Review of machine-vision based methodologies for displacement measurement in civil structures

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record.Vision-based systems are promising tools for displacement measurement in civil structures, possessing advantages over traditional displacement sensors in instrumentation cost, installation efforts and measurement capacity in terms of frequency range and spatial resolution. Approximately one hundred papers to date have appeared on this subject, investigating topics like: system development and improvement, the viability on field applications and the potential for structural condition assessment. The main contribution of this paper is to present a literature review of vision-based displacement measurement, from the perspectives of methodologies and applications. Video processing procedures in this paper are summarised as a three-component framework, camera calibration, target tracking and structural displacement calculation. Methods for each component are presented in principle, with discussions about the relative advantages and limitations. Applications in the two most active fields: bridge deformation and cable vibration measurement are examined followed by a summary of field challenges observed in monitoring tests. Important gaps requiring further investigation are presented e.g. robust tracking methods, non-contact sensing and measurement accuracy evaluation in field conditions

Preoperative liver registration for augmented monocular laparoscopy using backward–forward biomechanical simulation

PURPOSE: Augmented reality for monocular laparoscopy from a preoperative volume such as CT is achieved in two steps. The first step is to segment the organ in the preoperative volume and reconstruct its 3D model. The second step is to register the preoperative 3D model to an initial intraoperative laparoscopy image. To date, there does not exist an automatic initial registration method to solve the second step for the liver in the de facto operating room conditions of monocular laparoscopy. Existing methods attempt to solve for both deformation and pose simultaneously, leading to nonconvex problems with no optimal solution algorithms. METHODS: We propose in contrast to break the problem down into two parts, solving for (i) deformation and (ii) pose. Part (i) simulates biomechanical deformations from the preoperative to the intraoperative state to predict the liver’s unknown intraoperative shape by modeling gravity, the abdominopelvic cavity’s pressure and boundary conditions. Part (ii) rigidly registers the simulated shape to the laparoscopy image using contour cues. RESULTS: Our formulation leads to a well-posed problem, contrary to existing methods. This is because it exploits strong environment priors to complement the weak laparoscopic visual cues. CONCLUSION: Quantitative results with in silico and phantom experiments and qualitative results with laparosurgery images for two patients show that our method outperforms the state-of-the-art in accuracy and registration time

Non-contact vision-based deformation monitoring on bridge structures

Information on deformation is an important metric for bridge condition and performance assessment, e.g. identifying abnormal events, calibrating bridge models and estimating load carrying capacities, etc. However, accurate measurement of bridge deformation, especially for long-span bridges remains as a challenging task. The major aim of this research is to develop practical and cost-effective techniques for accurate deformation monitoring on bridge structures. Vision-based systems are taken as the study focus due to a few reasons: low cost, easy installation, desired sample rates, remote and distributed sensing, etc. This research proposes an custom-developed vision-based system for bridge deformation monitoring. The system supports either consumer-grade or professional cameras and incorporates four advanced video tracking methods to adapt to different test situations. The sensing accuracy is firstly quantified in laboratory conditions. The working performance in field testing is evaluated on one short-span and one long-span bridge examples considering several influential factors i.e. long-range sensing, low-contrast target patterns, pattern changes and lighting changes. Through case studies, some suggestions about tracking method selection are summarised for field testing. Possible limitations of vision-based systems are illustrated as well. To overcome observed limitations of vision-based systems, this research further proposes a mixed system combining cameras with accelerometers for accurate deformation measurement. To integrate displacement with acceleration data autonomously, a novel data fusion method based on Kalman filter and maximum likelihood estimation is proposed. Through field test validation, the method is effective for improving displacement accuracy and widening frequency bandwidth. The mixed system based on data fusion is implemented on field testing of a railway bridge considering undesired test conditions (e.g. low-contrast target patterns and camera shake). Analysis results indicate that the system offers higher accuracy than using a camera alone and is viable for bridge influence line estimation. With considerable accuracy and resolution in time and frequency domains, the potential of vision-based measurement for vibration monitoring is investigated. The proposed vision-based system is applied on a cable-stayed footbridge for deck deformation and cable vibration measurement under pedestrian loading. Analysis results indicate that the measured data enables accurate estimation of modal frequencies and could be used to investigate variations of modal frequencies under varying pedestrian loads. The vision-based system in this application is used for multi-point vibration measurement and provides results comparable to those obtained using an array of accelerometers

D5.1 SHM digital twin requirements for residential, industrial buildings and bridges

This deliverable presents a report of the needs for structural control on buildings (initial imperfections, deflections at service, stability, rheology) and on bridges (vibrations, modal shapes, deflections, stresses) based on state-of-the-art image-based and sensor-based techniques. To this end, the deliverable identifies and describes strategies that encompass state-of-the-art instrumentation and control for infrastructures (SHM technologies).Objectius de Desenvolupament Sostenible::8 - Treball Decent i Creixement EconòmicObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPreprin

Innovative Methods and Materials in Structural Health Monitoring of Civil Infrastructures

In the past, when elements in sructures were composed of perishable materials, such as wood, the maintenance of houses, bridges, etc., was considered of vital importance for their safe use and to preserve their efficiency. With the advent of materials such as reinforced concrete and steel, given their relatively long useful life, periodic and constant maintenance has often been considered a secondary concern. When it was realized that even for structures fabricated with these materials that the useful life has an end and that it was being approached, planning maintenance became an important and non-negligible aspect. Thus, the concept of structural health monitoring (SHM) was introduced, designed, and implemented as a multidisciplinary method. Computational mechanics, static and dynamic analysis of structures, electronics, sensors, and, recently, the Internet of Things (IoT) and artificial intelligence (AI) are required, but it is also important to consider new materials, especially those with intrinsic self-diagnosis characteristics, and to use measurement and survey methods typical of modern geomatics, such as satellite surveys and highly sophisticated laser tools

Vibration Analyses of a Gantry Structure by Mobile Phone Digital Image Correlation and Interferometric Radar

The study presents results from applying the Real Aperture Radar interferometry technique and Digital Image Correlation through a mobile phone camera to identify static and dynamic deformations of a gantry during surveying operations on the Michelangelo’s David at the Galleria dell’Accademia di Firenze Museum in Florence. The statue has considerable size and reaches an elevation of more than seven meters on its pedestal. An ad-hoc gantry was designed and deployed, given the cramped operating area around the statue. The scanner had a stability control system that forbid surveying in instrument movements. However, considering the unicity of the survey and its rare occurrence, the previous survey had been carried out in the year 2000; verifying stability and recording deformations is a crucial task, and necessary for validation. As the gantry does not have an on-board stability sensor, and considering the hi-survey accuracy requested, a redundant, contactless, remote monitoring system of the gantry and the statue stability was chosen to guarantee the maximum freedom of movement around the David to avoid any interference during scanning operations. Thanks to the TInRAR technique, the gantry and the statue were monitored with an accuracy of 0.01 mm. At the same time, a Digital Image Correlation analysis was performed on the gantry, which can be considered a Multi-Degree-Of-Freedom (MDOF) system, to accurately calculate the vibration frequency and amplitude. A comparison between TInRAR and DIC results reported substantial accordance in detecting gantry’s oscillating frequencies; a predominant oscillation frequency of 1.33 Hz was identified on the gantry structure by TinSAR and DIC analysis