Terrestrial Laser Scanning Roughness Assessments for Infrastructure

Road roughness is a key parameter for controlling pavement construction processes and for assessing ride quality of both paved and unpaved roads. This paper describes algorithms used in processing three-dimensional (3D) stationary terrestrial laser scanning (STLS) point clouds to obtain surface maps of point wise indices that characterize pavement roughness. The backbone of the analysis is a quarter-car model simulation over a spatial 3D mesh grid representing the pavement surface. Two case studies are presented, and results show high spatial variability in the roughness indices both longitudinally and transversely (i.e., different wheel path positions). It is proposed that road roughness characterization using a spatial framework provides more details on the severity and location of roughness features compared to the one-dimensional methods. This paper describes approaches that provide an algorithmic framework for others collecting similar STLS 3D spatial data to be used in advanced road roughness characterization

The Investigation of the Ardales Cave, Spain – 3D Documentation, Topographic Analyses, and Lighting Simulations based on Terrestrial Laser Scanning

Artículo sobre nuevas posibilidades de investigación topográfica en cuevas gracias a sistemas de escáner y otros

Three-Dimensional Thermal Mapping from IRT Images for Rapid Architectural Heritage NDT

Thermal infrared imaging is fundamental to architectural heritage non-destructive diagnostics. However, thermal sensors’ low spatial resolution allows capturing only very localized phenomena. At the same time, thermal images are commonly collected with independence of geometry, meaning that no measurements can be performed on them. Occasionally, these issues have been solved with various approaches integrating multi-sensor instrumentation, resulting in high costs and computational times. The presented work aims at tackling these problems by proposing a workflow for cost-effective three-dimensional thermographic modeling using a thermal camera and a consumer-grade RGB camera. The discussed approach exploits the RGB spectrum images captured with the optical sensor of the thermal camera and image-based multi-view stereo techniques to reconstruct architectural features’ geometry. The thermal and optical sensors are calibrated employing custom-made low-cost targets. Subsequently, the necessary geometric transformations between undistorted thermal infrared and optical images are calculated to replace them in the photogrammetric scene and map the models with thermal texture. The method’s metric accuracy is evaluated by conducting comparisons with different sensors and the efficiency by assessing how the results can assist the better interpretation of the present thermal phenomena. The conducted application demonstrates the metric and radiometric performance of the proposed approach and the straightforward implementability for thermographic surveys, as well as its usefulness for cost-effective historical building assessments

Quantifying road roughness: multiresolution and near real-time analysis

Road roughness is a key parameter for road construction and for assessing ride quality during the life of paved and unpaved road systems. The quarter-car model (QC model), is a standard mathematical tool for estimating suspension responses and can be used for summative or pointwise analysis of vehicle response to road geometry. In fact, transportation agencies specify roughness requirements as summative values for pavement projects that affect construction practices and contractor pay factors. The International Roughness Index (IRI), a summative statistic of quarter-car suspension response, is widely used to characterize overall roughness profiles of pavement stretches but does not provide sufficient detail about the frequency or spatial distribution of roughness features. This research focuses on two pointwise approaches, continuous roughness maps and wavelets analysis, that both characterize overall roughness and identify localized features and compares these findings with IRI results. Automated algorithms were developed to preform finite difference analysis of point cloud data collected by three-dimensional (3D) stationary terrestrial laser scans of paved and unpaved roads. This resulted in continuous roughness maps that characterized both spatial roughness and localized features. However, to address the computational limitations of finite difference analysis, Fourier and wavelets (discrete and continuous wavelet transform) analyses were conducted on sample profiles from the federal highway administration (FHWA) Long Term Pavement Performance data base. The Fourier analysis was performed by transforming profiles into frequency domain and applying the QC filter to the transformed profile. The filtered profiles are transformed back to spatial domain to inspect the location of high amplitudes in the suspension rate profiles. Finite difference analysis provides suspension responses in spatial domain, on the other hand Fourier analysis can be performed in either frequency or spatial domains only. To describe the location and frequency content of localized features in a profile, wavelet filters were customized to separate the suspension response profiles into sub profiles with known frequency bands. Other advantages of wavelets analysis includes data compression, making inferences from compressed data, and analyzing short profiles (\u3c 7.6 m). The proposed approaches present the basis for developing real-time autonomous algorithms for smoothness based quality control and maintenance

