Enhance GO methodology for reliability analysis of the closed-loop system using Cyclic Bayesian Networks

Jardine, 2006, A review on machinery diagnostics and prognostics implementing condition-based maintenance, Mech. Syst. Signal Pr., 20, 1483, 10.1016/j.ymssp.2005.09.012 Peng, 2004, Application of the wavelet transform in machine condition monitoring and fault diagnostics: a review with bibliography, Mech. Syst. Signal Pr., 18, 199, 10.1016/S0888-3270(03)00075-X Kerschen, 2006, Past, present and future of nonlinear system identification in structural dynamics, Mech. Syst. Signal Pr., 20, 505, 10.1016/j.ymssp.2005.04.008 Sun, 2012, Application of a state space modeling technique to system prognostics based on a health index for condition-based maintenance, Mech. Syst. Signal Pr., 28, 585, 10.1016/j.ymssp.2011.09.029 Williams, 1977, Use of the GO methodology to directly generate minimal cut sets W.V. Gately, R.L. Williams, GO Methodology—Overview, EPRI NP-765, 1978. B.B. Chu, Overview Manual GO Methodology, EPRI NP-3123, V1, 1983. Matsuoka, 2009, An exact method for solving logical loops in reliability analysis, Reliab. Eng. Syst. Safe., 94, 1282, 10.1016/j.ress.2009.01.007 Araújo, 2016, State derivative feedback in second-order linear systems: a comparative analysis of perturbed eigenvalues under coefficient variation, Mech. Syst. Signal Pr., 76–77, 33, 10.1016/j.ymssp.2016.02.014 Coles, 1988, Breaking the logic loop to complete the Probabilistic Risk Assessment, Specif. Nucl. Reactors Assoc. Plants Jung, 2005, Development of an analytical method to break logical loops at the system level, Reliab. Eng. Syst. Safe., 90, 37, 10.1016/j.ress.2004.10.005 Matsuoka, 2000, A method to solve logical loops in the GO-FLOW methodology, 1461 Yang, 1997, Analytic method to break logical loops automatically in PSA, Reliab. Eng. Syst. Safe., 56, 101, 10.1016/S0951-8320(96)00142-1 Vaurio, 2007, A recursive method for breaking complex logic loops in Boolean system models, Reliab. Eng. Syst. Safe., 92, 1473, 10.1016/j.ress.2006.09.020 Matsuoka, 2015, Evaluation of plant operational states with the consideration of loop structures under accident conditions, Nucl. Eng. Technol., 47, 157, 10.1016/j.net.2014.12.011 X. Yi, J. Shi, H. Mu, H. Dong, S. Guo, Reliability analysis of hydraulic steering system with DICLFL considering shutdown correlation based on GO methodology, Reliability Systems Engineering (ICRSE), First International Conference on: IEEE, 2015, pp. 1–6. Perkusich, 2015, A procedure to detect problems of processes in software development projects using Bayesian networks, Expert. Syst. Appl., 42, 437, 10.1016/j.eswa.2014.08.015 Abimbola, 2015, Safety and risk analysis of managed pressure drilling operation using Bayesian network, Saf. Sci., 76, 133, 10.1016/j.ssci.2015.01.010 Khakzad, 2015, Application of dynamic Bayesian network to risk analysis of domino effects in chemical infrastructures, Reliab. Eng. Syst. Safe., 138, 263, 10.1016/j.ress.2015.02.007 Rabhi, 2011, Structure dynamic reliability: a hybrid approach and robust meta-models, Mech. Syst. Signal Pr., 25, 2313, 10.1016/j.ymssp.2011.02.014 Pearl, 1986, Fusion, propagation, and structuring in belief networks, Artif. Intell., 29, 241, 10.1016/0004-3702(86)90072-X Bobbio, 2001, Improving the analysis of dependable systems by mapping fault trees into Bayesian networks, Reliab. Eng. Syst. Safe., 71, 249, 10.1016/S0951-8320(00)00077-6 