- Developing a smart algorithm to integrate fault detection and classification
- Algorithms to investigate different testing scenarios for various anomalies in electric motors
- Data fusion to detect and assess electromechanical damage
- Neural networks for rolling bearing fault diagnosis
- Evolutionary algorithms to optimize deep learning models for water industry forecasts
- AI-based anomaly detection and root-cause analysis
An overarching theme is the transition from traditional mechanical, electrical, and management systems to AI-enabled smart systems. The book helps readers make sense of the challenges of integrating smart systems. It equips engineers with theoretical understanding as well as insight based on hands-on expertise. It shows how to better link and automate systems and improve productivity. This book not only shows how to implement smart solutions now but also shows the way to a more intelligent, productive, and interconnected future.
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