969 resultados para Statistical damage identification
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Vibration-based damage identification (VBDI) techniques have been developed in part to address the problems associated with an aging civil infrastructure. To assess the potential of VBDI as it applies to highway bridges in Iowa, three applications of VBDI techniques were considered in this study: numerical simulation, laboratory structures, and field structures. VBDI techniques were found to be highly capable of locating and quantifying damage in numerical simulations. These same techniques were found to be accurate in locating various types of damage in a laboratory setting with actual structures. Although there is the potential for these techniques to quantify damage in a laboratory setting, the ability of the methods to quantify low-level damage in the laboratory is not robust. When applying these techniques to an actual bridge, it was found that some traditional applications of VBDI methods are capable of describing the global behavior of the structure but are most likely not suited for the identification of typical damage scenarios found in civil infrastructure. Measurement noise, boundary conditions, complications due to substructures and multiple material types, and transducer sensitivity make it very difficult for present VBDI techniques to identify, much less quantify, highly localized damage (such as small cracks and minor changes in thickness). However, while investigating VBDI techniques in the field, it was found that if the frequency-domain response of the structure can be generated from operating traffic load, the structural response can be animated and used to develop a holistic view of the bridge’s response to various automobile loadings. By animating the response of a field bridge, concrete cracking (in the abutment and deck) was correlated with structural motion and problem frequencies (i.e., those that cause significant torsion or tension-compression at beam ends) were identified. Furthermore, a frequency-domain study of operational traffic was used to identify both common and extreme frequencies for a given structure and loading. Common traffic frequencies can be compared to problem frequencies so that cost-effective, preventative solutions (either structural or usage-based) can be developed for a wide range of IDOT bridges. Further work should (1) perfect the process of collecting high-quality operational frequency response data; (2) expand and simplify the process of correlating frequency response animations with damage; and (3) develop efficient, economical, preemptive solutions to common damage types.
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This work is divided into three volumes: Volume I: Strain-Based Damage Detection; Volume II: Acceleration-Based Damage Detection; Volume III: Wireless Bridge Monitoring Hardware. Volume I: In this work, a previously-developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The statistical damage-detection tool, control-chart-based damage-detection methodologies, were further investigated and advanced. For the validation of the damage-detection approaches, strain data were obtained from a sacrificial specimen attached to the previously-utilized US 30 Bridge over the South Skunk River (in Ames, Iowa), which had simulated damage,. To provide for an enhanced ability to detect changes in the behavior of the structural system, various control chart rules were evaluated. False indications and true indications were studied to compare the damage detection ability in regard to each methodology and each control chart rule. An autonomous software program called Bridge Engineering Center Assessment Software (BECAS) was developed to control all aspects of the damage detection processes. BECAS requires no user intervention after initial configuration and training. Volume II: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The objective of this part of the project was to validate/integrate a vibration-based damage-detection algorithm with the strain-based methodology formulated by the Iowa State University Bridge Engineering Center. This report volume (Volume II) presents the use of vibration-based damage-detection approaches as local methods to quantify damage at critical areas in structures. Acceleration data were collected and analyzed to evaluate the relationships between sensors and with changes in environmental conditions. A sacrificial specimen was investigated to verify the damage-detection capabilities and this volume presents a transmissibility concept and damage-detection algorithm that show potential to sense local changes in the dynamic stiffness between points across a joint of a real structure. The validation and integration of the vibration-based and strain-based damage-detection methodologies will add significant value to Iowa’s current and future bridge maintenance, planning, and management Volume III: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. This report volume (Volume III) summarizes the energy harvesting techniques and prototype development for a bridge monitoring system that uses wireless sensors. The wireless sensor nodes are used to collect strain measurements at critical locations on a bridge. The bridge monitoring hardware system consists of a base station and multiple self-powered wireless sensor nodes. The base station is responsible for the synchronization of data sampling on all nodes and data aggregation. Each wireless sensor node include a sensing element, a processing and wireless communication module, and an energy harvesting module. The hardware prototype for a wireless bridge monitoring system was developed and tested on the US 30 Bridge over the South Skunk River in Ames, Iowa. The functions and performance of the developed system, including strain data, energy harvesting capacity, and wireless transmission quality, were studied and are covered in this volume.
