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M. Ghienne¹, A. Limare¹, L. Platon², T. Barbagelata², P. Escamilla², S. Mzali², M. Liao², S. Lassonde² and A. Braun²

¹Institut Supérieur de Mécanique de Paris (ISAE-SUPMECA), Laboratoire Quartz, Saint-Ouen, France.
²Aquila Data Enabler,Courbevoie, France

doi:10.4203/ccc.3.22.4

M. Ghienne, A. Limare, L. Platon, T. Barbagelata, P. Escamilla, S. Mzali, M. Liao, S. Lassonde, A. Braun, "Learning virtual sensors of structural stress from on-board instrumentation of a commercial aircraft", in B.H.V. Topping, J. Kruis, (Editors), "Proceedings of the Fourteenth International Conference on Computational Structures Technology", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 3, Paper 22.4, 2022, doi:10.4203/ccc.3.22.4

Keywords: virtual sensor, structural stress prediction, machine learning.

Abstract

The prediction of actual loads on aircraft structures in service phase is an on-going challenge of particular interest for aircraft manufacturers and operators as it directly impacts the optimization of the aircraft design or the optimization of maintenance scheduling in service phase. The variability of mission history, pilot actions or environmental perturbations, for instance, makes accurate prediction particularly challenging. As part of the IA2021 plan, the french Île-de-France region and Dassault Aviation have organised the challenge "AI Challenge for Industry 2020" whose objective was to develop virtual sensors through learning techniques that estimate the mechanical stress of various structural parts of a Falcon business jet using only the aircraft's onboard instruments. The work presented here is based on the response to this challenge provided by the consortium Aquila Data Enabler and ISAE-Supméca. It introduces the approach implemented to predict the mechanical stress of the structure of a business jet in service phase from flight instruments solely.

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Front Page Browse CCC CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Conferences ISSN 2753-3239 CCC: 3 PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY Edited by: B.H.V. Topping and J. Kruis Paper 22.4 Learning virtual sensors of structural stress from on-board instrumentation of a commercial aircraft M. Ghienne¹, A. Limare¹, L. Platon², T. Barbagelata², P. Escamilla², S. Mzali², M. Liao², S. Lassonde² and A. Braun² ¹Institut Supérieur de Mécanique de Paris (ISAE-SUPMECA), Laboratoire Quartz, Saint-Ouen, France. ²Aquila Data Enabler,Courbevoie, France doi:10.4203/ccc.3.22.4 Full Bibliographic Reference for this paper M. Ghienne, A. Limare, L. Platon, T. Barbagelata, P. Escamilla, S. Mzali, M. Liao, S. Lassonde, A. Braun, "Learning virtual sensors of structural stress from on-board instrumentation of a commercial aircraft", in B.H.V. Topping, J. Kruis, (Editors), "Proceedings of the Fourteenth International Conference on Computational Structures Technology", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 3, Paper 22.4, 2022, doi:10.4203/ccc.3.22.4 Keywords: virtual sensor, structural stress prediction, machine learning. Abstract The prediction of actual loads on aircraft structures in service phase is an on-going challenge of particular interest for aircraft manufacturers and operators as it directly impacts the optimization of the aircraft design or the optimization of maintenance scheduling in service phase. The variability of mission history, pilot actions or environmental perturbations, for instance, makes accurate prediction particularly challenging. As part of the IA2021 plan, the french Île-de-France region and Dassault Aviation have organised the challenge "AI Challenge for Industry 2020" whose objective was to develop virtual sensors through learning techniques that estimate the mechanical stress of various structural parts of a Falcon business jet using only the aircraft's onboard instruments. The work presented here is based on the response to this challenge provided by the consortium Aquila Data Enabler and ISAE-Supméca. It introduces the approach implemented to predict the mechanical stress of the structure of a business jet in service phase from flight instruments solely. download the full-text of this paper (PDF, 5 pages, 244 Kb) go to the previous paper go to the next paper return to the table of contents return to the volume description
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