Enhanced Sensor Placement Optimization and Defect Detection in Structural Health Monitoring Using Hybrid PI-DEIM Approach

Enhanced Sensor Placement Optimization and Defect Detection in Structural Health Monitoring Using Hybrid PI-DEIM Approach

This work introduces a novel methodology for identifying critical sensor locations and detecting defects in structural components. Initially, a hybrid method is proposed to determine optimal sensor placements by integrating results from both the discrete empirical interpolation method (DEIM) and the...

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Bibliographic Details
Main Authors: Minyoung Yun, Mikhael Tannous, Chady Ghnatios, Eivind Fonn, Trond Kvamsdal, Francisco Chinesta
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Sensors
Subjects:
random permutation features importance method
optimal sensor placement
discrete empirical interpolation method
machine learning
Online Access:https://www.mdpi.com/1424-8220/25/1/91
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