933 resultados para condition monitoring system


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This paper summarizes the experience and the lessons learned from the European project PERFORM (A sophisticated multi-parametric system FOR the continuous effective assessment and monitoring of motor status in Parkinson s disease and other neurodegenerative diseases). PERFORM is aimed to provide a telehealth system for the remote monitoring of Parkinson s disease patients (PD) at their homes. This paper explains the global experience with PERFORM. It summarizes the technical performance of the system and the feedback received from the patients in terms of usability and wearability.

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This paper describes the experimental set up of a system composed by a set of wearable sensors devices for the recording of the motion signals and software algorithms for the signal analysis. This system is able to automatically detect and assess the severity of bradykinesia, tremor, dyskinesia and akinesia motor symptoms. Based on the assessment of the akinesia, the ON-OFF status of the patient is determined for each moment. The assessment performed through the automatic evaluation of the akinesia is compared with the status reported by the patients in their diaries. Preliminary results with a total recording period of 32 hours with two PD patients are presented, where a good correspondence (88.2 +/- 3.7 %) was observed. Best (93.7 por ciento) and worst (87 por ciento) correlation results are illustrated, together with the analysis of the automatic assessment of the akinesia symptom leading to the status determination. The results obtained are promising, and if confirmed with further data, this automatic assessment of PD motor symptoms will lead to a better adjustment of medication dosages and timing, cost savings and an improved quality of life of the patients.

