Design of an Electrical Power System using a Functional Failure and Flow State Logic Reasoning Methodology
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Abstract
Knowledge about failures and failure propagation paths in early design can benefit Prognostics and Health Management (PHM) system development by identifying expected system failures, determining adequate system monitoring, and improving system reliability through hardware configurational changes. Function-based failure analysis provides a means for early system representation that can provide meaningful results for failure analysis. Function-based failure analysis methods model failures propagating between components based on shared energy, material, and signal (EMS) flows. Limiting these connections to the designed system representation limits the scope of failure impact and propagation analysis. This paper presents a method of defining and reasoning on flow states for designed and potential EMS flows and using this information to determine impact and propagation behavior for failures based on early design information. To demonstrate the value of this approach, an electrical power system design is developed and analyzed as a case study. The initial results presented in this paper specifically benefit the development of PHM by providing simulated system behavior for a wide scope of propagation paths and by identifying the impact of failures with respect to system functions.
How to Cite
##plugins.themes.bootstrap3.article.details##
failure analysis, fault diagnosis
(Clarkson, 2004) Simons C. Eckert C. Clarkson, P. Predicting change propagation in complex design. Journal of Mechanical Design, 126:788, 2004.
(de Kleer and Kurien, 2003) J. de Kleer and J. Kurien. Fundamentals of model-based diagnosis. Safe Pro- cess,2003.
(Deb et al., 1995) S. Deb, K. R. Pattipati, V. Ragha- van, M. Shakeri, and R. Shrestha. Multisignal flow graphs: a novel approach for system testability analysis and fault diagnosis. IEEE Aerospace and Electronics Systems Magazine, 10:14–25, 1995.
(Forbus, 1984) K. Forbus. Qualitative Process Theory. Artificial Intelligence, 24, 85-168, 1984.
(Giarratano and Riley, 2004) J. C. Giarratano and G. D. Riley. Expert Systems: Principles and Programming. PWS, Boston, MA, 2004.
(Grantham-Lough et al., 2008) K. Grantham-Lough, R. B. Stone, and I. Y. Tumer. Implementation Procedures for the Risk in Early Design (RED) Method. Journal of Industrial and Systems Engineering, 2(2):126–143, 2008.
(Greer et al., 2004) J. Greer, D. Jensen, and K. Wood. Effort flow analysis: a methodology for directed product evolution. Design Studies, 25(2):193–214, 2004.
(Hirtz et al., 2002) J. Hirtz, R. Stone, D. McAdams, S. Szykman, and K. Wood. A Functional Basis for Engineering Design: Reconciling and Evolving Previous Efforts. Research in Engineering Design, 13:65–82, 2002.
(Huang and Jin, 2008) Z. Huang and Y. Jin. Conceptual Stress and Conceptual Strength for Functional Design-for-Reliability. In Proceedings of the ASME Design Engineering Technical Conferences; International Design Theory and Methodology Conference, 2008.
(Hutcheson and Tumer, 2005) 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.
(Hutcheson et al., 2006) R. Hutcheson, D. McAdams, R. Stone, and I. Y. Tumer. FACE A function-based methodology for analyzing critical events. In Proceedings of the ASME Design Engineering Technical Conferences, 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.
(Krus and Grantham Lough, 2007) D. Krus and K. Grantham Lough. Applying function-based failure propagation in conceptual design. InProceedings of the ASME Design Engineering Technical Conferences; International Design Theory and Methodology Conference, 2007.
(Kuipers,1986) B.J.Kuipers.QualitativeSimulation. Artificial Intelligence, 29/3:289–338, 1986.
(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.
(Meshkat et al., 2007) L. Meshkat, S. Jenkins, S. Mandutianu, and V. Heron. Automated Generation of Risk and Failure Models during Early Phase Design. In Proceedings of the IEEE Aerospace Conference, 2007.
(Otto and Wood, 2001) K. N. Otto and K. L. Wood. Product Design: Techniques in reverse engineering and new product development. Prentice Hall, 2001.
(Pahl and Beitz, 1996) G. Pahl and W. Beitz. Engi- neering Design: A Systematic Approach. Springer- Verlag, London, UK, 1996.
(Patterson-Hine, 2005) Narasimhan S. Aaseng G. Biswas G. Pattipati K. Patterson-Hine, A. A review of diagnostic techniques for ishm applications. In 1st Integrated Systems Health Engineering and Management Forum., 2005.
(Patton et al., 1998) R.J. Patton, P. Frank, and R. Clark. Fault Diagnosis in Dynamic Systems: Theory and Applications. Prentice Hall, Hertfordshire, UK, 1998.
(Poll et al., 2007) S. Poll, A. Patterson-Hine , J. Camisa, D. Garcia, D. Hall, C. Lee, O. Meng- shoel, C. Neukom, D. Nishikawa, J. Ossenfort, A. Sweet, S. Yentus, I. Roychoudhury, M. Daigle, G. Biswas, and X. Koutsoukos. Advanced diagnostics and prognostics testbed. In 18th International Workshop on Principles of Diagnosis, 2007.
(Stone and Wood, 2000) R. B. Stone and K. L. Wood. Development of a functional basis for design. Journal of Mechanical Design, 122(4):359–370, 2000.
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.