Implementation of a Probabilistic Structural Health Monitoring Method on a Highway Bridge
Author(s): |
Adam Scianna
Zhaoshuo Jiang Richard Christenson John DeWolf |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Advances in Civil Engineering, 2012, v. 2012 |
Page(s): | 1-9 |
DOI: | 10.1155/2012/307515 |
Abstract: |
This paper describes the application of a probabilistic structural health monitoring (SHM) method to detect global damage in a highway bridge in Connecticut. The proposed method accounts for the variability associated with environmental and operational conditions. The bridge is a curved three-span steel dual-box girder bridge located in Hartford, Connecticut. The bridge, monitored since Fall 2001, experienced a period of settling in the Winter of 2002-2003. While this change was not associated with structural damage, it was observed in a permanent rotation of the bridge superstructure. Three damage measures are identified in this study: the value of fundamental natural frequency determined from peak picking of autospectral density functions of the bridge acceleration measurements; the magnitude of the peak acceleration measured during a truck crossing; the magnitude of the tilt measured at 10-minute intervals. These damage measures, including thermal effects, are shown to be random variables and associatedPvalues are calculated to determine if the current probability distributions are the same as the distributions of the baseline bridge data from 2001. Historical data measured during the settling of the bridge is used to verify the performance of the bridge, and the field implementation of the proposed method is described. |
Copyright: | © 2012 Adam Scianna et al. |
License: | This creative work has been published under the Creative Commons Attribution 3.0 Unported (CC-BY 3.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
2.5 MB
- About this
data sheet - Reference-ID
10176954 - Published on:
07/12/2018 - Last updated on:
02/06/2021