999 resultados para Thermal Sensor
Resumo:
A distributed temperature sensor is presented which uses a chirped Moiré fibre Bragg grating to give a thermal resolution of 0.2°C with a spatial resolution of 164 μm. The wavelength sensitivity of the device is 0.01 ± 4 × 10-4 nm/°C. Such a sensor has biomedical and industrial applications where accurate measurement of location and intensity of temperature is essential. The sensor may be used as a one- or two-dimensional temperature monitor, depending on the configuration. © 2004 Elsevier B.V. All rights reserved.
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Combined the large evanescent field of microfiber with the high thermal conductivity of graphene, a sensitive all-fiber temperature sensor based on graphene-assisted micro fiber is proposed and experimentally demonstrated. Microfiber can be easily attached with graphene due to the electrostatic 6 force, resulting in an effective interaction between graphene and the evanescent field of microfiber. The change of the ambient temperature has a great influence on the conductivity of graphene, leading to the variation of the effective refractive index of microfiber. Consequently, the optical power transmission will be changed. The temperature sensitivity of 0.1018 dB/°C in the heating process and 0.1052 dB/°C in the cooling process as well as a high resolution of 0.0098 °C is obtained in the experiment. The scheme may have great potential in sensing fields owing to the advantages of high sensitivity, compact size, and low cost.
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For the first time to the authors' knowledge, fiber Bragg gratings (FBGs) with >80° tilted structures nave been fabricated and characterized. Their performance in sensing temperature, strain, and the surrounding medium's refractive index was investigated. In comparison with normal FBGs and long-period gratings (LPGs), >80° tilted FBGs exhibit significantly higher refractive-index responsivity and lower thermal cross sensitivity. When the grating sensor was used to detect changes in refractive index, a responsivity as high as 340 nm/refractive-index unit near an index of 1.33 was demonstrated, which is three times higher than that of conventional LPGs. © 2006 Optical Society of America.
Novel fiber Bragg grating sensor implemented in a polymer-core/silica- cladding hybrid optical fiber
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A polymer-core/silica-cladding hybrid optical fiber is implemented by filling a capillary with UV-curable epoxy and a following UV-laser scanning exposure. A fiber Bragg grating is successfully inscribed in parallel using a phase mask. The experimental results show a reduced thermal response for the FBG and a theoretical analysis for such a hybrid optical fiber is performed which corroborates existing of a turning temperature for minimized thermal response. © 2014 SPIE.
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We propose and demonstrate an optical liquid level sensor based on the surrounding medium refractive index (SRI) sensing using an excessively tilted fibre grating (ETFG). When the ETFG submerged in water, two sets of cladding modes are coupled, corresponding to air- and water-surrounded grating structures, respectively. The coupling strengths of the two sets of cladding modes evolve with the submerging length of the grating, providing a mechanism to measure the liquid level. Comparing with long-period fibre grating based liquid level sensor, the ETFG sensor has a much higher SRI responsivity for liquids with refractive index around 1.33 and a lower thermal cross sensitivity. © 2013 Published by Elsevier B.V. All rights reserved.
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A highly sensitive liquid-level sensor based on dual-wavelength single-longitudinal-mode fiber laser is proposed and demonstrated. The laser is formed by exploiting two parallel arranged phase-shift fiber Bragg gratings (ps-FBGs), acting as ultra-narrow bandwidth filters, into a doublering resonators. By beating the dual-wavelength lasing output, a stable microwave signal with frequency stability better than 5 MHz is obtained. The generated beat frequency varies with the change of dual-wavelength spacing. Based on this characteristic, with one ps-FBG serving as the sensing element and the other one acting as the reference element, a highly sensitive liquid level sensor is realized by monitoring the beat frequency shift of the laser. The sensor head is directly bonded to a float which can transfer buoyancy into axial strain on the fiber without introducing other elastic elements. The experimental results show that an ultra-high liquidlevel sensitivity of 2.12 × 107 MHz/m within the measurement range of 1.5 mm is achieved. The sensor presents multiple merits including ultra-high sensitivity, thermal insensitive, good reliability and stability. © 2012 Optical Society of America.
