Intelligent Health Monitoring System for a Railway Cable-Stayed Bridge

De Shan Shan; Peng Yan; Zhen Hua Wang

doi:10.4028/www.scientific.net/AMR.148-149.1390

Paper Titles

Preparation and Properties of a Novel Azobenzene-Based Polyacrylamide Hydrogels with Photoresponse
p.1369

Preparation and Influence Factors of SO₄^2-/ZrO₂ Nanotube Catalyst
p.1375

Size Controllable Synthesis of Magnetite Fe₃O₄ Nanoparticles
p.1379

Microstructure and Dielectric Properties of Ni²⁺-Doped (Ba,Sr)TiO³ Ceramics
p.1383

Intelligent Health Monitoring System for a Railway Cable-Stayed Bridge
p.1390

Synthesis, Characterization and Properties of Poly (ε-Caprolactone) Glycol Based Casting Polyurethane Elastomers Containing Nano-Size Sio₂ Particles
p.1394

The Synthesis of Multi-Morphologic Nickel Sulfides Nanostructures by a Solution Chemical Route
p.1400

A Low Temperature Precursor Sulfuration Route to Metal Sulfides Nanomaterials
p.1404

Preparation and Properties of Electrospun Cellulose Acetate Nanofiber Mats
p.1408

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 148-149Intelligent Health Monitoring System for a Railway...

Intelligent Health Monitoring System for a Railway Cable-Stayed Bridge

Abstract:

Intelligent health monitoring system of the long-span railway cable-stayed bridge requires the comprehensive knowledge of instrumentation, analytical and information processing technologies with the knowledge and experiences in design, construction, operation and maintenance of railway cable-stayed bridge for long-term monitoring the performance throughout its lifecycle. It is necessary to perform sensor-based structural monitoring for identifying the bridge conditions in order to assure the structural safety and to evaluate the operational performance. The considerations for deploying a proper monitoring system are appropriate sensor instrumentation, robust signal acquisition, reliable signal processing, and intelligent signal and information processing. The experience on developing an autonomous monitoring system in the one certain railway cable-stayed bridge newly constructed is introduced in this paper. Sensor and hardware instrumentation, signal transmission, signal acquisition and analysis are schematically described mainly. Experience through this work will be worthwhile lessons for other similar efforts.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 148-149)

Pages:

1390-1393

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.148-149.1390

Citation:

Cite this paper

Online since:

October 2010

Authors:

De Shan Shan, Peng Yan, Zhen Hua Wang

Keywords:

Cable-Stayed Bridge, Instrumentation, Measurement System, Railway, Structural Health Monitoring System

Export:

RIS, BibTeX

Price:

Permissions:

Request Permissions

References

[1] Sreenivas Alampalli, Mohammed Ettouney. Structural Health Monitoring as a Bridge Management Tool [J]. STRUCTURES (2006).

DOI: 10.1061/40889(201)131

Google Scholar

[2] Deshan Shan, Qiao li, Chunyu Fu and Peng Yan, Smart Bridge Health Monitoring and Damage Diagnosis, Beijing: China Communication Press, (2010).

Google Scholar

[3] Saeed V. Vaseghi. Advanced Digital Signal Processing and Noise Reduction [M]. Second Edition. John Wiley & Sons Ltd, (2000).

Google Scholar

[4] Kai-Yuen Wong. Instrumentation and health monitoring of cable-supported bridges [J]. Structural Control Health Monitoring. 2004, 11: 91~124.

DOI: 10.1002/stc.33

Google Scholar

[5] Tao Hongyan, Yu Chengbo. Sensor and modern detection technology [M]. Beijing: Tsinghua University Press, 2009, 8-15.

Google Scholar

[6] A. Emin Aktan, F. Necati Catbas, Kirk A. Grimmelsman, etc. Development of a Model Health Monitoring Guide for Major Bridges[R]. Report Submitted to: Federal Highway Administration Research and Development For: CONTRACT/ORDER NO. DTFH61-01-P-00347. September (2002).

Google Scholar

[7] Southwest Jiaotong University. Design of Bridge Health Monitoring System for Long Span Cable-stayed Bridge [R]. Chengdu: Southwest Jiaotong University, (2010).

DOI: 10.25103/jestr.074.16

Google Scholar

[8] Vladimir N. Vapnik, Statistical Learning Theory, New York: John Wiley & Sons, Inc., (1998).

Google Scholar

[9] Brent M. Phares, Terry J. Wipf, Lowell F. Greimann etc. Health Monitoring of Bridge Structures and Components Using Smart-Structure Technology: Volume I [R]. Center for Transportation Research and Education, Iowa State University, January (2005).

Google Scholar