Dataset Generation Based on 1D-CAE Modeling for Fault Diagnostics in a Spacecraft Propulsion System

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

PDF
Published Sep 4, 2023
DOI https://doi.org/10.36001/phmap.2023.v4i1.3784
Kohji Tominaga
Research and Development Directorate, Japan Aerospace Exploration Agency (JAXA)
Yu Daimon
Research and Development Directorate, Japan Aerospace Exploration Agency (JAXA)
Masao Toyama
Aerospace Engineering Solution Division, Business Headquarters, Ryoyu Systems Co., Ltd
Kazushi Adachi
Department of Aeronautics and Astronautics, The University of Tokyo
Seiji Tsutsumi
Research and Development Directorate, Japan Aerospace Exploration Agency (JAXA)
Noriyasu Omata
Research and Development Directorate, Japan Aerospace Exploration Agency (JAXA)
Taiichi Nagata
Research and Development Directorate, Japan Aerospace Exploration Agency (JAXA)

Abstract

The objective of this study is to generate a classified dataset of valve faults and bubble contamination anomalies in the propellant supply pipe of spacecraft propulsion systems. The dataset is available in PHMAP23, and the paper intends to describe its characteristics. The dataset includes time and pressure information and has been generated through numerical simulations using SimlationX, a 1D-CAE software. The condition of the propulsion system is reflected by the characteristics of the pressure dynamic response generated by the water hammer in the supply pipe caused by the rapid opening and closing of the downstream solenoid valve. Therefore, accurate classification of anomalies and faults can be achieved by extracting characteristics from the pressure dynamic response waveform.

Abstract 149 | PDF Downloads 111

##plugins.themes.bootstrap3.article.details##

Keywords

Anomaly detection, PHM, SimulationX, Data generation

References
K. Tominaga, G. Fujii, T. Nagata, D. Wada, S. Hisada, K. Kawatsu, and T. Kasai. (2023). Anomaly Detection Method for Spacecraft Propulsion System using Frequency Response Functions of Multiplexed FBG Data. Acta Astronotica, In press. https://doi.org/10.1016/j.actaastro.2023.07.022.

K. Kawatsu, C. Inoue, Y. Terauchi, Y. Daimon, G. Fujii, and A. Noumi. (2019). System-level Integrated Modeling and Simulation Targeting Space Propulsion System for Design Evaluation and Risk Assessment. 32nd International Symposium on Space Technology and Science, July 15-21, Fukui, Japan.

K. Kawatsu, A. Noumi, N. Ishihama, T. Nagata, C. Inoue, G. Fujii, H. Tani, and Y. Daimon. (2020). Resilient Redundant Spacecraft GN&C System Fault Detection and Diagnostics. Aerospace Europe Conference 2020. February 25-28, Bordeaux, France.

K. Adachi, S. Khan, K. Tominaga, N. Omata, S. Tsutsumi, and T. Nagata, (2023). Study on Anomaly Detection of a Spacecraft Propulsion System using Machine Learning. Asian Joint Conference on Propulsion and Power 2023, March 15-18, Ishikawa, Japan.

Y. Daimon; K. Tominaga; G. Fujii; T. Nagata; Y. Matsuura; Y. Kano; E. Uchiyama, (2023). One-dimensional Modeling of Ignition Timing for Hypergolic Bipropellant Thrusters. Aerospace Europe Conference 2023. July 9-13, Lausanne, Switzerland. SimulationX. https://www.simulationx.com/
Issue
Vol. 4 No. 1 (2023): Proceedings of the Asia Pacific Conference of the PHM Society 2023
Section
Data Challenge Papers
Creative Commons License

This work is licensed under a Creative Commons Attribution 3.0 Unported License.