123 resultados para SHM


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The structural health monitoring (SHM) systems based on electromechanical (E/M) impedance technique have been widely investigated. Although many studies indicate the reliability of this technique, some practical considerations still have to be considered in real applications. This paper presents an experimental analysis of the effect of the structure area on the system's performance. The results indicate that the sensitivity of the system to detect damage decreases significantly when the host structure has large cross-section area. Copyright © 2009 by ASME.

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This paper presents a new approach for damage detection in structural health monitoring systems exploiting the coherence function between the signals from PZT (Lead Zirconate Titanate) transducers bonded to a host structure. The physical configuration of this new approach is similar to the configuration used in Lamb wave based methods, but the analysis and operation are different. A PZT excited by a signal with a wide frequency range acts as an actuator and others PZTs are used as sensors to receive the signal. The coherences between the signals from the PZT sensors are obtained and the standard deviation for each coherence function is computed. It is demonstrated through experimental results that the standard deviation of the coherence between the signals from the PZTs in healthy and damaged conditions is a very sensitive metric index to detect damage. Tests were carried out on an aluminum plate and the results show that the proposed methodology could be an excellent approach for structural health monitoring (SHM) applications.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Engenharia Elétrica - FEIS

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Structural Health Monitoring (SHM) is the process of characterization for existing civil structures that proposes for damage detection and structural identification. It's based firstly on the collection of data that are inevitably affected by noise. In this work a procedure to denoise the measured acceleration signal is proposed, based on EMD-thresholding techniques. Moreover the velocity and displacement responses are estimated, starting from measured acceleration.

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Nowadays, devices that monitor the health of structures consume a lot of power and need a lot of time to acquire, process, and send the information about the structure to the main processing unit. To decrease this time, fast electronic devices are starting to be used to accelerate this processing. In this paper some hardware algorithms implemented in an electronic logic programming device are described. The goal of this implementation is accelerate the process and diminish the information that has to be send. By reaching this goal, the time the processor needs for treating all the information is reduced and so the power consumption is reduced too.

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Ageing and deterioration of infrastructure is a challenge facing transport authorities. In
particular, there is a need for increased bridge monitoring in order to provide adequate
maintenance and to guarantee acceptable levels of transport safety. The Intelligent
Infrastructure group at Queens University Belfast (QUB) are working on a number of aspects
of infrastructure monitoring and this paper presents summarised results from three distinct
monitoring projects carried out by this group. Firstly the findings from a project on next
generation Bridge Weight in Motion (B-WIM) are reported, this includes full scale field testing
using fibre optic strain sensors. Secondly, results from early phase testing of a computer
vision system for bridge deflection monitoring are reported on. This research seeks to exploit
recent advances in image processing technology with a view to developing contactless
bridge monitoring approaches. Considering the logistical difficulty of installing sensors on a
‘live’ bridge, contactless monitoring has some inherent advantages over conventional
contact based sensing systems. Finally the last section of the paper presents some recent
findings on drive by bridge monitoring. In practice a drive-by monitoring system will likely
require GPS to allow the response of a given bridge to be identified; this study looks at the
feasibility of using low-cost GPS sensors for this purpose, via field trials. The three topics
outlined above cover a spectrum of SHM approaches namely, wired monitoring, contactless
monitoring and drive by monitoring

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Para se evitarem agentes mutagênicos no ambiente são necessários indicadores sensíveis para detectar todo o espectro desses compostos. Tais sistemas indicadores tem sido definidos como testes de mutagênese de tipo II, ou seja, aqueles que apresentam alta sensibilidade e baixa especificidade. A maioria dos bioensaios vegetais são considerados testes do tipo II, com especial referencia para os ensaios do micronúcleo e do pelo estaminal em Tradescantia (comelinacea), e o ensaio do grão de pólen ceroso em milho. Outro bioensaio vegetal de interesse para o monitoramento de agentes mutagênicos ambientais e o teste do mosaicismo em soja, que permite especulação sobre o mecanismo envolvido na toxicidade genética. O bioensaio não exige qualquer instrumentação sofisticada, e e adequado para experimentação in situ. Esses bioensaios vem sendo empregados com sucesso em estudos sobre a mutagenicidade de pesticidas aplicados conforme prescrição agronômica. Resultados adicionais sobre a utilização desses bioensaios in situ nas mais diversas situações indicam que esses testes são adequados para o monitoramento extensivo de mutagênese ambiental.

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The thesis explores recent technology developments in the field of structural health monitoring and its application to railway bridge projects. It focuses on two main topics. First, service loads and effect of environmental actions are modelled. In particular, the train moving load and its interaction with rail track is considered with different degrees of detail. Hence, results are compared with real-time experimental measurements. Secondly, the work concerns the identification, definition and modelling process of damages for a prestressed concrete railway bridge, and their implementation inside FEM models. Along with a critical interpretation of the in-field measurements, this approach results in the development of undamaged and damaged databases for the AI-aided detection of anomalies and the definition of threshold levels to prompt automatic alert interventions. In conclusion, an innovative solution for the development of the railway weight-in-motion system is proposed.

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Dissertação para obtenção do grau de Mestre em Engenharia Mecânica na Área de Manutenção e Produção

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Of the approximately 25,000 bridges in Iowa, 28% are classified as structurally deficient, functionally obsolete, or both. Because many Iowa bridges require repair or replacement with a relatively limited funding base, there is a need to develop new bridge materials that may lead to longer life spans and reduced life-cycle costs. In addition, new and effective methods for determining the condition of structures are needed to identify when the useful life has expired or other maintenance is needed. Due to its unique alloy blend, high-performance steel (HPS) has been shown to have improved weldability, weathering capabilities, and fracture toughness than conventional structural steels. Since the development of HPS in the mid-1990s, numerous bridges using HPS girders have been constructed, and many have been economically built. The East 12th Street Bridge, which replaced a deteriorated box girder bridge, is Iowa’s first bridge constructed using HPS girders. The new structure is a two-span bridge that crosses I-235 in Des Moines, Iowa, providing one lane of traffic in each direction. A remote, continuous, fiber-optic based structural health monitoring (SHM) system for the bridge was developed using off-the-shelf technologies. In the system, sensors strategically located on the bridge collect raw strain data and then transfer the data via wireless communication to a gateway system at a nearby secure facility. The data are integrated and converted to text files before being uploaded automatically to a website that provides live strain data and a live video stream. A data storage/processing system at the Bridge Engineering Center in Ames, Iowa, permanently stores and processes the data files. Several processes are performed to check the overall system’s operation, eliminate temperature effects from the complete strain record, compute the global behavior of the bridge, and count strain cycles at the various sensor locations.

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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.