848 resultados para NonDestructive Evaluation, Compressive Sensing, Lamb waves, Structural Health Monitoring


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This work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.

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The continuous technological advances require materials with properties that conventional material cannot display. Material property combinations are being the focus to the development of composite materials, which are considered a multiphase material that exhibits properties of the constituent phases. One interesting material to be studied as sensing material is the composite made of ferroelectric ceramic and polymeric matrix as a two-phases composite material. In that case, the combinations properties intended are the high piezo and pyroelectric activities of the dense ceramic with the impact resistance, flexibility, formability and low densities of the polymer. Using the piezoelectric property of the composite film, it can be used to detect acoustic emission (AE), which is a transient elastic wave generated by sudden deformation in materials under stress. AE can be applied for evaluating the health of structures in a nondestructive way and without any lapse of time. The preliminary result indicates that the composite Pz34/PEEK can be used as sensing material for nondestructive evaluation. ©2009 IEEE.

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This paper describes an image compounding technique based on the use of different apodization functions, the evaluation of the signals phases and information from the interaction of different propagation modes of Lamb waves with defects for enhanced damage detection, resolution and contrast. A 16 elements linear array is attached to a 1 mm thickness isotropic aluminum plate with artificial defects. The array can excite the fundamental A0 and S0 modes at the frequencies of 100 kHz and 360 kHz, respectively. For each mode two synthetic aperture (SA) images with uniform and Blackman apodization and one image of Coherence Factor Map (CFM) are obtained. The specific interaction between each propagation mode and the defects and the characteristics of acoustic radiation patterns due to different apodization functions result in images with different resolution and contrast. From the phase information one of the SA images is selected at each pixel to compound the final image. The SA images are multiplied by the CFM image to improve contrast and for the dispersive A0 mode it is used a technique for dispersion compensation. There is a contrast improvement of 47.5 dB, reducing the dead zone and improving resolution and damage detection. © 2012 IEEE.

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Several Lamb wave modes can be coupled to a particular structure, depending on its geometry and transducer used to generate the guided waves. Each Lamb mode interacts in a particular form with different types of defects, like notches, delamination, surface defects, resulting in different information which can be used to improve damage detection and characterization. An image compounding technique that uses the information obtained from different propagation modes of Lamb waves for non-destructive testing of plate-like structures is proposed. A linear array consisting of 16 piezoelectric elements is attached to a 1 mm thickness aluminum plate, coupling the fundamental A0 and S0 modes at the frequencies of 100 kHz and 360 kHz, respectively. For each mode two images are obtained from amplitude and phase information: one image using the Total Focusing Method (TFM) and one phase image obtained from the Sign Coherence Factor (SCF). Each TFM image is multiplied by the SCF image of the respective mode to improve contrast and reduce side and grating lobes effects. The high dispersive characteristic of the A0 mode is compensated for adequate defect detection. The information in the SCF images is used to select one of the TFM mode images, at each pixel, to obtain the compounded image. As a result, dead zone is reduced, resolution and contrast are improved, enhancing damage detection when compared to the use of only one mode. © 2013 Elsevier Ltd.

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Pós-graduação em Engenharia Mecânica - FEIS

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Background: Despite the consensus regarding the existence of a relationship between “impacts on oral health” and “health-related quality of life”, this relationship, considering the latent nature of these variables, is still poorly investigated. Thus, we performed this study in order to determine the magnitude of the impacts of oral health, demographic and symptom/clinical variables on the health-related quality of life in a Brazilian sample of dental patients. Methods: A total of 1,007 adult subjects enrolled in the School of Dentistry of São Paulo State University (UNESP) - Araraquara Campus for dentistry care between September/2012 and April/2013, participated. 72.4 % were female. The mean age was 45.7 (SD = 12.5) years. The Oral Health Impact Profile (OHIP-14) and the Short Form Health Survey (SF-36) were used. The demographic and symptom/clinical variables collected were gender, age, economic status, presence of pain and chronic disease. The impact of studied variables on health-related quality of life were evaluated with a structural equation model, considering the factor “Health” as the central construct. The fit of the model was first analyzed by the evaluation of the goodness of fit indices (χ 2 /df ≤ 2.0, CFI and TLI ≥ 0.90 and RMSEA < 0.10) and the evaluation of the variables’ impact over health-related quality of life was based on the statistical significance of causal paths (β), evaluated by z tests, for a significance level of 5 %. Results: We observed adequate fit of the model to the data (χ 2 /df = 3.55; CFI = 0.95; TLI = 0.94; RMSEA = 0.05). The impacts on oral health explained 28.0 % of the variability of the health-related quality of life construct, while the total variance explained of the model was 39.0 %. For the demographic and symptom/clinical variables, only age, presence of pain and chronic disease showed significant impacts (p < 0.05). Conclusion: The oral health, age, presence of pain and chronic disease of individuals had significant influence on health-related quality of life.

