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

Abstract

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.

The Need for Multi-Sensor Data Fusion in Structural Health Monitoring of Composite Aircraft Structures

“…Note that the proposed framework is discussed on a high level in a conceptual manner, and merely serves to demonstrate the first indications of the enhanced capabilities of a multi-sensor-based SHM system. To fully unleash its potential, in-depth research studies are crucial that consist of experimental campaigns, detailed diagnostic and prognostic methodology development, and validation exercises [8,36,50,72,[89][90][91][92][93][94][95][96][97][98], which are beyond the scope of this work.…”