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What is Structural Health Monitoring (SHM)

Artificial Intelligence and Machine Learning Techniques for Civil Engineering
Observation and analysis of structural systems over time using periodically sampled response measurements in order to monitor changes in the material or the geometry of the systems.
Published in Chapter:
Machine Learning Applications for Vibration-Based Structural Health Monitoring
Zeinep Achmet (National Technical University of Athens, Greece) and Michalis Fragiadakis (National Technical University of Athens, Greece)
DOI: 10.4018/978-1-6684-5643-9.ch003
Abstract
The recent advances in sensing technology and in the field of artificial intelligence (AI) have boosted the development of techniques based on machine learning (ML) for structural health monitoring (SHM). The chapter provides a discussion on the application of machine learning (ML) methods for vibration-based SHM. The fundamental principles of machine learning are presented and the steps of vibration-based SHM for damage detection are outlined. The application of ML with respect to every step of SHM process is subsequently discussed. Among the vast existing literature, the milestones are identified and the endless possibilities for the successful application of ML are presented.
Full Text Chapter Download: US $37.50 Add to Cart
More Results
Applications of Wireless Sensor Networks
Deals with the observation of structural health in different research fields like building health or animal observation.
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Validation of Damage Identification Using Non-Linear Data-Driven Modelling
The process of acquiring and analysing data from a set of permanently installed sensors to determine the health of a structure in a non-destructive way.
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Methodologies of Damage Identification Using Non-Linear Data-Driven Modelling
The process of acquiring and analysing data from a set of permanently installed sensors to determine the health of a structure in a non-destructive way.
Full Text Chapter Download: US $37.50 Add to Cart
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