Towards StateCharts Based Failure Propagation Analysis for Designing Embedded PHM Systems
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Abstract
Modern complex systems have evolved into artifacts that rely on both hardware and software to dependably function without human control. Health management software control systems have been developed to manage failures in such complex systems. The Prognostics and Health Management (PHM) systems have also developed to detect and identify failures and support operation by guiding either operator or automated software response. Of growing of importance in the PHM community is the need to develop formal methodologies to help integrate PHM into the system architecture during the early design stages. Early integration provides designers with the potential to consider PHM capabilities and limitations and make appropriate changes to the overall system earlier in the design stage, where changes are less costly and more effective. In previous work, the Function Failure Identification Propagation Framework (FFIP) was introduced as a novel methodology to help with early design of PHM systems, followed by several required augmentations to make FFIP more effective for PHM design specifically. In this paper, this research is extended by taking the data gathered from FFIP and applying a development language often used in the field of embedded systems design. Specifically, the concept of State- Charts from the embedded systems design field is used to further augment the FFIP methodology to more completely program the Function Failure Logic (FFL) reasoner module within FFIP. Stat- eCharts are shown to augment the FFIP framework by clearly laying out the hierarchical relationships between system health, function health, component status, command signal, and sensor signals. StateCharts are then applied to the development of a preliminary PHM hardware and software architecture using a liquid fuel rocket engine as a working example. Additional considerations, such as sensor and software reliability, as well as future considerations are discussed.
How to Cite
##plugins.themes.bootstrap3.article.details##
failure analysis, failure modes effects and criticality analysis (FMECA), PHM system design and engineering
(Duncavage et al., 2006) D. Duncavage, F. Figueroa, R. Holland, and C. Schamalzel. Integrated system health management (ishm): Systematic capability implementation. In IEEE Sensors Applications Symposium, 2006.
(Edwards et al., 1997) S. Edwards, L. Lavango, E. Lee, and A. L. Langiovanni-Vincentelli. Design of embedded systems: Formal models, validation, and synthesis. In Proceedings of the IEEE, volume 85, 1997.
(Ernst, 1998) R. Ernst. Codesign of embedded systems: Status and trends. IEEE Design and Test of Computers, 1998.
(Fujita and Hakamura, 2001) M. Fujita and H. Haka- mura. The standard specc language. In Proceedings of the ISSS, 2001.
(Gajski, 1994) D. Gajski. Specification and Design of Embedded Systems. Kluwer Academic Publishers, 1994.
(Gajski, 2003) D. Gajski. Embedded System Design. Kluwer Academic Publishers, Boston, MA, 2003.
(Gallardo et al., 2006) M. Gallardo, J. Martinez, P. Merino, and E. Pimentel. On the evolution of reliability methods for critical software. Transactions of the Society for Process and Design Science, 10(4), 2006.
(Graham, 2005) J. H. Graham. Fmeca control for software development. In Proceedings of the 29th Annual International Computer Software and Applications Conference, 2005.
(Harel et al., 1990) D. Harel, H. Lachover, A. Naa- mad, A. Pnueli, M. Politi, R. Sherman, A. Shtull- Trauring, and M. Trakhtenbrot. Statemate: A working environment for the development of complex reactive systems. IEEE Transactions on Software Engineering, 16(4):403–414, 1990.
(Harel, 2001) D. Harel. Statecharts: A visual formalism for computer systems. Science of Computer Programming, 8:231–274, 2001.
(Hoyle et al., 2009) C. Hoyle, I. Y. Tumer, and and W. Chen A. F. Mehr. Health Management Allocation During Conceptual System Design. Journal of Computing and Information Science in Engineering, 9(2), 2009.
(Hutcheson and Tumer, 2005a) R. Hutcheson and I. Y. Tumer. Function-based Co-design Paradigm for Robust Health Management. In Proceedings of the 5th International Workshop on Structural Health Monitoring, 2005.
