Description
This book gives a detailed introduction to the technical background, feature extraction methods, PHM models and big data embedding methods of the big data theory in PHM for intelligent electromechanical systems. Combination with deep learning and big data, this book explains the hybrid algorithm framework of PHM such as ensemble intelligence and optimized intelligence and introduces PHM models for bearing, IGBT, MOSFET and other components and their big data embedding platform. This book improves the PHM method and theory of electromechanical system under industrial big data and provides reference for the development of intelligent electromechanical equipment and intelligent industrial production in the future.
Table of Contents
Introduction.- Feature extraction of bearing vibration signal.- Ensemble intelligent diagnosis for bearing faults.- Deep learning based prediction for bearing remaining useful life.-Optimization based prediction for IGBT remaining useful life.
