Visual change detection on tunnel linings

We describe an automated system for detecting, localising, clustering and ranking visual changes on tunnel surfaces. The system is designed to provide assistance to expert human inspectors carrying out structural health monitoring and maintenance on ageing tunnel networks. A three-dimensional tunnel surface model is first recovered from a set of reference images using Structure from Motion techniques. New images are localised accurately within the model and changes are detected versus the reference images and model geometry. We formulate the problem of detecting changes probabilistically and evaluate the use of different feature maps and a novel geometric prior to achieve invariance to noise and nuisance sources such as parallax and lighting changes. A clustering and ranking method is proposed which efficiently presents detected changes and further improves the inspection efficiency. System performance is assessed on a real data set collected using a low-cost prototype capture device and labelled with ground truth. Results demonstrate that our system is a step towards higher frequency visual inspection at a reduced cost.The authors gratefully acknowledge the support by Toshiba Research Europe.This is the accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s00138-014-0648-8

Towards Long-Term Monitoring of the Structural Health of Deep Rock Tunnels with Remote Sensing Techniques

Due to the substantial need to continuously ensure safe excavations and sustainable operation of deep engineering structures, structural health monitoring based on remote sensing techniques has become a prominent research topic in this field. Indeed, throughout their lifetime, deep tunnels are usually exposed to many complex situations which inevitably affect their structural health. Therefore, appropriate and effective monitoring systems are required to provide real-time information that can be used as a true basis for efficient and timely decision-making. Since sensors are at the heart of any monitoring system, their selection and conception for deep rock tunnels necessitates special attention. This work identifies and describes relevant structural health problems of deep rock tunnels and the applicability of sensors employed in monitoring systems, based on in-depth searches performed on pertinent research. The outcomes and challenges of monitoring are discussed as well. Results show that over time, deep rock tunnels suffer several typical structural diseases namely degradation of the excavation damaged areas, corrosion of rock bolts and cable bolts, cracks, fractures and strains in secondary lining, groundwater leaks in secondary lining, convergence deformation and damage provoked by the triggering of fires. Various types of remote sensors are deployed to monitor such diseases. For deep rock tunnels, it is suggested to adopt comprehensive monitoring systems with adaptive and robust sensors for their reliable and long-lasting performance

Automated manufacturing of smart tunnel segments

Tunnels, essential infrastructures, require regular inspections and maintenance to ensure their prolonged service life. While conventional methods heavily rely on expert human manpower, modern tunnel structural monitoring techniques, such as sensor-based Structural Health Monitoring (SHM), are increasingly utilized in both existing and newly constructed tunnels. Despite providing valuable insights into post-construction structural behaviour, these methods often overlook the behaviour of individual precast elements, such as tunnel segments, before their installation. This thesis explores the concept of smart tunnel segments instrumented by robotic means to address this gap. In this project lab-scale tunnel segments were instrumented using a 6-axis robotic arm making them smart enabling their properties to be tracked from manufacturing through the operational phase of the tunnel. The research involves a comprehensive review of current tunnel instrumentation practices, identifying structural strains as the most monitored parameters. Vibrating Wire Strain Gauges (VWSGs) were identified as the most suitable sensors for this application due to their compatibility with a modular system and superior long-term properties, especially when embedded in concrete. Furthermore, the study identifies untapped potential in fully automated precast factories and proposes repurposing certain features of industrial robots to deploy VWSGs nodes via robotic pick-and-place. Through a novel evaluation framework, the research demonstrates the effectiveness of automated sensor deployment by robots. This includes the robotic installation of a pair of embedded VWSGs in lab-scale tunnel segments, thereby rendering them "smart," and subjecting them to repetitive flexural loadings to evaluate their performance and accuracy. The calculated strain transfer exhibits consistent and repeatable behaviour across segments. Finally, the thesis outlines the economic justification for smart segments, which outperform traditional on-site wired and wireless alternatives, thereby contributing to a more comprehensive and cost-effective tunnel maintenance strategyTunnels, essential infrastructures, require regular inspections and maintenance to ensure their prolonged service life. While conventional methods heavily rely on expert human manpower, modern tunnel structural monitoring techniques, such as sensor-based Structural Health Monitoring (SHM), are increasingly utilized in both existing and newly constructed tunnels. Despite providing valuable insights into post-construction structural behaviour, these methods often overlook the behaviour of individual precast elements, such as tunnel segments, before their installation. This thesis explores the concept of smart tunnel segments instrumented by robotic means to address this gap. In this project lab-scale tunnel segments were instrumented using a 6-axis robotic arm making them smart enabling their properties to be tracked from manufacturing through the operational phase of the tunnel. The research involves a comprehensive review of current tunnel instrumentation practices, identifying structural strains as the most monitored parameters. Vibrating Wire Strain Gauges (VWSGs) were identified as the most suitable sensors for this application due to their compatibility with a modular system and superior long-term properties, especially when embedded in concrete. Furthermore, the study identifies untapped potential in fully automated precast factories and proposes repurposing certain features of industrial robots to deploy VWSGs nodes via robotic pick-and-place. Through a novel evaluation framework, the research demonstrates the effectiveness of automated sensor deployment by robots. This includes the robotic installation of a pair of embedded VWSGs in lab-scale tunnel segments, thereby rendering them "smart," and subjecting them to repetitive flexural loadings to evaluate their performance and accuracy. The calculated strain transfer exhibits consistent and repeatable behaviour across segments. Finally, the thesis outlines the economic justification for smart segments, which outperform traditional on-site wired and wireless alternatives, thereby contributing to a more comprehensive and cost-effective tunnel maintenance strateg

