941 resultados para Sensors


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Dissertação de Mestrado, Engenharia Elétrica e Eletrónica, Instituto Superior de Engenharia, Universidade do Algarve, 2015

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The objective of the work described in this dissertation is the development of new wireless passive force monitoring platforms for applications in the medical field, specifically monitoring lower limb prosthetics. The developed sensors consist of stress sensitive, magnetically soft amorphous metallic glass materials. The first technology is based on magnetoelastic resonance. Specifically, when exposed to an AC excitation field along with a constant DC bias field, the magnetoelastic material mechanically vibrates, and may reaches resonance if the field frequency matches the mechanical resonant frequency of the material. The presented work illustrates that an applied loading pins portions of the strip, effectively decreasing the strip length, which results in an increase in the frequency of the resonance. The developed technology is deployed in a prototype lower limb prosthetic sleeve for monitoring forces experienced by the distal end of the residuum. This work also reports on the development of a magnetoharmonic force sensor comprised of the same material. According to the Villari effect, an applied loading to the material results in a change in the permeability of the magnetic sensor which is visualized as an increase in the higher-order harmonic fields of the material. Specifically, by applying a constant low frequency AC field and sweeping the applied DC biasing field, the higher-order harmonic components of the magnetic response can be visualized. This sensor technology was also instrumented onto a lower limb prosthetic for proof of deployment; however, the magnetoharmonic sensor illustrated complications with sensor positioning and a necessity to tailor the interface mechanics between the sensing material and the surface being monitored. The novelty of these two technologies is in their wireless passive nature which allows for long term monitoring over the life time of a given device. Additionally, the developed technologies are low cost. Recommendations for future works include improving the system for real-time monitoring, useful for data collection outside of a clinical setting.

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Opto-acoustic imaging is a growing field of research in recent years, providing functional imaging of physiological biomarkers, such as the oxygenation of haemoglobin. Piezo electric transducers are the industry standard detector for ultrasonics, but their limited bandwidth, susceptibility to electromagnetic interference and their inversely proportional sensitivity to size all affect the detector performance. Sensors based on polymer optical fibres (POF) are immune to electromagnetic interference, have lower acoustic impedance and a reduced Young's Modulus compared to silica fibres. Furthermore, POF enables the possibility of a wideband sensor and a size appropriate to endoscopy. Micro-structured POF (mPOF) used in an interferometric detector has been shown to be an order of magnitude more sensitive than silica fibre at 1 MHz and 3 times more sensitive at 10 MHz. We present the first opto-acoustic measurements obtained using a 4.7mm PMMA mPOF Bragg grating with a fibre diameter of 130 μm and present the lateral directivity pattern of a PMMA mPOF FBG ultrasound sensor over a frequency range of 1-50 MHz. We discuss the impact of the pattern with respect to the targeted application and draw conclusions on how to mitigate the problems encountered.

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Non-intrusive monitoring of health state of induction machines within industrial process and harsh environments poses a technical challenge. In the field, winding failures are a major fault accounting for over 45% of total machine failures. In the literature, many condition monitoring techniques based on different failure mechanisms and fault indicators have been developed where the machine current signature analysis (MCSA) is a very popular and effective method at this stage. However, it is extremely difficult to distinguish different types of failures and hard to obtain local information if a non-intrusive method is adopted. Typically, some sensors need to be installed inside the machines for collecting key information, which leads to disruption to the machine operation and additional costs. This paper presents a new non-invasive monitoring method based on GMRs to measure stray flux leaked from the machines. It is focused on the influence of potential winding failures on the stray magnetic flux in induction machines. Finite element analysis and experimental tests on a 1.5-kW machine are presented to validate the proposed method. With time-frequency spectrogram analysis, it is proven to be effective to detect several winding faults by referencing stray flux information. The novelty lies in the implement of GMR sensing and analysis of machine faults.

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Electrical properties of polycrystalline gas sensors are analyzed by d.c. and a.c. measurements. d.c. electrical conductivity values compared with those obtained by admittance spectroscopy methods help to obtain a detailed 'on line' analysis of conductivity-modulated gas sensors. The electrical behaviour of grain boundaries is obtained and a new design of sensors can be achieved by enhancing the activity of surface states in the detecting operation. A Schottky barrier model is used to explain the grain boundary action under the presence of surrounding gases. The height of this barrier is a function of gas concentration due to the trapping of excess charge generated by gas adsorption at the interface. A comparison between this dependence, and a plot of the real and imaginary components of the admittance versus frequency at different gas concentrations, provides information on the different parameters that play a role in the conduction mechanisms. These methods have been applied to the design of a CO sensor based on tin oxide films for domestic purposes, the characteristics of which are presented.

