A Bayesian updating approach in structural health monitoring for damage detection and assessment

The 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.;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 is constructed; (2) the measured modal data is updated using a Bayesian framework; and (3) the FE model of existing structure is obtained using updated modal data based on an iterative optimization method. 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." 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.;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 general formulations of the Bayesian updating method is presented.