Status of structural health monitoring of long‐span bridges in the United States
Tóm tắt
This paper gives an overview of ongoing research and development in the field of structural health monitoring technologies in the US, with application to long‐span bridges. Specifically, this paper attempts to review various key structural health monitoring technologies, including sensor development, data processing, damage detection algorithms, data analysis and information processing. Several examples are cited from the aerospace, civil and mechanical communities. Monitoring of constructed systems are of considerable interest since the consequences of failure can have a significant effect on the society at large. For instance, consider the 1100 major long‐span bridges in the USA (those with spans of 100 m or longer), many are over 50 years old, and several notable ones are over 100 years old. These bridges fall outside the Standard Specifications issued by AASHTO (1998), and there is little generic experience related to maintaining their performance, especially after they age and/or following any damage. More than 800 of the long‐span bridges in the National Bridge Inventory are classified as fracture‐critical. It follows that structural health monitoring techniques may prove to be useful for maintaining and preserving this population of aging civil infrastructure. It is hoped that the following will stimulate additional discussion regarding the importance of structural health monitoring as an emerging research area for a variety of aerospace, civil and mechanical applications.
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Tài liệu tham khảo
Yao JTP, 1997, Uncertainty Modeling and Analysis in Civil Engineering, 233
AASHTO.Manual for Condition Evaluation of Bridges. Washington DC: American Association of State Highway and Transportation Officials.1998.
FrangopolDM.Bridge Reliability Components and Systems(with Ghosn M) Chapter 4 in Bridge Safety and Reliability ASCE Reston Virginia 1999 83–112.
Aktan AE, 1998, Issues in health monitoring for intelligent infrastructure, SPIE Journal of Smart Materials and Structures, 7, 1
AktanAE. for the ASCE SEI Committee.Performance metrics for constructed systems. Proceedings of the 7th International Symposium on Smart Structures and Materials Newport CA 4–8 March2001.
PharesB.Highlights of study of reliability of visual inspection. Presentation at the Annual Meeting of TRB Subcommittee A2C05(1) Non‐destructive Evaluation of Structures.2001. Report is also available from FHWA Turner Fairbanks Research Center.
DubinEE&YanevBS.Managing the East River bridges in New York City Proceedings of the 7th International Symposium on Smart Structures and Materials Newport CA 4–8 March2001.
LivingstonRA&AmdeAM.Nondestructive test field survey for assessing the extent of Ettringite‐related damage in concrete bridges. Proceedings of the 10th International Symposium on the Nondestructive Characterization of Materials Karuizawa Japan 28 June2000.
TennysonRC MuftiAA&NealeK.Fiber optic sensing for civil infrastructure. Proceedings of the 7th International Symposium on Smart Structures and Materials Newport CA 4–8 March2001.
WangMK LloydG&HovorkaO.Development of a remote coil magnetoelastic stress sensor for steel cables. Proceedings of the 7th International Symposium on Smart Structures and Materials Newport CA 4–8 March2001.
AktanAE CatbasFN PervizpourM KulcuE GrimmelsmanK BarrishR&QinX.Real‐time bridge health‐monitoring for management. Proceedings of the 2nd Workshop on Advanced Technologies in Urban Earthquake Disaster Mitigation Kyoto 9–14 July2000.
DoeblingSW FarrarCR PrimeMB&ShevitzDW.Damage identification and health monitoring of structural and mechanical systems from changes in their characteristics: a literature review. Los Alamos National Laboratory Report LA‐13070‐MS Los Alamos NM June1995.
SunZG KoJM&NiYQ.Modal indices for identifying damage location in cable‐stayed Kap Shui Mun bridge. Proceedings of the 7th International Symposium on Smart Structures and Materials Newport CA 4–8 March2001.
Park G, An integrated health monitoring technique using structural impedance sensors, Journal of Intelligent Material Systems and Structures
LivingstonRA JinS&MarzoughiD.Stochastic modeling of ambient traffic loadings in LS‐DYNA nonlinear FE analysis. Proceedings of the 7th International Symposium on Smart Structures and Materials Newport CA 4–8 March2001.
SoonH FarrarC HunterN&WordenK.Applying the LANL statistical pattern recognition paradigm for structural health monitoring to data from a surface‐effect fast patrol boat. Los Alamos National Laboratory Report LA‐13761‐MS Los Alamos New Mexico 2001.
FengMQ KimDK ShengLH FijiLM&KimYJ.Instrumentation for long‐term performance monitoring. Proceedings of the 7th International Symposium on Smart Structures and Materials Newport CA 4–8 March2001.
MurugeshG.Health monitoring of the new Benicia‐Martinez bridge. Proceedings of the 7th International Symposium on Smart Structures and Materials Newport CA 4–8 March2001.
CatbasFN CilogluSK GrimmelsmanKA&AktanAE.Issues in fleet health monitoring of aged concrete T‐beam bridges in Pennsylvania. Proceedings of the 80th Annual Meeting of the Transportation Research Board Washington DC 7–11 January2001.
KoJM NiYQ SunZG&ChanTHT.Remote visualized health monitoring of cable‐supported bridges. Proceedings of the 7th International Symposium on Smart Structures and Materials Newport CA 4–8 March2001.
NiYQ JiangSF&KoJM.Application of adaptive probabilistic neural network to damage detection of Tsing Ma suspension bridge. Proceedings of the 7th International Symposium on Smart Structures and Materials Newport CA 4–8 March2001.
SumitroS.Current and future trends in long span bridge health monitoring system in Japan. Proceedings of the 7th International Symposium on Smart Structures and Materials Newport CA 4–8 March2001.
PinesD AtkanAE&InmanD.NSF Workshop on Long Span Bridges UC Irivine March2001 page90.