Download or read book An Evaluation of Surface Defect Detection in Reinforced Concrete Bridge Decks Using Terrestrial LiDAR written by Ryan C. Hoensheid and published by . This book was released on 2012 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Automated Bridge Inspection for Concrete Surface Defect Detection Using Deep Neural Network Based on LiDAR Scanning written by Majid Nasrollahi and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural inspection and maintenance of bridges are essential to improve the safety and sustainability of the infrastructure systems. Visual inspection using non-equipped eyes is the principal method of detecting surface defects of bridges, which is time-consuming, unsafe, and encounters inspectors falling risks. Therefore, there is a need for automated bridge inspection. Recently, Light Detection and Ranging (LiDAR) scanners are used for detecting surface defects. LiDAR scanners can collect high-quality 3D point cloud datasets. In order to automate the process of structural inspection, it is important to collect proper datasets and use an efficient approach to analyze them and find the defects. Deep Neural Networks (DNNs) have been recently used for detecting 3D objects within 3D point clouds. PointNet and PointNet++ are deep neural networks for classification, part segmentation, and semantic segmentation of point clouds that are modified and adapted in this work to detect surface concrete defects. The research contributions are: (1) Designing a LiDAR-equipped UAV platform for structural inspection using an affordable 2D scanner for data collection, and (2) Proposing a method for detecting concrete surface defects using deep neural networks based on LiDAR generated point clouds. Training and testing datasets are collected from four concrete bridges in Montréal and annotated manually. The point cloud dataset prepared in five areas, which contain more than 51 million points and 2,572 annotated defects in four classes of crack, light spalling, medium spalling, and severe spalling. The accuracies of 75% (adapted PointNet) and 79% (adapted PointNet++) in detecting defects are achieved in binary semantic segmentation.

Download or read book Nondestructive Testing to Identify Concrete Bridge Deck Deterioration written by and published by Transportation Research Board. This book was released on 2013 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: " 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.

Download or read book Surface Defect Detection Segmentation and Quantification for Concrete Bridge Assessment Using Deep Learning and 3D Reconstruction written by Chaobo Zhang and published by . This book was released on 2020 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book An Automated Framework for Defect Detection in Concrete Bridge Decks Using Fractals and Independent Component Analysis written by Fadi Abu-Amara and published by . This book was released on 2010 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Computer Vision for Automated Surface Evaluation of Concrete Bridge Decks written by Prateek Prasanna and published by . This book was released on 2013 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: Structural health monitoring of concrete bridges requires accurate and efficient surface crack detection. Early detection of cracks helps prevent further damage. Safety inspection tests are conducted at regular intervals to assess deterioration. Traditional methods involve detection of cracks by human visual inspection. These methods are costly, inefficient and labor intensive, especially for long-span bridges. This thesis presents the use of computer vision and pattern recognition techniques in assessment of cracks on a concrete bridge surface. Bridge deck images are first collected using high-resolution cameras mounted on a robot. Statistical inference algorithms are then implemented to build an automated crack detection system. The proposed machine learning method reduces manual effort and enables automatic labeling over large bridge deck areas to quantify size and location for future reference or comparisons. A panoramic camera is used for the purpose of context localization. Additionally, we demonstrate image-stitching to obtain a coherent spatial mosaic of the bridge deck.

Download or read book Integrated NDE Methods Using Data Fusion For Bridge Condition Assessment written by Marwa Hussein Ahmed and published by . This book was released on 2018 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Nondestructive Evaluation of Concrete Bridge Decks with Overlays written by Shibin Lin and published by . This book was released on 2021 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concrete bridge deck overlays have been used in the United States since 1960 to extend the service life of deteriorated concrete bridge decks and improve reliability. Concrete bridge decks with overlays suffer various types of deterioration, so it is necessary to identify and assess the effectiveness of different nondestructive evaluation (NDE) technologies in the laboratory under controlled conditions and in the field under actual conditions. This report provides an overview of seven types of widely used overlays: asphalt with a liquid membrane, asphalt with a fabric membrane, asphalt without a membrane, silica fume-modified concrete, latex-modified concrete (LMC), epoxy polymer concrete, and polyester polymer concrete. This report identifies and ranks available and promising NDE technologies to assess the performance of different types of overlays and concrete bridge decks. This report describes laboratory validation on overlays for nine commonly used NDE technologies. The nine NDE technologies are: sounding, ultrasonic surface waves (USW), impact echo (IE), ultrasonic tomography (UT), impulse response (IR), ground-penetrating radar (GPR), electrical resistivity (ER), half-cell potential (HCP), and infrared thermography (IRT). This report details the results of laboratory tests validating the NDE technologies for the seven different types of overlays. Field validation using the RABITTM bridge deck assessment tool and manual testing equipment was also performed. Results from the study on which this report is based indicated that GPR was the most effective method for detecting defects in underlying concrete specimens through both bonded and debonded overlays; however, GPR could not detect overlay debonding. Results also showed that USW, IE, and UT were effective stress-wave-based methods for detecting defects under bonded overlays but not asphalt overlays. Researchers found that asphalt overlays at low temperatures (i.e., 32°F or below) improved the applicability of

