Acoustic emission-based remaining useful life prognosis of aeronautical structures subjected to compressive fatigue loading

An increasing interest for Structural Health Monitoring has emerged in the last decades. Acoustic emission (AE) is one of the most popular and widely studied methodologies employed for monitoring, due to its capabilities of detecting, locating and capturing the evolution of damage. Most literature so far, has employed AE for characterizing...

A data driven methodology for upscaling remaining useful life predictions: From single- to multi-stiffened composite panels

In this paper we execute a complex test campaign to develop a novel methodology for the Remaining Useful Life (RUL) estimation of complex multi-stiffened composite aeronautical panels utilizing Machine Learning models trained with Structural Health Monitoring (SHM) data from hierarchically simpler elements, i.e., single-stiffened panels....

Hierarchical Upscaling of Data-Driven Damage Diagnostics for Stiffened Composite Aircraft Structures

To move towards a condition-based maintenance practice for aircraft structures, design of reliable health management methodologies is required. Development of diagnostic methodologies is commonly realised on simplified sample structures with assumptions that methodologies can be adapted for application to realistic aircraft structures under...

An SHM Data-Driven Methodology for the Remaining Useful Life Prognosis of Aeronautical Subcomponents

Prognosis of the Remaining Useful Life (RUL) of a structure from Structural Health Monitoring data is the ultimate level in the SHM hierarchy. Reliable prognostics are key to a Condition Based Maintenance paradigm for aerospace systems and structures. In the present work, we propose a methodology for RUL prognosis of generic aeronautical...

Intelligent Health Indicators Based on Semi-supervised Learning Utilizing Acoustic Emission Data

Health indicators are indices that act as intermediary links between raw SHM data and prognostic models. An efficient HI should satisfy prognostic requirements such as monotonicity, trendability, and prognosability in such a way that it can be effectively used as an input in a prognostic model for remaining useful life estimation. However,...

Intelligent health indicator construction for prognostics of composite structures utilizing a semi-supervised deep neural network and SHM data

A health indicator (HI) is a valuable index demonstrating the health level of an engineering system or structure, which is a direct intermediate connection between raw signals collected by structural health monitoring (SHM) methods and prognostic models for remaining useful life estimation. An appropriate HI should conform to prognostic...

A novel strain-based health indicator for the remaining useful life estimation of degrading composite structures

We present a generic methodology for developing a Health Indicator out of strain-based Structural Health Monitoring data suitable for implementation in prognostic tasks. For this purpose, an in-house test campaign is launched. Single-stringered composite panels are subjected to compression-compression fatigue with the strains being monitored...

Assessing stiffness degradation of stiffened composite panels in post-buckling compression-compression fatigue using guided waves

The application of structural health monitoring (SHM) in composite airframe structural elements under long-term realistic fatigue loading needs to consider the structural behavior on the global level, which is an intricate task. The overall structural stiffness is a key design parameter for composite structures and the stiffness degradation...

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

With the increased use of composites in aircraft, many new successful contributions to the advancement of the structural health monitoring (SHM) field for composite aerospace structures have been achieved. Yet its application is still not often seen in operational conditions in the aircraft industry, mostly due to a gap between research focus...

Health monitoring of aerospace structures utilizing novel health indicators extracted from complex strain and acoustic emission data

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 ...

Health indicators for diagnostics and prognostics of composite aerospace structures

In order to reduce aircraft downtimes Condition-Based-Maintenance (CBM) is a topic gaining increased popularity in recent years. However, to apply such maintenance policies reliable health monitoring techniques should be implemented. Two state of the art monitoring techniques, namely Fiber Bragg Gratings (FBG) and Acoustic Emission (AE) are...

3D Helix Engineering in Chiral Photonic Materials

Engineering the helical structure of chiral photonic materials in three dimensions remains a challenge. 3D helix engineered photonic materials are fabricated by local stratification in a photopolymerizable chiral nematic liquid crystal. The obtained chiral photonic materials reflect both handedness of circular polarized light and show super...