Hybrid Particle Petri Nets for Systems Health Monitoring under Uncertainty
This paper focuses on how to treat uncertainty in health monitoring of hybrid systems by using a model-based method. The Hybrid Particle Petri Nets (HPPN) formalism is defined
in the context of health monitoring to model hybrid systems and to generate diagnosers of such systems. The main advantage of this formalism is that it takes into account knowledgebased uncertainty and uncertainty in diagnosis process. The HPPN-based diagnoser deals with occurrences of unobservable discrete events (such as faults) and is robust to false observations. It also estimates the continuous state of the system by using particle filtering. Finally, HPPN can represent the system degradation that is often dealt with using probabilistic tools. A hybrid technique is thus used to group all this knowledge and to deduce the diagnosis results. The approach is demonstrated on a three-tank system. Experimental results are given, illustrating how different kinds of uncertainty are taken into account when using HPPN.
health monitoring, fault detection uncertainty, particle Petri nets
Bayoudh, M., Travé-Massuyes, L., & Olive, X. (2008). Hybrid systems diagnosis by coupling continuous and discrete event techniques. In Proceedings of the IFAC World Congress (pp. 7265–7270). Seoul, Korea.
Boubour, R., Jard, C., Aghasaryan, A., Fabre, E., & Benveniste, A. (1997, December). A Petri net approach to fault detection and diagnosis in distributed systems. part i: application to telecommunication networks, motivations, and modelling. In the 36th conference on decision & control. San Diego, Califomia, USA.
Cabasino, M. P., Giua, A., & Seatzu, C. (2014). Diagnosability of discrete-event systems using labeled Petri nets. IEEE Transactions on Automation Science and Engineering, 11(1), 144–153.
Chanthery, E., & Ribot, P. (2013). An integrated framework for diagnosis and prognosis of hybrid systems. In 3rd Workshop on Hybrid Autonomous System (HAS). Roma, Italy.
Cocquempot, V., El Mezyani, T., & Staroswiecki, M. (2004). Fault detection and isolation for hybrid systems using structured parity residuals. In 5th Asian Control Conference. (Vol. 2, pp. 1204–1212).
Gaudel, Q., Chanthery, E., & Ribot, P. (2014). Health monitoring of hybrid systems using hybrid particle Petri nets. In Annual conference of the prognostics and health management society 2014.
Gaudel, Q., Chanthery, E., Ribot, P.,&Le Corronc, E. (2014). Hybrid systems diagnosis using modified particle Petri nets. In Proceedings of the 25th International Workshop on Principles of Diagnosis (DX’14). Graz, Austria.
Genc, S., & Lafortune, S. (2007, April). Distributed diagnosis of place-bordered Petri nets. IEEE Transactions on Automation Science and Engineering, 4(2), 206–219.
Henzinger, T. (1996). The theory of hybrid automata. In Proceedings of the 11th Annual IEEE Symposium on Logic in Computer Science (pp. 278–292).
Jianxiong, W., Xudong, X., Xiaoying, B., Chuang, L., Xiangzhen, K., & Jianxiang, L. (2013). Performability analysis of avionics system with multilayer hm/fm using stochastic Petri nets. Chinese Journal of Aeronautics, 26(2), 363–377.
Koutsoukos, X., Kurien, J., & Zhao, F. (2002, August). Monitoring and diagnosis of hybrid systems using particle filtering methods. In Proceedings of the 15th international symposium on mathematical theory of networks and systems, mtns 2003. Notre Dame, IN.
Lesire, C., & Tessier, C. (2005). Particle Petri nets for aircraft procedure monitoring under uncertainty. In Applications and Theory of Petri Nets (pp. 329–348). Springer.
Maquin, D., Cocquempot, V., Cassar, J.-P., Staroswiecki, M., Ragot, J., et al. (1997). Generation of analytical redundancy relations for fdi purposes. In Ifac symposium on diagnostics for electrical machines, power electronics and drives, sdemped’97 (pp. 86–93).
Ru, Y., & Hadjicostis, C. N. (2009). Fault diagnosis in discrete event systems modeled by partially observed Petri nets. Discrete Event Dynamic Systems, 19(4), 551–575.
Sampath, M., Sengupta, R., Lafortune, S., Sinnamohideen, K., & Teneketzis, D. (1995). Diagnosability of discrete-event systems. IEEE Transactions on Automatic Control, 40(9), 1555–1575.
Soldani, S., Combacau, M., Subias, A., & Thomas, J. (2007). On-board diagnosis system for intermittent fault: Application in automotive industry. In 7th ifac international conference on fieldbuses and networks in industrial and embedded systems (Vol. 7-1, p. 151-158). doi: 10.3182/20071107-3-FR-3907.00021
Staroswiecki, M., & Comtet-Varga, G. (2001). Analytical redundancy relations for fault detection and isolation in algebraic dynamic systems. Automatica, 37(5), 687–699.
Zouaghi, L., Alexopoulos, A., Wagner, A., & Badreddin, E. (2011a). Modified particle Petri nets for hybrid dynamical systems monitoring under environmental uncertainties. In IEEE/SICE International Symposium on System Integration (SII) (pp. 497–502).
Zouaghi, L., Alexopoulos, A., Wagner, A., & Badreddin, E. (2011b). Probabilistic online-generated monitoring models for mobile robot navigation using modified Petri net. In 15th International Conference on Advanced Robotics (ICAR) (pp. 594–599).