Structural health monitoring (SHM) is an emerging field in civil engineering in recent years. The main objectives of the SHM are to identify structural integrity issues at early stage and improve the structural safety through measuring and analyzing structural behaviors. Sensing systems for SHM can be used to identify applied vehicle loads for bridge structures. Bridge weigh-in-motion (BWIM) is one type of such vehicle load identification. As a tool to monitor the vehicle weight moving on the bridges, BWIM uses the structural responses induced by moving vehicle on the bridge to back-calculate vehicle information. In this thesis, optimized BWIM systems using multimetric measurements will be investigated. In Chapter 1, the concept and background of BWIM systems will be introduced. The objective of this research will be also demonstrated in this chapter. Chapter 2 is the literature review section. In Chapter 3, the finite element bridge model adopted for this study will be described. In this section, the moving-load time history analysis, sectional properties for bridge members, and other structural parameters of bridge model will be introduced. The methodology of BWIM systems used in this study will be demonstrated in Chapter 4. In Chapter 5, optimized sensor locations for BWIM using normal and shear strain measurements and acceleration measurement will be discussed for the case without measurement noise. In Chapter 6, sensor location optimization for the case considering measurement noises will be investigated. A new acceleration-based BWIM method is proposed in this section. Non-drift displacement reconstruction technique using acceleration measurement and FIR filtering is applied for BWIM. Finally, Chapter 7 is the conclusion part of this thesis.

This research was done as part of a long term project, with the goal to monitor multiple bridges over an extended period of time. Due to the nation’s aging infrastructure and the limited amount of funds to upgrade and maintain it, structural health monitoring (SHM) is very important because it provides in depth information about a structure to be used in decision making. SHM of bridges includes monitoring the effects of traffic loads. This paper discusses the development of a bridge weigh-in-motion (B-WIM) technique that uses the rainflow counting of strain cycles. Typical B-WIM techniques have proven to be accurate but require large algorithms and gauges at multiple locations across the span, and the strain gauge temperature drift must be accounted for. The rainflow B-WIM (RF-BWIM) decreases the processing of the B-WIM and automatically accounts for drift, thus allowing temperature and other analyses of the same bridge to be possible. RF-BWIM also has the potential to decrease the number of sensors required. Strain data taken from an existing long term monitoring system was used to develop the RF-BWIM. The development of the RF-BWIM, as well as a method to determine a virtual gross vehicle weight (C-GVW) used in calculating the RF-BWIM output, is presented.

Structural Health Monitoring (SHM) is a promising tool for condition assessment of bridge structures. SHM of bridges can be performed for different purposes in long or short-term. A few aspects of short- and long-term monitoring of highway bridges are addressed in this research. Without quantifying environmental effects, applying vibration-based damage detection techniques may result in false damage identification. As part of a long-term monitoring project, the effect of temperature on vibrational characteristics of two continuously monitored bridges are studied. Natural frequencies of the structures are identified from ambient vibration data using the Natural Excitation Technique (NExT) along with the Eigen System Realization (ERA) algorithm. Variability of identified natural frequencies is investigated based on statistical properties of identified frequencies. Different statistical models are tested and the most accurate model is selected to remove the effect of temperature from the identified frequencies. After removing temperature effects, different damage cases are simulated on calibrated finite-element models. Comparing the effect of simulated damages on natural frequencies showed what levels of damage could be detected with this method. Evaluating traffic loads can be helpful to different areas including bridge design and assessment, pavement design and maintenance, fatigue analysis, economic studies and enforcement of legal weight limits. In this study, feasibility of using a single-span bridge as a weigh-in-motion tool to quantify the gross vehicle weights (GVW) of trucks is studied. As part of a short-term monitoring project, this bridge was subjected to four sets of high speed, live-load tests. Measured strain data are used to implement bridge weigh-in-motion (B-WIM) algorithms and calculate the corresponding velocities and GVWs. A comparison is made between calculated and static weights, and furthermore, between supposed speeds and estimated speeds of the trucks. Vibration-based techniques that use finite-element (FE) model updating for SHM of bridges are common for infrastructure applications. This study presents the application of both static and dynamic-based FE model updating of a full scale bridge. Both dynamic and live-load testing were conducted on this bridge and vibration, strain, and deflections were measured at different locations. A FE model is calibrated using different error functions. This model could capture both global and local response of the structure and the performance of the updated model is validated with part of the collected measurements that were not included in the calibration process.