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Hydroelectric systems are well-known for large scale power generation. However, there are virtually no studies on energy harvesting with these systems to produce tens or hundreds of milliwatts. The goal of this work was to study which design parameters from large-scale systems can be applied to small-scale systems. Two types of hydro turbines were evaluated. The first one was a Pelton turbine which is suitable for high heads and low flow rates. The second one was a propeller turbine used for low heads and high flow rates. Several turbine geometries and nozzle diameters were tested for the Pelton system. For the propeller, a three-bladed turbine was tested for different heads and draft tubes. The mechanical power provided by these turbines was measured to evaluate the range of efficiencies of these systems. A small three-phase generator was developed for coupling with the turbines in order to evaluate the generated electric power. Selected turbines were used to test battery charging with hydroelectric systems and a comparison between several efficiencies of the systems was made. Keywords

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Interactions in mobile devices normally happen in an explicit manner, which means that they are initiated by the users. Yet, users are typically unaware that they also interact implicitly with their devices. For instance, our hand pose changes naturally when we type text messages. Whilst the touchscreen captures finger touches, hand movements during this interaction however are unused. If this implicit hand movement is observed, it can be used as additional information to support or to enhance the users’ text entry experience. This thesis investigates how implicit sensing can be used to improve existing, standard interaction technique qualities. In particular, this thesis looks into enhancing front-of-device interaction through back-of-device and hand movement implicit sensing. We propose the investigation through machine learning techniques. We look into problems on how sensor data via implicit sensing can be used to predict a certain aspect of an interaction. For instance, one of the questions that this thesis attempts to answer is whether hand movement during a touch targeting task correlates with the touch position. This is a complex relationship to understand but can be best explained through machine learning. Using machine learning as a tool, such correlation can be measured, quantified, understood and used to make predictions on future touch position. Furthermore, this thesis also evaluates the predictive power of the sensor data. We show this through a number of studies. In Chapter 5 we show that probabilistic modelling of sensor inputs and recorded touch locations can be used to predict the general area of future touches on touchscreen. In Chapter 7, using SVM classifiers, we show that data from implicit sensing from general mobile interactions is user-specific. This can be used to identify users implicitly. In Chapter 6, we also show that touch interaction errors can be detected from sensor data. In our experiment, we show that there are sufficient distinguishable patterns between normal interaction signals and signals that are strongly correlated with interaction error. In all studies, we show that performance gain can be achieved by combining sensor inputs.

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Hydroelectric systems are well-known for large scale power generation. However, there are virtually no studies on energy harvesting with these systems to produce tens or hundreds of milliwatts. The goal of this work was to study which design parameters from large-scale systems can be applied to small-scale systems. Two types of hydro turbines were evaluated. The first one was a Pelton turbine which is suitable for high heads and low flow rates. The second one was a propeller turbine used for low heads and high flow rates. Several turbine geometries and nozzle diameters were tested for the Pelton system. For the propeller, a three-bladed turbine was tested for different heads and draft tubes. The mechanical power provided by these turbines was measured to evaluate the range of efficiencies of these systems. A small three-phase generator was developed for coupling with the turbines in order to evaluate the generated electric power. Selected turbines were used to test battery charging with hydroelectric systems and a comparison between several efficiencies of the systems was made. Keywords

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Site-specific management (SSM) is a form of precision agriculture whereby decisions on resource application and agronomic practices are improved to better match soil and crop requirements as they vary in the field. SSM enables the identification of regions (homogeneous management zones) within the area delimited by field boundaries. These subfield regions constitute areas that have similar permanent characteristics. Traditional soil and pasture sampling and the necessary laboratory analysis are time-consuming, labour-intensive and cost prohibitive, not viable from a SSM perspective because it needs a large number of soil and pasture samples in order to achieve a good representation of soil properties, nutrient levels and pasture quality and productivity. The main objective of this work was to evaluate technologies which have potential for monitoring aspects related to spatial and temporal variability of soil nutrients and pasture green and dry matter yield (respectively, GM and DM, in kg/ha) and support to decision making for the farmer. Three types of sensors were evaluated in a 7ha pasture experimental field: an electromagnetic induction sensor (“DUALEM 1S”, which measures the soil apparent electrical conductivity, ECa), an active optical sensor ("OptRx®", which measures the NDVI, “Normalized Difference Vegetation Index”) and a capacitance probe ("GrassMaster II" which estimates plant mass). The results indicate the possibility of using a soil electrical conductivity probe as, probably, the best tool for monitoring not only some of the characteristics of the soil, but also those of the pasture, which could represent an important help in simplifying the process of sampling and support SSM decision making, in precision agriculture projects. On the other hand, the significant and very strong correlations obtained between capacitance and NDVI and between any of these parameters and the pasture productivity shows the potential of these tools for monitoring the evolution of spatial and temporal patterns of the vegetative growth of biodiverse pasture, for identifying different plant species and variability in pasture yield in Alentejo dry-land farming systems. These results are relevant for the selection of an adequate sensing system for a particular application and open new perspectives for other works that would allow the testing, calibration and validation of the sensors in a wider range of pasture production conditions, namely the extraordinary diversity of botanical species that are characteristic of the Mediterranean region at the different periods of the year.

