Sensores de fibra ótica para arquiteturas e-Health

In this work, optical fiber sensors were developed and optimized for biomedical applications in wearable and non-intrusive and/or invisible solutions. As it was intended that the developed devices would not interfere with the user's movements and their daily life, the fibre optic sensors presented several advantages when compared to conventional electronic sensors, among others, the following stand out: size and reduced weight, biocompatibility, safety, immunity to electromagnetic interference and high sensitivity. In a first step, wearable devices with fibre optic sensors based in Fiber Bragg gratings (FBG) were developed to be incorporated into insoles to monitor different walking parameters based on the analysis of the pressure exerted on several areas of the insole. Still within this theme, other sensors were developed using the same sensing technology, but capable of monitoring pressure and shear forces simultaneously. This work was pioneering and allowed monitoring one of the main causes of foot ulceration in people with diabetes: shear. At a later stage, the study focused on the issue related with the appearance of ulcers in people with reduced mobility and wheelchair users. In order to contribute to the mitigation of this scourge, a system was developed composed of a network of fibre optic sensors capable of monitoring the pressure at various points of the wheelchair. It not only measures the pressure at each point, but also monitors the posture of the wheelchair user and advises him/her to change posture regularly to reduce the probability of this pathology occurring. Still within this application, another work was developed where the sensor not only monitored the pressure but also the temperature in each of the analysis points, thus indirectly measuring shear. In another phase, plastic fibre optic sensors were studied and developed to monitor the body posture of an office chair user. Simultaneously, software was developed capable of monitoring and showing the user all the acquired data in real time and warning for incorrect postures, as well as advising for work breaks. In a fourth phase, the study focused on the development of highly sensitive sensors embedded in materials printed by a 3D printer. The sensor was composed of an optical fibre with a FBG and the sensor body of a flexible polymeric material called "Flexible". This material was printed on a 3D printer and during its printing the optical fibre was incorporated. The sensor proved to be highly sensitive and was able to monitor respiratory and cardiac rate, both in wearable solutions (chest and wrist) and in "invisible" solutions (office chair).Neste trabalho foram desenvolvidos e otimizados sensores em fibra ótica para aplicações biomédicas em soluções vestíveis e não intrusivas/ou invisíveis. Tendo em conta que se pretende que os dispositivos desenvolvidos não interfiram com os movimentos e o dia-a-dia do utilizador, os sensores de fibra ótica apresentam inúmeras vantagens quando comparados com os sensores eletrónicos convencionais, de entre várias, destacam-se: tamanho e peso reduzido, biocompatibilidade, segurança, imunidade a interferências eletromagnéticas e elevada sensibilidade. Numa primeira etapa, foram desenvolvidos dispositivos vestíveis com sensores de fibra ótica baseados em redes de Bragg (FBG) para incorporar em palmilhas de modo a monitorizar diferentes parâmetros da marcha com base na análise da pressão exercida em várias zonas da palmilha. Ainda no âmbito deste tema, adicionalmente, foram desenvolvidos sensores utilizando a mesma tecnologia de sensoriamento, mas capazes de monitorizar simultaneamente pressão e forças de cisalhamento. Este trabalho foi pioneiro e permitiu monitorizar um dos principais responsáveis pela ulceração dos pés em pessoas com diabetes: o cisalhamento. Numa fase posterior, o estudo centrou-se na temática relacionada com o aparecimento de úlceras em pessoas com mobilidade reduzida e utilizadores de cadeiras de rodas. De modo a contribuir para a mitigação deste flagelo, procurou-se desenvolver um sistema composto por uma rede de sensores de fibra ótica capaz de monitorizar a pressão em vários pontos de uma cadeira de rodas e não só aferir a pressão em cada ponto, mas monitorizar a postura do cadeirante e aconselhá-lo a mudar de postura com regularidade, de modo a diminuir a probabilidade de ocorrência desta patologia. Ainda dentro desta aplicação, foi publicado um outro trabalho onde o sensor não só monitoriza a pressão como também a temperatura em cada um dos pontos de análise, conseguindo aferir assim indiretamente o cisalhamento. Numa outra fase, foi realizado o estudo e desenvolvimento de sensores de fibra ótica de plástico para monitorizar a postura corporal de um utilizador de uma cadeira de escritório. Simultaneamente, foi desenvolvido um software capaz de monitorizar e mostrar ao utilizador todos os dados adquiridos em tempo real e advertir o utilizador de posturas incorretas, bem como aconselhar para pausas no trabalho. Numa quarta fase, o estudo centrou-se no desenvolvimento de sensores altamente sensíveis embebidos em materiais impressos 3D. O sensor é composto por uma fibra ótica com uma FBG e o corpo do sensor por um material polimérico flexível, denominado “Flexible”. O sensor foi impresso numa impressora 3D e durante a sua impressão foi incorporada a fibra ótica. O sensor demonstrou ser altamente sensível e foi capaz de monitorizar frequência respiratória e cardíaca, tanto em soluções vestíveis (peito e pulso) como em soluções “invisíveis” (cadeira de escritório).Programa Doutoral em Engenharia Físic

