Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Structural health monitoring and bridge condition assessment

Thesis (Ph.D.) University of Alaska Fairbanks, 2016This research is mainly in the field of structural identification and model calibration, optimal sensor placement, and structural health monitoring application for large-scale structures. The ultimate goal of this study is to identify the structure behavior and evaluate the health condition by using structural health monitoring system. To achieve this goal, this research firstly established two fiber optic structural health monitoring systems for a two-span truss bridge and a five-span steel girder bridge. Secondly, this research examined the empirical mode decomposition (EMD) method’s application by using the portable accelerometer system for a long steel girder bridge, and identified the accelerometer number requirements for comprehensively record bridge modal frequencies and damping. Thirdly, it developed a multi-direction model updating method which can update the bridge model by using static and dynamic measurement. Finally, this research studied the optimal static strain sensor placement and established a new method for model parameter identification and damage detection.Chapter 1: Introduction -- Chapter 2: Structural Health Monitoring of the Klehini River Bridge -- Chapter 3: Ambient Loading and Modal Parameters for the Chulitna River Bridge -- Chapter 4: Multi-direction Bridge Model Updating using Static and Dynamic Measurement -- Chapter 5: Optimal Static Strain Sensor Placement for Bridge Model Parameter Identification by using Numerical Optimization Method -- Chapter 6: Conclusions and Future Work

Wireless Monitoring Systems for Long-Term Reliability Assessment of Bridge Structures based on Compressed Sensing and Data-Driven Interrogation Methods.

The state of the nation’s highway bridges has garnered significant public attention due to large inventories of aging assets and insufficient funds for repair. Current management methods are based on visual inspections that have many known limitations including reliance on surface evidence of deterioration and subjectivity introduced by trained inspectors. To address the limitations of current inspection practice, structural health monitoring (SHM) systems can be used to provide quantitative measures of structural behavior and an objective basis for condition assessment. SHM systems are intended to be a cost effective monitoring technology that also automates the processing of data to characterize damage and provide decision information to asset managers. Unfortunately, this realization of SHM systems does not currently exist. In order for SHM to be realized as a decision support tool for bridge owners engaged in performance- and risk-based asset management, technological hurdles must still be overcome. This thesis focuses on advancing wireless SHM systems. An innovative wireless monitoring system was designed for permanent deployment on bridges in cold northern climates which pose an added challenge as the potential for solar harvesting is reduced and battery charging is slowed. First, efforts advancing energy efficient usage strategies for WSNs were made. With WSN energy consumption proportional to the amount of data transmitted, data reduction strategies are prioritized. A novel data compression paradigm termed compressed sensing is advanced for embedment in a wireless sensor microcontroller. In addition, fatigue monitoring algorithms are embedded for local data processing leading to dramatic data reductions. In the second part of the thesis, a radical top-down design strategy (in contrast to global vibration strategies) for a monitoring system is explored to target specific damage concerns of bridge owners. Data-driven algorithmic approaches are created for statistical performance characterization of long-term bridge response. Statistical process control and reliability index monitoring are advanced as a scalable and autonomous means of transforming data into information relevant to bridge risk management. Validation of the wireless monitoring system architecture is made using the Telegraph Road Bridge (Monroe, Michigan), a multi-girder short-span highway bridge that represents a major fraction of the U.S. national inventory.PhDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116749/1/ocosean_1.pd

Improving Resilience of Transport Instrastructure to Climate Change and other natural and Manmande events based on the combined use of Terrestrial and Airbone Sensors and Advanced Modelling Tools

The project PANOPTIS, funded by the European Commission under the H2020 Programme, aims at increasing the resilience of the transport infrastructures (focusing on roads) and ensuring reliable network availability under unfavourable conditions, such as extreme weather, landslides, and earthquakes. The main target is to combine downscaled climate change scenarios (applied to road infrastructures) with structural and geotechnical simulation tools and with actual data from a multi-sensor network (terrestrial and airborne-based), so as to provide the operators with an integrated tool able to support more effective management of their infrastructures at planning, maintenance and operation level. During the first stage of the project, the consortium will develop advanced technologies to monitor and control transport infrastructures, such as a Geotechnical and Structural Simulation Tool (SGSA) to predict structural and geotechnical risks in road infrastructures; drone-technologies applied to road upkeep and incident management; improved computer vision and machine learning techniques for damage diagnosis of infrastructure, and early warning systems to help operators identify and communicate emerging systemic risks. At the same time, experts in climate modelling, will analyse the possible short and long term effects of climate change on transport infrastructure (e.g. flooding, heavier snows). All the information from the different sensors, models and applications will be integrated and processed through a unique Resilience Assessment Platform that will support operators in the introduction of adaptation and mitigation strategies based on multi-risk scenarios. During the second stage of the project, ACCIONA Engineering will implement the developed technologies and methodologies in a section of the Spanish A-2 motorway, in the province of Guadalajara. PANOPTIS integrated Platform will help optimize the management and maintenance of the Ministry of Public Works' concession for a 77.5-km section, all in collaboration with ACCIONA Infrastructure Maintenance (AMISA) and ACCIONA Concessions. In parallel, PANOPTIS platform will also be implemented in a section of 62 Km of a Greek motorway, renowned for its seismic activity. The trials in Greece hosted by the operator Egnatia Odos will integrate the motorway that serves the Airport of Thessaloniki. So the scenario will integrate a modal transfer segment.Le projet PANOPTIS, financé par la Commission européenne dans le cadre du programme H2020, vise à accroître la résilience de l'infrastructure de transport et à permettre une disponibilité fiable du réseau dans des conditions défavorables, telles que les conditions météorologiques extrêmes, les glissements de terrain et les tremblements de terre. L'objectif principal doit être associé à un réseau multi-capteurs (terrestre et aéroporté) pour permettre une gestion plus efficace de leurs infrastructures au niveau de la planification, de la maintenance et de l'exploitation. Au cours de la première phase du projet, le consortium développera des technologies avancées pour surveiller et contrôler les infrastructures de transport, telles que l'outil de simulation géotechnique et structurelle (SGSA) permettant de prévoir les risques structurels et géotechniques dans les infrastructures routières; technologies de drones appliquées à l'entretien des routes et à la gestion des incidents; la vision par ordinateur et les techniques d'apprentissage automatique pour le diagnostic des infrastructures et les systèmes d'alerte précoce. Dans le même temps, des experts en modélisation du climat analyseront le potentiel du changement climatique sur les infrastructures de transport (par exemple, les inondations, les neiges plus lourdes). Toutes les informations provenant des différents capteurs, modèles et applications seront intégrées dans un scénario unique comportant plusieurs risques. Au cours de la deuxième phase du projet, ACCIONA Engineering mettra en oeuvre les technologies et les méthodologies dans une section de l'autoroute espagnole A-2, dans la province de Guadalajara. La plate-forme intégrée PANOPTIS contribuera à optimiser la gestion et la maintenance de la concession du ministère des Travaux publics pour une section de 77,5 km, le tout en collaboration avec ACCIONA Infrastructure Maintenance (AMISA) et ACCIONA Concessions. Parallèlement, la plate-forme PANOPTIS sera également mise en oeuvre dans une section de 62 Km d'une autoroute grecque réputée pour son activité sismique. Les essais en Grèce organisés par l'opérateur Egnatia Odos vont rejoindre l'aéroport de Thessalonique. Le scénario intégrera donc un segment de transfert modal