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Esta Tesis tiene como objetivo principal el desarrollo de métodos de identificación del daño que sean robustos y fiables, enfocados a sistemas estructurales experimentales, fundamentalmente a las estructuras de hormigón armado reforzadas externamente con bandas fibras de polímeros reforzados (FRP). El modo de fallo de este tipo de sistema estructural es crítico, pues generalmente es debido a un despegue repentino y frágil de la banda del refuerzo FRP originado en grietas intermedias causadas por la flexión. La detección de este despegue en su fase inicial es fundamental para prevenir fallos futuros, que pueden ser catastróficos. Inicialmente, se lleva a cabo una revisión del método de la Impedancia Electro-Mecánica (EMI), de cara a exponer sus capacidades para la detección de daño. Una vez la tecnología apropiada es seleccionada, lo que incluye un analizador de impedancias así como novedosos sensores PZT para monitorización inteligente, se ha diseñado un procedimiento automático basado en los registros de impedancias de distintas estructuras de laboratorio. Basándonos en el hecho de que las mediciones de impedancias son posibles gracias a una colocación adecuada de una red de sensores PZT, la estimación de la presencia de daño se realiza analizando los resultados de distintos indicadores de daño obtenidos de la literatura. Para que este proceso sea automático y que no sean necesarios conocimientos previos sobre el método EMI para realizar un experimento, se ha diseñado e implementado un Interfaz Gráfico de Usuario, transformando la medición de impedancias en un proceso fácil e intuitivo. Se evalúa entonces el daño a través de los correspondientes índices de daño, intentando estimar no sólo su severidad, sino también su localización aproximada. El desarrollo de estos experimentos en cualquier estructura genera grandes cantidades de datos que han de ser procesados, y algunas veces los índices de daño no son suficientes para una evaluación completa de la integridad de una estructura. En la mayoría de los casos se pueden encontrar patrones de daño en los datos, pero no se tiene información a priori del estado de la estructura. En este punto, se ha hecho una importante investigación en técnicas de reconocimiento de patrones particularmente en aprendizaje no supervisado, encontrando aplicaciones interesantes en el campo de la medicina. De ahí surge una idea creativa e innovadora: detectar y seguir la evolución del daño en distintas estructuras como si se tratase de un cáncer propagándose por el cuerpo humano. En ese sentido, las lecturas de impedancias se emplean como información intrínseca de la salud de la propia estructura, de forma que se pueden aplicar las mismas técnicas que las empleadas en la investigación del cáncer. En este caso, se ha aplicado un algoritmo de clasificación jerárquica dado que ilustra además la clasificación de los datos de forma gráfica, incluyendo información cualitativa y cuantitativa sobre el daño. Se ha investigado la efectividad de este procedimiento a través de tres estructuras de laboratorio, como son una viga de aluminio, una unión atornillada de aluminio y un bloque de hormigón reforzado con FRP. La primera ayuda a mostrar la efectividad del método en sencillos escenarios de daño simple y múltiple, de forma que las conclusiones extraídas se aplican sobre los otros dos, diseñados para simular condiciones de despegue en distintas estructuras. Demostrada la efectividad del método de clasificación jerárquica de lecturas de impedancias, se aplica el procedimiento sobre las estructuras de hormigón armado reforzadas con bandas de FRP objeto de esta tesis, detectando y clasificando cada estado de daño. Finalmente, y como alternativa al anterior procedimiento, se propone un método para la monitorización continua de la interfase FRP-Hormigón, a través de una red de sensores FBG permanentemente instalados en dicha interfase. De esta forma, se obtienen medidas de deformación de la interfase en condiciones de carga continua, para ser implementadas en un modelo de optimización multiobjetivo, cuya solución se haya por medio de una expansión multiobjetivo del método Particle Swarm Optimization (PSO). La fiabilidad de este último método de detección se investiga a través de sendos ejemplos tanto numéricos como experimentales. ABSTRACT This thesis aims to develop robust and reliable damage identification methods focused on experimental structural systems, in particular Reinforced Concrete (RC) structures externally strengthened with Fiber Reinforced Polymers (FRP) strips. The failure mode of this type of structural system is critical, since it is usually due to sudden and brittle debonding of the FRP reinforcement originating from intermediate flexural cracks. Detection of the debonding in its initial stage is essential thus to prevent future failure, which might be catastrophic. Initially, a revision of the Electro-Mechanical Impedance (EMI) method is carried out, in order to expose its capabilities for local damage detection. Once the appropriate technology is selected, which includes impedance analyzer as well as novel PZT sensors for smart monitoring, an automated procedure has been design based on the impedance signatures of several lab-scale structures. On the basis that capturing impedance measurements is possible thanks to an adequately deployed PZT sensor network, the estimation of damage presence is done by analyzing the results of different damage indices obtained from the literature. In order to make this process automatic so that it is not necessary a priori knowledge of the EMI method to carry out an experimental test, a Graphical User Interface has been designed, turning the impedance measurements into an easy and intuitive procedure. Damage is then assessed through the analysis of the corresponding damage indices, trying to estimate not only the damage severity, but also its approximate location. The development of these tests on any kind of structure generates large amounts of data to be processed, and sometimes the information provided by damage indices is not enough to achieve a complete analysis of the structural health condition. In most of the cases, some damage patterns can be found in the data, but none a priori knowledge of the health condition is given for any structure. At this point, an important research on pattern recognition techniques has been carried out, particularly on unsupervised learning techniques, finding interesting applications in the medicine field. From this investigation, a creative and innovative idea arose: to detect and track the evolution of damage in different structures, as if it were a cancer propagating through a human body. In that sense, the impedance signatures are used to give intrinsic information of the health condition of the structure, so that the same clustering algorithms applied in the cancer research can be applied to the problem addressed in this dissertation. Hierarchical clustering is then applied since it also provides a graphical display of the clustered data, including quantitative and qualitative information about damage. The performance of this approach is firstly investigated using three lab-scale structures, such as a simple aluminium beam, a bolt-jointed aluminium beam and an FRP-strengthened concrete specimen. The first one shows the performance of the method on simple single and multiple damage scenarios, so that the first conclusions can be extracted and applied to the other two experimental tests, which are designed to simulate a debonding condition on different structures. Once the performance of the impedance-based hierarchical clustering method is proven to be successful, it is then applied to the structural system studied in this dissertation, the RC structures externally strengthened with FRP strips, where the debonding failure in the interface between the FRP and the concrete is successfully detected and classified, proving thus the feasibility of this method. Finally, as an alternative to the previous approach, a continuous monitoring procedure of the FRP-Concrete interface is proposed, based on an FBGsensors Network permanently deployed within that interface. In this way, strain measurements can be obtained under controlled loading conditions, and then they are used in order to implement a multi-objective model updating method solved by a multi-objective expansion of the Particle Swarm Optimization (PSO) method. The feasibility of this last proposal is investigated and successfully proven on both numerical and experimental RC beams strengthened with FRP.

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This paper presents a structural analysis of a masonry chimney built in the 1940s, which is currently being cataloged as local interest heritage. This structure has not served any industrial purpose for the last thirty years. The chimney is located in the town of Agost (Alicante - Spain) and directly exposed to the prevailing winds from the sea, as it is approximately 12 km away from the waterfront and there are not any significant barriers, which could protect the structure against the wind. There are longitudinal cracks and fissures all along the shaft because of the chimney’s geometrical characteristics, the effect of the masonry creep and especially the lack of maintenance. Moreover, there is also a permanent bending deformation in the upper 1/3 of the height due to the wind pressure. A numerical analysis for the static behavior against gravity and wind loads was performed using the structure’s current conditions after a detailed report of its geometry, its construction system and the cracking pattern. Afterwards, the dynamic behavior was studied, i.e. a seismic analysis using both response spectra and accelerograms in order to examine the structural stability. This work shows the pre-monitoring analysis before any experimental testing. Using the current results the future test conditions will be determined (e.g. number of sensors and monitoring point location, excitation systems, etc) prior to a possible structural reinforcement by applying composite material (fiber reinforced polymers).