Smart Sensors for Healthcare and Medical Applications

This book focuses on new sensing technologies, measurement techniques, and their applications in medicine and healthcare. Specifically, the book briefly describes the potential of smart sensors in the aforementioned applications, collecting 24 articles selected and published in the Special Issue “Smart Sensors for Healthcare and Medical Applications”. We proposed this topic, being aware of the pivotal role that smart sensors can play in the improvement of healthcare services in both acute and chronic conditions as well as in prevention for a healthy life and active aging. The articles selected in this book cover a variety of topics related to the design, validation, and application of smart sensors to healthcare

The use of a CFBG sensor for detecting damage in composite laminates and adhesively bonded joints

Reliable in-situ damage detection techniques which can detennine the existence and location of damage in composite materials and structures are critical for the effective use of these materials. In this work, embedded chirped fibre Bragg grating (CFBG) sensors have been shown to be successful for both detection and location of matrix cracks in composite laminates and disbond detection in bonded composite joints. In all the cases, the CFBG reflection spectra were predicted using commercial software and agreed well with the experimental results. In the matrix cracking work, single matrix cracks in cross-ply GFRP (glass' fibre reinforced plastic) laminates were detected and located using a CFBG sensor embedded within the 0° plies, near the 0/90 interface. The CFBG sensor showed an approximately sinusoidal variation of the intensity of the reflected spectrum at the position of the crack, enabling both crack development and crack position to be identified. It was shown that the precise position of the cracks does not correspond with the bottom of a dip in the reflected spectrum, as has previously been thought. Disbond initiation and progression from either end of a composite bonded joint was monitored by embedding the CFBG sensor in one of the GFRP adherends, with the low wavelength end ofthe sensor positioned at the cut end ofthe adherend. A shift in the low wavelength end of the spectrum to lower wavelengths indicated disbond initiation and movement of a perturbation in the reflected spectrum towards higher wavelengths indicated disbond propagation. In a related fashion, disbond initiation and propagation was detected from the high-wavelength end ofthe spectrum (adjacent to the other cut end of the adherend). With the aid of a parametric study based on a closed-form solution for the strain field in the bonded joint (available in the literature), it has been shown that the sensitivity ofthe CFBG sensor in detecting the disbond depends mainly on the position of the sensor within the adherend and the strain distribution in the adherend. Finally, artificial manufacturing defects were introduced into GFRP-GFRP bonded joints using Teflon inserts and it has been demonstrated that the location of the defects is possible using the CFBG technique.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Prediction and mitigation of scour and scour damage to Vermont bridges

Over 300 Vermont bridges were damaged in the 2011 Tropical Storm Irene and many experienced significant scour. Successfully mitigating bridge scour in future flooding events depends on our ability to reliably estimate scour potential, design safe and economical foundation elements accounting for scour potential, design effective scour prevention and countermeasures, and design reliable and economically feasible monitoring systems, which served as the motivation for this study. This project sought to leverage data on existing Vermont bridges and case studies of bridge scour damage, and integrate available information from stream geomorphology to aid in prediction of bridge scour vulnerability. Tropical Storm Irene’s impact on Vermont bridges was used as a case study, providing damage information on a wide range of bridges throughout the State. Multiple data sources were combined in an effort to include data, which represents the complex, interconnected processes of stream stability and bridge scour, then identify and incorporate feature that would be useful in a probabilistic model to predict bridge susceptibility to scour damage. The research also sought to identify features that could be included in inspections and into a scour rating system that are capable of assessing network-level scour vulnerability of bridges more holistically. This research also sought to review existing scour countermeasures and scour monitoring technologies available in the literature and examine efficacy of new, indirect scour countermeasures and passive scour monitoring techniques. The specific objectives of this research were to: (1) review the literature and identify methods/technologies that are adaptable to Vermont; (2) analyze Tropical Storm Irene bridge damage information and observations by collecting and geo-referencing all available bridge records and stream geomorphic assessment data into a comprehensive database for identifying features that best represent bridge scour damage; (3) conduct watershed analysis on all bridges, including creation of stream power data to assess if watershed stream power improves the prediction of bridge scour damage; and (4) investigate new scour countermeasures and monitoring technologies, and provide recommendations on implementations

