Upscaling the data-driven prognostic methodologies towards a condition-based structural health management of composite structures

Theodoros Loutas, Dimitrios Zarouchas

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)

Abstract

We present a conceptual methodology built in the framework of the ongoing EU H2020 Real-time Condition-based Maintenance for Adaptive Aircraft Maintenance Planning project, that leverages structural health monitoring data from different sensing technologies that goes a step beyond damage detection and diagnosis towards the probabilistic remaining useful life estimation in the presence of adverse conditions during flight. The methodology relies in several parallel activities from damage detection and localization to damage identification and severity assessment, sensitive-to-damage feature extraction processes, training methodologies, data fusion and remaining useful life predictions. Various sensing technologies i.e. static and dynamic strain sensing with FBGs, guided waves and acoustic emission are employed. An extensive hierarchical test campaign on test articles of increased complexity based on the building block approach is discussed with details as to the types of damage that are going to be targeted. Single and multi-stringer composite stiffened panels are subjected to realistic loading conditions. Emphasis on impact damage and skin/stringer fatigue disbonding/delamination is given. Last but not least, sophisticated mathematical algorithms are proposed e.g., multi-state degradation models such as Non-Homogeneous Hidden Semi Markov Model in order to deal with the data-driven RUL prediction with uncertainty quantification.

Original languageEnglish
Title of host publicationStructural Health Monitoring 2019
Subtitle of host publicationEnabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
EditorsFu-Kuo Chang, Alfredo Guemes, Fotis Kopsaftopoulos
PublisherDEStech Publications Inc.
Pages1573-1581
Number of pages9
Volume1
ISBN (Electronic)9781605956015
DOIs
Publication statusPublished - 2019
Event12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019 - Stanford, United States
Duration: 10 Sep 201912 Sep 2019

Publication series

NameStructural Health Monitoring 2019: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT) - Proceedings of the 12th International Workshop on Structural Health Monitoring
Volume1

Conference

Conference12th International Workshop on Structural Health Monitoring: Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), IWSHM 2019
Country/TerritoryUnited States
CityStanford
Period10/09/1912/09/19

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