Mechanical Engineering

Offers a comprehensive guide to the design and selection of machine elements, supported by detailed examples and over 600 illustrations. It introduces a blended design process and covers essential components like gears, bearings, and hydraulics for diverse mechanical engineering applications.

This book explores the integration of IoT with mechanical and manufacturing engineering, covering fundamentals, recent developments, and applications in areas like product development, energy, and automotive systems. It serves as a practical guide for researchers, engineers, and students, featuring diagrams and reference tools to support learning and implementation.

Explores AI and machine learning applications in smart electrical and mechanical systems, offering methods, case studies, visuals, and data. It supports interdisciplinary research and practical implementation in areas like robotics, manufacturing, and power systems, serving as a resource for engineers, researchers, and students.

Based on AI and machine learning, this book systematically presents the theories and methods for complex electro-mechanical system fault prognosis, intelligent diagnosis, and health state assessment in modern industry. The book emphasizes feature extraction, incipient fault prediction, fault classification, and degradation assessment, which are based on supervised-, semi-supervised-, manifold-, and deep learning; machinery degradation state tracking and prognosis by phase space reconstruction; and complex electro-mechanical system reliability assessment and health maintenance based on running state info. These theories and methods are integrated with practical industrial applications, which can help the readers get into the field more smoothly and provide an important reference for their study, research, and engineering practice.