37 research outputs found
Desarrollo de geotecnologías aplicadas a la inspección y monitorización de entornos industriales
Tesis por compendio de publicaciones[ES]El desarrollo tecnológico de las últimas dos décadas ha supuesto un cambio radical que está llevando a un nuevo paradigma en el que se entremezclan el mundo físico y el digital. Estos cambios han influido enormemente en la sociedad, modificando las formas de comunicación, acceso a información, ocio, trabajo, etc. Asimismo, la industria ha adoptado estas tecnologías disruptivas, las cuales están
contribuyendo a lograr un mayor control y automatización del proceso productivo. En el ámbito industrial, las tareas de mantenimiento son críticas para garantizar el correcto funcionamiento de una planta o instalación, ya que influyen directamente en la productividad y pueden suponer un elevado costo adicional. Las nuevas tecnologías están posibilitando la monitorización continua y a la inspección automatizada, proporcionando herramientas auxiliares a los inspectores que mejoran la detección de fallos y permiten anticipar y optimizar la planificación de las tareas de mantenimiento. Con el objetivo de desarrollar herramientas que aporten mejoras en las tareas de mantenimiento en industria, la presente tesis doctoral se basa en el estudio de como las geotecnologías pueden aportar soluciones óptimas en la monitorización e inspección. Debido a la gran variedad de entornos industriales, las herramientas de
apoyo al mantenimiento deben adaptarse a cada caso en concreto. En este aspecto, y con el fin de demostrar la adaptabilidad de la geomática y las geotecnologías, se han estudiado instalaciones industriales de ámbitos muy diversos, como una sala de máquinas (escenario interior), plantas fotovoltaicas (escenario exterior) y soldaduras (interior y exterior). La escala de los escenarios objeto de estudio ha sido muy variada, desde las escalas más pequeñas, para el estudio de las soldaduras y la sala de máquinas, a las escalas más grandes, en los estudios de evolución de la vegetación y presencia
de masas de agua en plantas fotovoltaicas. Las geotecnologías demuestran su versatilidad para trabajar a distintas escalas, con soluciones que permiten un gran detalle y precisión, como la fotogrametría de rango cercano y el sistema de escaneado portátil (Portable Mobile Mapping System - PMMS), y otras que pueden abarcar zonas más amplias del territorio, como es el caso de la teledetección o la
fotogrametría con drones. Según lo expuesto anteriormente, el enfoque de la tesis ha sido el estudio de elementos o instalaciones industriales a diferentes escalas. En el primer caso se desarrolló una herramienta para el control de calidad externo de soldaduras utilizando fotogrametría de rango cercano y algoritmos para la detección automática de defectos. En el segundo caso se propuso el uso de un PMMS para optimizar la toma de datos en las tareas de inspección en instalaciones fluidomecánicas. En el tercer caso se utilizó la fotogrametría con drones y la combinación de imágenes RGB y térmicas con algoritmos de visión computacional para la detección de patologías en paneles fotovoltaicos. Finalmente, para la monitorización de la vegetación y la detección de masas de agua en el entorno de plantas fotovoltaicas, se empleó la teledetección mediante el cálculo de índices espectrales.
