A fault diagnosis method based on signed directed graph and matrix for nuclear power plants

Abstract In order to solve SDG online fault diagnosis and inference, matrix diagnosis and inference methods are proposed for fault detection and diagnosis (FDD). Firstly, “rules matrix” based on SDG model is used for FDD. Secondly, “status matrix” is proposed to achieve SDG online inference. According to different diagnosis results, “status matrix” is applied for the depth-first search and the breadth-first search respectively to find the propagation paths of each fault. Finally, the SDG model of the secondary-loop system in pressurized water reactor (PWR) is built to verify the effectiveness of the proposed method. The simulation experiment results indicate that the “status matrix” used for online inference can be used to find the fault propagation paths and to explain the causes for fault. Therefore, it can be concluded that the proposed method is one of the fault diagnosis for nuclear power plants (NPPs), which can be used to facilitate the development of fault diagnostic system.

[1]  Tao Chen,et al.  Root cause analysis in multivariate statistical process monitoring: Integrating reconstruction-based multivariate contribution analysis with fuzzy-signed directed graphs , 2014, Comput. Chem. Eng..

[2]  C. McGreavy,et al.  Qualitative process modelling: a fuzzy signed directed graph method , 1995 .

[3]  Eiji O'Shima,et al.  A graphical approach to cause and effect analysis of chemical processing systems , 1980 .

[4]  M. Iri,et al.  An algorithm for diagnosis of system failures in the chemical process , 1979 .

[5]  Xie Gang,et al.  Hierarchy fault diagnosis based on signed directed graphs model , 2012, 2012 24th Chinese Control and Decision Conference (CCDC).

[6]  Raghunathan Rengaswamy,et al.  A signed directed graph-based systematic framework for steady-state malfunction diagnosis inside control loops , 2006 .

[7]  O. O. Oyeleye,et al.  Qualitative simulation of chemical process systems: Steady‐state analysis , 1988 .

[8]  Satoshi Miyazaki,et al.  Fault location using digraph and inverse direction search with application , 1983, Autom..

[9]  Raghunathan Rengaswamy,et al.  Application of signed digraphs-based analysis for fault diagnosis of chemical process flowsheets , 2004, Eng. Appl. Artif. Intell..

[10]  Rakesh Sehgal,et al.  Fault location of tribo-mechanical systems - a graph theory and matrix approach , 2000, Reliab. Eng. Syst. Saf..

[11]  Nicolás J. Scenna,et al.  Fault diagnosis for a MSF using a SDG and fuzzy logic , 2003 .

[12]  Qin Yan,et al.  Study on Fault Diagnosis Based on the Qualitative / Quantitative Model of SDG and Genetic Algorithm , 2006, 2006 International Conference on Machine Learning and Cybernetics.

[13]  Venkat Venkatasubramanian,et al.  A hybrid framework for large scale process fault diagnosis , 1997 .

[14]  Venkat Venkatasubramanian,et al.  Signed Digraph based Multiple Fault Diagnosis , 1997 .

[15]  Xie Chun-li,et al.  Research and design of distributed fault diagnosis system in nuclear power plant , 2013 .

[16]  Xiao De-yun.  Application of Structural Residuals in SDG-based Fault Isolation , 2007 .

[17]  Eiji O'Shima,et al.  An improved algorithm for diagnosis of system failures in the chemical process , 1985 .

[18]  Mark A. Kramer,et al.  A rule‐based approach to fault diagnosis using the signed directed graph , 1987 .

[19]  Venkat Venkatasubramanian,et al.  PCA-SDG based process monitoring and fault diagnosis , 1999 .