Structural integrity monitoring for dependability

Structure and Infrastructure Engineering

Volumn 7, Issue 1, 2011, Pages 75-86

  Arangio, S ^a   Bontempi, F ^a   Ciampoli, M ^a  

^a SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

Bayesian neural network models; Dependability; Fault detection; Fault diagnosis; Integrity monitoring; Structural systems

Indexed keywords

BAYESIAN NEURAL NETWORK MODELS; DEPENDABILITY; FAULT DIAGNOSIS; INTEGRITY MONITORING; STRUCTURAL SYSTEMS;

BAYESIAN NETWORKS; CABLE STAYED BRIDGES; COMPUTER SIMULATION; FAULT DETECTION; FIBER OPTIC SENSORS; NEURAL NETWORKS; STRUCTURAL ANALYSIS; SUSPENSION BRIDGES; TRAFFIC SURVEYS;

MONITORING;

EID: 78349247857     PISSN: 15732479     EISSN: 17448980     Source Type: Journal    
DOI: 10.1080/15732471003588387     Document Type: Article

References (34)

1. Abe, K. and Amano, K., 1998. Monitoring system of the Akashi Kaikyo Bridge. Honshi Technical Report, 22 (86), 29-34.
2. Adeli, H., 2001. Neural Networks in Civil Engineering: 1989-2000. Computer-Aided Civil and Infrastructure Engineering, 16 (2), 126-142.
3. Aktan, A.E., Helmicki, A.J., and Hunt, V.J., 1998. Issues in health monitoring for intelligent infrastructure. Smart Materials and Structures, 7, 674-692.
4. Aktan, A.E., Catbas, F.N., Grimmelsman, K.A., and Pervizpour, M., 2002. Development of a model health monitoring guide for major bridges. Report DTFH61-01P-00347, Federal Highway Administration Research and Development, Drexel Intelligent Infrastructure and Transportation Safety Institute.
5. Arangio, S., 2008. Inference models for structural integrity monitoring: neural networks and Bayesian enhancements. Thesis on Structural Engineering (PhD). University of Rome 'La Sapienza'. networks for predicting the structural response of a long suspension bridge subjected to wind actions. In: Proceedings of SEMC 2007, Cape Town (on CD-ROM).
6. Arangio, S. and Beck, J.L., 2010. Bayesian neural networks for bridges integrity assessment. Structural Control and Health Monitoring (in press).
7. Avizienis, I., Laprie, J.C., and Randell, B., 2004. Dependability and its threats: a taxonomy. In: 18th IFIP World Computer Congress, Building the Information Society. Kluwer Academic Publishers, 91-120.
8. Beck, J.L. and Yuen, K.V., 2004. Model selection using response measurements: Bayesian probabilistic approach. Journal of Engineering Mechanics, 130, 192-203.
9. Berthold, M. and Hand, D.J., 1999. Intelligent data analysis. Berlin/Heidelberg: Springer-Verlag.
10. Bishop, C.M., 1995. Neural networks for pattern recognition. Oxford: Clarendon Press.
11. Bishop, C.M., 2006. Pattern recognition and machine learning. New York: Springer-Verlag.
12. Bontempi, F., 2006. Basis of design and expected performances for the Messina Strait Bridge. In: Proceedings of BRIDGE 2006, Hong Kong (on CD-ROM).
13. Bontempi, F., Gkoumas, K., and Arangio, S., 2008. Systemic approach for the maintenance of complex structural systems. Structure and Infrastructure Engineering, 4, 77-94.
14. 008, Seoul (on CD-ROM).
15. Casciati, F., 2003. An overview of structural health monitoring expertise within the European Union. In: Z.S. Wu and M. Abe, eds. Structural health monitoring and intelligent infrastructure. London: Balkema Publisher, 31-37.
16. Doebling, S.W., Farrar, C.R., Prime, M.B., and Shevitz, D.W., 1996. Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review. Report LA-13070-MS, Los Alamos National Laboratory, New Mexico.
17. Fussel, D., 2002. Fault diagnosis with tree-structured neurofuzzy systems. Fortschr-Ber, VDI Reihe 8, 957, VDI (Verlag, Dusseldorf).
18. Isermann, R., 2006. Fault-diagnosis systems. An introduction from fault detection to fault tolerance. Berlin/Heidelberg: Springer-Verlag.
19. Jaynes, E.T., 2003. Probability theory: The logic of science. Cambridge: Cambridge University Press.
20. Ko, J.M., Sun, Z.G., and Ni, Y.Q., 2002. Multi-stage identification scheme for detecting damage in cable stayed Kap Shui Mun Bridge. Engineering Structures, 24, 857-868.
21. Ko, J.M. and Ni, Y.Q., 2005. Technology developments in structural health monitoring of large-scale bridges. Engineering Structures, 27, 1715-1725.
22. Li, H. and Ou, J., 2006. The intelligent health monitoring system for Shandong Binzhou Yellow River Highway Bridge. Computer-Aided Civil and Infrastructure Engineering, 21 (4), 612-615.
23. Liu, G.R. and Han, X., 2004. Computational inverse techniques in nondestructive evaluation. Boca Raton, Florida: CRC Press.
24. MacKay, D.J.C., 1995. Bayesian methods for back propagation networks. In: E. Domany, J.L van Hemmen, and K. Schulten, eds. Model of neural networks III. New York: Springer-Verlag, 211-254.
25. 008, Seoul (on CD-ROM).
26. Mufti, A., 2002. (ISIS Canada Corporation 2002). Guidelines for Structural Health Monitoring. Design Manual No. 2. Winnipeg, Manitoba: ISIS Canada.
27. NASA-SEH, 2007. Systems engineering handbook. Report SP 610S. National Aeronautics and Space Administration. Available from: http://education.ksc.nasa.gov/ esmdspacegrant/Documents/NASA%20SP-2007-6105%20Rev%201%20Final%2031Dec2007.pdf (Accessed 24 February 2010).
28. Ni, Y.Q., Wong, B.S., and Ko, J.M., 2002. Constructing input vectors to neural networks for structural damage identification. Smart Materials and Structures, 11, 825-833.
29. Pines, D.J. and Aktan, A.E., 2002. Status of structural health monitoring of long-span bridges in the United States. Progress in Structural Engineering and Materials, 4 (4), 372-380.
30. Sommerville, I., 2000. Critical systems engineering, PPT presentation [online]. Available from: http.sunset.usc.edu/classes/cs377_2008/Week11b.ppt [Accessed July 2009].
31. Sohn, H., Farrar, C.R., Hemez, F.M., Shunk, D.D., Stinemates, D.W., Nadler, B.R., and Czarnecki, J.J., 2004. A review of structural health monitoring literature: 1996-2001. Report LA-13976-MS, Los Alamos National Laboratory, New Mexico.
32. Waszczyszyn, Z., 1999. Neural networks in the analysis and design of structures (CISM Courses and Lectures). Vienna: Springer-Verlag.
33. Wong, K.Y., Lau, C.K., and Flint, A.R., 2000. Planning and Implementation of the structural health monitoring system for cable-supported bridges in Hong Kong. In: Nondestructive Evaluation of Highways, Utilities, and Pipelins IV, A.E. Aktan, and S.R. Gosselin, eds. Proceedings of SPIE, 7-9 March 2000. Newport Beach, USA: Bellingham, Washington, Vol. 3995, 266-275.
34. Xu, H. and Humar, J., 2006. Damage detection in a girder bridge by artificial neural network technique. Computer Aided Civil and Infrastructure Engineering, 21, 450-464.