Bridge Inspection: Human Performance, Unmanned Aerial Systems and Automation

Unmanned aerial systems (UASs) have become of considerable private and commercial interest for a variety of jobs and entertainment in the past 10 years. This paper is a literature review of the state of practice for the United States bridge inspection programs and outlines how automated and unmanned bridge inspections can be made suitable for present and future needs. At its best, current technology limits UAS use to an assistive tool for the inspector to perform a bridge inspection faster, safer, and without traffic closure. The major challenges for UASs are satisfying restrictive Federal Aviation Administration regulations, control issues in a GPS-denied environment, pilot expenses and availability, time and cost allocated to tuning, maintenance, post-processing time, and acceptance of the collected data by bridge owners. Using UASs with self-navigation abilities and improving image-processing algorithms to provide results near real-time could revolutionize the bridge inspection industry by providing accurate, multi-use, autonomous three-dimensional models and damage identification

A Systematic Literature Survey of Unmanned Aerial Vehicle Based Structural Health Monitoring

Unmanned Aerial Vehicles (UAVs) are being employed in a multitude of civil applications owing to their ease of use, low maintenance, affordability, high-mobility, and ability to hover. UAVs are being utilized for real-time monitoring of road traffic, providing wireless coverage, remote sensing, search and rescue operations, delivery of goods, security and surveillance, precision agriculture, and civil infrastructure inspection. They are the next big revolution in technology and civil infrastructure, and it is expected to dominate more than $45 billion market value. The thesis surveys the UAV assisted Structural Health Monitoring or SHM literature over the last decade and categorize UAVs based on their aerodynamics, payload, design of build, and its applications. Further, the thesis presents the payload product line to facilitate the SHM tasks, details the different applications of UAVs exploited in the last decade to support civil structures, and discusses the critical challenges faced in UASHM applications across various domains. Finally, the thesis presents two artificial neural network-based structural damage detection models and conducts a detailed performance evaluation on multiple platforms like edge computing and cloud computing

UAV-BASED PHOTOGRAMMETRY DATA TRANSFORMATION AS A BUILDING INSPECTION TOOL: APPLICABILITY IN MID-HIGH-RISE BUILDING

The photogrammetric concept is used as a practical implementation of this study. Data management is proposed as an active contribution in the process of data integration and data in-operability to develop solutions based on UAV-based Photogrammetry as part of building inspection activities. Point Cloud adjusts the main role as data to initialize objects whose information can be represented in 2D / 3D / 4D rich-data format. Decision making on each management framework is planned with the DJI Go and Pix4D Capture Application which is controlled by a smartphone that has been pre-configured for the plan UAV flights. The flight plan quality control, flight mission supervision, and data acquisition results are important factors in the management and related infor-mation framework. The Point Cloud created by the SfM (Structure from Motion) application is then imported by Autodesk Recap and reconstructed in Revit BIM. The 3D Point Cloud is lastly enhanced with some practically detailed information to contribute to the data management experiment. The collaboration model of this study is presented using AR / VR (Augmented Reality / Virtual Reality) to enable mobile monitoring as a research objective and substantial examination. The essence of this study is to develop UAV-based Photogrammetry / BIM / AR-VR as a method to reduce the risk of data mismatches, monitor communications, and increase the impact of practical instructions on de-cision making on building inspection activities. The results of each verified workflow show that the methodology applied produces informational and visual data products that allow user mobility within the scope of building inspection and monitoring. Furthermore, device limitations do not affect the data acquisition process to provide user safety and efficiency

Impact of UAV Hardware Options on Bridge Inspection Mission Capabilities

Uncrewed Aerial Vehicles (UAV) constitute a rapidly evolving technology field that is becoming more accessible and capable of supplementing, expanding, and even replacing some traditionally manual bridge inspections. Given the classification of the bridge inspection types as initial, routine, in-depth, damage, special, and fracture critical members, specific UAV mission requirements can be developed, and their suitability for UAV application examined. Results of a review of 23 applications of UAVs in bridge inspections indicate that mission sensor and payload needs dictate the UAV configuration and size, resulting in quadcopter configurations being most suitable for visual camera inspections (43% of visual inspections use quadcopters), and hexa- and octocopter configurations being more suitable for higher payload hyperspectral, multispectral, and Light Detection and Ranging (LiDAR) inspections (13%). In addition, the number of motors and size of the aircraft are the primary drivers in the cost of the vehicle. 75% of vehicles rely on GPS for navigation, and none of them are capable of contact inspections. Factors that limit the use of UAVs in bridge inspections include the UAV endurance, the capability of navigation in GPS deprived environments, the stability in confined spaces in close proximity to structural elements, and the cost. Current research trends in UAV technologies address some of these limitations, such as obstacle detection and avoidance methods, autonomous flight path planning and optimization, and UAV hardware optimization for specific mission requirements

