917 resultados para structural health monitoring method


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The paper proposes a new application of non-parametric statistical processing of signals recorded from vibration tests for damage detection and evaluation on I-section steel segments. The steel segments investigated constitute the energy dissipating part of a new type of hysteretic damper that is used for passive control of buildings and civil engineering structures subjected to earthquake-type dynamic loadings. Two I-section steel segments with different levels of damage were instrumented with piezoceramic sensors and subjected to controlled white noise random vibrations. The signals recorded during the tests were processed using two non-parametric methods (the power spectral density method and the frequency response function method) that had never previously been applied to hysteretic dampers. The appropriateness of these methods for quantifying the level of damage on the I-shape steel segments is validated experimentally. Based on the results of the random vibrations, the paper proposes a new index that predicts the level of damage and the proximity of failure of the hysteretic damper

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This paper reports on the development of an artificial neural network (ANN) method to detect laminar defects following the pattern matching approach utilizing dynamic measurement. Although structural health monitoring (SHM) using ANN has attracted much attention in the last decade, the problem of how to select the optimal class of ANN models has not been investigated in great depth. It turns out that the lack of a rigorous ANN design methodology is one of the main reasons for the delay in the successful application of the promising technique in SHM. In this paper, a Bayesian method is applied in the selection of the optimal class of ANN models for a given set of input/target training data. The ANN design method is demonstrated for the case of the detection and characterisation of laminar defects in carbon fibre-reinforced beams using flexural vibration data for beams with and without non-symmetric delamination damage.

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Sudden changes in the stiffness of a structure are often indicators of structural damage. Detection of such sudden stiffness change from the vibrations of structures is important for Structural Health Monitoring (SHM) and damage detection. Non-contact measurement of these vibrations is a quick and efficient way for successful detection of sudden stiffness change of a structure. In this paper, we demonstrate the capability of Laser Doppler Vibrometry to detect sudden stiffness change in a Single Degree Of Freedom (SDOF) oscillator within a laboratory environment. The dynamic response of the SDOF system was measured using a Polytec RSV-150 Remote Sensing Vibrometer. This instrument employs Laser Doppler Vibrometry for measuring dynamic response. Additionally, the vibration response of the SDOF system was measured through a MicroStrain G-Link Wireless Accelerometer mounted on the SDOF system. The stiffness of the SDOF system was experimentally determined through calibrated linear springs. The sudden change of stiffness was simulated by introducing the failure of a spring at a certain instant in time during a given period of forced vibration. The forced vibration on the SDOF system was in the form of a white noise input. The sudden change in stiffness was successfully detected through the measurements using Laser Doppler Vibrometry. This detection from optically obtained data was compared with a detection using data obtained from the wireless accelerometer. The potential of this technique is deemed important for a wide range of applications. The method is observed to be particularly suitable for rapid damage detection and health monitoring of structures under a model-free condition or where information related to the structure is not sufficient.

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Although aspects of power generation of many offshore renewable devices are well understood, their dynamic responses under high wind and wave conditions are still to be investigated to a great detail. Output only statistical markers are important for these offshore devices, since access to the device is limited and information about the exposure conditions and the true behaviour of the devices are generally partial, limited, and vague or even absent. The markers can summarise and characterise the behaviour of these devices from their dynamic response available as time series data. The behaviour may be linear or nonlinear and consequently a marker that can track the changes in structural situations can be quite important. These markers can then be helpful in assessing the current condition of the structure and can indicate possible intervention, monitoring or assessment. This paper considers a Delay Vector Variance based marker for changes in a tension leg platform tested in an ocean wave basin for structural changes brought about by single column dampers. The approach is based on dynamic outputs of the device alone and is based on the estimation of the nonlinearity of the output signal. The advantages of the selected marker and its response with changing structural properties are discussed. The marker is observed to be important for monitoring the as- deployed structural condition and is sensitive to changes in such conditions. Influence of exposure conditions of wave loading is also discussed in this study based only on experimental data.

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Pavements tend to deteriorate with time under repeated traffic and/or environmental loading. By detecting pavement distresses and damage early enough, it is possible for transportation agencies to develop more effective pavement maintenance and rehabilitation programs and thereby achieve significant cost and time savings. The structural health monitoring (SHM) concept can be considered as a systematic method for assessing the structural state of pavement infrastructure systems and documenting their condition. Over the past several years, this process has traditionally been accomplished through the use of wired sensors embedded in bridge and highway pavement. However, the use of wired sensors has limitations for long-term SHM and presents other associated cost and safety concerns. Recently, micro-electromechanical sensors and systems (MEMS) and nano-electromechanical systems (NEMS) have emerged as advanced/smart-sensing technologies with potential for cost-effective and long-term SHM. This two-pronged study evaluated the performance of commercial off-the-shelf (COTS) MEMS sensors embedded in concrete pavement (Final Report Volume I) and developed a wireless MEMS multifunctional sensor system for health monitoring of concrete pavement (Final Report Volume II).

