932 resultados para Optical monitoring
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A novel fibre optic sensor for the in situ measurement of the rate of deposition of thin films has been developed. Evanescent wave in the uncladded portion of a multimode fibre is utilised for this sensor development. In the present paper we demonstrate how this sensor is useful for the monitoring of the deposition rate of polypyrrole thin films, deposited by an AC plasma polymerisation method. This technique is simple, accurate and highly sensitive compared with existing techniques.
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The main objective of the present study is to understand different mechanisms involved in the production and evolution of plasma by the pulsed laser ablation and radio frequency magnetron sputtering. These two methods are of particular interest, as these are well accomplished methods used for surface coatings, nanostructure fabrications and other thin film devices fabrications. Material science researchers all over the world are involved in the development of devices based on transparent conducting oxide (TCO) thin films. Our laboratory has been involved in the development of TCO devices like thin film diodes using zinc oxide (ZnO) and zinc magnesium oxide (ZnMgO), thin film transistors (TFT's) using zinc indium oxide and zinc indium tin oxide, and some electroluminescent (EL) devices by pulsed laser ablation and RF magnetron sputtering.In contrast to the extensive literature relating to pure ZnO and other thin films produced by various deposition techniques, there appears to have been relatively little effort directed towards the characterization of plasmas from which such films are produced. The knowledge of plasma dynamics corresponding to the variations in the input parameters of ablation and sputtering, with the kind of laser/magnetron used for the generation of plasma, is limited. To improve the quality of the deposited films for desired application, a sound understanding of the plume dynamics, physical and chemical properties of the species in the plume is required. Generally, there is a correlation between the plume dynamics and the structural properties of the films deposited. Thus the study of the characteristics of the plume contributes to a better understanding and control of the deposition process itself. The hydrodynamic expansion of the plume, the composition, and SIze distribution of clusters depend not only on initial conditions of plasma production but also on the ambient gas composition and pressure. The growth and deposition of the films are detennined by the thermodynamic parameters of the target material and initial conditions such as electron temperature and density of the plasma.For optimizing the deposition parameters of various films (stoichiometric or otherwise), in-situ or ex-situ monitoring of plasma plume dynamics become necessary for the purpose of repeatability and reliability. With this in mind, the plume dynamics and compositions of laser ablated and RF magnetron sputtered zinc oxide plasmas have been investigated. The plasmas studied were produced at conditions employed typically for the deposition of ZnO films by both methods. Apart from this two component ZnO plasma, a multi-component material (lead zirconium titanate) was ablated and plasma was characterized.
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The objective of the preset work is to develop optical fiber sensors for various physical and chemical parameters. As a part of this we initially investigated trace analysis of silica, ammonia, iron and phosphate in water. For this purpose the author has implemented a dual wavelength probing scheme which has many advantages over conventional evanescent wave sensors. Dual wavelength probing makes the design more reliable and repeatable and this design makes the sensor employable for concentration, chemical content, adulteration level, monitoring and control in industries or any such needy environments. Use of low cost components makes the system cost effective and simple. The Dual wavelength probing scheme is employed for the trace analysis of silica, iron, phosphate, and ammonia in water. Such sensors can be employed for the steam and water quality analysers in power plants. Few samples from a power plant are collected and checked the performance of developed system for practical applications.
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The chemical contamination of natural waters is a global problem with a worldwide impact. Considering the relevance of this problem, this thesis is intended, on one hand, to develop different separation/preconcentration techniques based on membranes ability to permeate anions for the transport of toxic oxyanions of chromium(VI) and arsenic contained in aqueous matrices. In particular, we have investigated supported liquid membranes and polymer inclusion membranes, both of which contain the commercial quaternary ammonium salt Aliquat 336 as a carrier, as well as commercial anion exchange membranes. On the other hand, we have focused on the development of chemical sensors to facilitate the monitoring of several metals from different aqueous matrices. Thus, a selective optical sensor for Cr(VI) based on polymeric membranes containing Aliquat 336 as an ionophore has been designed. Additionally, mercury-based screen-printed electrodes have been evaluated for for cadmium, lead, copper and zinc detection.
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The Improved Stratospheric and Mesospheric Sounder (ISAMS) is designed to measure the Earths middle atmosphere in the range of 4.6 to 16.6 micorns. This paper considers all the coated optical elements in two radiometric test channels. (Analysis of the spectral response will be presented as a seperate paper at this symposium, see Sheppard et al). Comparisons between the compued spectral performance and measurements from actual coatings will be discussed: These will include substrate absorption simulations. The results of environmental testing (durability and stability) are included, together with details of coating deposition and monitoring conditions.
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A plastic optical fibre reflectance sensor that makes full use of the critical angle of the fibres is implemented to monitor dew formation on a Peltier-cooled reflector surface. The optical configuration permits isolation of optoelectronic components from the sensing head and better light coupling between the reflector and the detecting fibre, giving a better signal of the onset of dew formation on the reflector. Continuous monitoring of the rate of change in reflectance as well as the absolute reflectance signals, the use of a novel polymethyl-methacrylate-coated hydrophobic film reflector on the Peltier element and the application of feedback around the point of dew formation, further reduces the possibility of contamination of the sensor head. Under closed-loop operation, the sensor is capable of cycling around the point of dew formation at a frequency of 2.5 Hz.
