A Dynamic Bayesian Network Model for Structural Time-Dependent Reliability Analysis of Resistance Deterioration

SUN Hong-bin; WU Zi-yan; LIU Shu-kui

doi:10.3879/j.issn.1000-0887.2014.01.011

Volume 35 Issue 1

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SUN Hong-bin, WU Zi-yan, LIU Shu-kui. A Dynamic Bayesian Network Model for Structural Time-Dependent Reliability Analysis of Resistance Deterioration[J]. Applied Mathematics and Mechanics, 2014, 35(1): 102-110. doi: 10.3879/j.issn.1000-0887.2014.01.011

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A Dynamic Bayesian Network Model for Structural Time-Dependent Reliability Analysis of Resistance Deterioration

doi: 10.3879/j.issn.1000-0887.2014.01.011

School of Mechanics, Civil Engineering and Architecture, Northwestern Polytechnical University, Xi’an 710129, P.R.China

Funds: The National Natural Science Foundation of China（51278420）

Received Date: 2013-06-25
Rev Recd Date: 2013-11-01
Publish Date: 2014-01-15

Abstract

Abstract

A dynamic Bayesian network (DBN) model was proposed for timedependent reliability analysis of structures in deterioration. The structural resistance deterioration was modeled as a gamma process while the loads as random variables. The stochastic deterioration process was discretized in time domain as deterioration models. A DBN was established and comprised of the reliability model, deterioration model and observation model. Node elimination algorithm and discretization were applied to modify the DBN into a network with only discrete variables. Exact inferences with the DBN were presented to estimate the 3 structural states at present (filtering), in the future (prediction) and in the past (smoothing), respectively. The structural timedependent reliability was updated with the reestimated deterioration model when measurements were available. The proposed model was validated through the timedependent reliability analysis of a onebay example frame in resistance deterioration.
- time-dependent reliability,
- dynamic Bayesian network,
- resistance deterioration,
- exact inference,
- updating

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References(13)

References

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