The field of bridge monitoring is one of rapid development. Advances in sensor technologies, in data communication and processing algorithms all affect the possibilities of Structural Monitoring in Bridges. Bridges are a very critical part of a country’s infrastructure, they are expensive to build and maintain, and many uncertainties surround important factors determining their serviceability and deterioration state. As such, bridges are good candidates for monitoring. Monitoring can extend the service life and avoid or postpone replacement, repair or strengthening works. The amount of resources saved, both to the owner and the users, by reducing the amount of non-operational time can easily justify the extra investment in monitoring. This thesis consists of an extended summary and five appended papers. The thesis presents advances in sensor technology, damage identification algorithms, Bridge Weigh-In-Motion systems, and other techniques used in bridge monitoring. Four case studies are presented. In the first paper, a fully operational Bridge Weigh-In-Motion system is developed and deployed in a steel railway bridge. The gathered data was studied to obtain a characterization of the site specific traffic. In the second paper, the seasonal variability of a ballasted railway bridge is studied and characterized in its natural variability. In the third, the non-linear characteristic of a ballasted railway bridge is studied and described stochastically. In the fourth, a novel damage detection algorithm based in Bridge Weigh-In-Motion data and machine learning algorithms is presented and tested on a numerical experiment. In the fifth, a bridge and traffic monitoring system is implemented in a suspension bridge to study the cause of unexpected wear in the bridge bearings. Some of the major scientific contributions of this work are: 1) the development of a B-WIM for railway traffic capable of estimating the load on individual axles; 2) the characterization of in-situ measured railway traffic in Stockholm, with axle weights and train configuration; 3) the quantification of a hitherto unreported environmental behaviour in ballasted bridges and possible mechanisms for its explanation (this behaviour was shown to be of great importance for monitoring of bridges located in colder climate) 4) the statistical quantification of the nonlinearities of a railway bridge and its yearly variations and 5) the integration of B-WIM data into damage detection techniques. / <p>QC 20140910</p>

The field of monitoring is one of rapid development. Advances in sensor technologies, in data communication paradigms and data processing algorithms all influence the possibilities of Structural Health Monitoring, damage detection, traffic monitoring and other implementations of monitoring systems. Bridges are a very critical part of a country’s infrastructure, they are expensive to build and maintain, and many uncertainties surround important factors determining the serviceability and deterioration of bridges. As such, bridges are good candidates for monitoring. Monitoring can extend the service life and avoid or postpone replacement, repair or strengthening work. Many bridges constitute a bottleneck in the transport network they serve with few or no alternative routes. The amount of resources saved, both to the owner and the users, by reducing the amount of non-operational time can easily justify the extra investment in monitoring. This thesis consists of an extended summary and three appended papers. The thesis presents advances in sensor technology, damage identification algorithms and Bridge Weigh-In-Motion techniques. Two case studies are carried out. In the first a bridge and traffic monitoring system is implemented in a highway suspension bridge to study the cause of unexpected wear in the bridge bearings. In the second a fully operational Bridge Weigh-In-Motion system is developed and deployed in a steel railway bridge. The gathered data was studied to obtain a characterization of the site specific traffic. / QC 20111122

