Delaminations in concrete bridge decks are a major cause of bridge maintenance problems. Sonic inspection techniques are currently being used for condition surveys to identify those bridge decks on which expenditures of funds are both necessary and cost effective. While the current sonic methods are reliable, they are too slow for the survey application. A need exists for a rapid, non-destructive method for assessing the general condition of the bridge decks without closing the deck to traffic. The inspection techniques considered for use were infrared thermography, electro-magnetic sounding, nuclear radiation and acoustic techniques. Electromagnetic sounding, by using pulsed radar, has the best potential for use in the development of a rapid survey system.

Reinforced concrete bridge decks are high performance structural elements that must survive decades of harsh mechanical and environmental loads. The structural health monitoring of bridges is a primary enabler of safe and cost-effective performance, relying on frequent inspections and repairs as needed. The undersides of concrete bridge decks are oft-overlooked areas of inspection, owing to a hard to reach and difficult location to access. Exacerbating factors to the degradation of concrete bridge decks are the freeze-thaw cycle and salt water related corrosion common in the world's Northern climates. As concrete weathers, it decays. Corrosion induced cracking and delamination are primary damage modes.Moreover, budgets are forced to contend with the seasonal roadway damage from frost-heaves and snowplows, which can lead to delays in the inspection and repair of the undersides of bridge decks. Years of neglect have led to a growing need for assessment and repair. Despite this need, the inspection of the undersides of bridge decks is laborious and costly, requiring the shutdown of roadways, the use of specialized equipment, and an above-average operator risk. Ironically, while the cost of early detection of subsurface cracks is prohibitive, the cost of repair rises when early detection is not feasible. The key is knowing where the defects are, and how extensive the damage. In recent decades, numerous methodologies for concrete crack and delamination detection have become commercially available, however the undersides of bridge decks continue to pose a challenge. Often, detection is not financially feasible until cracks have reached the surface, or concrete has fallen off the structure. Reports of vehicles struck by falling concrete are not uncommon, demonstrating the need for an affordable robust early detection methodology for failing concrete. In this thesis, a technology down-select is performed to determine the optimal solution to detecting subsurface delaminations in the underside of concrete bridge decks. The solution alighted upon is an active acoustic sensor (AAS) mounted on an unmanned arial vehicle (UAV) platform to tap and listen to the underside of bridge decks. A mechanical tapping mechanism is developed to acquire the tap data remotely using a high frequency acoustic sensor. Embedded void concrete samples of 12" and 24" form factors are used as test beds in laboratory conditions. Subsequent post-processing using the Fast Fourier Transform (FFT) and the Welch Power Spectral Density (PSD) and Hilbert-Huang Transform (HHT) are used to differentiate a solid slab from one with a void. This research has shown the methodology to be feasible, and has laid the groundwork for additional effort to refine the design and bring it to a readiness level robust enough for in-situ testing in the field.

