System Reliability Estimation of Divert Attitude Control System of a Launch Vehicle using Bayesian Networks

  • S. Muthukumar DRDO-Research Centre Imarat, Hyderabad - 500 069, India
  • R. A. Srivardhan DRDO-Defence Research and Development Laboratory, Hyderabad - 500 058, India
  • P. Subhash Chandra Bose Mechanical Engineering Department, National Institute of Technology, Warangal -506 004, India
Keywords: Propulsion system, Weighted sum algorithm, Conditional probability, MCMC, Bayesian networks, Reliability

Abstract

Divert attitude and control system (DACS) is a one-shot system and provides attitude correction and translation of the Launch vehicle. DACS consists of many flight critical sub systems which are arranged in a series configuration. The traditional Reliability block diagram and Fault tree diagram methods are unsuitable for reliability modelling, when considering uncertainty among the components and system. Bayesian network is the natural choice to model dependencies among the components and system. DACS being one shot system, it is very expensive and time consuming to test more number of systems during the design and development. Hence the data is drawn from component level, subsystem level and expert opinion is used for reliability estimation. In this paper, Bayesian network modelling of DAC system was carried out for estimating the reliability using multi-level data. An algorithm is developed for computation of Conditional probabilities in Bayesian network. Posterior probability distribution of components is calculated using Markov Chain Monte Carlo (MCMC) simulations and results are compared with Junction tree based exact inference algorithm. MATLAB code is developed to estimate the reliability of DAC system.

References

Wilson, A.G.; Graves, T.L.; Hamada, M.S. & Reese, C.S. Advances in data combination, analysis and collection for system reliability assessment. Statistical Science, 2006, 21(4), 514-531. https://doi.org/10.1214/088342306000000439

Wilson, A.G.; Laura, A.; Namara, Mc & Wilson, G.D. Information integration for complex systems. Reliability Eng. Sys. Safety, 2007, 92(1), 121-130. https://doi.org/10.1016/j.ress.2006.07.003

Wilson, A.G. & Fronczyk. Bayesian reliability: Combining information. Quality Engineering, 2017, 29, 119-129. https://doi.org/10.1080/08982112.201.1211889

Hamada, M.; Martz, H.; Reese, C.S.; Graves, T.; Johnson, V. & Wilson, A.A fully Bayesian approach for combining multilevel failure information in fault tree quantification and optimal follow-on resource allocation. Reliability Engineering and System Safety; 2004, 86, 297–305. https://doi.org/10.1016/j.ress.2004.02.001

Jiqiang, Guo & Wilson, A.G. Bayesian methods for estimating the reliability of complex systems using heterogeneous multilevel information. Technometrics, 2013, 55, 461-472. https://doi.org/10.1080/00401706.2013.804441

Zhai, S. & Lin, S.Z. Bayesian networks application in multi-state system reliability analysis. Appl. Mech. Mater., 2013, 347-350, 2590-2595. https://doi.org/10.4028/www.scientific.net/AMM.347-350.2590

Liu, Y; Lin, P; Li, Y. & Huang, H. Bayesian reliability and performance assessment for multi-state systems. IEEE Trans. Reliability, 2015, 64, 394-409. https://doi.org/10.1109/TR.2014.2366292

Das, Balaram. Generating conditional probabilities for Bayesian networks: Easing the knowledge acquisition problem. 2004, Journal CoRR cs.AI/0411034. https://doi.org/arxiv.org/abs/cs/0411034

Spiegalhalter, D.; Thomas, A.; Best, N. & Lunn, D. WinBuGS user Manual Version 1.4. Medical Research Council Biostatistics unit, Cambridge. 2003

Jenson, F.V. & Madsen, L. LAZy propagation; Junction tree inference based on lazy evaluation. Artificial Intelligence, 1999, 113, 203-245. https://doi.org/10.1016/S0004-3702(99)00062-4

Guo, H; Jin, T & Mettas, A. Deigning reliability demonstration tests for one shot systems under zero component failures. IEEE Trans. Reliability, 2011, 60(1), 286-294. https://doi.org/10.1109/TR.2010.2085552

Published
2020-02-10
How to Cite
MuthukumarS., SrivardhanR., & BoseP. S. (2020). System Reliability Estimation of Divert Attitude Control System of a Launch Vehicle using Bayesian Networks. Defence Science Journal, 70(1), 90-94. https://doi.org/10.14429/dsj.70.13708
Section
Missile System