H. Boudali, J.B. Duga, A new Bayesian network approach to solve dynamic fault trees, Reliability & Maintainability Symposium, 2005, pp. 451–456. Montani, 2008, A tool for reliability analysis of dynamic fault trees through conversion into dynamic Bayesian networks, Reliab. Eng. Syst. Safe., 93, 922, 10.1016/j.ress.2007.03.013 Khakzad, 2011, Safety analysis in process facilities: comparison of fault tree and Bayesian network approaches, Reliab. Eng. Syst. Safe., 96, 925, 10.1016/j.ress.2011.03.012 W. Marsh, G. Bearfield, Representing parameterised fault trees using Bayesian networks, Proceedings of the 26th International Conference on Computer Safety, Reliability, and Security, 2007, pp. 120–133. Sklet, 2004, Comparison of some selected methods for accident investigation, J. Hazard Mater., 111, 29, 10.1016/j.jhazmat.2004.02.005 Nivolianitou, 2004, Comparison of techniques for accident scenario analysis in hazardous systems, J. Loss Prevent. Proc., 17, 467, 10.1016/j.jlp.2004.08.001 Weber, 2012, Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas, Eng. Appl. Artif. Intel., 25, 671, 10.1016/j.engappai.2010.06.002 Y. Liu, Z. Zhang, M. Zhong, Reliability Analysis on the Injection System by Mapping T-S Fault Trees into Bayesian Networks, 2015, pp. 1134–1139. Kłopotek, 2006, Cyclic Bayesian network: Markov process approach, Stud. Inform.: Syst. Inform. Technol.., 1, 47 Shen, 2006, A supplemental algorithm for the repairable system in the GO methodology, Reliab. Eng. Syst. Safe., 91, 940, 10.1016/j.ress.2005.09.008 Chu, 1983, Go methodology, Application and comparison of the go methodology and fault tree analysis, EPRI NP-3123, 2 S.M. Azizi, S.M. Lainoff, D.C. Rees, GO methodology. Volume 3. GO modeling manual, Electric Power Research Institute Hillview Ave Palo Alto Ca, 1983. Balas, 1978, Feedback control of flexible systems, IEEE T Automat. Contr., 23, 673, 10.1109/TAC.1978.1101798 Isidori, 1992, Feedback control of nonlinear systems, Int. J. Robust. Nonlin., 2, 291, 10.1002/rnc.4590020404 Yue, 2010, State feedback controller design of networked control systems, Circ. Syst. II Express Briefs IEEE Trans., 51, 640, 10.1109/TCSII.2004.836043 Pearl, 1989 Jensen, 2007 P. Dagum, A. Galper, Dynamic network models for forecasting, Proceedings of the Eighth Conference on Uncertainty in Artificial Intelligence, AUAI Press, 1992, pp. 41–48. K. Murphy, Dynamic Bayesian Networks: Representation, Inference and Learning, UC Berkeley, 2002. Dongming, 2015, A repair GO algorithm based on Dynamic Bayesian network, Beijing Univ. Aeronaut. Astronaut. J., v.41, 2166 Liu Linlin, Ren Yi, Wang Zili, Yang Dezhen, GO algorithm based on Bayesian network, system engineering and electronic technology, vol. 37, no. 424, 2015, pp. 212–218. Guyader, 2001, Joint source-channel turbo decoding of entropy-coded sources, IEEE J. Sel. Area Comm., 19, 1680, 10.1109/49.947033 M.A. Kłopotek, Cyclic Bayesian Network – Markov Process Approach, 2006, pp. 47–55. Zou, 2005, A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data, Bioinformatics, 21, 71, 10.1093/bioinformatics/bth463 Zhou Zhongbao, The research and application of probabilistic safety assessment method based on Bayesian network, National University of defense technology, 2006. Hong, 2000 Fan, 2016, A modified GO-FLOW methodology with common cause failure based on Discrete Time Bayesian Network, Nucl. Eng. Des., 305, 476, 10.1016/j.nucengdes.2016.06.010