A method to generate equiprobale runs in TFPG models
Article No.: 19, Pages 1 - 7
Abstract
FDIR functionalities play a key role in several fields and a lot of techniques and methods have been developed in order to make them possible. TFPG is a causal model that captures the temporal aspects of failure propagation in a wide variety of engineering systems. As other sources of information, they require to be stored and retrieved. A key to index and query a TFPG documental base is in the sequence of events, i.e. runs, they are able to model. In this paper we propose a method to produce equiprobable runs of the TFPG model that can be used as support to index generation.
References
[1]
S. Abdelwahed and G. Karsai. Failure prognosis using timed failure propagation graphs. In The International Conference of the Prognostics and Health Management Society 2009, San Diego, CA 2009, 2009.
[2]
Sherif Abdelwahed, Gabor Karsai, and Gautam Biswas. System diagnosis using hybrid failure propagation graphs. In The 15th International Workshop on Principles of Diagnosis. Citeseer, 2004.
[3]
Marco Bozzano, Alessandro Cimatti, Marco Gario, and Andrea Micheli. Smt-based validation of timed failure propagation graphs. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, AAAI'15, pages 3724--3730. AAAI Press, 2015.
[4]
Elías F. Combarro, Ignacio F. Rúa, and José Ranilla. New advances in the computational exploration of semifields. Int. J. Comput. Math., 88(9):1990--2000, 2011.
[5]
Irene Díaz, Elías F. Combarro, Pasquale Marinaro, and Luigi Troiano. Ranking COMMPS chemical substances by an improved POT/RLE approach. Journal of Chemical Information and Modeling, 53(12):3190--3201, 2013.
[6]
A. Dubey, G. Karsai, and N. Mahadevan. Model-based software health management for real-time systems. In Aerospace Conference, 2011 IEEE, pages 1--18, 2011.
[7]
Sandra Hayden, Nikunj Oza, Robert Mah, Ryan Mackey, Sriram Narasimhan, Gabor Karsai, Scott Poll, Somnath Deb, and Mark Shirley. Diagnostic technology evaluation report for on-board crew launch vehicle. NASA, Tech. Rep, 2006.
[8]
S. Ierace, P. Marinaro, P. Tatavitto, and L. Troiano. Profiling the power usage of industrial machinery by ann. In Soft Computing and Pattern Recognition (SoCPaR), 2010 International Conference of, pages 413--418, 2010.
[9]
S. Ierace, R. Pinto, L. Troiano, and S. Cavalieri. Neural network as an efficient diagnostics tool: A case study in a textile company. volume 1, pages 122--127, 2010.
[10]
T. Kurtoglu, S.B. Johnson, E. Barszcz, J.R. Johnson, and P.I. Robinson. Integrating system health management into the early design of aerospace systems using functional fault analysis. In Prognostics and Health Management, 2008. PHM 2008. International Conference on, pages 1--11, 2008.
[11]
N. Mahadevan, S. Abdelwahed, A. Dubey, and G. Karsai. Distributed diagnosis of complex systems using timed failure propagation graph models. In AUTOTESTCON, 2010 IEEE, pages 1--6, 2010.
[12]
Amit Misra. Senor-based diagnosis of dynamical systems. PhD thesis, Vanderbilt University, 1994.
[13]
S.C. Ofsthun and S. Abdelwahed. Practical applications of timed failure propagation graphs for vehicle diagnosis. In Autotestcon, 2007 IEEE, pages 250--259, 2007.
[14]
S. Rampone, V. Pierro, L. Troiano, and I.M. Pinto. Neural network aided glitch-burst discrimination and glitch classification. International Journal of Modern Physics C, 24(11), 2013.
[15]
Jean-Marc Roussel, Alessandro Giua, et al. Designing dependable logic controllers using the supervisory control theory. In Proceedings of the 16th IFAC World Congress, 2005, 2005.
[16]
J. Schumann, O.J. Mengshoel, and T. Mbaya. Integrated software and sensor health management for small spacecraft. In Space Mission Challenges for Information Technology (SMC-IT), 2011 IEEE Fourth International Conference on, pages 77--84, 2011.
[17]
Claude E. Shannon. A mathematical theory of communication. The Bell System Technical Journal, 27:379--423, 623--656, July, October 1948.
[18]
L. Troiano, M. Tipaldi, A. Di Cerbo, M. Hoping, D. De Pasquale, and B. Bruenjcs. Satellite fdir practices using timed failure propagation graphs. volume 11, pages 8524--8531, 2012.
[19]
Luigi Troiano and Giacomo Scibelli. A time-efficient breadth-first level-wise lattice-traversal algorithm to discover rare itemsets. Data Mining and Knowledge Discovery, pages 1--35, 2013.
[20]
Luigi Troiano, Giacomo Scibelli, and Cosimo Birtolo. A fast algorithm for mining rare itemsets. In ISDA, pages 1149--1155, 2009.
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Published In
June 2016
146 pages
ISBN:9781450341417
DOI:10.1145/2934732
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- University of Granada: University of Granada
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Association for Computing Machinery
New York, NY, United States
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Published: 14 June 2016
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CERI '16
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CERI '16 Paper Acceptance Rate 18 of 27 submissions, 67%;
Overall Acceptance Rate 36 of 51 submissions, 71%
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