Submitted by Edisangela Bastos (edisangela@ufpa.br) on 2015-01-27T18:33:19Z No. of bitstreams: 2 license_rdf: 22974 bytes, checksum: 99c771d9f0b9c46790009b9874d49253 (MD5) Dissertacao_PesagemMovimentoCaracterizacao.pdf: 5817774 bytes, checksum: bffe4c7106d0747f52959b54504702a0 (MD5) / Rejected by Edisangela Bastos (edisangela@ufpa.br), reason: on 2015-01-29T18:13:44Z (GMT) / Submitted by Edisangela Bastos (edisangela@ufpa.br) on 2015-01-30T17:50:00Z No. of bitstreams: 2 license_rdf: 22974 bytes, checksum: 99c771d9f0b9c46790009b9874d49253 (MD5) Dissertacao_PesagemMovimentoCaracterizacao.pdf: 5817774 bytes, checksum: bffe4c7106d0747f52959b54504702a0 (MD5) / Approved for entry into archive by Albirene Aires (albireneufpa@gmail.com) on 2015-02-02T12:06:43Z (GMT) No. of bitstreams: 2 license_rdf: 22974 bytes, checksum: 99c771d9f0b9c46790009b9874d49253 (MD5) Dissertacao_PesagemMovimentoCaracterizacao.pdf: 5817774 bytes, checksum: bffe4c7106d0747f52959b54504702a0 (MD5) / Made available in DSpace on 2015-02-02T12:06:43Z (GMT). No. of bitstreams: 2 license_rdf: 22974 bytes, checksum: 99c771d9f0b9c46790009b9874d49253 (MD5) Dissertacao_PesagemMovimentoCaracterizacao.pdf: 5817774 bytes, checksum: bffe4c7106d0747f52959b54504702a0 (MD5) Previous issue date: 2014 / Nesta dissertação é apresentado o desenvolvimento de algoritmos para aplicação do método Bridge-Weigh In Motion (B-WIM) para a pesagem em movimento de trens e para a caracterização do tráfego ferroviário, permitindo-se obter informações sobre a velocidade de passagem dos trens, número e espaçamento entre eixos. Os sistemas B-WIM a partir de uma simples instrumentação permitem determinar as cargas por eixo de veículos em movimento, eliminando o efeito dinâmico. Foram implementados os algoritmos para a determinação dos valores referentes a geometria do trem e das cargas, que foi validado a partir de um exemplo teórico, onde se simulou a passagem de um trem de características conhecidas sobre a ponte e as cargas por eixos foram determinadas com 100% de exatidão. Além disso, foi feito um exemplo numérico em elementos finitos, de um viaduto em concreto armado para aplicação do método, onde foi feita a determinação das cargas por eixo para diferentes velocidades de passagem do trem. A fim de reduzir o tempo de processamento nas análises do exemplo numérico, foi desenvolvido um algoritmo para a geração de cargas nodais no modelo numérico que reduziram o tempo de processamento em até 96% quando comparado com a análise de múltiplos passos (“Multi-Step”), que simula automaticamente a passagem do trem sobre a estrutura. Finalmente, o método foi testado em um caso real a partir de monitorações realizadas em um viaduto de concreto armado da Estrada de Ferro Carajás. Apesar de não ter sido possível a determinação das cargas por eixo da locomotiva, foi possível medir precisamente o peso bruto total da locomotiva quando se utilizou o modelo constitutivo de Collins & Mitchell (1991) para o concreto. / This Master’s Thesis presents the development of algorithms for application of Bridge- Weigh In Motion (B-WIM) for weighing moving trains and method for the characterization of rail traffic, allowing up to obtain information about the speed of passage of trains , number and axle spacing. The B-WIM systems from a simple instrumentation for determining the axle loads of moving vehicles, eliminating the dynamic effect. The algorithms for determining the values related the geometry of the train and axle loads were implemented, which was validated from a theoretical example, where we simulated the passage of a train of known characteristics over the bridge and axle loads were determined 100% accuracy. In addition, a numerical example was done in finite element method, of a reinforced concrete viaduct for application of the method, where was determine axle loads for different speeds of train passage. In order to reduce the processing time of the analysis in the numerical example, an algorithm for generating the numerical model nodal loads was implemented that have reduced processing time by 96% compared to the analysis of multi-step, which automatically simulates the passage of the train over the structure. Finally, the method was tested on a real case from monitoring tests realized on a reinforced concrete viaduct in the Carajás Railroad. Although it was not possible to determine the axle load locomotive, it was possible to measure accurately the gross weight of the locomotive when using the constitutive model of Collins and Mitchell (1991) for concrete.