Modal parameters identification of heavy-haul railway RC bridges: Experience acquired

Sampaio, Regina & Chan, Tommy H.T. (2015) Modal parameters identification of heavy-haul railway RC bridges: Experience acquired. Structural Monitoring and Maintenance, 2(1), pp. 1-18.

View at publisher (open access)


Traditionally, it is not easy to carry out tests to identify modal parameters from existing railway bridges because of the testing conditions and complicated nature of civil structures. A six year (2007-2012) research program was conducted to monitor a group of 25 railway bridges. One of the tasks was to devise guidelines for identifying their modal parameters. This paper presents the experience acquired from such identification. The modal analysis of four representative bridges of this group is reported, which include B5, B15, B20 and B58A, crossing the Carajás railway in northern Brazil using three different excitations sources: drop weight, free vibration after train passage, and ambient conditions. To extract the dynamic parameters from the recorded data, Stochastic Subspace Identification and Frequency Domain Decomposition methods were used. Finite-element models were constructed to facilitate the dynamic measurements. The results show good agreement between the measured and computed natural frequencies and mode shapes. The findings provide some guidelines on methods of excitation, record length of time, methods of modal analysis including the use of projected channel and harmonic detection, helping researchers and maintenance teams obtain good dynamic characteristics from measurement data.

Impact and interest:

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 84812
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Railway Bridges, operational modal analysis, stochastic subspace identification, frequency domain decomposition
DOI: 10.12989/smm.2015.2.1.001
ISSN: 2288-6613
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500) > Structural Engineering (090506)
Divisions: Current > Schools > School of Civil Engineering & Built Environment
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 Techno-Press, Ltd
Deposited On: 16 Jun 2015 22:26
Last Modified: 17 Jun 2015 22:22

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page