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Anotace knihy

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.

Parametry knihy

• Plný název: Partial Discharge Classification in Solid Insulation
• Podnázev: Hybrid Genetic-Algorithm and Neural Network Approach
• Autor: Mohamad Kamarol Mohd Jamil, Norfadilah Rosle, Mohamad Nur Khairul Hafizi Rohani
• Edice: SpringerBriefs in Applied Sciences and Technology,
• Jazyk: Angličtina
• Vazba: Brožovaná
• EAN: 9789819266395
• ID: 53790489
• Nakladatelství: Springer, Berlin
• Rozměry: 235 × 155 mm
• Datum vydání: 15. January 2027

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