993 resultados para sensor characteristics
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In the thesis the principle of work of eddy current position sensors and the main cautions that must be taken into account while sensor design process are explained. A way of automated eddy current position sensor electrical characteristics measurement is suggested. A prototype of the eddy current position sensor and its electrical characteristics are investigated. The results obtained by means of the automated measuring system are explained.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Tese de Doutoramento Ciência e Engenharia de Polímeros e Compósitos.
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This work proposes the use of a simple voltage divider circuit composed by one potentiometer and one resistor to simulate the behavior of the electrical output signal of linear and nonlinear sensors. It is a low cost way to implement practical experiments in classroom and it also enables the analysis of interesting topics of electricity. This work induces naturally to a class guide where students can build and characterize a voltage divider to explore several concepts about sensors output signal. As the result of this teaching activity it is expected that students understand fundamentals of voltage divider, potentiometer operation, fundamental sensor characteristics, transfer function, and, besides, associate directly concepts of physics and mathematics with a practical approach.
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We re-analyze the signal of non-planetary energetic neutral atoms (ENAs) in the 0.4-5.0 keV range measured with the Neutral Particle Detector (NPD) of the ASPERA-3 and ASPERA-4 experiments on board the Mars and Venus Express satellites. Due to improved knowledge of sensor characteristics and exclusion of data sets affected by instrument effects, the typical intensity of the ENA signal obtained by ASPERA-3 is an order of magnitude lower than in earlier reports. The ENA intensities measured with ASPERA-3 and ASPERA-4 now agree with each other. In the present analysis, we also correct the ENA signal for Compton-Getting and for ionization loss processes under the assumption of a heliospheric origin. We find spectral shapes and intensities consistent with those measured by the Interstellar Boundary Explorer (IBEX). The principal advantage of ASPERA with respect to the IBEX sensors is the two times better spectral resolution. In this study, we discuss the physical significance of the spectral shapes and their potential variation across the sky. At present, these observations are the only independent test of the heliospheric ENA signal measured with IBEX in this energy range. The ASPERA measurements also allow us to check for a temporal variation of the heliospheric signal as they were obtained between 2003 and 2007, whereas IBEX has been operational since the end of 2008.
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In the last decade we have seen how small and light weight aerial platforms - aka, Mini Unmanned Aerial Vehicles (MUAV) - shipped with heterogeneous sensors have become a 'most wanted' Remote Sensing (RS) tool. Most of the off-the-shelf aerial systems found in the market provide way-point navigation. However, they do not rely on a tool that compute the aerial trajectories considering all the aspects that allow optimizing the aerial missions. One of the most demanded RS applications of MUAV is image surveying. The images acquired are typically used to build a high-resolution image, i.e., a mosaic of the workspace surface. Although, it may be applied to any other application where a sensor-based map must be computed. This thesis provides a study of this application and a set of solutions and methods to address this kind of aerial mission by using a fleet of MUAVs. In particular, a set of algorithms are proposed for map-based sampling, and aerial coverage path planning (ACPP). Regarding to map-based sampling, the approaches proposed consider workspaces with different shapes and surface characteristics. The workspace is sampled considering the sensor characteristics and a set of mission requirements. The algorithm applies different computational geometry approaches, providing a unique way to deal with workspaces with different shape and surface characteristics in order to be surveyed by one or more MUAVs. This feature introduces a previous optimization step before path planning. After that, the ACPP problem is theorized and a set of ACPP algorithms to compute the MUAVs trajectories are proposed. The problem addressed herein is the problem to coverage a wide area by using MUAVs with limited autonomy. Therefore, the mission must be accomplished in the shortest amount of time. The aerial survey is usually subject to a set of workspace restrictions, such as the take-off and landing positions as well as a safety distance between elements of the fleet. Moreover, it has to avoid forbidden zones to y. Three different algorithms have been studied to address this problem. The approaches studied are based on graph searching, heuristic and meta-heuristic approaches, e.g., mimic, evolutionary. Finally, an extended survey of field experiments applying the previous methods, as well as the materials and methods adopted in outdoor missions is presented. The reported outcomes demonstrate that the findings attained from this thesis improve ACPP mission for mapping purpose in an efficient and safe manner.
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In the last decade we have seen how small and light weight aerial platforms - aka, Mini Unmanned Aerial Vehicles (MUAV) - shipped with heterogeneous sensors have become a 'most wanted' Remote Sensing (RS) tool. Most of the off-the-shelf aerial systems found in the market provide way-point navigation. However, they do not rely on a tool that compute the aerial trajectories considering all the aspects that allow optimizing the aerial missions. One of the most demanded RS applications of MUAV is image surveying. The images acquired are typically used to build a high-resolution image, i.e., a mosaic of the workspace surface. Although, it may be applied to any other application where a sensor-based map must be computed. This thesis provides a study of this application and a set of solutions and methods to address this kind of aerial mission by using a fleet of MUAVs. In particular, a set of algorithms are proposed for map-based sampling, and aerial coverage path planning (ACPP). Regarding to map-based sampling, the approaches proposed consider workspaces with different shapes and surface characteristics. The workspace is sampled considering the sensor characteristics and a set of mission requirements. The algorithm applies different computational geometry approaches, providing a unique way to deal with workspaces with different shape and surface characteristics in order to be surveyed by one or more MUAVs. This feature introduces a previous optimization step before path planning. After that, the ACPP problem is theorized and a set of ACPP algorithms to compute the MUAVs trajectories are proposed. The problem addressed herein is the problem to coverage a wide area by using MUAVs with limited autonomy. Therefore, the mission must be accomplished in the shortest amount of time. The aerial survey is usually subject to a set of workspace restrictions, such as the take-off and landing positions as well as a safety distance between elements of the fleet. Moreover, it has to avoid forbidden zones to y. Three different algorithms have been studied to address this problem. The approaches studied are based on graph searching, heuristic and meta-heuristic approaches, e.g., mimic, evolutionary. Finally, an extended survey of field experiments applying the previous methods, as well as the materials and methods adopted in outdoor missions is presented. The reported outcomes demonstrate that the findings attained from this thesis improve ACPP mission for mapping purpose in an efficient and safe manner.