Download or read book Terrestrial Laser Scanning Based Bridge Structural Condition Assessment written by Yelda Turkan and published by . This book was released on 2016 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: Objective, accurate, and fast assessment of a bridge's structural condition is critical to the timely assessment of safety risks. Current practices for bridge condition assessment rely on visual observations and manual interpretation of reports and sketches prepared by inspectors in the field. Visual observation, manual reporting, and interpretation have several drawbacks, such as being labor intensive, subject to personal judgment and experience, and prone to error. Terrestrial laser scanners (TLS) are promising sensors for automatically identifying structural condition indicators, such as cracks, displacements, and deflected shapes, because they are able to provide high coverage and accuracy at long ranges. However, limited research has been conducted on employing laser scanners to detect cracks for bridge condition assessment, and the research has mainly focused on manual detection and measurement of cracks, displacements, or shape deflections from the laser scan point clouds. This research project proposed to measure the performance of TLS for the automatic detection of cracks for bridge structural condition assessment. Laser scanning is an advanced imaging technology that is used to rapidly measure the three-dimensional (3D) coordinates of densely scanned points within a scene. The data gathered by a laser scanner are provided in the form of point clouds, with color and intensity data often associated with each point within the cloud. Point cloud data can be analyzed using computer vision algorithms to detect cracks for the condition assessment of reinforced concrete structures. In this research project, adaptive wavelet neural network (WNN) algorithms for detecting cracks from laser scan point clouds were developed based on the state-of-the-art condition assessment codes and standards. Using the proposed method for crack detection would enable automatic and remote assessment of a bridge's condition. This would, in turn, result in reducing the costs associated with infrastructure management and improving the overall quality of our infrastructure by enhancing maintenance operations.

Download or read book Detection of Sub surface Anomalies in Concrete Bridge Decks Using Ground Penetrating Radar written by Vasudev A. Bhandarkar and published by . This book was released on 1993 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A New Approach for Performance Evaluation of Bridge Infrastructure Using Terrestrial LiDAR and Advanced Mathematical Modeling written by Ali Shafikhani and published by . This book was released on 2020 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: High plastic expansive clays when subjected to different climatic conditions undergo large ground movements causing distress to infrastructures including bridges, pavements,buildings, retaining structures, and others. Performance assessment of these structures built on problematic soils such as expansive clays is important to reduce maintenance and extending the design life of infrastructure. Rapid developments in remote sensing technologies with precise evaluation have influenced the monitoring techniques for assessing the health condition of civil infrastructure projects. While these technologies have considerably aided in performance evaluation, cogent procedures for evaluating the ground movements are still required that integrates technologies, climatic factors, soil behavior models. This research study presents an integrated approach using the Three-Dimensional Terrestrial Laser Scanning (3D-TLS)technique and advanced mathematical modeling (system identification approach) for assessing the performance of the bridge infrastructure including highway embankment, bridge deck,bridge approach slab, bridge abutments, and columns. First, an optimized framework is developed to evaluate ground movements using 3D-TLS technique, which is an active-remote sensing Light Detection and Ranging (LiDAR) remote sensing technology that uses near infrared light to monitor physical characteristics of earth's surface. The ground movements from the processed scans, and climatic factor parameters including temperature and precipitation variations were used to develop advanced mathematical models of dynamic systems using collected time-series data. The validation of the developed integrated framework is illustrated on a test site built on high plastic expansive clay soils located in North Texas. Cost-Benefit Analysis (COA) is performed to compare 3D-TLS remote sensing and prevalent monitoring approaches. This research highlights the integration of latest technological developments with advanced mathematical models to predict the condition of a bridge infrastructure.

