Uncertainty Handling in Structural Damage Detection via Non-Probabilistic Meta-Models and Interval Mathematics, a Data-Analytics Approach

Uncertainty Handling in Structural Damage Detection via Non-Probabilistic Meta-Models and Interval Mathematics, a Data-Analytics Approach

Recent advancements in sensor technology have resulted in the collection of massive amounts of measured data from the structures that are being monitored. However, these data include inherent measurement errors that often cause the assessment of quantitative damage to be ill-conditioned. Attempts to...

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Bibliographic Details
Main Authors: Ramin Ghiasi, Mohammad Noori, Wael A. Altabey, Ahmed Silik, Tianyu Wang, Zhishen Wu
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Applied Sciences
Subjects:
surrogate models
uncertainties
non-probabilistic
interval analysis
wavelet packet decomposition (WPD)
data analytics
Online Access:https://www.mdpi.com/2076-3417/11/2/770

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https://www.mdpi.com/2076-3417/11/2/770

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