ISSN:
1013-9826
Source:
Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
This paper presents a damage detection procedure based on Bayesian analysis of datarecorded by permanent monitoring systems as applied to condition assessment of Precast ReinforcedConcrete (PRC) bridges. The concept is to assume a set of possible condition states of the structure,including an intact condition and various combinations of damage, such as failure of strands, coverspalling and cracking. Based on these states, a set of potential time response scenarios is evaluatedfirst, each described by a vector of random parameters and by a theoretical model. Given the priordistribution of this vector, the method assigns posterior probability to each scenario as well as updatedprobability distributions to each parameter. The effectiveness of this method is illustrated as appliedto a short span PRC bridge, which is currently in the design phase and will be instrumented with anumber of fiber-optic long gauge-length strain sensors. A Finite Element Model is used to simulatethe instantaneous and time-dependent behavior of the structure, while Monte Carlo simulations areperformed to numerically evaluate the evidence functions necessary for implementation of themethod. The ability of the method to recognize damage is discussed
Type of Medium:
Electronic Resource
URL:
http://www.tib-hannover.de/fulltexts/2011/0528/01/54/transtech_doi~10.4028%252Fwww.scientific.net%252FKEM.347.227.pdf
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