AI and Machine Learning for Mechanical and Electrical Engineering

<p>Practical and informative <b><i>AI and Machine Learning for Mechanical and Electrical Engineering </i></b>examines how artificial intelligence (AI) is changing the status quo in mechanical engineering electrical systems and management. Real-world examples and case studies demonstrate the application of AI in such diverse settings as industry and policymaking. This book illustrates how AI is playing a crucial role in enhancing productivity and innovation in various industries. It discusses transition methods and the ethical implications of using AI in mechanical engineering. Chapter highlights include the following:</p><ul> <li>Developing a smart algorithm to integrate fault detection and classification</li> <li>Algorithms to investigate different testing scenarios for various anomalies in electric motors</li> <li>Data fusion to detect and assess electromechanical damage</li> <li>Neural networks for rolling bearing fault diagnosis</li> <li>Evolutionary algorithms to optimize deep learning models for water industry forecasts</li> <li>AI-based anomaly detection and root-cause analysis</li> </ul><p>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.</p>