Guided Waves for Structural Health Monitoring / GW4SHM

EU programme: Marie Skłodowska-Curie Actions Innovative Training Network (H2020-MSCA-ITN-2019-860104)

Objective of the project

The overall aim of GW4SHM is to turn SHM from a lab-based technology into real-world applications. To overcome current hurdles that prevent the widespread use of SHM, GW4SHM will pursue the following three objectives:

1. create efficient simulation tools to predict ultrasonic wave propagation in real-life structures made of complex materials;
2. develop sophisticated signal processing algorithms to interpret the measured signals, assessing the damage, and eliminating environmental and operational influences in combination with advanced transducer integration;
3. devise strategies to assess the reliability of SHM methods with respect to their standardisation and to utilise SHM data for Condition-Based Maintenance and digital twins.

Motivation

Structural health monitoring (SHM) is essential to guarantee the safe and reliable operation of technical appliances and will be a key enabler to exploit emerging technologies such as remaining useful lifetime prognosis, condition-based maintenance, and digital twins. Particularly, SHM using ultrasonic guided waves is a promising approach for monitoring chemical plants, pipelines, transport systems and aeronautical structures.

Emerging technologies such as Condition Based Maintenance (CBM), integrated health monitoring including remaining lifetime prognosis and machine learning which are in the focus of the GW4SHM’s research activities will be a key enabler for successful transformation towards Industry 4.0. The three main contributions from GW4SHM to Europe’s technological progress are: increase safety, increased reliability, saving resources and energy.

While substantial progress has been made in the development of SHM technology, current techniques are often realised only at lab-scale. Missing quantification of reliability hinders their practical application. The substantial effort for signal processing and of permanent transducer integration as well as the lack of efficient simulation tools to improve understanding of guided wave-structure interaction and to predict the capabilities of the system limit their widespread use. Training of PhD students specialised in SHM is limited and fragmented in Europe. The aim of this project is to combine for the first time efficient simulation and signal processing tools for SHM and to assess the reliability of the monitoring systems. The project will bring together partners from academia and industry and will train a new generation of researchers skilled in all aspects of SHM, enabling them to transform SHM research into practical applications. Focusing on aeronautics, petrochemistry and the automotive sector as initial pilot cases, we will develop SHM concept to assess the integrity of structures and create ready-to-use tools for industry and other SHM users. The strong collaboration between mathematicians, physicists and engineers aims to bring the capabilities and applicability of SHM methods to the next level. Our students will acquire multidisciplinary scientific expertise, complementary skills, and experience working in academia and industry. The outcome of the project will pave the way for integrating SHM into real-world engineering structures.

Potential end-users are SHELL, AIRBUS, Dalara Automobili S.p.A. etc.

Ultrasound Institute

The early stage researcher will perform investigations within thematic „Development of a Robust Signal Processing Approach for the Post-Processing of Guided Wave Signals for NDT and SHM of Composite Structures“. The aim is to develop efficient signal processing algorithms to detect, locate and characterize the defective regions in various composite structures with complex geometries.

Tasks will cover:

1. Selection and development of various signal processing approaches depending on the signals of propagating modes of guided waves in composite samples;
2. Selection of the appropriate way of data analysis and signal processing by investigating different approaches;
3. Analysis of the limiting factors such as low signal-to-noise ratio, effect of dispersive modes, attenuation, interference and overlapping of signals, environmental effects etc. to improve the developed algorithms;
4. Adjustment of developed algorithms and validations of their performance for the analysis of defects located on different parts of the objects being investigated.

Project partners

French Alternative Energies and Atomic Energy Commission (FR), Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek TNO (NL), Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung E.V. (DE), Goethe University Frankfurt (DE), Imperial College of Science Technology and Medicine (GB), Tallinn University of Technology (EE), Ruhr-University Bochum (DE), Safran S.A. (FR), Kaunas University of Technology (LT), University of Bolonia (IT), Institute of Telecommunications (PT).

Project coordinator: BAM Bundesanstalt für Materialforschung und -prüfung (BAM), Germany