D. G. Manning

Bio: D. G. Manning is an academic researcher. The author has contributed to research in topics: Radar engineering details & Radar. The author has an hindex of 1, co-authored 1 publications receiving 29 citations.

An automated signal processing system for the signature analysis of radar waveforms from bridge decks

Abstract: This paper describes the results of a project which employed impulse radar to detect faults existing beneath the surface of an asphalt-covered bridge deck at Papineau Creek, Ontario. A simple but enlightening mathematical analysis is provided which accurately predicts the waveforms actually observed. The methodology clearly demonstrates the usefulness of impulse radar as a diagnostic tool in remote sensing. Amongst the problems discussed and solved are: the identification of faults due to debonding, scaling, and delamination; the measurement of asphalt thickness at selected locations on the bridge deck and hence the determination of average thickness over the entire bridge deck; and the automated processing of the data using a computer. A comparison of the radar detected faults with those detected using conventional methods is provided. A set of parameters has been developed which permits data to be reduced to a simple set of measurements that can be plotted for visual inspection.

Principles of Thermography and Radar for Bridge Deck Assessment

Abstract: Traditional methods of bridge deck condition assessment are slow, labor‐intensive, intrusive to traffic, and unreliable. Two new technologies, radar and infrared thermography, which have recently been introduced, show promise for producing rapid and accurate condition assessment for bridge decks. These technologies are being applied without the benefit of a firm physical understanding of their inherent capabilities and limitations. This paper discusses the physical principles upon which these techniques are based, and proposes simple physical models for the prediction of radar and infrared response to various bridge deck conditions. Parameter studies are carried out using these models to predict the radar and infrared response to moisture, chloride, delamination, and deck geometry. The model study results show the range of sensitivity and the inherent limitations of these two techniques. These results have led to the suggestion of a predictive technique that has been used in field studies of repaired and ...

Automated GPR Rebar Analysis for Robotic Bridge Deck Evaluation

Abstract: Ground penetrating radar (GPR) is used to evaluate deterioration of reinforced concrete bridge decks based on measuring signal attenuation from embedded rebar. The existing methods for obtaining deterioration maps from GPR data often require manual interaction and offsite processing. In this paper, a novel algorithm is presented for automated rebar detection and analysis. We test the process with comprehensive measurements obtained using a novel state-of-the-art robotic bridge inspection system equipped with GPR sensors. The algorithm achieves robust performance by integrating machine learning classification using image-based gradient features and robust curve fitting of the rebar hyperbolic signature. The approach avoids edge detection, thresholding, and template matching that require manual tuning and are known to perform poorly in the presence of noise and outliers. The detected hyperbolic signatures of rebars within the bridge deck are used to generate deterioration maps of the bridge deck. The results of the rebar region detector are compared quantitatively with several methods of image-based classification and a significant performance advantage is demonstrated. High rates of accuracy are reported on real data that includes thousands of individual hyperbolic rebar signatures from three real bridge decks.