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The objective of this work was to develop a low-cost portable damage detection tool to assess and predict damage areas in highway bridges. The proposed tool was based on standard vibration-based damage identification (VBDI) techniques but was extended to a new approach based on operational traffic load. The methodology was tested using numerical simulations, laboratory experiments, and field testing.
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La idea básica de detección de defectos basada en vibraciones en Monitorización de la Salud Estructural (SHM), es que el defecto altera las propiedades de rigidez, masa o disipación de energía de un sistema, el cual, altera la respuesta dinámica del mismo. Dentro del contexto de reconocimiento de patrones, esta tesis presenta una metodología híbrida de razonamiento para evaluar los defectos en las estructuras, combinando el uso de un modelo de la estructura y/o experimentos previos con el esquema de razonamiento basado en el conocimiento para evaluar si el defecto está presente, su gravedad y su localización. La metodología involucra algunos elementos relacionados con análisis de vibraciones, matemáticas (wavelets, control de procesos estadístico), análisis y procesamiento de señales y/o patrones (razonamiento basado en casos, redes auto-organizativas), estructuras inteligentes y detección de defectos. Las técnicas son validadas numérica y experimentalmente considerando corrosión, pérdida de masa, acumulación de masa e impactos. Las estructuras usadas durante este trabajo son: una estructura tipo cercha voladiza, una viga de aluminio, dos secciones de tubería y una parte del ala de un avión comercial.
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Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in structures in order to improve reliability and reduce life-cycle costs. The greatest challenge for designing a SHM system is knowing what changes to look for and how to classify them. Different approaches for SHM have been proposed for damage identification, each one with advantages and drawbacks. This paper presents a methodology for improvement in vibration signal analysis using statistics information involving the probability density. Generally, the presence of noises in input and output signals results in false alarms, then, it is important that the methodology can minimize this problem. In this paper, the proposed approach is experimentally tested in a flexible plate using a piezoelectric (PZT) actuator to provide the disturbance.
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Structural damage identification is basically a nonlinear phenomenon; however, nonlinear procedures are not used currently in practical applications due to the complexity and difficulty for implementation of such techniques. Therefore, the development of techniques that consider the nonlinear behavior of structures for damage detection is a research of major importance since nonlinear dynamical effects can be erroneously treated as damage in the structure by classical metrics. This paper proposes the discrete-time Volterra series for modeling the nonlinear convolution between the input and output signals in a benchmark nonlinear system. The prediction error of the model in an unknown structural condition is compared with the values of the reference structure in healthy condition for evaluating the method of damage detection. Since the Volterra series separate the response of the system in linear and nonlinear contributions, these indexes are used to show the importance of considering the nonlinear behavior of the structure. The paper concludes pointing out the main advantages and drawbacks of this damage detection methodology. © (2013) Trans Tech Publications.
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In this paper is presented a multilayer perceptron neural network combined with the Nelder-Mead Simplex method to detect damage in multiple support beams. The input parameters are based on natural frequencies and modal flexibility. It was considered that only a number of modes were available and that only vertical degrees of freedom were measured. The reliability of the proposed methodology is assessed from the generation of random damages scenarios and the definition of three types of errors, which can be found during the damage identification process. Results show that the methodology can reliably determine the damage scenarios. However, its application to large beams may be limited by the high computational cost of training the neural network.
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Evolutionary algorithms are suitable to solve damage identification problems in a multiobjective context. However, the performance of these methods can deteriorate quickly with increasing noise intensities originating numerous uncertainties. In this work, a statistic structural damage detection method formulated in a multiobjective context is proposed, taking into account the uncertainties existing. The presented method is verified by a number of simulated damage scenarios. The effects of noise on damage detection are investigated.
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The effects of vehicle speed for Structural Health Monitoring (SHM) of bridges under operational conditions are studied in this paper. The moving vehicle is modelled as a single degree oscillator traversing a damaged beam at a constant speed. The bridge is modelled as simply supported Euler-Bernoulli beam with a breathing crack. The breathing crack is treated as a nonlinear system with bilinear stiffness characteristics related to the opening and closing of crack. The unevenness of the bridge deck is modelled using road classification according to ISO 8606:1995(E). The stochastic description of the unevenness of the road surface is used as an aid to monitor the health of the structure in its operational condition. Numerical simulations are conducted considering the effects of changing vehicle speed with regards to cumulant based statistical damage detection parameters. The detection and calibration of damage at different levels is based on an algorithm dependent on responses of the damaged beam due to passages of the load. Possibilities of damage detection and calibration under benchmarked and non-benchmarked cases are considered. Sensitivity of calibration values is studied. The findings of this paper are important for establishing the expectations from different vehicle speeds on a bridge for damage detection purposes using bridge-vehicle interaction where the bridge does not need to be closed for monitoring. The identification of bunching of these speed ranges provides guidelines for using the methodology developed in the paper.