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Asphalt pavements suffer various failures due to insufficient quality within their design lives. The American Association of State Highway and Transportation Officials (AASHTO) Mechanistic-Empirical Pavement Design Guide (MEPDG) has been proposed to improve pavement quality through quantitative performance prediction. Evaluation of the actual performance (quality) of pavements requires in situ nondestructive testing (NDT) techniques that can accurately measure the most critical, objective, and sensitive properties of pavement systems. The purpose of this study is to assess existing as well as promising new NDT technologies for quality control/quality assurance (QC/QA) of asphalt mixtures. Specifically, this study examined field measurements of density via the PaveTracker electromagnetic gage, shear-wave velocity via surface-wave testing methods, and dynamic stiffness via the Humboldt GeoGauge for five representative paving projects covering a range of mixes and traffic loads. The in situ tests were compared against laboratory measurements of core density and dynamic modulus. The in situ PaveTracker density had a low correlation with laboratory density and was not sensitive to variations in temperature or asphalt mix type. The in situ shear-wave velocity measured by surface-wave methods was most sensitive to variations in temperature and asphalt mix type. The in situ density and in situ shear-wave velocity were combined to calculate an in situ dynamic modulus, which is a performance-based quality measurement. The in situ GeoGauge stiffness measured on hot asphalt mixtures several hours after paving had a high correlation with the in situ dynamic modulus and the laboratory density, whereas the stiffness measurement of asphalt mixtures cooled with dry ice or at ambient temperature one or more days after paving had a very low correlation with the other measurements. To transform the in situ moduli from surface-wave testing into quantitative quality measurements, a QC/QA procedure was developed to first correct the in situ moduli measured at different field temperatures to the moduli at a common reference temperature based on master curves from laboratory dynamic modulus tests. The corrected in situ moduli can then be compared against the design moduli for an assessment of the actual pavement performance. A preliminary study of microelectromechanical systems- (MEMS)-based sensors for QC/QA and health monitoring of asphalt pavements was also performed.

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Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

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Piezoelectric array transducers applications are becoming usual in the ultrasonic non-destructive testing area. However, the number of elements can increase the system complexity, due to the necessity of multichannel circuitry and to the large amount of data to be processed. Synthetic aperture techniques, where one or few transmission and reception channels are necessary, and the data are post-processed, can be used to reduce the system complexity. Another possibility is to use sparse arrays instead of a full-populated array. In sparse arrays, there is a smaller number of elements and the interelement spacing is larger than half wavelength. In this work, results of ultrasonic inspection of an aluminum plate with artificial defects using guided acoustic waves and sparse arrays are presented. Synthetic aperture techniques are used to obtain a set of images that are then processed with an image compounding technique, which was previously evaluated only with full-populated arrays, in order to increase the resolution and contrast of the images. The results with sparse arrays are equivalent to the ones obtained with full-populated arrays in terms of resolution. Although there is an 8 dB contrast reduction when using sparse arrays, defect detection is preserved and there is the advantage of a reduction in the number of transducer elements and data volume. © 2013 Brazilian Society for Automatics - SBA.