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The primary aim of the research activity presented in this PhD thesis was the development of an innovative hardware and software solution for creating a unique tool for kinematics and electromyographic analysis of the human body in an ecological setting. For this purpose, innovative algorithms have been proposed regarding different aspects of inertial and magnetic data elaboration: magnetometer calibration and magnetic field mapping (Chapter 2), data calibration (Chapter 3) and sensor-fusion algorithm. Topics that may conflict with the confidentiality agreement between University of Bologna and NCS Lab will not be covered in this thesis. After developing and testing the wireless platform, research activities were focused on its clinical validation. The first clinical study aimed to evaluate the intra and interobserver reproducibility in order to evaluate three-dimensional humero-scapulo-thoracic kinematics in an outpatient setting (Chapter 4). A second study aimed to evaluate the effect of Latissimus Dorsi Tendon Transfer on shoulder kinematics and Latissimus Dorsi activation in humerus intra - extra rotations (Chapter 5). Results from both clinical studies have demonstrated the ability of the developed platform to enter into daily clinical practice, providing useful information for patients' rehabilitation.

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This Ph.D. Thesis concerns the design and characterisation of functional electrochemical interfaces in organic electronic devices for bioelectronic applications. The Thesis is structured as follows: Chapter I – Technological context that has inspired the research, introduction to Organic Bioelectronics and literature review concerning Organic Electrochemical Transistors (OECTs) for sensing applications. Chapter II – Working principle of an all-polymeric OECT and operando microscopic characterization using scanning electrochemical techniques. Chapter III – Dopamine detection with all-polymeric OECT sensors. Development of a potentiodynamic approach to address selectivity issues in the presence of interfering species and design of a needle-type, sub-micrometric OECT sensor for spatially resolved detection of biological Dopamine concentrations. Chapter IV – Development of an OECT pH sensor. Characterization of the electrochemical transducer and functionalization of the OECT gate electrode with the sensing material. Potentiodynamic and potentiostatic operation modalities are explored and the sensing performances are assessed in both cases. The final device is realized on a flexible substrate and tested in Artificial Sweat. Chapter V – Study of two-terminal, electrochemically gated sensors inspired by the OECT configuration. Design and characterization of novel functional materials showing a potentiometric transduction of the chemical signal that can be exploited in the realization of electrochemical sensors with simplified geometry for wearable applications. Chapter VI – Conclusion.

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Questo progetto di tesi fa parte di un più ampio studio clinico condotto all’interno dell’azienda NCS Lab (Carpi,(MO)), in collaborazione con il Dr. Claudio Chillemi (ICOT, Latina (RM)) che mira ad eseguire un confronto tra diverse tecniche chirurgiche per la riparazione della cuffia dei rotatori. Lo studio clinico in questione durerà circa due anni: per questo motivo i dati analizzati in questo progetto di tesi provengono solo dal gruppo di pazienti acquisiti nella fase preoperatoria. Tutti i dati sono stati acquisiti utilizzando i sensori magneto-inerziali WISE (tecnologia proprietaria dell’azienda NCS Lab). Questo lavoro di tesi si propone, quindi, di valutare la ripetibilità del movimento in termini di coefficiente di correlazione multipla e di estrapolare alcuni parametri di interesse clinico come, ad esempio, i range di movimento (ROM) della scapola e dell’omero e il ritmo scapolo-omerale (SHR). Questi parametri sono stati poi caratterizzati da un punto di vista statistico al fine di valutare le differenze tra arto patologico e controlaterale. Sono state calcolate, inoltre, le prediction bands con lo scopo di descrivere le differenze tra arto patologico e controlaterale nella coordinazione scapolo-omerale dei pazienti. Per quanto riguarda la ripetibilità del movimento, i risultati ottenuti in questo lavoro di tesi mostrano che la rotazione medio-laterale è caratterizzata da un eccellente CMC sia per l'arto patologico che per il controlaterale. Inoltre, sono state riscontrate differenze significative dal punto di vista statistico tra le distribuzioni dei range di movimento dell'arto patologico e controlaterale. Tali differenze sono state trovate anche per quanto riguarda il ritmo scapolo-omerale.