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Common problems encountered in clinical sensing are those of non-biocompatibility, and slow response time of the device. The latter, also applying to chemical sensors, is possibly due to a lack of understanding of polymer support or membrane properties and hence failure to optimise membranes chosen for specific sensor applications. Hydrogels can be described as polymers which swell in water. In addition to this, the presence of water in the polymer matrix offers some control of biocompatibility. They thus provide a medium through which rapid transport of a sensed species to an incorporated reagent could occur. This work considers the feasibility of such a system, leading to the design and construction of an optical sensor test bed. The development of suitable membrane systems and of suitable coating techniques in order to apply them to the fibre optics is described. Initial results obtained from hydrogel coatings implied that the refractive index change in the polymer matrix, due to a change in water content with pH is the major factor contributing to the sensor response. However the presence of the colourimetric reagent was also altering the output signal obtained. An analysis of factors contributing to the overall response, such as colour change and membrane composition were made on both the test bed, via optical response, and on whole membranes via measurement of water content change. The investigation of coatings with low equilibrium water contents, of less than 10% was carried out and in fact a clearer signal response from the test bed was noted. Again these membranes were suprisingly responding via refractive index change, with the reagent playing a primary role in obtaining a sensible or non-random response, although not in a colourimetric fashion. A photographic study of these coatings revealed some clues as to the physical nature of these coatings and hence partially explained this phenomenon. A study of the transport properties of the most successful membrane, on a coated wire electrode and also on the fibre optic test bed, in a series of test environments, indicated that the reagent was possibly acting as an ion exchanger and hence having a major influence on transport and therefore sensor characteristics.
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Recommendation for Oxygen Measurements from Argo Floats: Implementation of In-Air-Measurement Routine to Assure Highest Long-term Accuracy As Argo has entered its second decade and chemical/biological sensor technology is improving constantly, the marine biogeochemistry community is starting to embrace the successful Argo float program. An augmentation of the global float observatory, however, has to follow rather stringent constraints regarding sensor characteristics as well as data processing and quality control routines. Owing to the fairly advanced state of oxygen sensor technology and the high scientific value of oceanic oxygen measurements (Gruber et al., 2010), an expansion of the Argo core mission to routine oxygen measurements is perhaps the most mature and promising candidate (Freeland et al., 2010). In this context, SCOR Working Group 142 “Quality Control Procedures for Oxygen and Other Biogeochemical Sensors on Floats and Gliders” (www.scor-int.org/SCOR_WGs_WG142.htm) set out in 2014 to assess the current status of biogeochemical sensor technology with particular emphasis on float-readiness, develop pre- and post-deployment quality control metrics and procedures for oxygen sensors, and to disseminate procedures widely to ensure rapid adoption in the community.
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A simple, effective and inexpensive fiber optic sensor for investigating the setting characteristics of various grades of cement is described. A finite length of unsheathed multimode optical fiber laid inside the cement mix, is subjected to stress during the setting process. The microbends created on the fiber due to this stress directly influence the intensity of light propagating through the fiber. Continuous monitoring of such variations in the light output transmitted through the fiber gives a clear measure of the setting characteristics of the cement mix, thus providing a simple and elegant technique of great practical importance in the field of civil engineering. The smart fiber optic sensor described above can be incorporated into a building during the construction process itself so that continuous monitoring of the deterioration process for the entire life time of the building can be carried out.
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Subject category 35.
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Large monitoring networks are becoming increasingly common and can generate large datasets from thousands to millions of observations in size, often with high temporal resolution. Processing large datasets using traditional geostatistical methods is prohibitively slow and in real world applications different types of sensor can be found across a monitoring network. Heterogeneities in the error characteristics of different sensors, both in terms of distribution and magnitude, presents problems for generating coherent maps. An assumption in traditional geostatistics is that observations are made directly of the underlying process being studied and that the observations are contaminated with Gaussian errors. Under this assumption, sub–optimal predictions will be obtained if the error characteristics of the sensor are effectively non–Gaussian. One method, model based geostatistics, assumes that a Gaussian process prior is imposed over the (latent) process being studied and that the sensor model forms part of the likelihood term. One problem with this type of approach is that the corresponding posterior distribution will be non–Gaussian and computationally demanding as Monte Carlo methods have to be used. An extension of a sequential, approximate Bayesian inference method enables observations with arbitrary likelihoods to be treated, in a projected process kriging framework which is less computationally intensive. The approach is illustrated using a simulated dataset with a range of sensor models and error characteristics.
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The electromechanical transfer characteristics of adhesively bonded piezoelectric sensors are investigated. By the use of dynamic piezoelectricity theory, Mindlin plate theory for flexural wave propagation, and a multiple integral transform method, the frequency-response functions of piezoelectric sensors with and without backing materials are developed and the pressure-voltage transduction functions of the sensors calculated. The corresponding simulation results show that the sensitivity of the sensors is not only dependent on the sensors' inherent features, such as piezoelectric properties and geometry, but also on local characteristics of the tested structures and the admittance and impedance of the attached electrical circuit. It is also demonstrated that the simplified rigid mass sensor model can be used to analyze successfully the sensitivity of the sensor at low frequencies, but that the dynamic piezoelectric continuum model has to be used for higher frequencies, especially around the resonance frequency of the coupled sensor-structure vibration system.