Diagnostics, prognostics, and vibration control play an important role in rotating machinery (such as wind turbine, rail train transmission units, hydroelectric generating units, etc.). Many diagnostic, prognostic, and vibration control systems rely on vibration and sound signals (e.g. acoustic emission). Intelligent diagnostic, prognostic, and vibration control systems have the capabilities of perception, reasoning, learning, and decision making from incomplete information. Therefore, intelligent system approaches based on sound and vibration signals for monitoring, diagnosis, prognosis, and control can pave practical applications for machinery in the absence of human interaction.

This Special Issue aims to create an international forum for scientists and practicing engineers to publish the latest research findings and ideas in modelling, real-time monitoring, diagnosis, prognosis, and control of machinery. This Special Issue welcomes theoretical contributions aimed at further understanding of intelligent techniques, including advanced sound-based and vibration-based signal processing techniques, neurocomputing, deep learning, fuzzy logic, evolutionary algorithms, swarm intelligence, and interdisciplinary topics. Moreover, this Special Issue also welcomes reports on innovative machines and electromechanical systems with applications in intelligent health monitoring, diagnosis, prognosis, and control techniques. This Special Issue welcomes original research articles as well as review articles.

Potential topics include but are not limited to the following:

• Real-time prognosis and performance evaluation based on acoustic emission and/or vibration signals for critical components in rotating machinery
• Data-driven health indicator representation methodologies for remaining useful life (RUL) prediction of machinery
• Advanced acoustic emission-based and vibration-based signal processing methods
• Machine learning-based approaches for fault diagnosis of machinery
• Applications of artificial intelligence techniques to health monitoring and degradation assessment of rotating machinery
• Vibration control, motion control, force control, process control, and fault-tolerant control of machinery