Submission Deadline: 01 February 2026 View: 310 Submit to Special Issue
Dr. Sumika Chauhan
Email: sumi.chauhan2@gmail.com
Affiliation: Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, Wroclaw, Poland
Homepage: https://dmc.pwr.edu.pl/index.php/team/
Research Interests: optimization, signal processing, fault diagnosis, condition monitoring, filter design, wireless sensor design and application of machine learning and artificial intelligence
Dr. Govind Vashishtha
Email: govindyudivashishtha@gmail.com
Affiliation: Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, Wroclaw, Poland
Research Interests: fault diagnosis, condition monitoring, optimization, signal processing and application of artificial intelligence and machine learning
This special issue aims to explore the cutting edge of AI-driven techniques for ensuring the health and reliability of rotating equipment. The scope encompasses innovative methodologies for fault detection, diagnosis, and remaining useful life (RUL) prediction in machinery across diverse industrial sectors. The special issue invites submissions focusing on advanced machine learning models, including deep learning architectures, signal processing algorithms, and hybrid approaches combining physics-based knowledge with data-driven insights. The issue seeks to highlight techniques addressing key challenges, such as data scarcity, complex fault coupling, non-stationary operating conditions, and the need for interpretable and robust solutions. We aim to showcase the versatility and potential of these techniques to drive advancements and foster interdisciplinary collaborations. The scope of the issue includes:
· Condition monitoring, fault diagnosis and predictive maintenance
· Remaining useful life
· AI-enhanced feature engineering
· Explainable AI (XAI) for diagnostics
· Machine health monitoring
· Neural networks and Transfer learning
· Signal processing and optimization in fault diagnosis
· Cloud computing and distributed systems
The goal is to provide a comprehensive overview of the latest advancements, fostering the development and deployment of intelligent monitoring systems that optimize maintenance strategies, minimize downtime, and enhance the overall performance and safety of rotating machinery.
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