(Hutcheson and Tumer, 2005b) R. Hutcheson and I. Y. Tumer. Function-based design of a spacecraft power subsystem diagnostics testbed. In Proceedings of the ASME International Mechanical Engineering Congress and Exposition, 2005.
(IEEE, 2006) IEEE. IEEE Standards SystemC. Pren- tice Hall, 2006.
(Jensen et al., 2008) D. Jensen, I. Y. Tumer, and T. Kurtoglu. Modeling the propagation of failures in software-driven hardware systems to enable risk- informed design. In Proceedings of the ASME International Mechanical Engineering Congress and Exposition, 2008.
(Jensen et al., 2009) D. Jensen, I. Y. Tumer, and T. Kurtoglu. Flow State Logic (FSL) for analysis of failure propagation in early design. In Proceedings of the ASME Design Engineering Technical Conferences; International Design Theory and Methodology Conference, 2009.
(Kramer and Tumer, 2009) S. Kramer and I. Y. Tumer. A framework for early assessment of failures during the design of PHM systems. In Proceedings of the ASME Design Engineering Technical Conferences; Computers and Information in Engineering Conference, 2009.
(Kurtoglu and Tumer, 2008a) T. Kurtoglu and I. Y. Tumer. A graph-based fault identification and propagation framework for functional design of complex systems. Journal of Mechanical Design, 130(5), 2008.
(Kurtoglu and Tumer, 2008b) T. Kurtoglu and I. Y. Tumer. A risk-informed decision making methodology for evaluating failure impact of early system designs. In Proceedings of the ASME Design Engineering Technical Conferences; International Design Theory and Methodology Conference, 2008.
(Kurtoglu et al., 2008) T. Kurtoglu, S. Johnson, E. Barszcz, J. Johnson, and P. Robinson. Integrating system health management into early design of aerospace systems using functional fault analysis. In Proc. of the International Conference on Prognostics and Heath Management, PHM08, 2008.
(Leao et al., 2008) P. Leao, Bruno, T. Yoneyama, G.C. Rocha, and K.T. Fitzgibbon. Prognostics performance metrics and their relation to requirements, design, verification, and cost-benefit. In Proc. of the International Conference on Prognostics and Heath Management, PHM08, 2008.
(Lyu, 2007) M.R. Lyu. Software reliability engineering: A roadmap. IEEE Future of Software Engineering, 2007.
(M. et al., 2005) Roemer M., Byington C., Kacprzyn- ski G., and Vachtsevanos G. An overview of selected prognostic technologies with reference to an integrated phm architecture. In Proc. of the First Intl. Forum on Integrated System Health Engineering and Management Conference, 2005.
(McKelvin et al., 2005) M. L. McKelvin, G. Eirea, C. Pinello, S. Kanajan, and A. L. Langiovanni- Vincentelli. A formal approach to fault tree synthesis for the analysis of distributed fault tolerant systems. In Proceedings of the EMSOFT’05, 2005.
(Peterson, 1981) J. Peterson. Petri Net Theory and the Modeling of Systems. Prentice Hall, 1981.
(Sutton, 1986) J.P. Sutton. Rocket Propulsion Elements: An Introduction to the Engineering of Rockets. John Wiley and Sons, New York, 1986.
(Tayler and Hoek, 2007) R.N. Tayler and A. Hoek. Software design and architecture: The once and future focus of software engineering. IEEE Future of Software Engineering, 2007.
(Tumer, 2005) I. Y. Tumer. Towards ISHM Co-Design: Methods and practices for fault avoidance and management during early phase design. In Proceedings of the 1st Integrated Systems Health Engineering and Management Forum, 2005.
(Wu, 2005) G. Wu. Liquid-propellant rocket engines health-monitoringa survey. Acata Astronautica, 56(3):347–356, 2005.
(Zave, 1982) P. Zave. An operational approach to requirements specification for embedded systems. IEEE Transactions on Software Engineering, 1982.
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.