Documents - H2020 ReMAP

Documents

Project Public Deliverables

D3.2

Manuals/Guidelines for the sensor installation

D3.3

Sensors technical data package and reliability assessment

D4.4

SHM data repository

D5.1

Report on exploratory data analytics algorithms

D7.1

Hazards and Safety Barriers related with CBM technologies

D8.1

Integration, Verification and Validation strategy and plan

D9.2

Dissemination and Communication Package

D9.3

Data Management Plan

Scientific Publications

Airline maintenance task rescheduling in a disruptive environment

Paul J. van Kessel (KLM), Floris C. Freeman (klm), Bruno F. Santos (Faculty of Aerospace Engineering, Delft University of Technology)

Abstract. Work not published yet.

Age and Condition-Based Preventive Replacement Timing for Periodic Aircraft Maintenance Checks

Floris C. Freeman (KLM),Paul J. van Kessel(KLM), Wim J.C. Verhagen (RMIT)

Published in European Conference of the Prognostics and Health Management Society

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

Georgios Galanopoulos (U.Patras), Agnes Broer (TUD), Dimitrios Milanoski(U.Patras), Dimitrios Zarouchas (TUD),Theodoros Loutas (U.Patras)

Published in 2021 IEEE International Workshop on Metrology for AeroSpace

Analytical modelling of vibrations in a damaged beam using Green-Volterra formalism

Damien Bouvier, Nazih Mechbal, Marc Rebillat (Arts et Metiers Institute of Technology, CNRS, CNAM, PIMM, HESAM Univesité)

Published in HAL Archives ouvertes

TrajecNets: Online Failure Evolution Analysis in 2D Space

Nauman Shahid,Anarta Ghosh (United Technologies Research Center)

Published in International Journal of Prognostics and Health Management

Multi-objective design of aircraft maintenance using Gaussian process learning and adaptive sampling

Juseong Lee, Mihaela Mitici (Faculty of Aerospace Engineering, Delft University of Technology)

Published in Reliability Engineering and System Safety Journal

An Adaptive Framework For Remaining Useful Life Predictions Of Aircraft Systems

Marie Bieber, Wim J.C. Verhagen, and Bruno F. Santos (Faculty of Aerospace Engineering, Delft University of Technology)

Published in Proceedings of the 6th European Conference of the Prognostics and Health Management Society 2021

Estimation of Health Indicators using Advanced Analytics for Prediction of Aircraft Systems Remaining Useful Lifetime

Daniel Azevedo, Alberto Cardoso, and Bernardete Ribeiro (U. Coimbra)

Published in The International Journal of Prognostics and Health Management (ijPHM)

Aircraft Maintenance Check Scheduling Using Reinforcement Learning

Pedro Andrade (U. Coimbra), Catarina Silva (U. Coimbra), Bernardete Ribeiro (U. Coimbra), and Bruno F. Santos (TUD)

Published in the Aerospace Journal

Fusion-based damage diagnostics for stiffened composite panels

Agnes Broer (TUD), Georgios Galanopoulos (U.Patras), Rinze Benedictus(TUD), Theodoros Loutas (U.Patras) and Dimitrios Zarouchas (TUD)

Published in the Structural Health Monitoring Journal

Aircraft Fleet Health Monitoring with Anomaly Detection Techniques

Luis Basora (ONERA DTS), Paloma Bry(ONERA DTS), Xavier Olive(ONERA DTS), and Floris Freeman (KLM)

Published in the Aerospace Journal

Analytical modeling of vibrations in a damaged beam using Green-Volterra formalism

Damien Bouvier, Nazih Mechbal, and Marc Rebillat (ENSAM)

Presented in the 2020 Special Collection of the 10th European Workshop on SHM

Damage imaging post processing for delamination size assessment of CFRP aeronautic structures

William Briand, Marc Rebillat, Mikhail Guskov, and Nazih Mechbal (ENSAM)

Presented in the 2020 Special Collection of the 10th European Workshop on SHM

Estimation of health indicators using advanced analytics for prediction of aircraft systems remaining useful lifetime

Daniel Azevedo, Alberto Cardoso, and Bernardete Ribeiro (University of Coimbra)

Published in the ijPHM - The International Journal of Prognostics and Health Management
Presented in the European Conference of the Prognostics and Health Management Society 2020

Remaining Useful Life Estimation in Aircraft Components with Federated Learning

Raúl Llasag Rosero, Catarina Silva, and Bernardete Ribeiro (University of Coimbra)

Presented in the European Conference of the Prognostics and Health Management Society 2020

An integrated assessment of safety and efficiency of aircraft maintenance strategies using agent-based modelling and stochastic Petri nets

J. Lee and M. Mitici (TUDelft)

Published in the Journal of Reliability Engineering and System Safety, 2020

Recent Advances in Anomaly Detection Methods Applied to Aviation

Luis Basora, Xavier Olive, Thomas Dubot (ONERA)

Published in MDPI – Aerospace, 2019

Improving Lamb Wave detection for SHM using a dedicated LWDS electronics

G. Jaussaud (CEDRAT), J. Rebufa (CEDRAT), M. Fournier (CEDRAT), F. Claeyssen (CEDRAT), M.Logeais (CEDRAT), N. Bencheikh (CEDRAT), M. Rébillat (ENSAM) and M. Guskov (ENSAM)

Presented in the 11th International Symposium on NDT in Aerospace, 2019

Damage size quantification in aeronautic composite structures based on imaging results post-processing

William BRIAND, Marc REBILLAT, Mikhail GUSKOV and Nazih Mechbal (ENSAM)

Presented at IX ECCOMAS Thematic Conference on Smart Structures and Materials, SMART 2019

Strain-based Damage Assessment of Stiffened Composite Panels for Structural Health Monitoring Purposes

Dimitrios P. Milanoski & Theodoros H. Loutas (University of Patras)

Presented at IX ECCOMAS Thematic Conference on Smart Structures and Materials, SMART 2019

Improving Efficiency and Robustness of Structural Health Monitoring Techniques Based on Lamb Wave Detection

J. Rebufa (CEDRAT), G. Jaussaud (CEDRAT), F. Claeyssen (CEDRAT), M. Fournier (CEDRAT), M. Logeais (CEDRAT), N. Bencheikh (CEDRAT),M. Rébillat (ENSAM) & M. Guskov (ENSAM)

Presented at IX ECCOMAS Thematic Conference on Smart Structures and Materials, SMART 2019

Principal Least Squares Canonical Correlation Analysis for Damage Quantification in Aeronautic Composite Structures

Marc Rebillat & Nazih Mechbal (ENSAM)

Presented in IWSHM 2019 – Stanford, CA, USA

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 769288

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