[EN]The technological development of the last two decades has brought about a radical change that is leading to a new paradigm in which the physical and digital worlds are intertwined. These changes have had a great impact on society, modifying communication methods, access to information, leisure, work, etc. In addition, the industry has adopted these disruptive technologies, which are contributing to achieving greater control and automation of the production process. In the industrial sector, maintenance tasks are critical to ensuring the proper operation of a plant or facility, as they directly influence productivity and can involve high additional costs. New technologies are making continuous monitoring and automated inspection possible, providing auxiliary tools to inspectors that improve fault detection and allow for the anticipation and optimization of maintenance task planning. With the aim of developing tools that provide improvements in maintenance tasks in industry, this doctoral thesis is based on the study of how geotechnologies can provide optimal solutions in monitoring and inspection. Due to the great variety of industrial environments, maintenance support tools must adapt to each specific case. In this regard, and in order to demonstrate the adaptability of geomatics and geotechnologies, industrial installations from very diverse areas have been studied, such as a machine room (indoor scenario), photovoltaic plants (outdoor scenario), and welding (indoor and outdoor scenarios). The scale of the studied scenarios has been very varied, ranging from smaller scales for the study of welds and machine rooms, to larger scales in the studies of vegetation evolution and the presence of bodies of water in photovoltaic plants. Geotechnologies demonstrate their versatility to work at different scales, with solutions that allow for great detail and precision, such as close-range photogrammetry and the Portable Mobile Mapping System (PMMS), as well as others that can cover larger areas of the territory, such as remote sensing or photogrammetry with drones. The focus of the thesis has been the study of industrial elements or installations at different scales. In the first case, a tool was developed for external quality control of welding, using close-range photogrammetry and algorithms for automatic defect detection. In the second case, the use of a PMMS is proposed to optimize data collection in fluid-mechanical installation inspection tasks. In the third case, drone photogrammetry and the combination of RGB and thermal images with computer vision algorithms were used for the detection of pathologies in photovoltaic panels.
Finally, for the monitoring of vegetation and the detection of water masses in the environment of photovoltaic plants, remote sensing was employed through the calculation of spectral indices
Villages et quartiers à risque d’abandon
The issue of villages and neighborhoods at risk of abandonment is a common topic in many Mediterranean regions and is considered as a strategic point of the new European policies. The progressive abandonment of inland areas, with phenomena of emigration and fragmentation of cultural heritage, is a common trend in countries characterized by economic underdevelopment. This leads to the decay of architectural artifacts and buildings and problems with land management. Some aspects of this issue are also found in several urban areas. The goal of this research work is collecting international debates, discussions, opinions and comparisons concerning the analysis, study, surveys, diagnoses and graphical rendering of architectural heritage and landscape as well as demo-ethno-anthropological witnesses, typological-constructive stratifications, materials and technologies of traditional and vernacular constructions of historic buildings
UAV or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments
The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains.This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments.Contributions include:UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging;UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use;Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques;UAV-based change detection
Remote Sensing Applications in Coastal Environment
Coastal regions are susceptible to rapid changes, as they constitute the boundary between the land and the sea. The resilience of a particular segment of coast depends on many factors, including climate change, sea-level changes, natural and technological hazards, extraction of natural resources, population growth, and tourism. Recent research highlights the strong capabilities for remote sensing applications to monitor, inventory, and analyze the coastal environment. This book contains 12 high-quality and innovative scientific papers that explore, evaluate, and implement the use of remote sensing sensors within both natural and built coastal environments
