A Strain-Based Health Indicator for the SHM of Skin-to-Stringer Disbond Growth of Composite Stiffened Panels in Fatigue

Milanoski, Dimitrios; Galanopoulos, Georgios; Broer, Agnes; Zarouchas, Dimitrios; Λούτας, Θεόδωρος

doi:10.1007/978-3-030-64594-6_61

Cited by 10 publications

(10 citation statements)

References 17 publications

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“…42 Application at various structural complexities may be found in the literature, spanning from coupon level, 24,43,44 or components with assembly details [45][46][47][48] to more representative structures. [49][50][51][52][53][54] Strain-based methodologies can also be divided in accordance with the nature of the interrogated strains, that is, dynamic 55,56 or static. 57 In each case, proper postprocessing of the multivariate uninformative raw strain data is required.…”

Section: Strain-based Shm Methodologiesmentioning

confidence: 99%

Multi-level damage diagnosis on stiffened composite panels based on a damage-uninformative digital twin

Milanoski

Galanopoulos

Zarouchas

et al. 2022

Structural Health Monitoring

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In this study, a multi-level Structural Health Monitoring methodology for stiffened composite panels is introduced. A digital twin (DT), that is, a three-dimensional finite element (FE) model, representing the pristine state baseline of the test article, is developed and verified for compressive loading in the post-buckling regime. The detailed FE model is utilized to train a surrogate model with respect to exogenous input, that is, axial load magnitude. The surrogate assists the DT concept that would allow prediction of the load acting on the structure based on an influx of strain data, acquired from fiber Bragg grating sensors permanently attached along the stringer feet. For this purpose, we leverage on the observation that remote from the damage, the strain field remains virtually unaltered with regard to the pristine state. The load is estimated by a sensor placed far from the damage whilst the diagnostic actions are performed by exploiting measurements from the remaining sensing locations. A health indicator, which compares the experimentally received strains with those from the surrogate representing the pristine state, is utilized to (1) detect, (2) localize, and (3) characterize the damage. As damage, we consider either skin-to-stringer disbond or initial impact damage propagation as well as overall stiffness degradation during thousands or millions of fatigue cycles. The sensors that have detected a disbond are dedicated to evaluating the potential propagation of it, while the remaining sensors evaluate the overall stiffness degradation. The proposed methodology is tested for one artificially disbonded and two impacted single-stringer panels subjected to block loading compression-compression fatigue.

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Section: Strain-based Shm Methodologiesmentioning

confidence: 99%

Multi-level damage diagnosis on stiffened composite panels based on a damage-uninformative digital twin

Milanoski

Galanopoulos

Zarouchas

et al. 2022

Structural Health Monitoring

Self Cite

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“…The change in buckling pattern with now multiple half waves present in the multi-stiffener panel will affect the strain measurements and correspondingly the algorithms based on those measurements. A strain-based health indicator relying on certain trends in the data under damage, such as the ones presented in [6,8,9], may be affected when mode I and II are both predominantly present along the same stiffener foot. Consequently, it necessitates an adaption in its methodology to handle the simultaneous presence of both modes as well as a new inclusion of an approach on how to deal with the transfer-region between both modes.…”

Section: Structural Health Methodology Aspectsmentioning

confidence: 99%

On the Challenges of Upscaling Damage Monitoring Methodologies for Stiffened Composite Aircraft Panels

Broer¹,

Yue²,

Galanopoulos³

et al. 2022

Proceedings of the 13th International Workshop on Structural Health Monitoring

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Health management methodologies for condition-based maintenance are often developed using sensor data collected during experimental tests. Most tests performed in laboratories focus on a coupon level or flat panels, while structural component testing is less commonly seen. As researchers, we often consider our experimental tests to be representative of a structure in a final application and consider the developed methodologies to be transferrable to these real-life structures. Yet, structures in their final applications such as wind turbines or aircraft are often larger, more complex, might contain various assembly details, and are loaded in complex conditions. These factors might influence the performance of developed diagnostic and prognostic methodologies and should therefore not be ignored. In our work, we consider the aspects of upscaling structural health monitoring (SHM) methodologies for stiffened composite panels with the design of the panels inspired by an aircraft wing structure. For this, we examine two levels of panels, namely a single- and multi-stiffener composite panel, where we consider the single-stiffener panel to be a representative lower-level version of the multi-stiffener panel. Multiple SHM sensors (acoustic emission, Lamb waves, strain sensing) were installed on both composite panels to monitor damage propagation during testing. We identify and analyse challenges and further discuss considerations that must be taken during upscaling of diagnostics and prognostics, and with that, aid in the development of health management methodologies for condition-based maintenance.

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“…An example of a pHI can be found in [28], in which axial strain from DIC measurements was used to predict the RUL of open-hole composite coupons. Strain HIs were also developed in [29] to monitor disbond growth in composite stringer panels. VHIs are usually optimized to obtain desirable attributes, such as monotonicity, trendability, and prognosability, which significantly benefit the performance in prognostics, as postulated in [25].…”

Section: Health Indicatorsmentioning

confidence: 99%

Health Monitoring of Aerospace Structures Utilizing Novel Health Indicators Extracted from Complex Strain and Acoustic Emission Data

Galanopoulos

Milanoski

Broer

et al. 2021

Sensors

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The development of health indicators (HI) of diagnostic and prognostic potential from generally uninformative raw sensor data is both a challenge and an essential feature for data-driven diagnostics and prognostics of composite structures. In this study, new damage-sensitive features, developed from strains acquired with Fiber Bragg Grating (FBG) and acoustic emission (AE) data, were investigated for their suitability as HIs. Two original fatigue test campaigns (constant and variable amplitude) were conducted on single-stringer composite panels using appropriate sensors. After an initial damage introduction in the form of either impact damage or artificial disbond, the panels were subjected to constant and variable amplitude compression–compression fatigue tests. Strain sensing using FBGs and AE was employed to monitor the damage growth, which was further verified by phased array ultrasound. Several FBGs were incorporated in special SMARTapesTM, which were bonded along the stiffener’s feet to measure the strain field, whereas the AE sensors were strategically placed on the panels’ skin to record the acoustic emission activity. HIs were developed from FBG and AE raw data with promising behaviors for health monitoring of composite structures during service. A correlation with actual damage was attempted by leveraging the measurements from a phased array camera at several time instances throughout the experiments. The developed HIs displayed highly monotonic behaviors while damage accumulated on the composite panel, with moderate prognosability.

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A Strain-Based Health Indicator for the SHM of Skin-to-Stringer Disbond Growth of Composite Stiffened Panels in Fatigue

Cited by 10 publications

References 17 publications

Multi-level damage diagnosis on stiffened composite panels based on a damage-uninformative digital twin

Multi-level damage diagnosis on stiffened composite panels based on a damage-uninformative digital twin

On the Challenges of Upscaling Damage Monitoring Methodologies for Stiffened Composite Aircraft Panels

Health Monitoring of Aerospace Structures Utilizing Novel Health Indicators Extracted from Complex Strain and Acoustic Emission Data

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