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As the largest source of dimensional measurement uncertainty, addressing the challenges of thermal variation is vital to ensure product and equipment integrity in the factories of the future. While it is possible to closely control room temperature, this is often not practical or economical to realise in all cases where inspection is required. This article reviews recent progress and trends in seven key commercially available industrial temperature measurement sensor technologies primarily in the range of 0 °C–50 °C for invasive, semi-invasive and non-invasive measurement. These sensors will ultimately be used to measure and model thermal variation in the assembly, test and integration environment. The intended applications for these technologies are presented alongside some consideration of measurement uncertainty requirements with regard to the thermal expansion of common materials. Research priorities are identified and discussed for each of the technologies as well as temperature measurement at large. Future developments are briefly discussed to provide some insight into which direction the development and application of temperature measurement technologies are likely to head.
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Leishmaniasis is one of the most important emerging vector-borne diseases in Western Eurasia. Although winter minimum temperatures limit the present geographical distribution of the vector Phlebotomus species, the heat island effect of the cities and the anthropogenic heat emission together may provide the appropriate environment for the overwintering of sand flies. We studied the climate tempering effect of thermal bridges and the heat island effect in Budapest, Hungary. Thermal imaging was used to measure the heat surplus of heat bridges. The winter heat island effect of the city was evaluated by numerical analysis of the measurements of the Aqua sensor of satellite Terra. We found that the surface temperature of thermal bridges can be at least 3-7 °C higher than the surrounding environment. The heat emission of thermal bridges and the urban heat island effect together can cause at least 10 °C higher minimum ambient temperature in winter nights than the minimum temperature of the peri-urban areas. This milder micro-climate of the built environment can enable the potential overwintering of some important European Phlebotomus species. The anthropogenic heat emission of big cities may explain the observed isolated northward populations of Phlebotomus ariasi in Paris and Phlebotomus neglectus in the agglomeration of Budapest.
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Technological developments in biomedical microsystems are opening up new opportunities to improve healthcare procedures. Swallowable diagnostic sensing capsules are an example of these. In none of the diagnostic sensing capsules, is the sensor’s first level packaging achieved via Flip Chip Over Hole (FCOH) method using Anisotropic Conductive Adhesive (ACA). In a capsule application with direct access sensor (DAS), ACA not only provides the electrical interconnection but simultaneously seals the interconnect area and the underlying electronics. The development showed that the ACA FCOH was a viable option for the DAS interconnection. Adequate adhesive formed a strong joint that withstood a shear stress of 120N/mm2 and a compressive stress of 6N required to secure the final sensor assembly in place before encapsulation. Electrical characterization of the ACA joint in a fluid environment showed that the ACA was saturated with moisture and that the ions in the solution actively contributed to the leakage current, characterized by the varying rate of change of conductance. Long term hygrothermal aging of the ACA joint showed that a thermal strain of 0.004 and a hygroscopic strain of 0.0052 were present and resulted in a fatigue like process. In-vitro tests showed that high temperature and acidity had a deleterious effect of the ACA and its joint. It also showed that the ACA contact joints positioned at around or over 1mm would survive the gastrointestinal (GI) fluids and would be able to provide a reliable contact during the entire 72hr of the GI transit time. A final capsule demonstrator was achieved by successfully integrating the DAS, the battery and the final foldable circuitry into a glycerine capsule. Final capsule soak tests suggested that the silicone encapsulated system could survive the 72hr gut transition.
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Due to increasing integration density and operating frequency of today's high performance processors, the temperature of a typical chip can easily exceed 100 degrees Celsius. However, the runtime thermal state of a chip is very hard to predict and manage due to the random nature in computing workloads, as well as the process, voltage and ambient temperature variability (together called PVT variability). The uneven nature (both in time and space) of the heat dissipation of the chip could lead to severe reliability issues and error-prone chip behavior (e.g. timing errors). Many dynamic power/thermal management techniques have been proposed to address this issue such as dynamic voltage and frequency scaling (DVFS), clock gating and etc. However, most of such techniques require accurate knowledge of the runtime thermal state of the chip to make efficient and effective control decisions. In this work we address the problem of tracking and managing the temperature of microprocessors which include the following sub-problems: (1) how to design an efficient sensor-based thermal tracking system on a given design that could provide accurate real-time temperature feedback; (2) what statistical techniques could be used to estimate the full-chip thermal profile based on very limited (and possibly noise-corrupted) sensor observations; (3) how do we adapt to changes in the underlying system's behavior, since such changes could impact the accuracy of our thermal estimation. The thermal tracking methodology proposed in this work is enabled by on-chip sensors which are already implemented in many modern processors. We first investigate the underlying relationship between heat distribution and power consumption, then we introduce an accurate thermal model for the chip system. Based on this model, we characterize the temperature correlation that exists among different chip modules and explore statistical approaches (such as those based on Kalman filter) that could utilize such correlation to estimate the accurate chip-level thermal profiles in real time. Such estimation is performed based on limited sensor information because sensors are usually resource constrained and noise-corrupted. We also took a further step to extend the standard Kalman filter approach to account for (1) nonlinear effects such as leakage-temperature interdependency and (2) varying statistical characteristics in the underlying system model. The proposed thermal tracking infrastructure and estimation algorithms could consistently generate accurate thermal estimates even when the system is switching among workloads that have very distinct characteristics. Through experiments, our approaches have demonstrated promising results with much higher accuracy compared to existing approaches. Such results can be used to ensure thermal reliability and improve the effectiveness of dynamic thermal management techniques.
