Artificial Intelligence for Fault Diagnostics and Prognostics

Dear Colleagues,

The aim of this Special Issue is to publish cutting edge research on artificial intelligence-based diagnosis techniques to estimate the health of rotating machines. Rotating machines such as compressors, pumps, and motors are vital elements of the industry. The performance of these machines could deteriorate due to various faults such as bearing faults, stator faults, rotor faults, eccentricity, and shaft misalignment. The more than 90% motor failures in the industry are linked with stator faults, rotor faults, and bearing faults. Thus, the objective of this Special Issue is to publish the latest research on fault diagnostics of rotating machines using artificial intelligence-based techniques.

This Special Issue is intended for industrial engineers, technicians and researchers, with a research interest in the advanced technologies related to machine condition monitoring.  It will cover the applications of Artificial Intelligence (AI), the Internet of Things (IoT), smart sensors, and nanotechnologies to solve the vital issues faced by the industrial sector.

Therefore, this Special Issue will focus on, but is not limited to, the following topics:

• Intelligent fault diagnostics of rotating machines
• Machine condition monitoring
• Modern communication systems for machine reliability
• Fault diagnostics of medical instruments
• Reliability of medical instruments
• Modern condition monitoring techniques
• Signal & image processing
• Smart machines for smart cities
• Power system stability
• Smart grids
• Power system reliability
• False data injection attacks detection
• Reliability of modern communication systems

Prof. Dr. Adam Glowacz
Prof. Dr. Jose Alfonso Antonino-Daviu
Dr. Wahyu Caesarendra
Guest Editors

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