Damage detection and identification in fiber reinforced plastic structural members and field bridges using acoustic emission technique

With the increased use of fiber reinforced polymer (FRP) based structural systems for rehabilitation of existing and construction of new bridges there is a requirement for identification of critical components of these structural systems and the determination of critical damage thresholds in them. Of the many available non-destructive techniques (NDT), acoustic emission (AE) monitoring had been identified as one of the most popular techniques applicable for damage discrimination in composites. The current study aimed at using patterns in AE data for the identification of damage modes exhibited by composite structural systems. The extensive experimental program involved testing of two structural systems: (i) Reinforced concrete specimens with CFRP retrofit to study debonding failure mechanism and (ii) GFRP laminates coupon specimens tested under varied load conditions to study critical failure modes such as fiber breakage, matrix cracking, delamination and debonding. Real-time AE monitoring was also conducted for a newly installed FRP deck field bridge subjected to live load tests. The AE data collected from the bridge revealed the overall structural performance of the new bridge and helped establish baseline AE activity for future condition evaluation. The AE data acquired from all the experimental tests conducted in this research were subjected two methods of analysis. The first analysis technique involved subjecting the data to the traditional signal processing techniques and identifying various AE sources by visual observations of trends in correlation plots. Meanwhile the same dataset was analyzed using neural networks to perform pattern recognition. In this work, a methodology based on the use of an unsupervised k-means clustering to generate the learning dataset for the training of the multi-layer perceptron (MLP) classifier was developed. The method adopted here showed good results for the clustering and classification of AE signals from different sources for the specimens studied in this research. But, clustering does not always lead to a unique solution and some failure mode characteristics were more easily identifiable than others. Thus further study for enriching of the training dataset is warranted. The high performance efficiency achieved by the developed neural network model for damage identification in full scale specimens further confirms the potential of the developed methodology in being feasible for damage identification in full-scale structures

Testing of Materials and Elements in Civil Engineering

This book was proposed and organized as a means to present recent developments in the field of testing of materials and elements in civil engineering. For this reason, the articles highlighted in this editorial relate to different aspects of testing of different materials and elements in civil engineering, from building materials to building structures. The current trend in the development of testing of materials and elements in civil engineering is mainly concerned with the detection of flaws and defects in concrete elements and structures, and acoustic methods predominate in this field. As in medicine, the trend is towards designing test equipment that allows one to obtain a picture of the inside of the tested element and materials. Interesting results with significance for building practices were obtained

Computer Vision Based Structural Identification Framework for Bridge Health Mornitoring

The objective of this dissertation is to develop a comprehensive Structural Identification (St-Id) framework with damage for bridge type structures by using cameras and computer vision technologies. The traditional St-Id frameworks rely on using conventional sensors. In this study, the collected input and output data employed in the St-Id system are acquired by series of vision-based measurements. The following novelties are proposed, developed and demonstrated in this project: a) vehicle load (input) modeling using computer vision, b) bridge response (output) using full non-contact approach using video/image processing, c) image-based structural identification using input-output measurements and new damage indicators. The input (loading) data due vehicles such as vehicle weights and vehicle locations on the bridges, are estimated by employing computer vision algorithms (detection, classification, and localization of objects) based on the video images of vehicles. Meanwhile, the output data as structural displacements are also obtained by defining and tracking image key-points of measurement locations. Subsequently, the input and output data sets are analyzed to construct novel types of damage indicators, named Unit Influence Surface (UIS). Finally, the new damage detection and localization framework is introduced that does not require a network of sensors, but much less number of sensors. The main research significance is the first time development of algorithms that transform the measured video images into a form that is highly damage-sensitive/change-sensitive for bridge assessment within the context of Structural Identification with input and output characterization. The study exploits the unique attributes of computer vision systems, where the signal is continuous in space. This requires new adaptations and transformations that can handle computer vision data/signals for structural engineering applications. This research will significantly advance current sensor-based structural health monitoring with computer-vision techniques, leading to practical applications for damage detection of complex structures with a novel approach. By using computer vision algorithms and cameras as special sensors for structural health monitoring, this study proposes an advance approach in bridge monitoring through which certain type of data that could not be collected by conventional sensors such as vehicle loads and location, can be obtained practically and accurately