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Title

A BAYESIAN UPDATING APPROACH IN STRUCTURAL HEALTH MONITORING FOR DAMAGE DETECTION AND ASSESSMENT

Creator

Dirbaz, Mojtaba

Date

2013, 2013-05

Description

The primary goal of Bridge Condition Assessment (BCA) is to determine the condition of a bridge to prevent any catastrophic failure as well as...
Show moreThe primary goal of Bridge Condition Assessment (BCA) is to determine the condition of a bridge to prevent any catastrophic failure as well as to enhance the structure’s safety and serviceability. The structural health and condition of in-service bridges is generally assessed through visual inspections and nondestructive testing and evaluation (NDT/NDE) methods conducted on a pre-set schedule. However, the ratings obtained from current visual inspections on a bridge are subjective, and do not include the uncertainty inherent in the results. Moreover, the condition ratings are often based on independent inspections and do not take into account the dependence of results on previous conditions of a bridge and prior condition ratings compiled for it. Furthermore, there is also a certain level of uncertainty involved in relating subjective ratings to the actual condition of the bridge. This study is aimed at conducting a research on damage detection of existing bridges utilizing available information on their structural conditions. The first part of the research focuses on a new method for assessing the condition of a bridge based on subjective ratings obtained for the bridge. This method will hereafter be referred to as Bayesian Bridge Condition Assessment (BBCA). BBCA consists of three parts: (1) identification of condition states for structural components, (2) determination of a Damage Index (DI), a parameter to describe the extent of damage to a structural component, and (3) determination of an Updated Damage Index (UDI) using Bayesian updating approach. UDI offers an enhanced measure that incorporates not only the relation between subjective rating and the structure’s health condition, but also the significance of new information as it becomes available. The basic assumptions and x general formulations of the Bayesian updating method is presented. Numerical illustrations are provided to demonstrate the applicability of the method to highway bridges. It is shown that the method described in this study is especially applicable to bridges for which visual inspection data are compiled on a periodic basis. One of the methodologies for damage detection and assessment is to use sensor data for identifying the modal characteristics of the structure. The second part of this research focuses on improving upon damage detection methods using sensor and/or modal data. Thus a new method for damage detection and assessment of structures using finite element analysis, and modal data is developed and demonstrated. This method will hereafter be referred to as Bayesian Structural Condition Assessment (BSCA). Using this method, (1) a Finite Element (FE) design model of the structure (undamaged) is constructed; (2) the measured modal data is updated using a Bayesian framework; and (3) the FE model of existing structure (with possibility of damage) is obtained using updated modal data based on an iterative optimization method that is used in estimating the stiffness of the damaged structure. Using these steps, the location and extent of any possible damage is then determined based on the difference between a structural element stiffness for the “as built condition” and “damaged condition.” Several numerical illustrations are presented to demonstrate the capability of the method to detect the location and extent of the damage. This method has been applied to a structural health monitoring benchmark problem; and it has been shown that it can identify the location and extent of damage with more accuracy than most other existing models. Keywords: Bayesian Updating, Condition Assessment of Structures, Modal Data, Visual Inspections, Finite Element Model, Bridges
PH.D in Structural Engineering, May 2013
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