Intelligent Algorithms and Signal Processing Techniques for Fault Diagnosis in Mechanical and Electrical Systems

Dear Colleagues,

In recent years, the growing complexity of mechanical and electrical systems has highlighted the critical need for accurate and efficient fault diagnosis methods. Unexpected failures in such systems can lead to significant economic losses, safety hazards, and reduced operational reliability. Consequently, integrating intelligent algorithms and advanced signal processing techniques has emerged as a powerful approach for addressing these challenges.

This Special Issue will bring together cutting-edge research contributions that explore innovative algorithmic approaches, such as machine learning, optimization, evolutionary computation, and bio-inspired methods, combined with signal processing techniques for analyzing vibration, acoustic, electrical, and other relevant signals. These methods are increasingly applied to early fault detection, condition monitoring, and predictive maintenance across varied domains, including industrial machinery, electrical systems (including renewable energy sources), electrical machines, cyber–physical systems, etc.

We welcome high-quality submissions presenting original research, comprehensive reviews, and novel applications of intelligent algorithms and signal processing for fault diagnosis. Both theoretical developments and practical implementations are of interest. Contributions incorporating modern technologies, such as the Internet of Things (IoT), edge computing, digital twins, and embedded systems, to enhance scalability, connectivity, and real-time performance are especially encouraged. Studies emphasizing noise robustness, interpretability, and hardware–software integration are also welcome.

Dr. Martin Valtierra-Rodriguez
Dr. Maximiliano Bueno-Lopez
Dr. Afshin Rahimi
Guest Editors

Manuscript Submission Information

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