Failure Prognosis Using Timed Failure Propagation Graphs



Published Mar 26, 2021
Sherif Abdelwahed Gabor Karsai


Timed failure propagation graph (TFPG) is a causal model that captures the causal and temporal aspects of failure propagation in a wide variety of engineering systems. In this paper we investigate the problem of failure prognosis within the TFPG model settings. The paper introduces a formal definition for system reliability based on measures of failure criticality, proximity between alarm observations, and plausibility of the estimated current system condition. An algorithm to compute the time to reach a given criticality level of the system, referred to as time to criticality, based on the current conditions of the system is introduced. The time to criticality, also known as the system’s Remaining Useful Life (RUL), can be used as a measure for system reliability at any given time in the future.

How to Cite

Abdelwahed, S., & Karsai, G. (2021). Failure Prognosis Using Timed Failure Propagation Graphs. Annual Conference of the PHM Society, 1(1). Retrieved from
Abstract 3 | PDF Downloads 1



model based prognostics, model-based methods, prognostics, remaining useful life (RUL)

(Abdelwahed et al., 2004) S. Abdelwahed, G. Karsai, and G. Biswas. System diagnosis using hybrid failure propagation graphs. In The 15th International Workshop on Principles of Diagnosis, Carcassonne, France, 2004.
(Abdelwahed et al., 2005) S. Abdelwahed, G. Karsai, and G. Biswas. A consistency-based robust diagnosis approach for temporal causal systems. In The 16th International Workshop on Principles of Diagnosis, Pacific Grove, CA, 2005.
(Chelidze et al., 2002) D. Chelidze, J.P. Cusumano, and A. Charterjee. A dynamical systems approach to damage evolution tracking, part 1: The experimental method. Journal of Vibration and Acoustics, 124:250–257, 2002.
(ISO-13381-1, 2004 ) ISO-13381-1. Condition monitoring and diagnostics of machines - prognostics - part1: General guidelines. Int. Standard, 2004.
(Jardine and Lin, 2006) A. K. S. Jardine and D. Lin. A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, 20(7):1483–1510, 2006.
(Karsai et al., 2003) G. Karsai, G. Biswas, and S. Ab- delwahed. Towards fault-adaptive control of complex dynamic systems. In T. Samad and G. Balas, editors, Software-Enabled Control: Information Technology for Dynamical Systems, chapter 17. IEEE publication, 2003.
(Lebold and Thurston, 2001 ) M. Lebold and M. Thurston. Open standards for condition- based maintenance and prognostic systems. In 5th annual maintenance and reliability conference, Gatlinburg, USA., 2001.
(Luo et al., 2003) J. Luo, M. Namburu, K. Pattipati, L. Qiao, M. Kawamoto, and S. Chigusa. Model- based prognostic techniques. In Proc. of IEEE AU- TOTESTCON, pages 330–340, 2003.
(Medjaher et al., 2009) K. Medjaher, J.-Y. Moya, and N. Zerhouni. Failure prognostic by using dynamic
bayesian networks. In 2nd IFAC Workshop on Dependable Control of Discrete Systems, DCDS’09, Bari, Italy, 2009.
(Misra et al., 1994) A. Misra, J. Sztipanovits, and J. Carnes. Robust diagnostics: Structural redundancy approach. In SPIE’s Symposium on Intelligent Systems, 1994.
(Muller et al., 2008) A. Muller, M.C. Suhner, and B. Iung. Formalisation of a new prognosis model for supporting proactive maintenance implementation on industrial system. Reliability Engineering and System Safety, 93:234–253, 2008.
(Ofsthun and Abdelwahed, 2007 ) S. Ofsthun and S. Abdelwahed. Practical applications of timed failure propagation graphs for vehicle diagnosis. In IEEE Systems Readiness Technology Conference, Autotestcon’07, pages 250–259, Baltimore, MD, September 2007.
(Padalkar et al., 1991) S. Padalkar, J. Sztipanovits, G. Karsai, N. Miyasaka, and K. C. Okuda. Real- time fault diagnostics. IEEE Expert, 6(3):75–85, 1991.
(Provan, 2003) G. Provan. Prognosis and condition- based monitoring: an open systems architecture. In 5th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, 2003.
(Vachtsevanos et al., Wiley Sons) G. Vachtsevanos, F. L. Lewis, M. Roemer, A. Hess, and B. Wu. Intelligent Fault Diagnosis and Prognosis for Engineering Systems, volume 2006. Intelligent Fault Diagnosis and Prognosis for Engineering Systems., New Jersey, Hoboken, Wiley & Sons.
(Vichare and Pecht, 2006) N. Vichare and M. Pecht. Prognostics and health management of electronics. IEEE Transactions on Components and Packaging Technologies, 29(1):222–229, 2006.
Technical Papers