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Optical characteristics of stirred curd were simultaneously monitored during syneresis in a 10-L cheese vat using computer vision and colorimetric measurements. Curd syneresis kinetic conditions were varied using 2 levels of milk pH (6.0 and 6.5) and 2 agitation speeds (12.1 and 27.2 rpm). Measured optical parameters were compared with gravimetric measurements of syneresis, taken simultaneously. The results showed that computer vision and colorimeter measurements have potential for monitoring syneresis. The 2 different phases, curd and whey, were distinguished by means of color differences. As syneresis progressed, the backscattered light became increasingly yellow in hue for circa 20 min for the higher stirring speed and circa 30 min for the lower stirring speed. Syneresis-related gravimetric measurements of importance to cheese making (e.g., curd moisture content, total solids in whey, and yield of whey) correlated significantly with computer vision and colorimetric measurements..
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The cheese industry has continually sought a robust method to monitor milk coagulation. Measurement of whey separation is also critical to control cheese moisture content, which affects quality. The objective of this study was to demonstrate that an online optical sensor detecting light backscatter in a vat could be applied to monitor both coagulation and syneresis during cheesemaking. A prototype sensor having a large field of view (LFV) relative to curd particle size was constructed. Temperature, cutting time, and calcium chloride addition were varied to evaluate the response of the sensor over a wide range of coagulation and syneresis rates. The LFV sensor response was related to casein micelle aggregation and curd firming during coagulation and to changes in curd moisture and whey fat contents during syneresis. The LFV sensor has potential as an online, continuous sensor technology for monitoring both coagulation and syneresis during cheesemaking.
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To analyze patterns in marine productivity, harmful algal blooms, thermal stress in coral reefs, and oceanographic processes, optical and biophysical marine parameters, such as sea surface temperature, and ocean color products, such as chlorophyll-a concentration, diffuse attenuation coefficient, total suspended matter concentration, chlorophyll fluorescence line height, and remote sensing reflectance, are required. In this paper we present a novel automatic Satellite-based Ocean Monitoring System (SATMO) developed to provide, in near real-time, continuous spatial data sets of the above-mentioned variables for marine-coastal ecosystems in the Gulf of Mexico, northeastern Pacific Ocean, and western Caribbean Sea, with 1 km spatial resolution. The products are obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) images received at the Direct Readout Ground Station (located at CONABIO) after each overpass of the Aqua and Terra satellites. In addition, at the end of each week and month the system provides composite images for several ocean products, as well as weekly and monthly anomaly composites for chlorophyll-a concentration and sea surface temperature. These anomaly data are reported for the first time for the study region and represent valuable information for analyzing time series of ocean color data for the study of coastal and marine ecosystems in Mexico, Central America, and the western Caribbean.
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Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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In this work we proposed a relative humidity (RH) sensor based on a Bragg grating written in an optical fiber, associated with a coating of organo-silica hybrid material prepared by the sol-gel method. The organo-silica-based coating has a strong adhesion to the optical fiber and its expansion is reversibly affected by the change in the RH values (15.0-95.0%) of the surrounding environment, allowing an increased sensitivity (22.2 pm/%RH) and durability due to the presence of a siliceous-based inorganic component. The developed sensor was tested in a real structure health monitoring essay, in which the RH inside two concrete blocks with different porosity values was measured over 1 year. The results demonstrated the potential of the proposed optical sensor in the monitoring of civil engineering structures.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The Amazon River floodplain is an important source of atmospheric CO2 and CH4. Aquatic herbaceous vegetation (macrophytes) have been shown to contribute significantly to floodplain net primary productivity (NPP) and methane emission in the region. Their fast growth rates under both flooded and dry conditions make herbaceous vegetation the most variable element in the Amazon floodplain NPP budget, and the most susceptible to environmental changes. The present study combines multitemporal Radarsat-1 and MODIS images to monitor spatial and temporal changes in herbaceous vegetation cover in the Amazon floodplain. Radarsat-1 images were acquired from Dec/2003 to Oct/2005, and MODIS daily surface reflectance products were acquired for the two cloud-free dates closest to each Radarsat-1 acquisition. An object-based, hierarchical algorithm was developed using the temporal SAR information to discriminate Permanent Open Water (OW), Floodplain (FP) and Upland (UL) classes at Level 1, and then subdivide the FP class into Woody Vegetation (WV) and Possible Macrophytes (PM) at Level 2. At Level 3, optical and SAR information were combined to discriminate actual herbaceous cover at each date. The resulting maps had accuracies ranging from 80% to 90% for Level 1 and 2 classifications, and from 60% to 70% for Level 3 classifications, with kappa values ranging between 0.7 and 0.9 for Levels 1 and 2 and between 0.5 and 0.6 for Level 3. All study sites had noticeable variations in the extent of herbaceous cover throughout the hydrological year, with maximum areas up to four times larger than minimum areas. The proposed classification method was able to capture the spatial pattern of macrophyte growth and development in the studied area, and the multitemporal information was essential for both separating vegetation cover types and assessing monthly variation in herbaceous cover extent.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)