Evaluation of new technologies to support asset management of metro systems

Since 1930, London Underground Limited (LUL) has performed visual inspections to understand the condition of the physical assets such as tunnels, bridges and structures. The major problem with this kind of inspection is the lack in quality of the data, as it depends on the ability of the inspector to assess and interpret the condition of the asset both accurately and with repeatability. In addition, data collection is time-consuming and, therefore, costly when the whole of the metro network needs to be regularly inspected and there are limited periods when access is available. The problems associated with access to the infrastructure have increased significantly with the implementation of the night tube and will increase further as the night tube is extended over the next 5 to 10 years. To determine the condition of metro assets and to predict the need for intervention, monitoring the changes in the assets’ condition is key to any further evaluation and maintenance planning. This thesis presents the outcomes of using new technologies such as Thermography, Kinematic and Static Laser Scanning, Close-Range Photogrammetry and Total Station to measure defects, such as water seepage, mortar loss in joints, lining face loss (in brick tunnels), cracks, corrosion, voids, cavities and spalls. Each technique is explored through three case studies that evaluate the performance and limitation in the determination of the asset condition. The first case study was performed to compare and contrast the use of Euroconsult’s high definition laser survey against a Principal Inspection Report to determine the level of consistency in predicting the asset condition. During this case study, reports from laser surveys and principal inspections of brick tunnels and covered ways were compared. This analysis showed that a direct comparison between the two inspections is not appropriate because the laser inspection does not capture all the defects mentioned in the Engineering Standard S1060. It also showed that to close the gap between the laser survey and visual inspection, laser surveys would have to be performed every year in brick tunnels and then compare any changes in asset condition with that from the previous scan. The second case study was performed using Infrared Thermography (IRT) to identify water seepage in the brick tunnels as well as test the system in a configuration that would allow the survey to be done from an engineering train. A set of calibration tests were performed in the lab and later the technique was trialled on an engineering train. The results showed that it is possible to measure the level of moisture on specific parts of the lining and that the comparison of surveys performed at different times can allow asset managers to react before a seepage is established, potentially reducing the risk of system disruption caused by water ingress in tunnels. The data also revealed that this technique could be used for other purposes, such as examining the condition of other assets such as brackets, cable supports and broken light bulbs. The third case study was performed using a Terrestrial Laser Scanner, Close-Range Photogrammetry and Total Station Survey to identify defects in structures. In order to test these technologies, a wing wall, located on the north-east wing of the HC3 underbridge at Ladbroke Grove Station, was chosen. This case study demonstrated that LUL can easily implement this type of technology to inspect rapidly their buildings and structures, being able to identify defects and monitor their assets for translation, rotation and changes in shape during changes in loading or the decay of the structure (insidious decline) and the construction of nearby assets. In this research, a large volume of data was captured, and further work is needed in order to manage the data using ‘big data’ concepts. Although it may not be possible to fully understand the insidious decline of an asset, the use of these techniques allows us to better understand how a civil asset behaves, potentially reducing the amount of reactive maintenance to a minimum, consequently reducing service costs and falls in revenue due to disruptions in the system. To successfully analyse the data from new technologies a combination of skills is required and different or retrained personal will be needed

