Application Of Signal Processing Tools And Neural Network In Diagnosis Of Power System Faults

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Application of Signal Processing Tools and Artificial Neural Network in Diagnosis of Power System Faults

Accurate, fast, and reliable fault classification techniques are an important operational requirement in modern-day power transmission systems. Application of Signal Processing Tools and Neural Network in Diagnosis of Power System Faults examines power system faults and conventional techniques of fault analysis. The authors provide insight into artificial neural networks and their applications, with illustrations, for identifying power system faults. Wavelet transform and its application are discussed as well as an elaborate method of Stockwell transform. The authors also employ probabilistic neural networks (PNN) and back propagation neural networks (BPNN) to identify the different types of faults and determine their corresponding locations, respectively. Both PNN and BPNN are presented in detail, and their applications are illustrated through simple programming in MATLAB®. Furthermore, their applications in fault diagnosis are discussed through multiple case studies. FEATURES Explores methods of fault identification through programming and simulation in MATLAB® Examines signal processing tools and their applications with examples Provides knowledge of artificial neural networks and their application with illustrations Uses PNN and BPNN to identify the different types of faults and obtain their corresponding locations Discusses the programming of signal processing using wavelet transform and Stockwell transform This book is designed for engineering students and for practitioners. Readers will find methods of programming and simulation of any network in MATLAB® as well as ways to extract features from a signal waveform by using a suitable signal processing toolbox and by application of artificial neural networks.
Multidimensional Signals Processing, AI Methods and Applications

This book contains new research works presented at the Third World Conference on Intelligent and 3D Technologies (WCI3DT2024), organized by IRNet International Academic Communication Center, held in Shanghai, China during May 24-26, 2024. The main topics in this volume cover contemporary parts in the area of the multidimensional signal processing, based on deep learning and related applications. Special attention is given to neural networks, which make up the backbone of deep learning algorithms and their improvement, and research works aimed at the real-time interaction with unmanned vehicles, machine translation, cloud computing, personalized product recommendation model for autonomous robots, power production monitoring and control, optimization and acceleration of machine learning algorithms, pattern recognition, building crack detection and many others.
Partial Discharges (PD)

Author: Norasage Pattanadech
language: en
Publisher: John Wiley & Sons
Release Date: 2023-07-31
PARTIAL DISCHARGES (PD) — DETECTION, IDENTIFICATION AND LOCALIZATION Explore state-of-the-art partial discharge measurement techniques In Partial Discharges (PD) — Detection, Identification and Localization, a team of distinguished electrical engineers delivers a comprehensive treatment of the behavior, modeling, measurement, monitoring, localization, and evaluation of partial discharges. It includes coverage of all major advancements in the field that have occurred over the last few decades. It also discusses partial discharge phenomena, detection methods, and strategies for analyzing and processing collected data. Mechanisms of insulation failure are explored, as is the denoising of partial discharge measurement data and the localization of partial discharge in large, high-voltage equipment. Non-electric principles and procedures are discussed, and the book offers a variety of tables, figures, and photographs to illustrate the concepts discussed within. Partial Discharges(PD) also provides: A thorough introduction to the physical behavior of partial discharges, including their causes and classification Comprehensive modeling of partial discharge behavior, including classical and dipole discharges Practical discussions of the measurement of partial discharges, including the electrical method, partial discharge decoupling, and pre- and post-processing of partial discharges In-depth examinations of the monitoring of partial discharge behavior, including methods and realization Perfect for electrical engineers engaged in electrical power engineering, Partial Discharges (PD) will also earn a place in the libraries of research and development specialists employed in the manufacturing, quality testing and operation of electrical systems.