Delamination detection in concrete bridge decks is a critical process to the maintenance and upkeep of concrete bridges. Excessive delamination can lead to spalling, damages to properties or human life, and possible failure in extreme cases. Therefore, intense work has been directed toward developing accurate and efficient detection methods. The methods adopted were mainly within the non-destructive evaluation realm of detection to avoid damages to the structure and the financial losses associated. The methods range from traditional techniques such as hammer-sounding, and chain dragging to more effective methods such as impact echo, groundpenetrating radar, ultrasonic test, and infrared thermography. This research focused on the application of infrared thermography as a non-destructive evaluation method through the utilization of an unmanned aerial vehicle-mounted consumer-grade thermal camera. The purpose main purpose was to investigate the accuracy of detection using a consumer-grade thermal camera vs. research-grade thermal camera. Another goal was to provide an efficient and cost-effective data collection method for concrete bridge delamination detection that does not require traffic obstruction such as other NDE methods, and provides more accurate results compared currently deployed methods such as hammer-sounding. Concrete delamination detection using (UAV)-mounted infrared cameras has proved effective in recent research. However, most successful implementations used expensive research-grade infrared cameras. Despite research-grade thermal camera having high resolution and providing accurate results, they are heavy, expensive, need onboard computers, customized drones, and require-proprietary software to operate. This makes the process challenging to implement in state Department of Transportations (DOTs) due to the lack of specialty professionals. Many state DOTs started deploying lightweight consumer-grade infrared cameras UAVs for delamination detection. However, few studies have quantitatively evaluated the accuracy of the lower-resolution uncooled consumer-grade infrared camera for delamination detection. To fill this gap, this study intends to investigate if a consumer-grade infrared camera can maintain an acceptable level of delamination detection, allowing for infrared thermography to be a more accessible and affordable detection method. The advantage of utilizing a consumer-grade camera is that they are less expensive, and lighter thus allowing them to be carried by smaller drones. This study explores the application of infrared thermography (IRT) and a consumer-grade thermal camera mounted on an unmanned aerial vehicle (UAV) for delamination detection while employing the level-set method for image analysis. Data was collected for a slab with mimicked delamination and two in-service bridge decks. For the case of the slab, maximum detectability of 70 - 72% was achieved. A transient numerical simulation was also conducted to provide a supplemental and noise-free dataset to explore detectability accuracy peaks throughout the day. The results of the in-service bridge decks indicated that the consumer-grade infrared camera provided adequate detection of the locations of suspected delamination. Results of both the slab and in-service bridge decks were comparable to those of a research-grade infrared camera.

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.

" TRB's second Strategic Highway Research Program (SHRP 2) Report S2-R06A-RR-1: Nondestructive Testing to Identify Concrete Bridge Deck Deterioration identifies nondestructive testing technologies for detecting and characterizing common forms of deterioration in concrete bridge decks.The report also documents the validation of promising technologies, and grades and ranks the technologies based on results of the validations.The main product of this project will be an electronic repository for practitioners, known as the NDToolbox, which will provide information regarding recommended technologies for the detection of a particular deterioration. " -- publisher's description.

Bridge decks deteriorate over time as a result of deicing salts, freezing-and-thawing, and heavy use, resulting in internal defects. According to a 2006 study by the American Society of Civil Engineers, 29% of bridges in the United States are considered structurally deficient or functionally obsolete. Ground penetrating radar (GPR) is a promising non-destructive evaluation technique for assessing subsurface conditions of bridge decks. However, the analysis of GPR scans is typically done manually, where the accuracy of the detection process depends on the technician's trained eye. In this work, a framework is developed to automate the detection, locailzation, and characterization of subsurface defects inside bridge decks. This framework is composed of a fractal-based feature extraction algorithm to detect defective regions, a deconvolution algorithm using banded-ICA to reduce overlapping between reflections and to estimate the depth of defects, and a classification algorithm using principal component analysis to identify main features in defective regions. This framework is implemented and simulated using MATLAB and GPR real scans of simulated concrete bridge decks. This framework, as demonstrated by the experimental results, has the following contributions to the current body of knowledge in ground penetrating radar detection and analysis techniques, and in concrete bridge deck condition assessment: 1) developed a framework that integrated detection, localization, and classificationof subsurface defects inside concrete bridge decks, 2) presented a comparison between the most common fractal methods to determine the most suitable one for bridge deck condition assessment, 3) introduced a fractal-based feature extraction algorithm that is capable of detecting and horizontally labeling defective regions using only the underlying GPR B-scan without the need for a training dataset, 4) developed a deconvolution algorithm using EFICA to detect embedded defects in bridge decks, 5) introduced an automated identification methodology of defective regions which can be integrated into a CAD system that allows for better visual assessment by the maintenance engineer and has the potential to eliminate human interpretation errors and reduce condition assessment time and cost, and 6) presented an investigation and a successful attempt to classify some of the common defects in bridge decks.