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In the recent years, vibration-based structural damage identification has been subject of significant research in structural engineering. The basic idea of vibration-based methods is that damage induces mechanical properties changes that cause anomalies in the dynamic response of the structure, which measures allow to localize damage and its extension. Vibration measured data, such as frequencies and mode shapes, can be used in the Finite Element Model Updating in order to adjust structural parameters sensible at damage (e.g. Young’s Modulus). The novel aspect of this thesis is the introduction into the objective function of accurate measures of strains mode shapes, evaluated through FBG sensors. After a review of the relevant literature, the case of study, i.e. an irregular prestressed concrete beam destined for roofing of industrial structures, will be presented. The mathematical model was built through FE models, studying static and dynamic behaviour of the element. Another analytical model was developed, based on the ‘Ritz method’, in order to investigate the possible interaction between the RC beam and the steel supporting table used for testing. Experimental data, recorded through the contemporary use of different measurement techniques (optical fibers, accelerometers, LVDTs) were compared whit theoretical data, allowing to detect the best model, for which have been outlined the settings for the updating procedure.
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Dissertação para obtenção do grau de Mestre em Engenharia Mecânica na Área de Manutenção e Produção
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Ao longo dos últimos anos, acompanhada da evolução tecnológica, da dificuldade da inspeção visual e da consciencialização dos efeitos de uma má inspeção, verificou-se uma maior sensibilidade para a importância da monitorização estrutural, principalmente nas grandes infra-estruturas de engenharia civil. Os sistemas de monitorização estrutural permitem o acompanhamento contínuo do comportamento de uma determinada estrutura de tal forma que com os dados obtidos, é possível avaliar alterações no comportamento da mesma. Com isso, tem-se desenvolvido e implementado estratégias de identificação de danos estruturais com o intuito de aumentar a fiabilidade estrutural e evitar precocemente que alterações na condição da estrutura possam evoluir para situações mais severas. Neste contexto, a primeira parte desta dissertação consiste numa introdução à monitorização estrutural e à deteção de dano estrutural. Relativamente à monitorização, são expostos os seus objetivos e os princípios da sua aplicação. Conjuntamente são apresentados e descritos os principais sensores e são explicadas as funcionalidades de um sistema de aquisição de dados. O segundo tema aborda a importância da deteção de dano introduzindo os métodos estudados neste trabalho. Destaca-se o método das linhas de influência, o método da curvatura dos modos de vibração e o método da transformada de wavelet. Na segunda parte desta dissertação são apresentados dois casos de estudo. O primeiro estudo apresenta uma componente numérica e uma componente experimental. Estuda-se um modelo de viga que se encontra submetida a vários cenários de dano e valida-se a capacidade do método das linhas de influência em detetar e localizar essas anomalias. O segundo estudo consiste na modelação numérica de uma ponte real, na posterior simulação de cenários de dano e na análise comparativa da eficácia de cada um dos três métodos de deteção de dano na identificação e localização dos danos simulados. Por último, são apresentadas as principais conclusões deste trabalho e são sugeridos alguns tópicos a explorar na elaboração de trabalhos futuros.
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Within the civil engineering field, the use of the Finite Element Method has acquired a significant importance, since numerical simulations have been employed in a broad field, which encloses the design, analysis and prediction of the structural behaviour of constructions and infrastructures. Nevertheless, these mathematical simulations can only be useful if all the mechanical properties of the materials, boundary conditions and damages are properly modelled. Therefore, it is required not only experimental data (static and/or dynamic tests) to provide references parameters, but also robust calibration methods able to model damage or other special structural conditions. The present paper addresses the model calibration of a footbridge bridge tested with static loads and ambient vibrations. Damage assessment was also carried out based on a hybrid numerical procedure, which combines discrete damage functions with sets of piecewise linear damage functions. Results from the model calibration shows that the model reproduces with good accuracy the experimental behaviour of the bridge.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Engenharia Mecânica - FEIS