Bridge management system (BMS) is an effective mean for managing bridges throughout their design life. BMS requires accurate collection of data pertinent to bridge conditions. Non Destructive Evaluation methods (NDE) are automated accurate tools used in BMS to supplement visual inspection. This research provides overview of current practices in bridge inspection and in-depth study of thirteen NDE methods for condition assessment of concrete bridges and eleven for structural steel bridges. The unique characteristics, advantages and limitations of each method are identified along with feedback on their use in practice. Comparative study of current practices in bridge condition rating, with emphasis on the United States and Canada is also performed. The study includes 4 main criteria: inspection levels, inspection principles, inspection frequencies and numerical ratings for 4 provinces and states in North America and 5 countries outside North America. Considerable work has been carried out using a number of sensing technologies for condition assessment of civil infrastructure. Fewer efforts, however, have been directed for integrating the use of these technologies. This research presents a newly developed method for automated condition assessment and rating of concrete bridge decks. The method integrates the use of ground penetrating radar (GPR) and infrared thermography (IR) technologies. It utilizes data fusion at pixel and feature levels to improve the accuracy of detecting defects and, accordingly, that of condition assessment. Dynamic Bayesian Network (DBN) is utilized at the decision level of data fusion to overcome cited limitations of Markov chain type models in predicting bridge conditions based on prior inspection results. Pixel level image fusion is applied to assess the condition of a bridge deck in Montreal, Canada using GPR and IR inspection results. GPR data are displayed as 3D from 24 scans equally spaced by 0.33m to interpret a section of the bridge deck surface. The GPR data is fused with IR images using wavelet transform technique. Four scenarios based on image processing are studied and their application before and after data fusion is assessed in relation to accuracy of the employed fusion process. Analysis of the results showed that bridge condition assessment can be improved with image fusion and, accordingly, support inspectors in interpretation of the results obtained. The results also indicate that predicted bridge deck condition using the developed method is very close to the actual condition assessment and rating reported by independent inspection. The developed method was also applied and validated using three case studies of reinforced concrete bridge decks. Data and measurements of multiple NDE methods are extracted from Iowa, Highway research board project, 2011. The method utilizes data collected from ground penetrating radar (GPR), impact echo (IE), Half-cell potential (HCP) and electrical resistivity (ER). The analysis results of the three cases indicate that each level of data fusion has its unique advantage. The power of pixel level fusion lies in combining the location of bridge deck deterioration in one map as it appears in the fused image. While, feature fusion works in identification of specific types of defects, such as corrosion, delamination and deterioration. The main findings of this research recommend utilization of data fusion within two levels as a new method to facilitate and enhance the capabilities of inspectors in interpretation of the results obtained. To demonstrate the use of the developed method and its model at the decision level of data fusion an additional case study of a bridge deck in New Jersey, USA is selected. Measurements of NDE methods for years 2008 and 2013 for that bridge deck are used as input to the developed method. The developed method is expected to improve current practice in forecasting bridge deck deterioration and in estimating the frequency of inspection. The results generated from the developed method demonstrate its comprehensive and relatively more accurate diagnostics of defects.

These Proceedings, consisting of Parts A and B, contain the edited versions of most of the papers presented at the annual Review of Progress in Quantitative Nondestructive Evaluation held at the University of Washington, Seattle on July 30 to August 4, 1995. The Review was organized by the Center for NDE at Iowa State University, in cooperation with the Ames Laboratory of the USDOE, the American Society of Nondestructive Testing, the Department of Energy, the National Institute of Standards and Technology, the Federal Aviation Administration, the National Science Foundation IndustryiUniversity Cooperative Research Centers, and the Working Group in Quantitative NDE. This year's Review of Progress in QNDE was attended by approximately 450 participants from the US and many foreign countries who presented over 375 papers. The meeting was divided into 36 sessions with as many as four sessions running concurrently. The Review covered all phases of NDE research and development from fundamental investigations to engineering applications or inspection systems, and it included many important methods of inspection science from acoustics to x-rays. In the last several years, the Review has stabilized at about its current size. Most participants seem to agree it is large enough to permit a full-scale overview of the latest developments but still small enough to retain the collegial atmosphere which has marked the Review since its inception. The Proceedings are structured in a format to reflect the organization of the Review itself, producing a more logical organization for both the meeting and the present volume.

Infrastructure deterioration is an international problem requiring significant attention. One particular manifestation of this deterioration is the occurrence of sub-surface cracking (delaminations) in reinforced concrete bridge decks. Of many techniques available for inspection, air-coupled impact-echo testing, or sounding, is a non-destructive evaluation technique to determine the presence and location of delaminations based upon the acoustic response of a bridge deck when struck by an impactor. In this work, two automated air-coupled impact echo sounding devices were designed and constructed. Each device included fast and repeatable impactors, moving platforms for traveling across a bridge deck, microphones for air-coupled sensing, distance measurement instruments for keeping track of impact locations, and signal processing modules. First, a single-channel automated sounding device was constructed, followed by a multi channel system that was designed and built from the findings of the single-channel apparatus. The multi channel device performed a delamination inspection in the same manner as the single-channel device but could complete an inspection of an entire traffic lane in one pass. Each device was tested on at least one concrete bridge deck and the delamination maps produced by the devices were compared with maps generated from a traditional chain-drag sounding inspection. The comparison between the two inspection approaches yielded high correlations for bridge deck delamination percentages. Testing with the two devices was more than seven and thirty times faster, respectively, than typical manual sounding procedures. This work demonstrates a technological advance in which sounding can be performed in a manner that makes complete bridge deck scanning for delaminations rapid, safe, and practical.

This report documents progress made regarding the development and validation of a class of models examining the reliability of nondestructive vibrational inspection tests of single spanned bridges. Two important problems were identified for special consideration. The first concerned the development of a mathematical formulation of the nonlinear boundary conditions needed to accurately model the end support structures of single-span (stringerbased) timber spans. A computational algorithm for the numerical approximations of such systems was derived, implemented and tested with the commonly available Mathematica software package. The second focal problem involved the modeling and analysis of a newly-proposed vibrational testing method. The method seeks to predict bridge strength from vibrational data, and (most importantly) without the need to estimate overall bridge mass. Models developed in this project have provided the first steps towards developing a mathematical understanding of these issues, as well as the creation of a new bridge testing protocol involving the measurement of bridge vibrational responses to forced vibrations both with and without controlled loading. This work has contributed to the development and application of new motion detection sensor technologies addressing the problem of monitoring and estimating bridge integrity.