In-Service Diagnostics of a Highway Bridge from a Progressive Damage Case Study
Publication: Journal of Bridge Engineering
Volume 15, Issue 5
Abstract
Development of diagnostic and prognostic routines for application to in-service measurements from highway bridges necessitates analysis of experimental measurements from in-service highway bridges under natural or prescribed induced damage. This is generally limited to the unique opportunity of investigating end-of-service life bridges prior to reconstruction and consequently only a limited library of such case studies exist. This paper documents a field test of an end-of-service bridge span with prescribed progressive damage to a bearing as well as several diaphragm connections. Thirty dual-axis accelerometers were distributed across the bridge span with data acquisition and transmission facilitated by a real-time lossless wireless sensor network. A highway department service truck applied traffic excitation to the structure through routine passes on a consistent lane of traffic. Output-only system identification was applied to the baseline time history response to develop a state-space model of the bridge dynamics used for forward prediction in the form of a Kalman filter. Simple statistical evaluation of the prediction error in the model demonstrates the variance can be used to localize and generally quantify the degree of damage in the structure. The case study additionally illustrates the potential importance of monitoring lateral acceleration along the girders to permit identification of damage to elements, such as the diaphragms, that contributing primarily to the lateral and torsional response of primary structural members.
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Acknowledgments
The writers would like to acknowledge the New York State Department of Transportation and, in particular, the Region 7 engineers and bridge maintenance crew for facilitating and assisting with the field testing. Additionally, the writers also wish to thank graduate students, Michael Gangone, Wei Chen and Jessica Rocheleau, and undergraduate students, Francis Dayamba and Sarah Marin, for their on-site assistance during the sensor installation.
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Information & Authors
Information
Published In
Journal of Bridge Engineering
Volume 15 • Issue 5 • September 2010
Pages: 597 - 607
Copyright
© 2010 ASCE.
History
Received: Feb 12, 2009
Accepted: Nov 16, 2009
Published online: Nov 21, 2009
Published in print: Sep 2010
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