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Wearable electronic textiles are an emerging research field playing a pivotal role among several different technological areas such as sensing, communication, clothing, health monitoring, information technology, and microsystems. The possibility to realise a fully-textile platform, endowed with various sensors directly realised with textile fibres and fabric, represents a new challenge for the entire research community. Among several high-performing materials, the intrinsically conductive poly(3,4-ethylenedioxythiophene) (PEDOT), doped with poly(styrenesulfonic acid) (PSS), or PEDOT:PSS, is one of the most representative and utilised, having an excellent chemical and thermal stability, as well as reversible doping state and high conductivity. This work relies on PEDOT:PSS combined with sensible materials to design, realise, and develop textile chemical and physical sensors. In particular, chloride concentration and pH level sensors in human sweat for continuous monitoring of the wearer's hydration status and stress level are reported. Additionally, a prototype smart bandage detecting the moisture level and pH value of a bed wound to allow the remote monitoring of the healing process of severe and chronic wounds is described. Physical sensors used to monitor the pressure distribution for rehabilitation, workplace safety, or sport tracking are also presented together with a novel fully-textile device able to measure the incident X-ray dose for medical or security applications where thin, comfortable, and flexible features are essential. Finally, a proof-of-concept for an organic-inorganic textile thermoelectric generator that harvests energy directly from body heat has been proposed. Though further efforts must be dedicated to overcome issues such as durability, washability, power consumption, and large-scale production, the novel, versatile, and widely encompassing area of electronic textiles is a promising protagonist in the upcoming technological revolution.

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The Smart Grid needs a large amount of information to be operated and day by day new information is required to improve the operation performance. It is also fundamental that the available information is reliable and accurate. Therefore, the role of metrology is crucial, especially if applied to the distribution grid monitoring and the electrical assets diagnostics. This dissertation aims at better understanding the sensors and the instrumentation employed by the power system operators in the above-mentioned applications and studying new solutions. Concerning the research on the measurement applied to the electrical asset diagnostics: an innovative drone-based measurement system is proposed for monitoring medium voltage surge arresters. This system is described, and its metrological characterization is presented. On the other hand, the research regarding the measurements applied to the grid monitoring consists of three parts. The first part concerns the metrological characterization of the electronic energy meters’ operation under off-nominal power conditions. Original test procedures have been designed for both frequency and harmonic distortion as influence quantities, aiming at defining realistic scenarios. The second part deals with medium voltage inductive current transformers. An in-depth investigation on their accuracy behavior in presence of harmonic distortion is carried out by applying realistic current waveforms. The accuracy has been evaluated by means of the composite error index and its approximated version. Based on the same test setup, a closed-form expression for the measured current total harmonic distortion uncertainty estimation has been experimentally validated. The metrological characterization of a virtual phasor measurement unit is the subject of the third and last part: first, a calibrator has been designed and the uncertainty associated with its steady-state reference phasor has been evaluated; then this calibrator acted as a reference, and it has been used to characterize the phasor measurement unit implemented within a real-time simulator.

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Power electronic circuits are moving towards higher switching frequencies, exploiting the capabilities of novel devices to shrink the dimension of passive components. This trend demands sensors capable enough to operate at such high frequencies. This thesis aims to demonstrate through experimental characterization, the broadband capability of a fully integrated CMOS X-Hall current sensor in current mode interfaced with a transimpedance amplifier (TIA), chip CH09, realized in CMOS technology for power electronics applications such as power converters. The system exploits a common-mode control system to operate the dual supply system, 5-V for the X-Hall probe and 1.2-V for the readout. The developed prototype achieves a maximum acquisition bandwidth of 12 MHz, a power consumption of 11.46 mW, resolution of 39 mArms, a sensitivity of 8 % /T, and a FoM of 569-MHz/A2mW, significantly higher than current state-of-the-art. Further enhancements were proposed to CH09 as a new chip CH100, aiming for accuracy levels prerequisite for a real-time power electronic application. The TIA was optimized for a wider bandwidth of 26.7 MHz with nearly 30% reduction of the integrated input referred noise of 26.69 nArms at the probe-AFE interface in the frequency band of DC-30 MHz, and a 10% improvement in the dynamic range. The expected input range is 5-A. The chip incorporates a dual sensing chain for differential sensing to overcome common mode interferences. A novel offset cancellation technique is proposed that would require switching of polarity of bias currents. Thermal gain drift was improved by a factor of 8 and will be digitally calibrated utilizing a new built-in temperature sensor with a post calibration measurement accuracy greater than 1%. The estimated power consumption of the entire system is 55.6 mW. Both prototypes have been implemented through a 90-nm microelectronic process from STMicroelectronics and occupy a silicon area of 2.4 mm2.