Partial Discharge Classification in Solid Insulation

Beschreibung

This book highlights an intelligent framework for detecting and classifying partial discharge in solid insulation, a quiet but persistent threat to the reliability of high-voltage power systems. It presents the complete diagnostic pipeline, from capturing discharge signals with a custom, low-cost Rogowski coil sensor to characterising their phase-resolved patterns and distilling them into informative features through statistical analysis and principal component analysis. At its core lies a hybrid classifier that pairs a feedforward backpropagation neural network with a genetic algorithm, improving accuracy, efficiency, and generalisation beyond conventional methods. Bridging high-voltage insulation engineering and machine learning, the book explains specialist concepts in accessible terms while preserving technical rigour, offering researchers, graduate students, and practising engineers a practical route toward smarter insulation diagnostics.

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Mohamad Kamarol Mohd Jamil

Themen in »Partial Discharge Classification in Solid Insulation«

Artificial Neural Network Cable Insulation Classification Solid Insulation Defects PD Pulse Signals Pattern Recognition Phase-Resolved Partial Discharge (PRPD) Rogowski Coil Sensing

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