A mechanics-informed method for real-time acoustic emission source classification during fatigue loading of composite structures

Dimitrios Zarouchas*

*Corresponding author for this work

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

Abstract

This paper presents a new approach aiming to improve the classification method of Acoustic Emission activity with a material mechanics perspective and to provide the means for real-time classification. This mechanics-informed approach consists of using the instantaneous fatigue cycle phase as hit labels. Two different types of materials were tested under Tension-Tension fatigue loading at R=0.1. The main goal was to trigger matrix cracking as the dominant failure mechanism and measure the stiffness degradation. In order to validate the approach, the stiffness degradation was measured using Digital Image Correlation. From the fatigue cycle phase labelling of hits, at least two distinct clusters were observed: first, the hits occurring mainly in the loading phase of the fatigue cycle, whichs activity correlates with the rate of stiffness degradation in the test specimens; and second, the hits occurring in the lower part the unloading phase of the fatigue cycle.

Original languageEnglish
Title of host publicationStructural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, IWSHM 2017
EditorsF.K. Chang, F. Kopsaftopoulos
PublisherDestech publications
Pages2147-2153
Number of pages7
Volume2
ISBN (Electronic)978-160595330-4
Publication statusPublished - 2017
Event11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Stanford, United States
Duration: 12 Sept 201714 Sept 2017
Conference number: 11

Conference

Conference11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance
Abbreviated titleIWSHM 2017
Country/TerritoryUnited States
CityStanford
Period12/09/1714/09/17

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