· 2012· Book chapter
Structural Health Monitoring: A Machine Learning Perspective
- 1,082citations
- 2012year
Short summary
This book provides a comprehensive overview of structural health monitoring (SHM) techniques, focusing on the application of machine learning and statistical pattern recognition methods.
AI-generated from the title and abstract; the full text is not read.
Key points
- Focuses on the intersection of structural health monitoring and machine learning.
- Reviews technical literature and includes practical case studies.
- Covers key SHM components: operational evaluation, sensing, data acquisition, probability, statistics, machine learning, and prognosis.
AI-generated from the title and abstract; the full text is not read.
Abstract
This book focuses on structural health monitoring in the context of machine learning. The authors review the technical literature and include case studies. Chapters include: operational evaluation, sensing and data acquisition, introduction to probability and statistics, machine learning and statistical pattern recognition, and data prognosis.
The authors' abstract, as published at the source., 2012
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Field: Civil and Structural Engineering
Civil and Structural EngineeringEngineering