Automatic Change-based Diagnosis of Structures Using Spatiotemporal Data and As- Designed Model

abstract: Civil infrastructures undergo frequent spatial changes such as deviations between as-designed model and as-is condition, rigid body motions of the structure, and deformations of individual elements of the structure, etc. These spatial changes can occur during the design phase, the construction phase, or during the service life of a structure. Inability to accurately detect and analyze the impact of such changes may miss opportunities for early detections of pending structural integrity and stability issues. Commercial Building Information Modeling (BIM) tools could hardly track differences between as-designed and as-built conditions as they mainly focus on design changes and rely on project managers to manually update and analyze the impact of field changes on the project performance. Structural engineers collect detailed onsite data of a civil infrastructure to perform manual updates of the model for structural analysis, but such approach tends to become tedious and complicated while handling large civil infrastructures. Previous studies started collecting detailed geometric data generated by 3D laser scanners for defect detection and geometric change analysis of structures. However, previous studies have not yet systematically examined methods for exploring the correlation between the detected geometric changes and their relation to the behaviors of the structural system. Manually checking every possible loading combination leading to the observed geometric change is tedious and sometimes error-prone. The work presented in this dissertation develops a spatial change analysis framework that utilizes spatiotemporal data collected using 3D laser scanning technology and the as-designed models of the structures to automatically detect, classify, and correlate the spatial changes of a structure. The change detection part of the developed framework is computationally efficient and can automatically detect spatial changes between as-designed model and as-built data or between two sets of as-built data collected using 3D laser scanning technology. Then a spatial change classification algorithm automatically classifies the detected spatial changes as global (rigid body motion) and local deformations (tension, compression). Finally, a change correlation technique utilizes a qualitative shape-based reasoning approach for identifying correlated deformations of structure elements connected at joints that contradicts the joint equilibrium. Those contradicting deformations can help to eliminate improbable loading combinations therefore guiding the loading path analysis of the structure.Dissertation/ThesisDoctoral Dissertation Civil and Environmental Engineering 201

A review of the use of terrestrial laser scanning application for change detection and deformation monitoring of structures

Change detection and deformation monitoring is an active area of research within the field of engineering surveying as well as overlapping areas such as structural and civil engineering. The application of Terrestrial Laser Scanning (TLS) techniques for change detection and deformation monitoring of concrete structures has increased over the years as illustrated in the past studies. This paper presents a review of literature on TLS application in the monitoring of structures and discusses registration and georeferencing of TLS point cloud data as a critical issue in the process chain of accurate deformation analysis. Past TLS research work has shown some trends in addressing issues such as accurate registration and georeferencing of the scans and the need of a stable reference frame, TLS error modelling and reduction, point cloud processing techniques for deformation analysis, scanner calibration issues and assessing the potential of TLS in detecting sub-centimetre and millimetre deformations. However, several issues are still open to investigation as far as TLS is concerned in change detection and deformation monitoring studies such as rigorous and efficient workflow methodology of point cloud processing for change detection and deformation analysis, incorporation of measurement geometry in deformation measurements of high-rise structures, design of data acquisition and quality assessment for precise measurements and modelling the environmental effects on the performance of laser scanning. Even though some studies have attempted to address these issues, some gaps exist as information is still limited. Some methods reviewed in the case studies have been applied in landslide monitoring and they seem promising to be applied in engineering surveying to monitor structures. Hence the proposal of a three-stage process model for deformation analysis is presented. Furthermore, with technological advancements new TLS instruments with better accuracy are being developed necessitating more research for precise measurements in the monitoring of structures

Laser Scanning and the Continuous Wavelet Transform for Flatness Control

Current methods for surface flatness control in construction are based on sparse measurements and therefore may lead to inaccurate and imprecise results. Previous research has shown that Terrestrial Laser Scanning (TLS), with the accuracy and density of 3D point clouds it can provide, could support more complete and reliable control of surface flatness in construction. However, these previous works have only applied to existing methods based on sparse measurements, or used defect detection methods that are not based on the analysis of surface waviness (i.e. the frequencies in the floor surface profile), although this generally constitutes the key information sought after in surface flatness assessment. In this paper, we investigate the application of a frequency analysis technique, more particularly the Continuous Wavelet Trans-form (CWT), to TLS point clouds associated to surfaces. The aim is to make full use of the density of points provided by TLS and provide detailed results frequency-wise. We provide the reasoning behind employing the CWT for analyzing frequencies in this context, and report results obtained using data acquired from actual slabs. The CWT results are also compared with those obtained when applying the Waviness Index method. The encouraging preliminary results lead us to suggest a path forward for future development and testing with a view on possibly establishing a new standard test method for floor flatness

