Supervised Distributed Multi-Instance and Unsupervised Single-Instance Autoencoder Machine Learning for Damage Diagnostics with High-Dimensional Data—A Hybrid Approach and Comparison Study

Supervised Distributed Multi-Instance and Unsupervised Single-Instance Autoencoder Machine Learning for Damage Diagnostics with High-Dimensional Data—A Hybrid Approach and Comparison Study

Structural health monitoring (SHM) is a promising technique for in-service inspection of technical structures in a broad field of applications in order to reduce maintenance efforts as well as the overall structural weight. SHM is basically an inverse problem deriving physical properties such as dam...

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Bibliographic Details
Main Authors: Stefan Bosse, Dennis Weiss, Daniel Schmidt
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Computers
Subjects:
structural health monitoring
distributed sensor networks
distributed machine learning
model fusion
autoencoder learning
Online Access:https://www.mdpi.com/2073-431X/10/3/34

Internet

https://www.mdpi.com/2073-431X/10/3/34

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