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The purpose of this study is to develop a building information modelling (BIM)-based mixed reality (MR) application to enhance and facilitate the process of managing bridge inspection and maintenance works remotely from office. It aims to address the ineffective decision-making process on maintenance tasks from the conventional method which relies on documents and 2D drawings on visual inspection. This study targets two key issues: creating a BIM-based model for bridge inspection and maintenance; and developing this model in a MR platform based on Microsoft Hololens.

Literature review is conducted to determine the limitation of MR technology in the construction industry and identify the gaps of integration of BIM and MR for bridge inspection works. A new framework for a greater adoption of integrated BIM and Hololens is proposed. It consists of a bridge information model for inspection and a newly-developed Hololens application named “HoloBridge”. This application contains the functional modules that allow users to check and update the progress of inspection and maintenance. The application has been implemented for an existing bridge in South Korea as the case study.

The results from pilot implementation show that the inspection information management can be enhanced because the inspection database can be systematically captured, stored and managed through BIM-based models. The inspection information in MR environment has been improved in interpretation, visualization and visual interpretation of 3D models because of intuitively interactive in real-time simulation.

The proposed framework through “HoloBridge” application explores the potential of integrating BIM and MR technology by using Hololens. It provides new possibilities for remote inspection of bridge conditions.

The purpose of this paper is to develop a novel and systematic framework for bridge inspection and management to improve the efficiency in current practice.

A new framework that implements camera-based unmanned aerial systems (UASs) with computer vision algorithms to collect and process inspection data, and Bridge Information Modeling (BrIM) to store and manage all related inspection information is proposed. An illustrative case study was performed using the proposed framework to test its feasibility and efficiency.

The test results of the proposed framework on an existing bridge verified that: high-resolution images captured by an UAS enable to visually identify different types of defects, and detect cracks automatically using computer vision algorithms, the use of BrIM enable assigning defect information on individual model elements, manage all bridge data in a single model across the bridge life cycle. The evaluation by bridge inspectors from 12 states across the USA demonstrated that all of the identified problems, except for being subjective, can be improved using the proposed framework.

The proposed framework enables to: collect and document accurate bridge inspection data, reduce the number of site visits and avoid data overload and facilitate a more efficient, cost-effective and safer bridge inspection process.

This paper contributes a novel and systematic framework for the collection and integration of inspection data for bridge inspection and management. The findings from the case study suggest that the proposed framework should help improve current bridge inspection and management practice. Furthermore, the difficulties experienced during the implementation are evaluated, which should be helpful for improving the efficiency and the degree of automation of the proposed framework further.

The utilisation of emerging technologies for the inspection of bridges has remarkably increased. In particular, non-destructive testing (NDT) technologies are deemed a potential alternative for costly, labour-intensive, subjective and unsafe conventional bridge inspection regimes. This paper aims to develop a framework to overcome conventional inspection regimes' limitations by deploying multiple NDT technologies to carry out digital visual inspections of masonry railway bridges.

This research adopts an exploratory case study approach, and the empirical data is collected through exploratory workshops, interviews and document reviews. The framework is implemented and refined in five masonry bridges as part of the UK railway infrastructure. Four NDT technologies, namely, terrestrial laser scanner, infrared thermography, 360-degree imaging and unmanned aerial vehicles, are used in this study.

A digitally enhanced visual inspection framework is developed by using complementary optical methods. Compared to the conventional inspection regimes, the new approach requires fewer subjective interpretations due to the additional qualitative and quantitative analysis. Also, it is safer and needs fewer operators on site, as the actual inspection can be carried out remotely.

This research is a step towards digitalising the inspection of bridges, and it is of particular interest to transport agencies and bridge inspectors and can potentially result in revolutionising the bridge inspection regimes and guidelines.

The purpose of this paper is to present a design of climbing robot with magnetic wheels which can move on the surface of steel bridge. The locomotion concept is based on adapted lightweight magnetic wheel units with relatively high attractive force and friction force.

The robot has the main advantages of being compact (352 × – 215 × – 155 mm), lightweight (2.3 kg without battery) and simple mechanical structure. It is not only able to climb vertical walls and follow circumferential paths, but also able to pass complex obstacles such as bolts, steps, convex and concave corners with almost any inclination regarding gravity. By using a servo as a compliant joint, the wheel base can be changed to enable the robot to overcome convex corners.

The experiment results show that the climbing robot has a good performance on locomotion, and it is successful in negotiating the complex obstacles. On the other hand, the limitations in locomotion of the robot are also presented.

Compared with the past researches, the robot shows good performance on overcoming complex obstacles such as concave corners, convex corners, bolts and steps on the steel bridge. Magnetic wheel with the characterization of compact size and lightweight is able to provide bigger adhesion force and friction coefficient.

Periodic inspection of bridge cables is essential, and cable-climbing robots can replace human workers to perform risky tasks and improve inspection efficiency. However, cable inspection robots often fail to surmount large obstacles and cable clamps. The purpose of this paper is to develop a practical cable inspection robot with stronger obstacle-surmounting performance and circumferential rotation capability.

A cable inspection robot with novel elastic suspension mechanisms and circumferential rotation mechanisms is designed and proposed in this study. The supporting force and spring deformation of the elastic suspension are investigated and calculated. Dynamic analysis of obstacle surmounting and circumferential rotation is performed. Experiments are conducted on vertical and inclined cables to test the obstacle-surmounting performance and cable-clamp passing of the robot. The practicality of the robot is then verified in field tests.

With its elastic suspension mechanisms, the cable inspection robot can carry a 12.4 kg payload and stably climb a vertical cable. The maximum heights of obstacles surmounted by the driving wheels and the passive wheels of the robot are 15 mm and 13 mm, respectively. Equipped with circumferential rotation mechanisms, the robot can flexibly rotate and successfully pass cable clamps.

