Damage Diagnostics of a Composite Single-Stiffener Panel Under Fatigue Loading Utilizing SHM Data Fusion

Abstract

A case study is presented in which the first steps are made towards the development of a structural health monitoring (SHM) data fusion framework. For this purpose, a composite single-stiffener panel is subjected to compression-compression fatigue loading (R = 10). The carbon-epoxy panel contains an artificial disbond of 30 mm, which was created using a Teflon insert during manufacturing and placed between the skin and the stiffener foot. Under the applied fatigue load, the disbond is expected to grow and its propagation is monitored using two SHM techniques, namely acoustic emission (AE) and Rayleigh-scattering based distributed fiber optic strain sensing. Four AE sensors are placed on the skin, thereby allowing for disbond growth detection and localization. On each stiffener foot, fiber optic sensors are surface-bonded to monitor the growth of the disbond under the applied fatigue loading. The distributed strain measurements are used to localize and monitor the disbond growth. The strength of each technique is utilized by fusing the data from the AE sensors and the fiber optic sensors. In this manner, a data-driven approach is presented in which a data fusion of the different techniques allows for monitoring the damage in the stiffened panel on multiple SHM levels, including disbond growth detection and localization.

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

“…Whereas for the single-stiffener panel, the predominant mode along a stiffener foot is constant as being either mode I (opening) or mode II (in-plane shear), the presence of multiple half waves in the multi-stiffener panel causes the predominant mode to shift between mode I and mode II longitudinally along each stiffener foot. From previous studies [6,7], we know that the disbond is more likely to propagate under mode I and in the case of the single-stiffener panel, this means that the disbond can grow freely in longitudinal direction. For the multi-stiffener panel, this is no longer the case causing the propagation of the disbond to change, for example by declining or having the disbond propagate to the other stiffener foot where mode I is observed.…”

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

“…Despite the low sensitivity of regular FBG sensors in AE recording [20,21], these specialized phase-shifted FBGs successfully identified damage modes in three-point bending experiments, and the results were comparable to those of regular AE sensors. Broer et al [22,23] recently proposed a methodology of fusing two SHM techniques, namely AEs and strain sensing. The idea of fusing results from several sensors was proposed in order to take advantage of the strengths of both SHM techniques, and thus obtain more effective damage diagnostics of deteriorating composite panels.…”

Health indicators for diagnostics and prognostics of composite aerospace structures

“…HIs are features capable of capturing the structure's degradation information. As discussed in [2], [5] the quality of the HI's evolution through time affects the performance of diagnostic systems and prognostic algorithms. HIs, as stated in [6], can be categorized into physical HIs (pHI) and virtual HIs (vHI).…”

“…De Oliveira et al [22] proposed a classification algorithm based on ANN and used AE signal to classify different damage mechanisms. Broer et al [2], [23], used AE to monitor localize damage initiation on composite single stiffened panels during compression-compression fatigue. A fusion with strain readings was also proposed to enhance the SHM system's monitoring capabilities.…”

“…Structural health monitoring (SHM) is a constantly evolving concept over the last decades. Utilization of SHM systems in more demanding applications, such as intelligent diagnostics and prognostics of structures has been a focus of several researchers [1], [2]. Strategically placed sensor networks can provide the ability to utilize SHM and lead to the implementation of Condition-Based-Maintenance (CBM), reducing aircraft downtimes and maintenance costs.…”