EVOLUTION OF THE SUBCONTINENTAL LITHOSPHERE DURING MESOZOIC TETHYAN RIFTING: CONSTRAINTS FROM THE EXTERNAL LIGURIAN MANTLE SECTION (NORTHERN APENNINE, ITALY)
Our study is focussed on mantle bodies from the External Ligurian ophiolites, within the Monte Gavi and Monte Sant'Agostino areas. Here, two distinct pyroxenite-bearing mantle sections were recognized, mainly based on their plagioclase-facies evolution. The Monte Gavi mantle section is nearly undeformed and records reactive melt infiltration under plagioclase-facies conditions. This process involved both peridotites (clinopyroxene-poor lherzolites) and enclosed spinel pyroxenite layers, and occurred at 0.7–0.8 GPa. In the Monte Gavi peridotites and pyroxenites, the spinel-facies clinopyroxene was replaced by Ca-rich plagioclase and new orthopyroxene, typically associated with secondary clinopyroxene. The reactive melt migration caused increase of TiO2 contents in relict clinopyroxene and spinel, with the latter also recording a Cr2O3 increase. In the Monte Gavi peridotites and pyroxenites, geothermometers based on slowly diffusing elements (REE and Y) record high temperature conditions (1200-1250 °C) related to the melt infiltration event, followed by subsolidus cooling until ca. 900°C. The Monte Sant'Agostino mantle section is characterized by widespread ductile shearing with no evidence of melt infiltration. The deformation recorded by the Monte Sant'Agostino peridotites (clinopyroxene-rich lherzolites) occurred at 750–800 °C and 0.3–0.6 GPa, leading to protomylonitic to ultramylonitic textures with extreme grain size reduction (10–50 μm). Compared to the peridotites, the enclosed pyroxenite layers gave higher temperature-pressure estimates for the plagioclase-facies re-equilibration (870–930 °C and 0.8–0.9 GPa). We propose that the earlier plagioclase crystallization in the pyroxenites enhanced strain localization and formation of mylonite shear zones in the entire mantle section. We subdivide the subcontinental mantle section from the External Ligurian ophiolites into three distinct domains, developed in response to the rifting evolution that ultimately formed a Middle Jurassic ocean-continent transition: (1) a spinel tectonite domain, characterized by subsolidus static formation of plagioclase, i.e. the Suvero mantle section (Hidas et al., 2020), (2) a plagioclase mylonite domain experiencing melt-absent deformation and (3) a nearly undeformed domain that underwent reactive melt infiltration under plagioclase-facies conditions, exemplified by the the Monte Sant'Agostino and the Monte Gavi mantle sections, respectively. We relate mantle domains (1) and (2) to a rifting-driven uplift in the late Triassic accommodated by large-scale shear zones consisting of anhydrous plagioclase mylonites.
Hidas K., Borghini G., Tommasi A., Zanetti A. & Rampone E. 2021. Interplay between melt infiltration and deformation in the deep lithospheric mantle (External Liguride ophiolite, North Italy). Lithos 380-381, 105855
Toward Global Localization of Unmanned Aircraft Systems using Overhead Image Registration with Deep Learning Convolutional Neural Networks
Global localization, in which an unmanned aircraft system (UAS) estimates its unknown current location without access to its take-off location or other locational data from its flight path, is a challenging problem. This research brings together aspects from the remote sensing, geoinformatics, and machine learning disciplines by framing the global localization problem as a geospatial image registration problem in which overhead aerial and satellite imagery serve as a proxy for UAS imagery. A literature review is conducted covering the use of deep learning convolutional neural networks (DLCNN) with global localization and other related geospatial imagery applications. Differences between geospatial imagery taken from the overhead perspective and terrestrial imagery are discussed, as well as difficulties in using geospatial overhead imagery for image registration due to a lack of suitable machine learning datasets. Geospatial analysis is conducted to identify suitable areas for future UAS imagery collection. One of these areas, Jerusalem northeast (JNE) is selected as the area of interest (AOI) for this research. Multi-modal, multi-temporal, and multi-resolution geospatial overhead imagery is aggregated from a variety of publicly available sources and processed to create a controlled image dataset called Jerusalem northeast rural controlled imagery (JNE RCI). JNE RCI is tested with handcrafted feature-based methods SURF and SIFT and a non-handcrafted feature-based pre-trained fine-tuned VGG-16 DLCNN on coarse-grained image registration. Both handcrafted and non-handcrafted feature based methods had difficulty with the coarse-grained registration process. The format of JNE RCI is determined to be unsuitable for the coarse-grained registration process with DLCNNs and