Extracción de información geométrica y semántica mediante el tratamiento de datos 2D/3D para labores de documentación y rehabilitación del patrimonio arquitectónico

Las tareas de documentación digital del patrimonio arquitectónico requieren del manejo de muy diferentes tipos de datos. Los sistemas actuales de captura de datos permiten obtener enormes volúmenes de datos. Sin embargo la extracción de información que resulte útilpara la documentación digital supone un importante reto de investigación. Esta tesis se centra en el estudio y diseño de sistemas y metodologías que permitan extraer información relevante a partir de datos 20 y 30 utilizando técnicas de procesamiento de nubes de puntos, extracción automática de líneas características, superposición de imágenes a modelos tridimensionales para la obtención de modelos con información multicapa y ortofotos, y empleo de técnicas de inteligencia artificial (aprendizaje profundo) para el análisis y clasificación de imágenes de patrimonio arquitectónico.Se presentan también casos de uso realizados como la proyección de policromías sobre edificios patrimoniales, y por último se muestran los resultados obtenidos considerados más representativosDepartamento de Ingeniería de Sistemas y AutomáticaDoctorado en Ingeniería Industria

Close-Range Sensing and Data Fusion for Built Heritage Inspection and Monitoring - A Review

Built cultural heritage is under constant threat due to environmental pressures, anthropogenic damages, and interventions. Understanding the preservation state of monuments and historical structures, and the factors that alter their architectural and structural characteristics through time, is crucial for ensuring their protection. Therefore, inspection and monitoring techniques are essential for heritage preservation, as they enable knowledge about the altering factors that put built cultural heritage at risk, by recording their immediate effects on monuments and historic structures. Nondestructive evaluations with close-range sensing techniques play a crucial role in monitoring. However, data recorded by different sensors are frequently processed separately, which hinders integrated use, visualization, and interpretation. This article’s aim is twofold: i) to present an overview of close-range sensing techniques frequently applied to evaluate built heritage conditions, and ii) to review the progress made regarding the fusion of multi-sensor data recorded by them. Particular emphasis is given to the integration of data from metric surveying and from recording techniques that are traditionally non-metric. The article attempts to shed light on the problems of the individual and integrated use of image-based modeling, laser scanning, thermography, multispectral imaging, ground penetrating radar, and ultrasonic testing, giving heritage practitioners a point of reference for the successful implementation of multidisciplinary approaches for built cultural heritage scientific investigations

Information Technology and Human Factors to Enhance Design and Constructability Review Processes in Construction

abstract: Emerging information and communication technology (ICT) has had an enormous effect on the building architecture, engineering, construction and operation (AECO) fields in recent decades. The effects have resonated in several disciplines, such as project information flow, design representation and communication, and Building Information Modeling (BIM) approaches. However, these effects can potentially impact communication and coordination of the virtual design contents in both design and construction phases. Therefore, and with the great potential for emerging technologies in construction projects, it is essential to understand how these technologies influence virtual design information within the organizations as well as individuals’ behaviors. This research focusses on understanding current emerging technologies and its impacts on projects virtual design information and communication among projects stakeholders within the AECO organizations.Dissertation/ThesisDoctoral Dissertation Civil and Environmental Engineering 201

Inspección visual automática de superficies continuas, caracterizando anomalías locales en el dominio Espacio-Frecuencial

Esta tesis propone una metodología para la inspección visual automática de superficies continuas que abarca las etapas de adquisición de imágenes, su procesamiento y la utilización de los resultados obtenidos. Su objetivo es determinar qué zonas de la superficie son defectuosas por alejarse de la homogeneidad esperada y cuál es el tipo de defecto presente. Para ello, se caracterizan anomalías en el dominio espacio-frecuencial, explotando las posibilidades que ofrece el filtro de Gabor. Se ha definido una metodología para el diseño de bancos de filtros de Gabor que analiza una zona del espacio de frecuencias y orientaciones. La información extraída por estos filtros son las características evaluadas en la detección y clasificación de defectos. Este enfoque general ha sido particularizado a la resolución de tres problemas reales de reconocida trascendencia: la inspección de bobinas de chapa de acero laminado, del pavimento de carreteras y del revestimiento de túneles de hormigón.Departamento de Ingeniería de Sistemas y Automátic