Application of time series analysis for bridge health monitoring
Omenzetter, P; Brownjohn, James
Date: 9 January 2006
Article
Journal
Smart Materials and Structures
Publisher
IOP Publishing:
Publisher DOI
Abstract
Despite the recent considerable advances in structural health monitoring (SHM) of civil
infrastructure, converting large amount of data from SHM systems into usable information
and knowledge remains a great challenge. This paper addresses the problem through analysis
of time histories of static strain data recorded by an SHM system ...
Despite the recent considerable advances in structural health monitoring (SHM) of civil
infrastructure, converting large amount of data from SHM systems into usable information
and knowledge remains a great challenge. This paper addresses the problem through analysis
of time histories of static strain data recorded by an SHM system installed in a major bridge
structure and operating continuously for a long time. The reported study formulates a vector
seasonal autoregressive integrated moving average (ARIMA) model for the recorded strain
signals. The coefficients of the ARIMA model are allowed to vary with time and are
identified using an adaptive Kalman filter. The proposed method has been used for analysis of
the signals recorded during construction and service life of the bridge. By observing various
changes in the ARIMA model coefficients, unusual events as well as structural change or
damage sustained by the structure can be revealed.
Engineering
Faculty of Environment, Science and Economy
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