlet 5, and Discrete Approximation Meyer, to the current signals in a three-phase power system. By extracting and comparing the current signal’s detailed coefficients against predefined threshold values for fault detection and identifying optimal Wavelets using Wavelet coefficients' energy analysis, this study provided a comprehensive solution to the complex problem of fault detection in power systems.

The study utilized both qualitative and quantitative methodologies to gather and analyze data. By combining expert insights with numerical data, the study aimed to gain a comprehensive understanding of the fault detection process. The integration of qualitative and quantitative approaches allowed for a more holistic exploration of the subject, providing valuable insights into the complexity of fault detection.

The findings highlight the significance of adaptability in choosing the most suitable Wavelet for specific fault scenarios. The study revealed no universal "optimal" Wavelet for all fault types, emphasizing the need for tailored approaches. Applying Wavelet analysis combined with a threshold approach and energy-based analysis enhances the reliability and stability of power systems. This study addressed existing gaps and introduced innovative methodologies, thereby contributing to the advancement of power systems fault detection.

In summary, the study presents significant insights into the realm of electrical engineering and power systems fault detection. With the potential to enhance power system reliability, the findings contribute valuable knowledge to the field. Moreover, the study aims to deepen the overall understanding of fault detection processes, offering further advancements in this crucial aspect of electrical engineering.

Index terms—Detailed coefficients, fault detection, fault types, short circuit fault, Wavelet transforms.

Committee Chair/Advisor

Cajetan Akujuobi

Committee Member

Samir Abood

Committee Member


Committee Member

Justin Foreman


Prairie View A&M University


© 2021 Prairie View A & M University

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Date of Digitization


Contributing Institution

John B Coleman Library

City of Publication

Prairie View





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