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Today, faced with the constant rise of the Smart cities around the world, there is an exponential increase of the use and deployment of information technologies in the cities. The intensive use of Information Technology (IT) in these ecosystems facilitates and improves the quality of life of citizens, but in these digital communities coexist individuals whose health is affected developing or increasing diseases such as electromagnetic hypersensitivity. In this paper we present a monitoring, detection and prevention system to help this group, through which it is reported the rates of electromagnetic radiation in certain areas, based on the information that the own Smart City gives us. This work provides a perfect platform for the generation of predictive models for detection of future states of risk for humans.

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Russian gas industry: The current condition of the gas industry is one of the most crucial factors influencing the Russian state·s functioning, internal situation and international position. Not only is gas the principal energy resource in Russia, it also subsidises other sectors of the economy. Status of the main European gas exporter strengthens also Russia's importance in the international arena. New regional in-security: Ten years have passed since the Central Asian states declared their independence, but their relationship with Russia still remains close, and the latter treats them as its exclusive zone of influence. A crucial reason for keeping Central Asia within the orbit of Moscow·s influence is the fact that Russia exercises control over the most important transport routes out of the region of raw materials for the power industry, on which the economic development of Asia depends on. But this is the only manifestation of Central Asia·s economic dependence on Russia. Moscow lacks solid economic instruments (i.e. investment input or power industry dependence) to shape the situation in the region. Caspian oil and gas: Caspian stocks of energy resources are not, and most probably will not be, of any great significance on the world scale. Nevertheless it is the Caspian region which will have the opportunity to become an oil exporter which will reduce the dependence of the European countries on Arabian oil, and which will guarantee Russia the quantities of gas which are indispensable both for meeting its internal demands and for maintaining its current level of export. For Azerbaijan, Kazakhstan and Turkmenistan, the confirmation of the existence of successive oil strata is not only an opportunity to increase income, but also an additional bargaining chip in the game for the future of the whole region. The stake in this game is the opportunity to limit the economic, and by extension the political influences of Russia in the region.

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Background: Flu vaccine composition is reformulated on a yearly basis. As such, the vaccine effectiveness (VE) from previous seasons cannot be considered for subsequent years, and it is necessary to monitor the VE for each season. This study (MonitorEVA- monitoring vaccine effectiveness) intends to evaluate the feasibility of using the national influenza surveillance system (NISS) for monitoring the influenza VE. Material and methods: Data was collected within NISS during 2004 to 2014 seasons. We used a case-control design where laboratory confirmed incident influenza like illness (ILI) patients (cases) were compared to controls (ILI influenza negative). Eligible individuals consisted on all aged individuals that consult a general practitioner or emergency room with ILI symptoms with a swab collected within seven days of symptoms onset. VE was estimated as 1- odds ratio of being vaccinated in cases versus controls adjusted for age and month of onset by logistic regression. Sensitivity analyses were conducted to test possible effect of assumptions on vaccination status, ILI definition and timing of swabs (<3 days after onset). Results: During the 2004-2014 period, a total of 5302 ILI patients were collected but 798 ILI were excluded for not complying with inclusion criteria. After data restriction the sample size in both groups was higher than 148 individuals/ season; minimum sample size needed to detect a VE of at least 50% considering a level of significance of 5% and 80% power. Crude VE point estimates were under 45% in 2004/05, 2005/06, 2011/12 and 2013/14 season; between 50%-70% in 2006/07, 2008/09 and 2010/11 seasons, and above 70% in 2007/08 and 2012/13 season. From season 2006/07 to 2013/14, all crude VE estimates were statistically significant. After adjustment for age group and month of onset, the VE point estimates decreased and only 2008/09, 2012/13 and 2013/14 seasons were significant. Discussion and Conclusions: MonitorEVA was able to provide VE estimates for all seasons, including the pandemic, indicating if the VE was higher than 70% and less than 50%. When comparing with other observational studies, MonitorEVA estimates were comparable but less precise and VE estimates were in accordance with the antigenic match of the circulating virus/ vaccine strains. Given the sensitivity results, we propose a MonitorEVA based on: a) Vaccination status defined independently of number of days between vaccination and symptoms onset; b) use of all ILI data independent of the definition; c) stratification of VE according to time between onset and swab (< 3 and ≥3 days).

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National Highway Traffic Safety Administration, Office of Driver and Pedestrian Research, Washington, D.C.

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Title from cover.

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Mode of access: Internet.