The novel elastic suspension mechanism and circumferential rotation mechanism improve the performance of the cable inspection robot and solve the problem of surmounting obstacles and cable clamps. Application of the robot can promote the automation of bridge cable inspection.

The use of digital inspection or e-inspection of transportation projects has been proven as an efficient method over the last decade. A wide range of studies were dedicated to developing and applying e-inspection techniques and technologies. However, there is a lack of a comprehensive systematic review and content analysis of using e-inspection in highway construction and maintenance projects. The main objectives of this study were to explore the current trend and identify relevant inspection technologies and their applications for highway construction projects.

A systematic review of 172 articles from 16 high-ranked academic journals in construction engineering and management published during 2000–2021 was conducted. This process resulted in 67 relevant articles included in the detailed content analysis. The analysis involved synthesizing six main construction elements and work types, nine typical inspection activities, and 23 technologies.

The result of the analysis showed that among the six construction elements and work types, bridge and hot mix asphalt (HMA) recorded the largest share of e-inspection research. For the nine inspection activities, progress monitoring of construction operations was the highest focused area of e-inspection research. The most common e-inspection technologies are geospatial tools, 3D modeling, and unmanned aircraft systems (UASs). Camera-based inspection has existed for decades, however, has limited research development. The critical success factors in implementing e-inspection in highway projects are sharing data among different technologies, inspector training, and reducing the cost of technology purchase.

This study is one of the first attempts to conduct a content analysis of the e-inspection implementation for highway projects. The findings of this study expose knowledge gaps in contemporary research related to implementation barriers such as cost of purchase and operation of e-inspection technologies and transferring data between technologies.

The limitation of bridges’ operation can cause serious social, environmental and economic losses. Therefore, the monitoring and maintenance actions of these structures must be efficient and periodic, especially for bridges located in aggressive environments, such as urban-industrial centres, where the higher volume of carbon dioxide emissions favours carbonation induced corrosion. The purpose of this paper is to analyse the utility of including non-destructive testing (NDTs) to bridges assessment in that regions as a way of obtaining more in-depth information on the conditions of the material composing the structure.

First, the main bridges’ damages were detected by visual inspection. Then, based on the observations of bridges design, environment and main damages, an NDT programme was executed including surface hardness, ultrasonic pulse velocity test, pH indicator spraying, half-cell potential measurements and concrete resistivity tests.

It was observed that, for the studied cases, the carbonation did not present harmful depths, except for the structural elements where segregation and wear of the concrete were noticed. NDTs, associated with visual inspection, indicated the regions where corrective or preventive maintenance actions were actually needed, bringing greater security to the decision maker in regions where repairs are unnecessary or could be postponed.

This paper highlights the contribution of NDTs application in structures in urban-industrial regions where the main mechanism of deterioration is carbonation-induced corrosion, demonstrating the importance of these methods in the rational decision making of investments for maintenance.

The purpose of this paper is to provide an insight on the use of robots in a range of industrial test and inspection applications.

Following a brief introduction, this discusses robotic test and inspection products and practices in the following applications: pipelines, storage tanks, bridges, marine uses, green energy generation and aerospace. Finally, concluding comments are drawn.

This shows that robotic test and inspection practices are being used in a wide range of applications across a diversity of industries. This reflects the many operational and economic benefits arising from their use which include the ability to automate certain laborious manual methods; operation in hazardous locations; uses in inaccessible environments such as within pipelines; the ability to deploy several different techniques simultaneously and thus detect multiple potential defects; reduced workforce costs; and, very often, more rapid testing and greater data acquisition rates than are possible with human operators.

This illustrates the increasingly important role played by robotic technologies in industrial test and inspection practices.

Although ground penetrating radar (GPR) technology is commonly used to assess the condition of reinforced-concrete (RC) bridge decks, the GPR data interpretation is not straightforward. Further, the thresholds that define the severity of deterioration are selected arbitrarily. This paper aims to solve a problem associated with GPR results generated by using a numerical amplitude method to assess corrosiveness of bridge decks.

Data, for more than 50 different bridge decks, were collected using a ground-coupled antenna. Depth-correction was performed for the collected data to normalize the reflected amplitude. Using k-means clustering technique, the amplitude values of each bridge deck were classified into four categories. Later, statistical analysis was performed where the threshold values of different categories of corrosion and deterioration are chosen. Monte-Carlo simulation technique was used to validate the value of these thresholds. Moreover, a sensitivity analysis was performed to realize the effect of changing the thresholds in the areas of corrosion.

The final result of this research is a four-category (good, fair, poor and critical) GPR scale with three fixed numerical thresholds (−7.71 dB, −10.04 dB and −14.63 dB) that define these categories. Besides, deterioration curves have been modeled using Weibull function and based on GPR outputs and corrosion areas.

The developed numerical GPR-based scale and deterioration models are expected to help the decision-makers in assessing the corrosiveness of bridge decks accurately and objectively. Hence, they will be able to take the right intervention decision for managing these decks.

This paper aims to present a novel robotic system for airport pavement inspection tasks.

The cloud-edge-terminal-based distributed architecture is designed for the proposed robotic system. Then, the following three major parts are designed and deployed, respectively: Terminal: the wheeled-robot-based data collection system. Edge: remote monitoring and data analysis system. Cloud: shared database center of the inspection data and knowledge.

Validation and application results show that the proposed system satisfies the demands of automated airport pavement inspection tasks and saves the cost of manpower and time.

The proposed system provides a novel solution for the full process of airport pavement inspection. Compared with the traditional manual method, the robotic system can guarantee complete coverage and provide high-precision pavement inspection results with less time and labor costs.