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Book synopsis

This book lies at the intersection of engineering vibration and artificial intelligence, bridging core disciplines like mechanical engineering, civil engineering, and control science. It introduces a range of cutting-edge methods including machine learning, deep learning and reinforcement learning. It closely integrates these with the core links of engineering vibration, namely identification, prediction and control, puts forward a series of new approaches, and solves many practical engineering problems. These innovations address long-standing industry challenges of data scarcity, strong nonlinearity, and poor generalization of traditional methods. The book presents complex theories through intuitive visualizations and step-by-step technical workflows, balancing academic depth with practical operability. For readers, it offers actionable solutions for vibration identification, prediction, and control, while establishing a systematic knowledge system integrating data-driven and physics-informed modeling. It is ideal for researchers, engineers, and graduate students in vibration control, intelligent manufacturing, aerospace, civil engineering, and related fields seeking to advance their work with AI-powered technologies.

Book details

• Full title: Artificial Intelligence-Driven Engineering Vibration Identification, Prediction and Control
• Subtitle: Advances in Engineering Vibration
• Author: Wei Huang, Jian Xu
• Language: English
• Binding: Hardback
• Number of pages: 511
• EAN: 9789819228294
• ID: 52898115
• Publisher: Springer, Berlin
• Dimensions: 235 × 155 mm
• Date of publishing: 11. October 2026

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