A Trusted Platform for Unmanned Aerial Vehicle-Based Bridge Inspection Management System

Bridge inspection has a pivotal role in assuring the safety of critical structures constituting society. However, high cost, worker safety, and low objectivity of quality are classic problems in traditional visual inspection. Recent trends in bridge inspection have led to a proliferation of research utilizing Unmanned Aerial Vehicles (UAVs). This thesis proposes a Trusted Platform for Bridge Inspection Management System (Trusted-BIMS) for safe and efficient bridge inspection by proving the UAV-based inspection process and improving the prototype of the previous study. Designed based on a Zero-Trust (ZT) strategy, Trusted-BIMS consist of (1) a database-driven web framework with security features for bridge inspection management, (2) a mobile interface supporting the inspection data collection using UAVs, and (3) a mutual authentication protocol for the Internet of Things (IoTs). The server script language used to implement the web system was PHP and React Native was used for the mobile application development. The secure communication algorithm used server-side PHP and client-side JavaScript, and MySQL was adopted as the database. This paper provides an overview and details of Trusted-BIMS and demonstrates the overall process of bridge inspection using UAVs and applied technologies to the proposed platform. The result of this research will make an important contribution to the field of UAV-based bridge inspection. Further research can be conducted on refined implementations of security algorithms, more comprehensive security schemes, and machine learning technology to reduce human intervention

Condition Assessment of Concrete Bridge Decks Using Ground and Airborne Infrared Thermography

Applications of nondestructive testing (NDT) technologies have shown promise in assessing the condition of existing concrete bridges. Infrared thermography (IRT) has gradually gained wider acceptance as a NDT and evaluation tool in the civil engineering field. The high capability of IRT in detecting subsurface delamination, commercial availability of infrared cameras, lower cost compared with other technologies, speed of data collection, and remote sensing are some of the expected benefits of applying this technique in bridge deck inspection practices. The research conducted in this thesis aims at developing a rational condition assessment system for concrete bridge decks based on IRT technology, and automating its analysis process in order to add this invaluable technique to the bridge inspector’s tool box. Ground penetrating radar (GPR) has also been vastly recognized as a NDT technique capable of evaluating the potential of active corrosion. Therefore, integrating IRT and GPR results in this research provides more precise assessments of bridge deck conditions. In addition, the research aims to establish a unique link between NDT technologies and inspector findings by developing a novel bridge deck condition rating index (BDCI). The proposed procedure captures the integrated results of IRT and GPR techniques, along with visual inspection judgements, thus overcoming the inherent scientific uncertainties of this process. Finally, the research aims to explore the potential application of unmanned aerial vehicle (UAV) infrared thermography for detecting hidden defects in concrete bridge decks. The NDT work in this thesis was conducted on full-scale deteriorated reinforced concrete bridge decks located in Montreal, Quebec and London, Ontario. The proposed models have been validated through various case studies. IRT, either from the ground or by utilizing a UAV with high-resolution thermal infrared imagery, was found to be an appropriate technology for inspecting and precisely detecting subsurface anomalies in concrete bridge decks. The proposed analysis produced thermal mosaic maps from the individual IR images. The k-means clustering classification technique was utilized to segment the mosaics and identify objective thresholds and, hence, to delineate different categories of delamination severity in the entire bridge decks. The proposed integration methodology of NDT technologies and visual inspection results provided more reliable BDCI. The information that was sought to identify the parameters affecting the integration process was gathered from bridge engineers with extensive experience and intuition. The analysis process utilized the fuzzy set theory to account for uncertainties and imprecision in the measurements of bridge deck defects detected by IRT and GPR testing along with bridge inspector observations. The developed system and models should stimulate wider acceptance of IRT as a rapid, systematic and cost-effective evaluation technique for detecting bridge deck delaminations. The proposed combination of IRT and GPR results should expand their correlative use in bridge deck inspection. Integrating the proposed BDCI procedure with existing bridge management systems can provide a detailed and timely picture of bridge health, thus helping transportation agencies in identifying critical deficiencies at various service life stages. Consequently, this can yield sizeable reductions in bridge inspection costs, effective allocation of limited maintenance and repair funds, and promote the safety, mobility, longevity, and reliability of our highway transportation assets

