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
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.
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Dr. Nabamita Banerjee Roy is presently working as Associate Professor in Electrical Engineering Department of Narula Institute of Technology, Kolkata, India.
Prof. Kesab Bhattacharya is presently a Professor and H.O.D of the Department of Electrical Engineering, JU.
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Paperback. Condition: new. Paperback. 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 transformThis 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. Accurate, fast, and reliable fault classification techniques are an important operational requirement in modern-day power transmission systems. This book gives an elaboration of the power system faults and the conventional techniques of fault analysis. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781032043630
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