Intelligent diagnosis of rotating machines using VMD

This book presents an innovative approach to fault diagnosis in rotating machines, based on Variational Mode Decomposition (VMD) and artificial intelligence techniques. It begins with an analysis of condition monitoring strategies and the limitations of conventional signal processing methods. VMD is compared with Empirical Mode Decomposition (EMD) to demonstrate its superiority for extracting fault signatures in noisy environments. A criterion based on Shannon entropy is proposed to optimize the number of modes, while the integration of Multiresolution Wavelet Decomposition (WMRA) improves detection of weak defects. Finally, a hybrid VMD-LSTM model is developed for automatic classification and assessment of fault severity. Combining scientific rigor and experimental validation, this book offers a major contribution to predictive diagnostics and intelligent maintenance in the context of Industry 4.0.