Evaluating applications of the unmanned aerial system in construction project management

Using unmanned aerial vehicle systems (UAS) or drones in project management (PM) is a novel methodology aimed at enhancing the performance of the PM system. This technology is still in its infancy, and some serious progress is required to cover and advance in this field. UAS is used in various applications ranging from site mapping, surveying, traffic surveillance, bushfire monitoring and aerial photography. Despite the multiple functions offered by UAS, which are well covered in various sources, industry practitioners still have little confidence and knowledge on this technology. The value of the data collected using UAS technology is still poorly utilised and understood. This project aims to explore areas in PM that can be enhanced while using UAS and understand the added value of adopting this new technology. This research will utilise Unmanned Aerial Vehicle (UAV) with high- definition (HD) cameras to collect real time imageries of construction sites. The collected data, with the aid of a photogrammetric software Pix4D, is used to develop a detailed UAS system to determine the accuracy of performed work, the generation of the corresponding progress payment reports, and referencing and tracking information in real time for a residential project. This study also discusses combining the UAS and 5D Building Information Modelling (BIM) data to develop smart construction sites. The UAS–BIM combination enables the project stakeholders to be fully informed of the work’s progress and quality to prevent mistakes that could lead to additional costs and delays. The paper identified the primary obstacles to applying the UAS via interviews with the project managers and tradespersons involved in the selected project. Assuredly, digital culture is essential for an intelligent construction site to shift the project team from a passive data user to a more proactive analyser to improve performance and site safety. This research is aimed at building a holistic digital system which will be applied and utilised in Construction Project Management (CPM) fields to improve the performance of site management and the quality of work performed. Other obstacles include ethical reservations, legal requirements, liability risks, weather conditions and the continuation of using a UAS in non-open-air construction environments

Development of Bridge Information Model (BrIM) for digital twinning and management using TLS technology

In the current modern era of information and technology, the concept of Building Information Model (BIM), has made revolutionary changes in different aspects of engineering design, construction, and management of infrastructure assets, especially bridges. In the field of bridge engineering, Bridge Information Model (BrIM), as a specific form of BIM, includes digital twining of the physical asset associated with geometrical inspections and non-geometrical data, which has eliminated the use of traditional paper-based documentation and hand-written reports, enabling professionals and managers to operate more efficiently and effectively. However, concerns remain about the quality of the acquired inspection data and utilizing BrIM information for remedial decisions in a reliable Bridge Management System (BMS) which are still reliant on the knowledge and experience of the involved inspectors, or asset manager, and are susceptible to a certain degree of subjectivity. Therefore, this research study aims not only to introduce the valuable benefits of Terrestrial Laser Scanning (TLS) as a precise, rapid, and qualitative inspection method, but also to serve a novel sliced-based approach for bridge geometric Computer-Aided Design (CAD) model extraction using TLS-based point cloud, and to contribute to BrIM development. Moreover, this study presents a comprehensive methodology for incorporating generated BrIM in a redeveloped element-based condition assessment model while integrating a Decision Support System (DSS) to propose an innovative BMS. This methodology was further implemented in a designed software plugin and validated by a real case study on the Werrington Bridge, a cable-stayed bridge in New South Wales, Australia. The finding of this research confirms the reliability of the TLS-derived 3D model in terms of quality of acquired data and accuracy of the proposed novel slice-based method, as well as BrIM implementation, and integration of the proposed BMS into the developed BrIM. Furthermore, the results of this study showed that the proposed integrated model addresses the subjective nature of decision-making by conducting a risk assessment and utilising structured decision-making tools for priority ranking of remedial actions. The findings demonstrated acceptable agreement in utilizing the proposed BMS for priority ranking of structural elements that require more attention, as well as efficient optimisation of remedial actions to preserve bridge health and safety