Statistical Active-Sensing Structural Health Monitoring via Stochastic Time-Varying Time Series Models
Author:
Affiliation:
1. Rensselaer Polytechnic Institute,Intelligent Structural Systems Lab (ISSL),Department of Mechanical, Aerospace and Nuclear Engineering,Troy,NY
Funder
Air Force Office of Scientific Research
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9866948/9867142/09867472.pdf?arnumber=9867472
Reference19 articles.
1. A functional model based statistical time series method for vibration based damage detection, localization, and magnitude estimation
2. Vibration based health monitoring for a lightweight truss structure: Experimental assessment of several statistical time series methods
3. Stochastic identification of guided wave propagation under ambient temperature via non-stationary time series models;ahmed;SENSORS,2021
4. Parametric time-domain methods for non-stationary random vibration modelling and analysis — A critical survey and comparison
5. Non-stationary random vibration modelling and analysis via functional series time-dependent ARMA (FS-TARMA) models – A critical survey
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1. Active sensing ultrasonic guided wave-based damage diagnosis via stochastic stationary time-series models;Structural Health Monitoring;2023-11-25
2. Local and Global Structural Health Monitoring via Stochastic Functional Time Series Methods: A Critical Assessment and Comparison;AIAA AVIATION 2023 Forum;2023-06-08
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