Signal Processing and Artificial Intelligence Technology for High-End Equipment Fault Diagnosis

This Reprint presents the latest research progress of signal processing and artificial intelligence technologies for fault diagnosis of high-end mechanical equipment. It contains 13 original research papers, covering advanced dynamics modeling and mechanism analysis methods, novel signal processing and artificial intelligence methods for machine fault diagnosis using various sensing technologies, and their multi-field applications. These papers mainly report research outcomes in mechanical engineering and its interdisciplinary fields, covering different themes including fault mechanism analysis; structural health monitoring; fault diagnosis and remaining useful life prediction of rotating machinery; high-end mechanical equipment in different industrial fields including the railway, wind energy, machinery manufacturing, and aerospace industries; and different sensing technologies including vibration, temperature, thermal imaging, electrical signals, and force or torque. The Reprint highlights how different sensing technologies could be integrated with advanced signal processing and artificial intelligence technologies for fault diagnosis of industrial mechanical systems. The research results of these interdisciplinary applications will contribute to better understanding of the mechanisms of machine fault diagnosis and remaining useful life prediction, and the application of these advanced monitoring and diagnostic technologies will improve the safety and reliability of mechanical systems in various industrial fields.