Journal Design Engineering Masthead
African Maintenance Engineering | 2024-06-10

Bridge Verification Smoke

R, i, c, h, m, o, n, d, O, f, o, r, i, A, m, a, n, i, n, g
Predictive MaintenancePower TransformerMachine LearningFault Detection
Compares SVM, KNN, and Decision Tree models for transformer fault prediction
Achieves 95.65% testing accuracy with SVM and KNN classifiers
Focuses on dissolved gas analysis data for predictive maintenance
Demonstrates machine learning's potential over traditional detection methods

Abstract

Smoke verification from Codex

Machine Learning - A Case Study

BY

Project Supervisor

…..……………………………… DR JOSEPH C. ATTACHIE

August, 2024

i

Declaration

I declare that this project work is my own work. It is being submitted for the degree of Bachelor of Science in Electrical and Electronic Engineering in the University of Mines and Technology (UMaT), Tarkwa. It h as not been submitted for any degree or examination in any other University.

………………………… (Signature of Candidate) ………day of ……………………….., 2024.

ii

Dedication

This work is dedicated to my parents, Mr Tawiah Maxwell Ebu and Mrs Cecilia Nyarkoa, and my sister, Ms Alberta Agyapomaa Tawiah, for their support and unconditional love throughout my life.

iv

Contributions

My ultimate gratitude goes to God Almighty for giving me the insight and strength in all the days I spent to acquire my first degree. I am also grateful to my supervisor, Dr Joseph C. Attachie, for his maximum attention, time, and guidance while supervising this work. Finally, I appreciate my parents and siblings for their support throughout my study.

v

Table Of Contents

Contents Page DECLARATION i ABSTRACT ii DEDICATION iii ACKNOWLEDGEMENT iv TABLE OF CONTENTS v LIST OF FIGURES vii LIST OF TABLES viii LIST OF ABBREVIATIONS ix INTERNATIONAL SYSTEM OF UNITS (SI UNITS) x

K-nearest Neighbour (knn) 11

vi

Appendix B Codes For Developing Models 33

vii

List Of Figures

Figure Title Page

A Graphical Representation Of The 15

Distribution of the Faults in the Dataset

Pr Curves 22

viii

List Of Tables

Table Title Page

Fault Classification According To Iec 60599 And 7

IEEE C57.104 Standard

Classification Result And Confusion 18

Matrice for Decision Tree Classifier

Classification Result And Confusion 19

Matrice for SVM Classifier

Classification Result And Confusion 19

Matrice for KNN Classifier