the process to create a new supervised machine learning dataset, Jerusalem northeast machine learning (JNE ML) is covered in detail. A multi-resolution grid based approach is used, where each grid cell ID is treated as the supervised training label for that respective resolution. Pre-trained fine-tuned VGG-16 DLCNNs, two custom architecture two-channel DLCNNs, and a custom chain DLCNN are trained on JNE ML for each spatial resolution of subimages in the dataset. All DLCNNs used could more accurately coarsely register the JNE ML subimages compared to the pre-trained fine-tuned VGG-16 DLCNN on JNE RCI. This shows the process for creating JNE ML is valid and is suitable for using machine learning with the coarse-grained registration problem. All custom architecture two-channel DLCNNs and the custom chain DLCNN were able to more accurately coarsely register the JNE ML subimages compared to the fine-tuned pre-trained VGG-16 approach. Both the two-channel custom DLCNNs and the chain DLCNN were able to generalize well to new imagery that these networks had not previously trained on. Through the contributions of this research, a foundation is laid for future work to be conducted on the UAS global localization problem within the rural forested JNE AOI
Remote Sensing for Land Administration 2.0
The reprint “Land Administration 2.0” is an extension of the previous reprint “Remote Sensing for Land Administration”, another Special Issue in Remote Sensing. This reprint unpacks the responsible use and integration of emerging remote sensing techniques into the domain of land administration, including land registration, cadastre, land use planning, land valuation, land taxation, and land development. The title was chosen as “Land Administration 2.0” in reference to both this Special Issue being the second volume on the topic “Land Administration” and the next-generation requirements of land administration including demands for 3D, indoor, underground, real-time, high-accuracy, lower-cost, and interoperable land data and information
Impact of Etna’s volcanic emission on major ions and trace elements composition of the atmospheric deposition
Mt. Etna, on the eastern coast of Sicily (Italy), is one of the most active volcanoes on the planet and it is widely recognized as a big source of volcanic gases (e.g., CO2 and SO2), halogens, and a lot of trace elements, to the atmosphere in the Mediterranean region. Especially during eruptive periods, Etna’s emissions can be dispersed over long distances and cover wide areas. A group of trace elements has been recently brought to attention for their possible environmental and human health impacts, the Technology-critical elements. The current knowledge about their geochemical cycles is still scarce, nevertheless, recent studies (Brugnone et al., 2020) evidenced a contribution from the volcanic activity for some of them (Te, Tl, and REE). In 2021, in the framework of the research project “Pianeta Dinamico”, by INGV, a network of 10 bulk collectors was implemented to collect, monthly, atmospheric deposition samples. Four of these collectors are located on the flanks of Mt. Etna, other two are in the urban area of Catania and three are in the industrial area of Priolo, all most of the time downwind of the main craters. The last one, close to Cesarò (Nebrodi Regional Park), represents the regional background. The research aims to produce a database on major ions and trace element compositions of the bulk deposition and here we report the values of the main physical-chemical parameters and the deposition fluxes of major ions and trace elements from the first year of research. The pH ranged from 3.1 to 7.7, with a mean value of 5.6, in samples from the Etna area, while it ranged between 5.2 and 7.6, with a mean value of 6.4, in samples from the other study areas. The EC showed values ranging from 5 to 1032 μS cm-1, with a mean value of 65 μS cm-1. The most abundant ions were Cl- and SO42- for anions, Na+ and Ca+ for cations, whose mean deposition fluxes, considering all sampling sites, were 16.6, 6.8, 8.4, and 6.0 mg m-2 d, respectively. The highest deposition fluxes of volcanic refractory elements, such as Al, Fe, and Ti, were measured in the Etna’s sites, with mean values of 948, 464, and 34.3 μg m-2 d-1, respectively, higher than those detected in the other sampling sites, further away from the volcanic source (26.2, 12.4, 0.5 μg m-2 d-1, respectively). The same trend was also observed for volatile elements of prevailing volcanic origin, such as Tl (0.49 μg m-2 d-1), Te (0.07 μg m-2 d-1), As (0.95 μg m-2 d-1), Se (1.92 μg m-2 d-1), and Cd (0.39 μg m-2 d-1). Our preliminary results show that, close to a volcanic area, volcanic emissions must be considered among the major contributors of ions and trace elements to the atmosphere. Their deposition may significantly impact the pedosphere, hydrosphere, and biosphere and directly or indirectly human health