MBSE-Enhanced LSTM Framework for Satellite System Reliability and Failure Prediction

M. Alandihallaj, Mahya Ramezani, Andreas Hein

2024

Abstract

This paper investigates the integration of Artificial Intelligence (AI) and Model-Based Systems Engineering (MBSE) in the field of satellite system reliability. We employ Long Short-Term Memory (LSTM) networks, an AI technique, to predict the failure probabilities of various subsystems. These LSTM models are integrated into an MBSE framework, enhancing the accuracy of system-wide failure prediction and operational decision-making. The approach involves training LSTM networks on simulated datasets representing a range of operational scenarios for each subsystem. The outputs from these networks are then aggregated using a weighted approach to determine the optimal disposal time, aiming to extend the satellite’s operational lifespan. The performance of the system is evaluated a simulated real mission scenario. This research highlights the potential of AI-MBSE integration in advancing satellite system design and maintenance strategies.

Download


Paper Citation


in Harvard Style

Alandihallaj M., Ramezani M. and Hein A. (2024). MBSE-Enhanced LSTM Framework for Satellite System Reliability and Failure Prediction. In Proceedings of the 12th International Conference on Model-Based Software and Systems Engineering - Volume 1: MBSE-AI Integration; ISBN 978-989-758-682-8, SciTePress, pages 349-356. DOI: 10.5220/0012607600003645


in Bibtex Style

@conference{mbse-ai integration24,
author={M. Alandihallaj and Mahya Ramezani and Andreas Hein},
title={MBSE-Enhanced LSTM Framework for Satellite System Reliability and Failure Prediction},
booktitle={Proceedings of the 12th International Conference on Model-Based Software and Systems Engineering - Volume 1: MBSE-AI Integration},
year={2024},
pages={349-356},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012607600003645},
isbn={978-989-758-682-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Model-Based Software and Systems Engineering - Volume 1: MBSE-AI Integration
TI - MBSE-Enhanced LSTM Framework for Satellite System Reliability and Failure Prediction
SN - 978-989-758-682-8
AU - Alandihallaj M.
AU - Ramezani M.
AU - Hein A.
PY - 2024
SP - 349
EP - 356
DO - 10.5220/0012607600003645
PB - SciTePress