A Neural Network-Based System for Bridge Health Monitoring

Tzu Kang Lin; Ming Chih Huang; Jer Fu Wang

doi:10.4028/www.scientific.net/AMR.452-453.557

Paper Titles

Seepage through Earth Dams with Chimney Drain on Pervious Foundation
p.538

Levels of Difficulty for Sustainable Roadway Design
p.543

CAT III Autoland Control Laws Design Based on Multi-Objective Optimization
p.548

The SWOT Analysis and Countermeasures Research on the Acquisition of Volvo by Geely
p.553

A Neural Network-Based System for Bridge Health Monitoring
p.557

The Effect of Campus Culture on the Cultivation of Ethnic High Quality Talent
p.564

Study of Enterprise Strategic Combination in Jinan-Dezhou Regional Based on Supply Chain Partnership
p.568

Discussion on the Issues Related to the Evaluation of Corporate Social Responsibility
p.573

Research on the Choice of the Third-Party Reverse Logistics Enterprise Based on the Method of AHP and Goal Programming
p.581

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 452-453A Neural Network-Based System for Bridge Health...

A Neural Network-Based System for Bridge Health Monitoring

Abstract:

A bridge health monitoring system based on neural network technology is proposed in this paper. Two major ground excitations recorded in Taiwan were used to establish the NARX-based system. Analytical results from different methods including transfer function, ARX-based model, and the proposed neural network-based system were used to evaluate the efficiency in health monitoring. The result shows that the proposed system can be used successfully with superior advantages after major earthquakes for bridge health monitoring.

You might also be interested in these eBooks

Management, Manufacturing and Materials Engineering

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 452-453)

Pages:

557-563

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.452-453.557

Citation:

Cite this paper

Online since:

January 2012

Authors:

Tzu Kang Lin, Ming Chih Huang, Jer Fu Wang

Keywords:

Bridge Health Monitoring, Nonlinear Characteristic, System Identification

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] H. Adeli and S.L. Hung: Neural networks, Genetic Algorithms, and Fuzzy Systems. Machine Learning (1995).

Google Scholar

[2] S.F. Masri, A.G. Chassiakos and T.K. Caughey: Identification of Nonlinear Dynamic Systems using Neural Networks, Journal of Applied Mechanics, Vol.60, pp.123-133, (1993).

DOI: 10.1115/1.2900734

Google Scholar

[3] K. Worden, G. Manson, G.R. Tomlinson: A Harmonic Probing Algorithm for the Multi-input Volterra Series, Journal of Sound and Vibration, Vol.201(1), pp.67-84, (1997).

DOI: 10.1006/jsvi.1996.0746

Google Scholar

[4] J.E. Chance, J. Worden, G.R. Tomlinson: Frequency Domain Analysis of NARX Neural Networks, Journal of Sound and Vibration, Vol.213(5), pp.915-941, (1998).

DOI: 10.1006/jsvi.1998.1539

Google Scholar

[5] S.A. Billings and K.M. Tsang: Special Analysis for Nonlinear Systems, part III: Case Study Examples, Mechanical Systems and Signal Processing, Vol.4(1), pp.3-21, (1990).

DOI: 10.1016/0888-3270(90)90037-l

Google Scholar