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Dissertação de mestrado, Engenharia Electrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2011
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Atmospheric scattering plays a crucial rule in degrading the performance of electro optical imaging systems operating in the visible and infra-red spectral bands, and hence limits the quality of the acquired images, either through reduction of contrast or increase of image blur. The exact nature of light scattering by atmospheric media is highly complex and depends on the types, orientations, sizes and distributions of particles constituting these media, as well as wavelengths, polarization states and directions of the propagating radiation. Here we follow the common approach for solving imaging and propagation problems by treating the propagating light through atmospheric media as composed of two main components: a direct (unscattered), and a scattered component. In this work we developed a detailed model of the effects of absorption and scattering by haze and fog atmospheric aerosols on the optical radiation propagating from the object plane to an imaging system, based on the classical theory of EM scattering. This detailed model is then used to compute the average point spread function (PSF) of an imaging system which properly accounts for the effects of the diffraction, scattering, and the appropriate optical power level of both the direct and the scattered radiation arriving at the pupil of the imaging system. Also, the calculated PSF, properly weighted for the energy contributions of the direct and scattered components is used, in combination with a radiometric model, to estimate the average number of the direct and scattered photons detected at the sensor plane, which are then used to calculate the image spectrum signal to- noise ratio (SNR) in the visible near infra-red (NIR) and mid infra-red (MIR) spectral wavelength bands. Reconstruction of images degraded by atmospheric scattering and measurement noise is then performed, up to the limit imposed by the noise effective cutoff spatial frequency of the image spectrum SNR. Key results of this research are as follows: A mathematical model based on Mie scattering theory for how scattering from aerosols affects the overall point spread function (PSF) of an imaging system was developed, coded in MATLAB, and demonstrated. This model along with radiometric theory was used to predict the limiting resolution of an imaging system as a function of the optics, scattering environment, and measurement noise. Finally, image reconstruction algorithms were developed and demonstrated which mitigate the effects of scattering-induced blurring to within the limits imposed by noise.
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This paper presents a highly sensitive ambient refractive index (RI) sensor based on 81° tilted fiber grating (81°-TFG) structure UV-inscribed in standard telecom fiber (62.5μm cladding radius) with carbon nanotube (CNT) overlay deposition. The sensing mechanism is based on the ability of CNT to induce change in transmitted optical power and the high sensitivity of 81°-TFG to ambient refractive index. The thin CNT film with high refractive index enhances the cladding modes of the TFG, resulting in the significant interaction between the propagating light and the surrounding medium. Consequently, the surrounding RI change will induce not only the resonant wavelength shift but also the power intensity change of the attenuation band in the transmission spectrum. Result shows that the change in transmitted optical power produces a corresponding linear reduction in intensity with increment in RI values. The sample shows high sensitivities of ∼207.38nm/RIU, ∼241.79nm/RIU at RI range 1.344-1.374 and ∼113.09nm/RIU, ∼144.40nm/RIU at RI range 1.374-1.392 (for X-pol and Y-pol respectively). It also shows power intensity sensitivity of ∼ 65.728dBm/RIU and ∼ 45.898 (for X-pol and Y-pol respectively). The low thermal sensitivity property of the 81°-TFG offers reduction in thermal cross-sensitivity and enhances specificity of the sensor.
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A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.