High-Dimensional Phase Space Reconstruction with a Convolutional Neural Network for Structural Health Monitoring

High-Dimensional Phase Space Reconstruction with a Convolutional Neural Network for Structural Health Monitoring

In order to accurately diagnose the health of high-order statically indeterminate structures, most existing structural health monitoring (SHM) methods require multiple sensors to collect enough information. However, comprehensive data collection from multiple sensors for high degree-of-freedom struc...

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Bibliographic Details
Main Authors: Yen-Lin Chen, Yuan Chiang, Pei-Hsin Chiu, I-Chen Huang, Yu-Bai Xiao, Shu-Wei Chang, Chang-Wei Huang
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Sensors
Subjects:
convolutional neural network (CNN)
structural health monitoring (SHM)
Takens’ embedding theorem
attractor reconstruction
Online Access:https://www.mdpi.com/1424-8220/21/10/3514

Internet

https://www.mdpi.com/1424-8220/21/10/3514

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