Crack Analyser: a novel image-based NDT approach for measuring crack severity ​

openIn Europa, le infrastrutture civili e di trasporto necessitano di una manutenzione efficace e proattiva per garantire il continuo funzionamento in sicurezza durante l'intero loro ciclo di vita. I paesi europei devono ogni anno stanziare enormi risorse per mantenere il loro livello di funzionalità. Ciò fa sorgere la necessità urgente di adottare approcci di ispezione di monitoraggio più rapidi e affidabili per aiutare ad affrontare questi problemi. Il deterioramento delle strutture è più spesso anticipato dalla formazione di fessure sulla superficie del calcestruzzo. La presenza di fessurazioni può essere sintomo di diverse problematiche quali dilatazioni e ritiri dovuti a sbalzi di temperatura, assestamenti della struttura, copertura impropria fornita in fase di getto, corrosione delle armature in acciaio, carichi pesanti applicati, vibrazioni insufficienti al momento della posa del calcestruzzo o perdite d'acqua per ritiro superficiale del calcestruzzo. Diventa quindi di primaria importanza l'identificazione, la misurazione e il monitoraggio delle fessurazioni sulla superficie del calcestruzzo. I principali metodi di ispezione attualmente adottati si basano su strumenti manuali e righelli: un’attività lunga e ingombrante, soggetta a errori e scarsamente oggettiva sull'analisi quantitativa perché fortemente dipendente dall'esperienza dell'operatore. Secondo la norma UNI EN 1992-1-1:2005, la larghezza massima delle fessure del calcestruzzo ammessa per una generica classe di rischio è di 0,3 mm. Per questo motivo, per misurare in modo accurato e affidabile la dimensione della fessura, è necessario l’impiego di strumenti di misura con caratteristiche metrologiche adeguate (es. precisione e accuratezza almeno un ordine inferiore al valore da misurare). In caso contrario, la severità della fessura potrebbe essere classificata erroneamente. Questo lavoro di tesi propone un nuovo approccio automatico, basato su immagini, in grado di localizzare e misurare fessure su superfici in calcestruzzo rispettando il vincolo metrologico imposto dalla norma UNI EN 1992-1-1:2005. Utilizzando una sola immagine, il metodo sviluppato è in grado di localizzare e misurare automaticamente e rapidamente la larghezza e la lunghezza di una fessura su una superficie. Il sistema di misura sviluppato sfrutta una singola telecamera operante nel campo del visibile per acquisire un'immagine digitalizzata della superficie da ispezionare. Il componente software del sistema riceve in input la singola immagine che inquadra la crepa e fornisce in output un'immagine aumentata dove viene evidenziata la crepa e la sua larghezza e lunghezza media/max. La misura della larghezza della fessura viene eseguita perpendicolarmente alla linea centrale della fessura con una precisione sub-pixel. Il sistema di misurazione è stato implementato su uno smartphone per eseguire ispezioni manuali da parte dell'operatore e su sistemi integrati per l'ispezione remota con robot o velivoli senza pilota (UAV)). Le strategie sviluppate possono essere facilmente estese a qualsiasi altro contesto in cui sia richiesto un controllo di qualità superficiale mirato all'identificazione e misura di eventuali danni o difettosità. ​Europe’s ageing transport infrastructure needs effective and proactive maintenance in order to continue its safe operation during the entire life cycle; European countries have to allocate huge resources for maintaining their service-ability level. This give rise to the necessity of an urgent need to adopt faster and more reliable monitoring inspection approaches to help tackling these issues. The deterioration of structures is most often foreseen by the formation of cracks on concrete surface. The presence of cracks can be a symptom of various problems like expansion and shrinks due to temperature differences, settlement of the structure, improper cover provided during concreting, corrosion of reinforcement steel, heavy load applied, insufficient vibration at the time of laying the concrete or loss of water from concrete surface shrinkage, therefore the identification, measurement and monitoring of cracks on the concrete surface becomes of primary importance. The main currently adopted inspection methods rely on visual marking and rulers, long and cumbersome activity, prone to errors and poorly objective on quantitative analysis because it strongly depends on operator experience. According to UNI EN 1992-1-1:2005 standard , the maximum admitted concrete crack width is 0.3 mm. For this reason, to accurately and reliably measure the target dimension, it is necessary to employ measurement instruments with suitable metrological characteristics (e.g. precision and accuracy at least one order lower than the value to be measured). Otherwise, the crack severity could be misclassified. This thesis work proposes a novel automatic image-based approach able to locate and measure cracks on concrete surfaces respecting the metrological constraint imposed by UNI EN 1992-1-1:2005 standard. Using only one image, the developed method is able to automatically and rapidly locate and measure the average width and length of a crack in an existing concrete structure. The measurement system developed exploits a single camera working in the visible range to acquire a digitized image of the structure being inspected. The software component of the system receives as input the single image framing the crack and gives as output an augmented image where the crack is highlighted as well as its average/max width and length. The measure of the crack width is performed perpendicularly to the crack central line with sub-pixel accuracy. The measurement system has been deployed on a smartphone for operator-based manual inspections as well on embedded systems for remote inspection with robots or Unmanned Aerial Vehicles (UAVs). The strategies developed can be easily extended from concrete inspection applications to any other context where a surface quality control targeted to the identification of eventual damages/defects is required. The activity was triggered by an explicit need within the EnDurCrete project. ​INGEGNERIA INDUSTRIALEembargoed_20220321Giulietti, Nicol