Download or read book Evaluation of Reinforced Concrete Bridge Decks written by James G. Buckler and published by . This book was released on 2000 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bridge Deck Condition Assessment Using Destructive and Nondestructive Methods written by Brandon Tyler Goodwin and published by . This book was released on 2014 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This study investigates two bridge decks in the state of Missouri using both nondestructive and destructive testing methods. The Missouri Department of Transportation (MoDOT) is responsible for the monitoring and maintenance of over 10,000 bridges. Currently monitoring of these bridges includes a comprehensive visual inspection. In this study, ground-coupled ground penetrating radar (GPR) is used to estimate deterioration, along with other traditional methods, including visual inspection, and core evaluation. Extracted core samples were carefully examined, and the volume of permeable pore space was determined for each core. After the initial investigation, the two bridges underwent rehabilitation using hydrodemolition as a method to remove loose or deteriorated concrete. Depths and locations of material removal were determined using light detection and ranging (lidar). Data sets were compared to determine the accuracy of GPR to predict deterioration for condition monitoring and rehabilitation planning of bridge decks. As shown by the lidar survey of the material removed during rehabilitation, the GPR top reinforcement reflection amplitude accurately predicted regions of deterioration within the bridge decks. In general, regions with lower reflection amplitudes, indicating more evidence of deterioration, corresponded to regions with greater depths of material removal during the rehabilitation. Also, the GPR top reinforcement reflection amplitude indicated deterioration in areas where visual deterioration was noticed from the top surface of the deck. The majority of cores with delaminations were extracted from sections where the GPR top reinforcement reflection amplitude indicated greater evidence of deterioration based on lower amplitude values."--Abstract, page iii.

Download or read book Evaluation of Bridge Decks Using Non destructive Evaluation NDE at Near Highway Speeds for Effective Asset Management written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote sensing technologies allow for the condition evaluation of bridge decks at near highway speed. Data collection at near highway speed for assessment of the top of the concrete deck and proof of concept testing for the underside of the deck was conducted for surface and subsurface evaluation. 3-D photogrammetry was combined with passive thermography to detect spalls, cracks and delaminations for the top of the concrete bridge deck, while active thermography was investigated for bottom deck surface condition assessment. Successful field demonstrations validated results comparable to MDOT inspections. Recommendations for immediate implementation for condition assessment of the top of a concrete deck are included for introducing the BridgeViewer Remote Camera System into current bridge inspections to provide a photo inventory of the bridge deck captured at 45mph and above using GoPro cameras. The combined optical photogrammetry (3DOBS) and passive thermography technologies provide an objective analysis of spalls, cracks and suspected delaminations while traveling at near highways speed. Using the same 3DOBS technology with higher resolution cameras and slower speeds, cracks can be detected as small as 1/32 in. Laboratory and field demonstrations show active thermography would benefit from further development as a remote sensing technology for condition assessment on the underside of the bridge deck.

Download or read book An Integrated Method for Optimizing Bridge Maintenance Plans written by Eslam Mohammed Abdelkader and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridges are one of the vital civil infrastructure assets, essential for economic developments and public welfare. Their large numbers, deteriorating condition, public demands for safe and efficient transportation networks and limited maintenance and intervention budgets pose a challenge, particularly when coupled with the need to respect environmental constraints. This state of affairs creates a wide gap between critical needs for intervention actions, and tight maintenance and rehabilitation funds. In an effort to meet this challenge, a newly developed integrated method for optimized maintenance and intervention plans for reinforced concrete bridge decks is introduced. The method encompasses development of five models: surface defects evaluation, corrosion severities evaluation, deterioration modeling, integrated condition assessment, and optimized maintenance plans. These models were automated in a set of standalone computer applications, coded using C#.net in Matlab environment. These computer applications were subsequently combined to form an integrated method for optimized maintenance and intervention plans. Four bridges and a dataset of bridge images were used in testing and validating the developed optimization method and its five models. The developed models have unique features and demonstrated noticeable performance and accuracy over methods used in practice and those reported in the literature. For example, the accuracy of the surface defects detection and evaluation model outperforms those of widely-recognized machine leaning and deep learning models; reducing detection, recognition and evaluation of surface defects error by 56.08%, 20.2% and 64.23%, respectively. The corrosion evaluation model comprises design of a standardized amplitude rating system that circumvents limitations of numerical amplitude-based corrosion maps. In the integrated condition, it was inferred that the developed model accomplished consistent improvement over the visual inspection procedures in-use by the Ministry of Transportation in Quebec. Similarly, the deterioration model displayed average enhancement in the prediction accuracies by 60% when compared against the most commonly-utilized weibull distribution. The performance of the developed multi-objective optimization model yielded 49% and 25% improvement over that of genetic algorithm in a five-year study period and a twenty five-year study period, respectively. At the level of thirty five-year study period, unlike the developed model, classical meta-heuristics failed to find feasible solutions within the assigned constraints. The developed integrated platform is expected to provide an efficient tool that enables decision makers to formulate sustainable maintenance plans that optimize budget allocations and ensure efficient utilization of resources.

