COMBINING MACHINE LEARNING, EMBEDDED SENSOR NETWORKS AND ADDITIVE BURNER DESIGN FOR COMBUSTOR STRUCTURAL HEALTH MONITORING

Fabrice Giuliani; Nina Paulitsch; Andrea Hofer; Vojislav Petrovic-Filipovic; Benjamin Meier; Werner Bailer; Martin Winter; Roland Unterberger; Alexander Schricker

doi:10.1115/GT2024-127925

COMBINING MACHINE LEARNING, EMBEDDED SENSOR NETWORKS AND ADDITIVE BURNER DESIGN FOR COMBUSTOR STRUCTURAL HEALTH MONITORING

Fabrice Giuliani
, Nina Paulitsch
, Andrea Hofer
, Vojislav Petrovic-Filipovic
, Benjamin Meier
, Werner Bailer
, Martin Winter
, Roland Unterberger
, Alexander Schricker

Combustion Bay One e.U.
Joanneum Research
Piezocryst GmbH

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Original language	English
Title of host publication	Controls, Diagnostics, and Instrumentation
Publisher	American Society of Mechanical Engineers (ASME)
ISBN (Electronic)	9780791887967
DOIs	https://doi.org/10.1115/GT2024-127925
Publication status	Published - 2024
Externally published	Yes
Event	69th ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition, GT 2024 - London, United Kingdom Duration: 24 Jun 2024 → 28 Jun 2024

Publication series

Name	Proceedings of the ASME Turbo Expo
Volume	4

Conference

Conference	69th ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition, GT 2024
Country/Territory	United Kingdom
City	London
Period	24/06/24 → 28/06/24

Keywords

Combustion monitoring
large datasets
miniature fast pressure probe
multi-sensing
Recursive Sequential Combustion
signal processing
unsupervised machine learning

Access to Document

10.1115/GT2024-127925

Cite this

Giuliani, F., Paulitsch, N., Hofer, A., Petrovic-Filipovic, V., Meier, B., Bailer, W., Winter, M., Unterberger, R., & Schricker, A. (2024). COMBINING MACHINE LEARNING, EMBEDDED SENSOR NETWORKS AND ADDITIVE BURNER DESIGN FOR COMBUSTOR STRUCTURAL HEALTH MONITORING. In Controls, Diagnostics, and Instrumentation Article v004t05a037 (Proceedings of the ASME Turbo Expo; Vol. 4). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/GT2024-127925

@inproceedings{5490f492a1ce4082ba22beb52d22f154,

title = "COMBINING MACHINE LEARNING, EMBEDDED SENSOR NETWORKS AND ADDITIVE BURNER DESIGN FOR COMBUSTOR STRUCTURAL HEALTH MONITORING",

keywords = "Combustion monitoring, large datasets, miniature fast pressure probe, multi-sensing, Recursive Sequential Combustion, signal processing, unsupervised machine learning",

author = "Fabrice Giuliani and Nina Paulitsch and Andrea Hofer and Vojislav Petrovic-Filipovic and Benjamin Meier and Werner Bailer and Martin Winter and Roland Unterberger and Alexander Schricker",

note = "Publisher Copyright: {\textcopyright} 2024 by ASME.; 69th ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition, GT 2024 ; Conference date: 24-06-2024 Through 28-06-2024",

year = "2024",

doi = "10.1115/GT2024-127925",

language = "English",

series = "Proceedings of the ASME Turbo Expo",

publisher = "American Society of Mechanical Engineers (ASME)",

booktitle = "Controls, Diagnostics, and Instrumentation",

address = "United States",

}

Giuliani, F, Paulitsch, N, Hofer, A, Petrovic-Filipovic, V, Meier, B, Bailer, W, Winter, M, Unterberger, R & Schricker, A 2024, COMBINING MACHINE LEARNING, EMBEDDED SENSOR NETWORKS AND ADDITIVE BURNER DESIGN FOR COMBUSTOR STRUCTURAL HEALTH MONITORING. in Controls, Diagnostics, and Instrumentation., v004t05a037, Proceedings of the ASME Turbo Expo, vol. 4, American Society of Mechanical Engineers (ASME), 69th ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition, GT 2024, London, United Kingdom, 24/06/24. https://doi.org/10.1115/GT2024-127925

COMBINING MACHINE LEARNING, EMBEDDED SENSOR NETWORKS AND ADDITIVE BURNER DESIGN FOR COMBUSTOR STRUCTURAL HEALTH MONITORING. / Giuliani, Fabrice; Paulitsch, Nina; Hofer, Andrea et al.
Controls, Diagnostics, and Instrumentation. American Society of Mechanical Engineers (ASME), 2024. v004t05a037 (Proceedings of the ASME Turbo Expo; Vol. 4).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - COMBINING MACHINE LEARNING, EMBEDDED SENSOR NETWORKS AND ADDITIVE BURNER DESIGN FOR COMBUSTOR STRUCTURAL HEALTH MONITORING

AU - Giuliani, Fabrice

AU - Paulitsch, Nina

AU - Hofer, Andrea

AU - Petrovic-Filipovic, Vojislav

AU - Meier, Benjamin

AU - Bailer, Werner

AU - Winter, Martin

AU - Unterberger, Roland

AU - Schricker, Alexander

PY - 2024

Y1 - 2024

KW - Combustion monitoring

KW - large datasets

KW - miniature fast pressure probe

KW - multi-sensing

KW - Recursive Sequential Combustion

KW - signal processing

KW - unsupervised machine learning

UR - https://www.scopus.com/pages/publications/85204294654

U2 - 10.1115/GT2024-127925

DO - 10.1115/GT2024-127925

M3 - Conference contribution

AN - SCOPUS:85204294654

T3 - Proceedings of the ASME Turbo Expo

BT - Controls, Diagnostics, and Instrumentation

PB - American Society of Mechanical Engineers (ASME)

T2 - 69th ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition, GT 2024

Y2 - 24 June 2024 through 28 June 2024

ER -

Giuliani F, Paulitsch N, Hofer A, Petrovic-Filipovic V, Meier B, Bailer W et al. COMBINING MACHINE LEARNING, EMBEDDED SENSOR NETWORKS AND ADDITIVE BURNER DESIGN FOR COMBUSTOR STRUCTURAL HEALTH MONITORING. In Controls, Diagnostics, and Instrumentation. American Society of Mechanical Engineers (ASME). 2024. v004t05a037. (Proceedings of the ASME Turbo Expo). doi: 10.1115/GT2024-127925

COMBINING MACHINE LEARNING, EMBEDDED SENSOR NETWORKS AND ADDITIVE BURNER DESIGN FOR COMBUSTOR STRUCTURAL HEALTH MONITORING

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Keywords

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