As-Built 3D Heritage City Modelling to Support Numerical Structural Analysis: Application to the Assessment of an Archaeological Remain

Terrestrial laser scanning is a widely used technology to digitise archaeological, architectural and cultural heritage. This allows for modelling the assets’ real condition in comparison with traditional data acquisition methods. This paper, based on the case study of the basilica in the Baelo Claudia archaeological ensemble (Tarifa, Spain), justifies the need of accurate heritage modelling against excessively simplified approaches in order to support structural safety analysis. To do this, after validating the 3Dmeshing process frompoint cloud data, the semi-automatic digital reconstitution of the basilica columns is performed. Next, a geometric analysis is conducted to calculate the structural alterations of the columns. In order to determine the structural performance, focusing both on the accuracy and suitability of the geometric models, static and modal analyses are carried out by means of the finite element method (FEM) on three different models for the most unfavourable column in terms of structural damage: (1) as-built (2) simplified and (3) ideal model without deformations. Finally, the outcomes show that the as-built modelling enhances the conservation status analysis of the 3D heritage city (in terms of realistic compliance factor values), although further automation still needs to be implemented in the modelling process

Multi-technique approach to rockfall monitoring in the Montserrat massif (Catalonia, NE Spain)

Montserrat Mountain is located near Barcelona in Catalonia, in the northeast of Spain, and its massif is formed by conglomerate interleaved by siltstone/sandstone with steep slopes very prone to rockfalls. The increasing number of visitors in the monastery area, reaching 2.4 million per year, has highlighted the risk derived from rockfalls for this building area and also for the terrestrial accesses, both roads and the rack railway. A risk mitigation plan has been launched, and its first phase during 2014-2016 has been focused largely on testing several monitoring techniques for their later implementation. The results of the pilot tests, performed as a development from previous sparse experiences and data, are presented together with the first insights obtained. These tests combine four monitoring techniques under different conditions of continuity in space and time domains, which are: displacement monitoring with Ground-based Synthetic Aperture Radar and characterization at slope scale, with an extremely non-uniform atmospheric phase screen due to the stepped topography and atmosphere stratification; Terrestrial Laser Scanner surveys quantifying the frequency of small or even previously unnoticed rockfalls, and monitoring rock block centimetre scale displacements; the monitoring of rock joints implemented through a wireless sensor network with an ad hoc design of ZigBee loggers developed by ICGC; and, finally, monitoring singular rock needles with Total Station.Peer ReviewedPostprint (author's final draft

THE USE OF POINT CLOUD DATA TO SUPPORT CONCRETE BRIDGE DECK CONDITION ASSESSMENT

Bridge deck condition assessments are typically conducted through visual physical inspections, utilizing traditional contact sensors for Non-Destructive Evaluation techniques such as hammer Sounding and chain dragging which require the expertise of trained inspectors. However, the accuracy of these inspections is limited by the level of deterioration of the bridge deck, as the ability of the inspectors is proportional to the apparent level of damage. This study aims to improve the accuracy of bridge deck inspection processes by utilizing non-destructive evaluation techniques, including the analysis of point cloud data gathered via Light Detection and Ranging (LiDAR) as a geometry-capturing tool. The overall goal of this research is to evaluate and quantify the effectiveness and efficiency of LiDAR sensors in contributing to the suite of technologies available to perform bridge deck condition assessment. To achieve this, the research proposes to understand the deterioration pattern of New Jersey bridges, evaluate the results gathered from point cloud data collected on a full-scale bridge deck, quantify the information gained from deploying LiDAR on operating bridges in New Jersey, and investigate the costs related to current bridge condition assessment practices and the impact of incorporating the use of LiDAR sensors. Two data processing approaches were chosen to measure gross and fine dimensions of the evaluated bridge decks, resulting in an accuracy of 96% with respect to results gathered from inspection reports

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