Image processing of alos palsar satellite data, small unmanned aerial vehicle (UAV), and field measurement of land deformation

Pekanbaru, Indonesia is connected by four big bridges, Siak Bridge; I, II, III and IV. The quality of the Siak bridges deteriorated seriously at this time. Geological mapping for the land subsidence potency was conducted using small Unmanned Aerial Vehicle (UAV) in the Siak Bridge areas. The study of the Siak bridges are supported by the Differential Interferometric Synthetic Aperture Radar (DInSAR) analysis using ALOS PALSAR satellite data, and the deflection observation that occurs in Siak III Bridge was observed by field measurement. The results of 3D model analysis showed that there is no negative land deformation. DInSAR analysis shows the amount of positive deformation of Siak I is 81 cm, Siak II is 48 cm, Siak III is 89 cm, and Siak IV is 92. Deflection on Siak III Bridge was detected at around 25-26 cm. These models could be used as a new way of measuring the bridge deformation on a big scale

Remote Bridge Deflection Measurement Using an Advanced Video Deflectometer and Actively Illuminated LED Targets

An advanced video deflectometer using actively illuminated LED targets is proposed for remote, real-time measurement of bridge deflection. The system configuration, fundamental principles, and measuring procedures of the video deflectometer are first described. To address the challenge of remote and accurate deflection measurement of large engineering structures without being affected by ambient light, the novel idea of active imaging, which combines high-brightness monochromatic LED targets with coupled bandpass filter imaging, is introduced. Then, to examine the measurement accuracy of the proposed advanced video deflectometer in outdoor environments, vertical motions of an LED target with precisely-controlled translations were measured and compared with prescribed values. Finally, by tracking six LED targets mounted on the bridge, the developed video deflectometer was applied for field, remote, and multipoint deflection measurement of the Wuhan Yangtze River Bridge, one of the most prestigious and most publicized constructions in China, during its routine safety evaluation tests. Since the proposed video deflectometer using actively illuminated LED targets offers prominent merits of remote, contactless, real-time, and multipoint deflection measurement with strong robustness against ambient light changes, it has great potential in the routine safety evaluation of various bridges and other large-scale engineering structures

Caracterización mecánica de hormigones elaborados con áridos procedentes de residuos de construcción mediante correlación digital de imágenes 3D

Trabajo de Fin de Máster del Máster en Geotecnologías cartográficas en ingeniería y arquitectura, curso 2019-2020[ES]En el presente Trabajo Fin de Máster se propone una metodología para el análisis de las propiedades mecánicas de hormigones reciclados a partir de la correlación digital de imágenes 3D. El enfoque 3D-DIC es implementado con los ensayos de compresión del hormigón de manera que pueda llevarse a cabo la caracterización mecánica y comparativa de dos tipos de hormigón fabricados con áridos reciclados procedentes de residuos de hormigón y cerámicos. Para este fin, se presenta una configuración y protocolo 3D-DIC basado en el software de código abierto MultiDIC que permite obtener la reconstrucción tridimensional de una región de interés para cada probeta y calcular su correspondiente campo completo de desplazamientos. Datos que son capturados a través de un equipo de bajo coste constituido por dos cámaras DSLR Canon 700D, cada una de ellas equipada con un objetivo macro Canon 60 mm, las cuales son sincronizadas a través de un PLC y una plataforma de adquisición de datos Quantum. La iluminación de dicho sistema es conseguida a través de dos focos LED de luz neutra que logran tiempos de exposición y contrastes adecuados durante la captura y la correlación de imágenes. A partir de los datos obtenidos con este enfoque, se lleva a cabo un análisis de las deformaciones producidas en cada una de las probetas mediante la colocación de extensómetros virtuales. Los numerosos datos obtenidos en comparación con las mediciones puntuales de los métodos tradicionales permiten monitorizar el comportamiento heterogéneo de este tipo de materiales. Por último, se realiza un estudio comparativo de los valores de deformación obtenidos junto con las cargas asociadas a cada uno de ellos. Este análisis permite obtener la variabilidad espacial de las propiedades de cada una de las probetas, así como la diferencia entre el comportamiento de los dos tipos de hormigón analizados

Investigation of Computer Vision Concepts and Methods for Structural Health Monitoring and Identification Applications

This study presents a comprehensive investigation of methods and technologies for developing a computer vision-based framework for Structural Health Monitoring (SHM) and Structural Identification (St-Id) for civil infrastructure systems, with particular emphasis on various types of bridges. SHM is implemented on various structures over the last two decades, yet, there are some issues such as considerable cost, field implementation time and excessive labor needs for the instrumentation of sensors, cable wiring work and possible interruptions during implementation. These issues make it only viable when major investments for SHM are warranted for decision making. For other cases, there needs to be a practical and effective solution, which computer-vision based framework can be a viable alternative. Computer vision based SHM has been explored over the last decade. Unlike most of the vision-based structural identification studies and practices, which focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation, the proposed framework combines the vision-based structural input and the structural output from non-contact sensors to overcome the limitations given above. First, this study develops a series of computer vision-based displacement measurement methods for structural response (structural output) monitoring which can be applied to different infrastructures such as grandstands, stadiums, towers, footbridges, small/medium span concrete bridges, railway bridges, and long span bridges, and under different loading cases such as human crowd, pedestrians, wind, vehicle, etc. Structural behavior, modal properties, load carrying capacities, structural serviceability and performance are investigated using vision-based methods and validated by comparing with conventional SHM approaches. In this study, some of the most famous landmark structures such as long span bridges are utilized as case studies. This study also investigated the serviceability status of structures by using computer vision-based methods. Subsequently, issues and considerations for computer vision-based measurement in field application are discussed and recommendations are provided for better results. This study also proposes a robust vision-based method for displacement measurement using spatio-temporal context learning and Taylor approximation to overcome the difficulties of vision-based monitoring under adverse environmental factors such as fog and illumination change. In addition, it is shown that the external load distribution on structures (structural input) can be estimated by using visual tracking, and afterward load rating of a bridge can be determined by using the load distribution factors extracted from computer vision-based methods. By combining the structural input and output results, the unit influence line (UIL) of structures are extracted during daily traffic just using cameras from which the external loads can be estimated by using just cameras and extracted UIL. Finally, the condition assessment at global structural level can be achieved using the structural input and output, both obtained from computer vision approaches, would give a normalized response irrespective of the type and/or load configurations of the vehicles or human loads