M
M.D. Spiridonakos
Researcher at University of Patras
Publications - 12
Citations - 297
M.D. Spiridonakos is an academic researcher from University of Patras. The author has contributed to research in topics: Autoregressive–moving-average model & Parametric statistics. The author has an hindex of 7, co-authored 12 publications receiving 266 citations.
Papers
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Parametric identification of a time-varying structure based on vector vibration response measurements ☆
TL;DR: In this article, a functional series vector time-dependent autoregressive moving average (FS-VTARMA) method is introduced and employed for the identification of a "bridge-like" laboratory structure consisting of a beam and a moving mass.
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Non-stationary random vibration modelling and analysis via functional series time-dependent ARMA (FS-TARMA) models – A critical survey
TL;DR: A critical overview of non-stationary random vibration modelling and analysis via the class of Functional Series Time-dependent AutoRegressive Moving Average (FS-TARMA) models is presented.
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Output-only identification and dynamic analysis of time-varying mechanical structures under random excitation: A comparative assessment of parametric methods
TL;DR: In this paper, the problem of parametric time-domain identification and dynamic analysis for time-varying (TV) mechanical structures under unobservable random excitation is addressed.
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An FS-TAR based method for vibration-response-based fault diagnosis in stochastic time-varying structures: Experimental application to a pick-and-place mechanism
TL;DR: In this paper, a statistical time series method is proposed for fault detection and identification in stochastic time-varying structures via vibration response-based fault diagnosis, which is an output-only method, capable of operating with a minimal number of random vibration response signals.
Journal Article
In-Operation Identification of a Wind Turbine Structure via Non-Stationary Parametric Models
TL;DR: In this article, the in-operation identification of a wind turbine structure via non-stationary parametric Time-dependent AutoRegressive (TAR) models is presented based on a single vibration acceleration response signal obtained at the tower of a NegNicon NM52/900 wind turbine under normal operating conditions.