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A brief description of the main features of the health planning technique developed by the "Centro de Estudios del Desarrollo" (CENDES) in Venezuela, and proposed by the Pan-American Health Organization for use in Latin America, is presented. This presentation is followed by an appraisal of the planning method which includes comments both upon its positive aspects and upon its negative points. Comments are also made referring to other recent publications of the WHO/PAHO on health planning. In conclusion, the CENDES technique is considered a health planning method of great potential for use especially in underdeveloped areas, the success of its application depending upon the hability of the health planners to introduce the necessary modifications to adapt to the local circunstamces.

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Environmental pollution continues to be an emerging study field, as there are thousands of anthropogenic compounds mixed in the environment whose possible mechanisms of toxicity and physiological outcomes are of great concern. Developing methods to access and prioritize the screening of these compounds at trace levels in order to support regulatory efforts is, therefore, very important. A methodology based on solid phase extraction followed by derivatization and gas chromatography-mass spectrometry analysis was developed for the assessment of four endocrine disrupting compounds (EDCs) in water matrices: bisphenol A, estrone, 17b-estradiol and 17a-ethinylestradiol. The study was performed, simultaneously, by two different laboratories in order to evaluate the robustness of the method and to increase the quality control over its application in routine analysis. Validation was done according to the International Conference on Harmonisation recommendations and other international guidelines with specifications for the GC-MS methodology. Matrix-induced chromatographic response enhancement was avoided by using matrix-standard calibration solutions and heteroscedasticity has been overtaken by a weighted least squares linear regression model application. Consistent evaluation of key analytical parameters such as extraction efficiency, sensitivity, specificity, linearity, limits of detection and quantification, precision, accuracy and robustness was done in accordance with standards established for acceptance. Finally, the application of the optimized method in the assessment of the selected analytes in environmental samples suggested that it is an expedite methodology for routine analysis of EDC residues in water matrices.

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

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

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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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This paper explores some aspects of health monitoring in relation to black and ethnic minority populations in London. It considers where research in London and elsewhere has shown evidence of inequalities between ethnic groups, and draws out the issues for recording, analysis and sharing of ethnic-specific data.

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Micro-electromechanical systems (MEMS) provide vast improvements over existing sensing methods in the context of structural health monitoring (SHM) of highway infrastructure systems, including improved system reliability, improved longevity and enhanced system performance, improved safety against natural hazards and vibrations, and a reduction in life cycle cost in both operating and maintaining the infrastructure. Advancements in MEMS technology and wireless sensor networks provide opportunities for long-term continuous, real-time structural health monitoring of pavements and bridges at low cost within the context of sustainable infrastructure systems. The primary objective of this research was to investigate the use of MEMS in highway structures for health monitoring purposes. This study focused on investigating the use of MEMS and their potential applications in concrete through a comprehensive literature review, a vendor survey, and a laboratory study, as well as a small-scale field study. Based on the comprehensive literature review and vendor survey, the latest information available on off-the-shelf MEMS devices, as well as research prototypes, for bridge, pavement, and traffic applications were synthesized. A commercially-available wireless concrete monitoring system based on radio-frequency identification (RFID) technology and off-the-shelf temperature and humidity sensors were tested under controlled laboratory and field conditions. The test results validated the ability of the RFID wireless concrete monitoring system in accurately measuring the temperature both inside the laboratory and in the field under severe weather conditions. In consultation with the project technical advisory committee (TAC), the most relevant MEMS-based transportation infrastructure research applications to explore in the future were also highlighted and summarized.

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Increasing anthropogenic pressures urge enhanced knowledge and understanding of the current state of marine biodiversity. This baseline information is pivotal to explore present trends, detect future modifications and propose adequate management actions for marine ecosystems. Coralligenous outcrops are a highly diverse and structurally complex deep-water habitat faced with major threats in the Mediterranean Sea. Despite its ecological, aesthetic and economic value, coralligenous biodiversity patterns are still poorly understood. There is currently no single sampling method that has been demonstrated to be sufficiently representative to ensure adequate community assessment and monitoring in this habitat. Therefore, we propose a rapid non-destructive protocol for biodiversity assessment and monitoring of coralligenous outcrops providing good estimates of its structure and species composition, based on photographic sampling and the determination of presence/absence of macrobenthic species. We used an extensive photographic survey, covering several spatial scales (100s of m to 100s of km) within the NW Mediterranean and including 2 different coralligenous assemblages: Paramuricea clavata (PCA) and Corallium rubrum assemblage (CRA). This approach allowed us to determine the minimal sampling area for each assemblage (5000 cm² for PCA and 2500 cm²for CRA). In addition, we conclude that 3 replicates provide an optimal sampling effort in order to maximize the species number and to assess the main biodiversity patterns of studied assemblages in variability studies requiring replicates. We contend that the proposed sampling approach provides a valuable tool for management and conservation planning, monitoring and research programs focused on coralligenous outcrops, potentially also applicable in other benthic ecosystems