GIS and Remote Sensing for Renewable Energy Assessment and Maps

This book aims at providing the state-of-the-art on all of the aforementioned tools in different energy applications and at different scales, i.e., urban, regional, national, and even continental for renewable scenarios planning and policy making

Very High Resolution (VHR) Satellite Imagery: Processing and Applications

Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing

Review of Automatic Processing of Topography and Surface Feature Identification LiDAR Data Using Machine Learning Techniques

Machine Learning (ML) applications on Light Detection And Ranging (LiDAR) data have provided promising results and thus this topic has been widely addressed in the literature during the last few years. This paper reviews the essential and the more recent completed studies in the topography and surface feature identification domain. Four areas, with respect to the suggested approaches, have been analyzed and discussed: the input data, the concepts of point cloud structure for applying ML, the ML techniques used, and the applications of ML on LiDAR data. Then, an overview is provided to underline the advantages and the disadvantages of this research axis. Despite the training data labelling problem, the calculation cost, and the undesirable shortcutting due to data downsampling, most of the proposed methods use supervised ML concepts to classify the downsampled LiDAR data. Furthermore, despite the occasional highly accurate results, in most cases the results still require filtering. In fact, a considerable number of adopted approaches use the same data structure concepts employed in image processing to profit from available informatics tools. Knowing that the LiDAR point clouds represent rich 3D data, more effort is needed to develop specialized processing tools

Integrated Applications of Geo-Information in Environmental Monitoring

This book focuses on fundamental and applied research on geo-information technology, notably optical and radar remote sensing and algorithm improvements, and their applications in environmental monitoring. This Special Issue presents ten high-quality research papers covering up-to-date research in land cover change and desertification analyses, geo-disaster risk and damage evaluation, mining area restoration assessments, the improvement and development of algorithms, and coastal environmental monitoring and object targeting. The purpose of this Special Issue is to promote exchanges, communications and share the research outcomes of scientists worldwide and to bridge the gap between scientific research and its applications for advancing and improving society

Remote Sensing of the Oceans

This book covers different topics in the framework of remote sensing of the oceans. Latest research advancements and brand-new studies are presented that address the exploitation of remote sensing instruments and simulation tools to improve the understanding of ocean processes and enable cutting-edge applications with the aim of preserving the ocean environment and supporting the blue economy. Hence, this book provides a reference framework for state-of-the-art remote sensing methods that deal with the generation of added-value products and the geophysical information retrieval in related fields, including: Oil spill detection and discrimination; Analysis of tropical cyclones and sea echoes; Shoreline and aquaculture area extraction; Monitoring coastal marine litter and moving vessels; Processing of SAR, HF radar and UAV measurements

Domain-inspired image processing and computer vision to support deep-sea benthic ecology

Optical imagery is a necessary methodological tool for ecological research within marine environments, particularly in deeper waters. For benthic (seafloor) surveys, interpretation of image data is crucial to creating high-resolution maps of seabed habitats. This is fundamental to marine spatial planning and mitigating long-term damage of anthropogenic stressors such as growing resource demand, climate change and pollution. However there are numerous, and significant, issues in extracting a reliable ground-truth from imagery to support this process. Analysis of benthic images is difficult, due in part to the extreme variation and inconsistency in image quality - caused by complex interactions between light and water. It is also time-consuming. This thesis is dedicated to providing solutions to manage these challenges, from a strong perspective of the end-user. Specifically, we aim to improve the annotation of benthic habitats from imagery in terms of quality, consistency and efficiency. Throughout, we consider the purpose the imagery serves and work closely with end-users to best optimize our solutions. First, and for the majority of this thesis, we investigate image processing techniques to improve the appearance of image features important for habitat classification. We find that tone mapping is an effective and simple (and thus accessible) method through which to improve image quality for interpretation. We describe beneficial (expert-informed) properties for brightness distributions in underwater images and introduce a novel tone-mapping algorithm, Weibull Tone Mapping (WTM), to enhance benthic images. WTM theory operates within general constraints that model image requirements (properties) specified by image analysts, yet possesses a suitable degree of flexibility and customisation. As a tool, WTM provides analysts with a fast and ‘user-friendly’ method to improve benthic habitat classification. Second, we consider computer vision methods that could automatically identify benthic habitats in imagery, relieving the analysis bottleneck. We find that baseline transfer learning of machine learning models, with limited optimization, will better facilitate adoption by novice users, yet still provides a powerful means to swiftly extract and assess benthic data

Solar Power System Plaing & Design

Photovoltaic (PV) and concentrated solar power (CSP) systems for the conversion of solar energy into electricity are technologically robust, scalable, and geographically dispersed, and they possess enormous potential as sustainable energy sources. Systematic planning and design considering various factors and constraints are necessary for the successful deployment of PV and CSP systems. This book on solar power system planning and design includes 14 publications from esteemed research groups worldwide. The research and review papers in this Special Issue fall within the following broad categories: resource assessments, site evaluations, system design, performance assessments, and feasibility studies