Download or read book Advancements in Evaluating Reliability of Nondestructive Technologies for the Detection of Subsurface Fracture Damage in R C Bridge Decks written by Ali Abed Sultan and published by . This book was released on 2017 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last few decades, many efforts have been made to assess the reliability of nondestructive evaluation (NDE) technologies used for the detection of subsurface damage in concrete bridge decks. During these efforts, reliability of NDE technologies has either been described anecdotally, or been solely relegated to the probability of detection (POD) or accuracy estimation. Although these indices are important, most of the previous work did not take into account the probability of false alarm (POFA) of NDE technologies, nor did they investigate the reliability considering multiple threshold settings throughout test results. In addition, the existing body of research has used a limited physical sampling such as coring to validate NDE results. Consequently, the assessments were rather controversial, and there was no general agreement about the reliability of such technologies. Because most diagnosis systems are characterized by noisy data and less than perfect detection characteristics, reliability is to be carefully assessed considering all possible diagnosis output with multiple threshold settings within practical range of applications. In other words, when NDE data do not fall into either of the two obviously defined categories: true positive (TP), meaning the NDE data indicates a defect and there is a defect, or true negative (TN), meaning the NDT data indicates no defect and there is no defect, reliability analysis should also include the two types of incorrect indications: failure to give a positive indication in the presence of a defect (false negative, FN) and giving a positive indication when there is no defect (a false alarm or false positive, FP). The \three decades of NDI reliability assessments" report developed by Karta Technologies, Inc. in 2000 under supervision of the Air Force NDI Office stated that POD alone cannot describe the reliability of NDE technologies unless the probability of false alarm (POFA) is also considered in the analysis. POFA may be induced by noise with several possible sources: human, nature of phenomenon to be measured, and environmental conditions. The report covered nearly 150 reports and manuscripts from over 100 authors. However, a review of research literature reveals that little theoretical work on the reliability assessment in terms of both POD and POFA has been undertaken since then. In this research, the reliability of impact echo (IE), infrared thermography (IRT), and ground penetration radar (GPR) technologies for the detecting of subsurface damage in concrete plate-like members is assessed by using a statistical analysis method called receiver operating characteristic (ROC). The proposed analysis method has the capability to integrate POD and POFA indices over a wide range of decision threshold settings in a single curve, which is useful in assessing trade-off in choosing a threshold and for quantitatively comparing the performance of NDE technologies. This methodology for assessing NDE reliability is intended to provide a more effective means of comparing different technologies used in civil engineering applications, to make the evaluation process of a quantitative scheme, to reduce subjectivity and variability in interpreting NDE data, and to improve sensitivity to extract more information from NDE data. Area under ROC curve (AUC), which is interpreted as the probability of correctly classifying an arbitrarily pair of negative and positive test points, can provide for the desired quantitative reliability index, which can be used to compare the performance of one NDE technology to another. Results of this research obtained from ROC analysis indicate a great ability of IE and IR in detecting subsurface fracture damage such as delamination and debonding. In both technologies, there exist some threshold settings that can provide for a relatively high POD with very low POFA, and consequently, the areas under their ROC curves were very high. Data obtained from GPR testing, on the other hand, indicates that GPR technology has a very limited ability to detect physical damage such as subsurface delamination. This conclusion contrasts with that been argued by a large body of the previous work. However, GPR showed a good sensitivity to the presence of corrosive environments such as moisture and chloride when the concentrations of these factors are above some threshold values that may facilitate the initiation of steel reinforcement corrosion.

Download or read book Condition Assessment of Concrete Bridge Decks Using Ground Penetrating Radar written by Kien Dinh and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: