Assessing and classifying risk of pipeline third-party interference based on fault tree and SOM

Engineering Applications of Artificial Intelligence

Volumn 25, Issue 3, 2012, Pages 594-608

  Liang, Wei ^a   Hu, Jinqiu ^a   Zhang, Laibin ^a   Guo, Cunjie ^b   Lin, Weipeng ^a  

^a CHINA UNIVERSITY OF PETROLEUM   (China)

^b Petrochina Beijing Gas Pipeline Corporation Limited   (China)

Author keywords

Fault tree; Multi attribute risk assessment; Risk pattern classification; SOM; Third party interference

Indexed keywords

ASSESSMENT INDEX SYSTEM; CATASTROPHIC CONSEQUENCES; CLASSIFICATION RESULTS; DECISION MAKERS; ECONOMIC LOSS; FAULT-TREES; LONG TRANSMISSION PIPELINES; MANAGEMENT MEASURES; MULTI-ATTRIBUTES; MULTIPARAMETERS; RISK DISTRIBUTION; RISK MAPS; SAFE OPERATION; SOM;

CONFORMAL MAPPING; FORESTRY; LOSSES; NATURAL GAS TRANSPORTATION; PATTERN RECOGNITION; PIPELINES;

RISK ASSESSMENT;

ACCIDENTS; INTERFERENCE; NATURAL GAS; PATTERN RECOGNITION; PIPE LINES; PROBLEM SOLVING; RISK ASSESSMENT;

EID: 84857449880     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2011.08.010     Document Type: Article

References (15)

1. A.J. Brito, and A.T. de Almeida Multi-attribute risk assessment for risk ranking of natural gas pipelines Reliab. Eng. Syst. Saf. 94 2 2009 187 198
2. Y.G. Cao, X.Y. Sun, and S.H. Zhang Field experiments and FEM analysis of third-party damaged oil transmission pipeline Eng. Failure Anal. 17 1 2010 344 352
3. Y.G. Cao, Y.J. Shi, and S.H. Zhang Research on strength degradation of oil transmission pipeline by third-party damages Eng. Failure Anal. 17 4 2010 992 1007
4. Code for Design of Gas Transmission Pipeline Engineering (GB50251-2003), 20031001. Ministry of Construction.
5. S. Contini, L. Fabbri, and V. Matuzas A novel method to apply importance and sensitivity analysis to multiple Fault-trees J. Loss Prev. Process Ind. 23 5 2010 574 584
6. M.J. Gharabagh, H. Asilian, and S.B. Mortasavi Comprehensive risk assessment and management of petrochemical feed and product transportation pipelines J. Loss Prev. Process Ind. 22 4 2009 533 539
7. Y.D. Jo, and B.J. Ahn Analysis of hazard area associated with high pressure natural-gas pipeline J. Loss Prev. Process Ind. 15 3 2002 179 188 (Pubitemid 34490213)
8. J. Kangas, and T. Kohonen Developments and applications of the self-organizing map and related algorithms Math. Comput. Simulat. 41 12 1996 3 12 (Pubitemid 126411642)
9. N. Khakzad, F. Khan, and P. Amyotte Safety analysis in process facilities: comparison of fault tree and Bayesian network approaches Reliab. Eng. Syst. Saf. 96 8 2011 925 932
10. T. Kohonen Self-organizing neural projections Neural Networks 19 67 2006 723 733 (Pubitemid 44148941)
11. T.S. Li, and C.L. Huang Defect spatial pattern recognition using a hybrid SOMSVM approach in semiconductor manufacturing Expert Syst. Appl. 36 1 2009 374 385
12. A.S. Markowski, and M.S. Mannan Fuzzy logic for piping risk assessment (pfLOPA) J. Loss Prev. Process Ind. 22 6 2009 921 927
13. Miura, S.; Mishima, T.; November 69 1995. Damage monitoring system for pipelines. In: IGRC95 Proceedings.
14. National Transportation Safety Board Pipeline Accident Report for Texas Eastern Transmission Corporation Natural Gas Pipeline Explosion and Fire, March 23 1994. Edison, New Jersey. PB95-916501. NTSB/PAR-95/01.
15. K.S. Park, J.H. Lee, and Y.D. Jo An approach to risk management of city gas pipeline Process Saf. Environ. Prot. 82 6 2004 446 452