Nondestructive Testing of Rail Tunnel Linings

Rail tunnel linings are currently visually inspected and hammer sounded on all structural elements at random locations or where visual inspection shows the need for it. These methods are good; however, there will not always be visual signs of problems that occur below the surface. Therefore, nondestructive testing methods need to be implemented into inspection techniques to provide information below the surface of the lining. The best approach would be to use relatively fast methods to determine potential problems and then test those areas with slow, detailed methods. This would provide a more thorough investigation of the tunnel lining’s health. Infrared thermography (IRT), ground penetrating radar (GPR), and ultrasonic tomography (UST) techniques were used to do blind testing of slabs and field testing of tunnels. Once the blind testing of the slabs was complete, the data analysis was compared to the known conditions of the slabs. This provided information on the limitations, accuracy, and ease of use for each device. The two slow, detailed methods (UST and GPR) detected all of the anomalies within the slabs when the data was analyzed together. The depths of the problems determined from the devices was fairly accurate with an average delta of 10.6 mm. The infrared camera was only able to detect the shallowest problems. The field testing provided more information on limitations and testing procedures. The first tunnels tested were the five tunnels along the Historic Railroad Trail. The tunnels were bare rock and too rough for the devices. The changes in surface area created temperature variations that limited the effectiveness of the infrared imaging. Also, one area was tested with the UST but no useful information was provided. Finally, the Moab Tunnel was tested which had concrete lined sections. The infrared was able to locate two testing areas and one of them had an anomaly that was found with both the GPR and UST. When testing with the infrared camera, scans need to be taken traveling in both directions so that both perspectives are seen. The two detailed methods provided information on how the lining was constructed by finding the rebar and reinforcing beams. Ultimately, the methods worked well for inspecting the tunnel and the data resulted in a better understanding of the structure underneath the surface

Technology applications

A summary of NASA Technology Utilization programs for the period of 1 December 1971 through 31 May 1972 is presented. An abbreviated description of the overall Technology Utilization Applications Program is provided as a background for the specific applications examples. Subjects discussed are in the broad headings of: (1) cancer, (2) cardiovascular disease, (2) medical instrumentation, (4) urinary system disorders, (5) rehabilitation medicine, (6) air and water pollution, (7) housing and urban construction, (8) fire safety, (9) law enforcement and criminalistics, (10) transportation, and (11) mine safety

Using Different Data Sources for New Findings in Visualization of Highly Detailed Urban Data

Measurement of infrastructure has highly evolved in the last years. Scanning systems became more precise and many methods were found to add and improve content created for the analysis of buildings and landscapes. Therefore the pure amount of data increased significantly and new algorithms had to be found to visualize these data for further exploration. Additionally many data types and formats originate from different sources, such as Dibits hybrid scanning systems delivering laser-scanned point clouds and photogrammetric texture images. These are usually analyzed separately. Combinations of different types of data are not widely used but might lead to new findings and improved data exploration. In our work we use different data formats like meshes, unprocessed point clouds and polylines in tunnel visualization to give experts a tool to explore existing datasets in depth with a wide variety of possibilities. The diverse creation of datasets leads to new challenges for preprocessing, out-of-core rendering and efficient fusion of this varying information. Interactive analysis of different formats of data also has to have several approaches and is usually difficult to merge into one application. In this paper we describe the challenges and advantages of the combination of different data sources in tunnel visualization. Large meshes with high resolution textures are merged with dense point clouds and additional measurements. Interactive analysis can also create additional information, which has to be integrated precisely to prevent errors and misinterpretation. We present the basic algorithms used for heterogeneous data formats, how we combined them and what advantages are created by our methods. Several datasets evolve over time. This dynamic is also considered in our visualization and analysis methods to enable change detection. For tunnel monitoring this allows to investigate the entire history of the construction project and helps to make better informed decisions in the preceding construction phases or for repairs. Several methods are merged like the data they are based on enabling new ways of data exploration. In analyzing this new approach to look at heterogeneous datasets we come to the conclusion that the combination of different sources leads to a better solution than the sum of its parts

Shaking table model tests of reinforced concrete tunnels under multiple earthquake shakings

The cumulative effect of multiple relatively low or moderate seismic events on tunnels is not well-understood within an earthquake prone region. To investigate the effect of multiple earthquakes on the integrity of tunnel structures, 1 g shaking table tests were performed. This research also explored the impact of tunnel presence on the soil response, namely analyzing soil-structure interaction effects. Within the tests, a free-field model and a soil-tunnel model were employed synchronously. The shaking table study was designed and conducted following a new set of scaling laws able to faithfully simulate cracking of tunnel lining, and white noise tests were applied after each seismic shaking for dynamic identification. Except for the measurement of acceleration and bending strain, a new cracking monitoring system equipped with wireless mini-cameras was proposed to detect the evolution of tunnel damages during the tests, while Light Detection and Ranging (LiDAR) technology was utilized to examine the ground deformations in the two model configurations. Based on the point cloud data, it was observed that sand densification effects were obvious in the two models and the influence of tunnel presence on the soil response was restricted in a limited region. The trend in the evolution of an image-based damage index kept similar to that in the progression of surface settlements, implying that the seismically-induced ground failure might play an important role in the seismic response of shallow tunnels. Also, the frequency shifting behaviour of lining did not follow the intuitive pattern, where a reduction in natural frequencies is expected when structural damage occurs. Moreover, the variation of acceleration amplification factors of the tunnel was almost consistent with that of the soil, and the trend of strain agreed with that of surface settlements. The findings from this study provide an insight to better understand the resilience and life-long performance of earthquakes exposed underground structures