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This paper introduces an area- and power-efficient approach for compressive recording of cortical signals used in an implantable system prior to transmission. Recent research on compressive sensing has shown promising results for sub-Nyquist sampling of sparse biological signals. Still, any large-scale implementation of this technique faces critical issues caused by the increased hardware intensity. The cost of implementing compressive sensing in a multichannel system in terms of area usage can be significantly higher than a conventional data acquisition system without compression. To tackle this issue, a new multichannel compressive sensing scheme which exploits the spatial sparsity of the signals recorded from the electrodes of the sensor array is proposed. The analysis shows that using this method, the power efficiency is preserved to a great extent while the area overhead is significantly reduced resulting in an improved power-area product. The proposed circuit architecture is implemented in a UMC 0.18 [Formula: see text]m CMOS technology. Extensive performance analysis and design optimization has been done resulting in a low-noise, compact and power-efficient implementation. The results of simulations and subsequent reconstructions show the possibility of recovering fourfold compressed intracranial EEG signals with an SNR as high as 21.8 dB, while consuming 10.5 [Formula: see text]W of power within an effective area of 250 [Formula: see text]m × 250 [Formula: see text]m per channel.

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Background. Health literacy is an important determinant for quality health care, and affects communication between patients and physicians. Poor communication may result in negative effects in health. Improved communication between patients and physicians could positively affect health outcomes. Communication skills are teachable.^ Objectives. (1) to evaluate the process involved in the design and implementation of a health literacy intervention targeting pediatric providers’ communication skills at the Texas Children’s Health Plan in Houston, Texas; and (2) to describe lessons learned from this process that may be used in future attempts to address the issue of health literacy and health communication. ^ Design/methods. The process evaluation of the implementation of a health literacy strategy at the Texas Children’s Health Plan (TCHP) consisted of a critical analysis of all documents and minutes from meetings of the team of investigators. It also involved a secondary analysis of data collected between December 2006 and June 2007. Descriptive statistics, paired t-test and Wilcoxon-signed-rank test were employed in analyzing the data. This information was complemented with a limited review of existing literature on communication skills training programs. ^ Results. The design of the educational intervention followed recommendations from experts in the field of health literacy. The delivery of the intervention was possible and benefited from existing resources and logistics within the TCHP. Very few targeted providers participated in two offerings of the workshop (6.6% and 1.7% respectively). After the educational intervention, providers showed increased knowledge of health literacy facts and its effects in health (p=0.001); increased awareness of the low health literacy problem (p=0.003); increased expectations for change in practice (p=0.002), and intent to use health literacy strategies for communication immediately following the intervention (p=0.001). Low participation indicated the need for further investigation of barriers to, and means for successful implementation of programs aimed to improving health communication. ^ Conclusions. A short, focused intervention utilizing health literacy strategies for communication appeared effective in increasing knowledge and intentions for change in a small group of pediatric providers. ^

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Contact Spatially Resolved Spectroscopy (SRS) measurements by means of a fiber-optics probe were employed for nondestructive assessment and monitoring of Braeburn apples during shelflife storage. SRS measurements and estimation of optical properties were calibrated and validated by means of liquid optical phantoms with known optical properties and a metamodeling method. The acquired optical properties (absorption and reduced scattering coefficients) for the apples during shelf-life storage were found to provide useful information for nondestructive evaluation of apple quality attributes (firmness and SSC) and for monitoring the changes in their microstructure and chemical composition. On-line SRS measurement was achieved by mounting the SRS probe over a conveyor system

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Acknowledgments Financial Support: HERU and HSRU receive a core grant from the Chief Scientist’s Office of the Scottish Government Health and Social Care Directorates, and the Centre for Clinical epidemiology & Evaluation is funded by Vancouver Coastal Health Authority. The model used for the illustrative case study in this paper was developed as part of a NHS Technology Assessment Review, funded by the National Institute for Health Research (NIHR) Health Technology Assessment Program (project number 09/146/01). The views and opinions expressed in this paper are those of the authors and do not necessarily reflect those of the Scottish Government, NHS, Vancouver Coastal Health, NIHR HTA Program or the Department of Health. The authors wish to thank Kathleen Boyd and members of the audience at the UK Health Economists Study Group, for comments received on an earlier version of this paper. We also wish to thank Cynthia Fraser (University of Aberdeen) for literature searches undertaken to inform the manuscript, and Mohsen Sadatsafavi (University of British Columbia) for comments on an earlier draft