996 resultados para Oil leakage sensing
Resumo:
An attempt has been made to study the effect of time and test procedure on the behaviour of partial discharge (PD) pulses causing failure of oil-pressboard system under power frequency voltages using circular disc shaped samples and uniform field electrodes. Weibull statistics have been used to handle the large amount of PD data. The PD phenomena has been found to be stress and time dependent. On the basis of stress level, three different regions are identified and in one of the regions, the rate of deterioration of the sample is at a maximum. The work presents some interesting features of Weibull parameters as related to the condition of insulation studied in addition to its usual PD characteristics
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The nuclear magnetic resonance imaging technique has been used to obtain images of different transverse and vertical sections in groundnut and sunflower seeds. Separate images have been obtained for oil and water components in the seeds. The spatial distribution of oil and water inside the seed has been obtained from the detailed analysis of the images. In the immature groundnut seeds obtained commercially, complementary oil and water distributions have been observed. Attempts have been made to explain these results.
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Acyl carrier proteins (ACP) were purified to homogeneity in the active form from developing seeds of pisa (Actinodaphne hookeri) which synthesizes exclusively trilaurin and from ground nut (Arachis hypogaea) which synthesizes triacylglycerols containing long chain fatty acids. Two major isoforms of ACPs were purified from developing pisa seeds using DEAE-cellulose, Superose-6 FPLC and C-4 reversed phase HPLC chromatographic methods. In contrast, only a single form of ACP was present in ground nut seeds which was purified by anion-exchange and activated thiol-Sepharose 4B affinity chromatography. The two isoforms of ACPs from pisa showed nearly the same specific activity of 6,706 and 7,175 pmol per min per mg protein while ground nut ACP showed a specific activity of 3,893 pmol per min per mg protein when assayed using E. coli acyl-ACP synthetase and [1-C-14]palmitic acid. When compared with E. coli ACP, the purified ACPs from both the seeds showed considerable difference in their mobility in native PAGE, but showed similar mobility in SDS-PAGE under reducing conditions. In the absence of reducing agents formation of dimers was quite prominent. The ACPs from both the seed sources were acid- and heat-stable. The major isoform of pisa seed ACP and the ground nut ACP contain 91 amino acids with M(r) 11,616 and 1,228 respectively. However, there is significant variation in their amino acid composition. A comparision of the amino acid sequence in the N-terminal region of pisa and ground nut seed ACPs showed considerable homology between themselves and with other plant ACPs but not with E. coli ACP.
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This is an exploratory study to illustrate the feasibility of detecting delamination type of damage in polymeric laminates with one layer of magnetostrictive particles. One such beam encircled with excitation and sensing coils is used for this study. The change in stress gradient of the magnetostrictive layer in the vicinity of delamination shows up as a change in induced voltage in the sensing coil, and therefore provides a means to sense the presence of delamination. Recognizing the constitutive behavior of the Terfenol-D material is highly nonlinear, analytical expressions for the constitutive relations are developed by using curve fitting techniques to the experimental data. Analytical expressions that relate the applied excitation field with the stress and magnetic flux densities induced in the magnetostrictive layer are developed. Numerical methods are used to find the relative change in the induced voltage in the sensing coil due to the presence of delamination. A typical example of unidirectional laminate, with embedded delaminations, is used for the simulation purposes. This exploratory study illustrates that the open-circuit voltage induced in the sensing coil changes significantly (as large of 68 millivolts) with the occurrence of delamination. This feature can be exploited for device off-line inspection techniques and/or linking monitoring procedures for practical applications.
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A Wireless Sensor Network (WSN) powered using harvested energies is limited in its operation by instantaneous power. Since energy availability can be different across nodes in the network, network setup and collaboration is a non trivial task. At the same time, in the event of excess energy, exciting node collaboration possibilities exist; often not feasible with battery driven sensor networks. Operations such as sensing, computation, storage and communication are required to achieve the common goal for any sensor network. In this paper, we design and implement a smart application that uses a Decision Engine, and morphs itself into an energy matched application. The results are based on measurements using IRIS motes running on solar energy. We have done away with batteries; instead used low leakage super capacitors to store harvested energy. The Decision Engine utilizes two pieces of data to provide its recommendations. Firstly, a history based energy prediction model assists the engine with information about in-coming energy. The second input is the energy cost database for operations. The energy driven Decision Engine calculates the energy budgets and recommends the best possible set of operations. Under excess energy condition, the Decision Engine, promiscuously sniffs the neighborhood looking for all possible data from neighbors. This data includes neighbor's energy level and sensor data. Equipped with this data, nodes establish detailed data correlation and thus enhance collaboration such as filling up data gaps on behalf of nodes hibernating under low energy conditions. The results are encouraging. Node and network life time of the sensor nodes running the smart application is found to be significantly higher compared to the base application.
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Several pi-electron rich fluorescent aromatic compounds containing trimethylsilylethynyl functionality have been synthesized by employing Sonogashira coupling reaction and they were characterized fully by NMR (H-1, C-13)/IR spectroscopy. Incorporation of bulky trimethylsilylethynyl groups on the peripheral of the fluorophores prevents self-quenching of the initial intensity through pi-pi interaction and thereby maintains the spectroscopic stability in solution. These compounds showed fluorescence behavior in chloroform solution and were used as selective fluorescence sensors for the detection of electron deficient nitroaromatics. All these fluorophores showed the largest quenching response with high selectivity for nitroaromatics among the various electron deficient aromatic compounds tested. Quantitative analysis of the fluorescence titration profile of 9,10-bis(trimethylsilylethynyl) anthracene with picric acid provided evidence that this particular fluorophore detects picric acid even at ppb level. A sharp visual detection of 2,4,6-trinitrotoluene was observed upon subjecting 1,3,6,8-tetrakis (trimethylsilylethynyl) pyrene fluorophore to increasing quantities of 2,4,6-trinitrotoluene in chloroform. Furthermore, thin film of the fluorophores was made by spin coating of a solution of 1.0 x 10(-3) M in chloroform or dichloromethane on a quartz plate and was used for the detection of vapors of nitroaromatics at room temperature. The vapor-phase sensing experiments suggested that the sensing process is reproducible and quite selective for nitroaromatic compounds. Selective fluorescence quenching response including a sharp visual color change for nitroaromatics makes these fluorophores as promising fluorescence sensory materials for nitroaromatic compounds (NAC) with a detection limit of even ppb level as judged with picric acid.
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This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user is using Orthogonal Frequency Division Multiplexing (OFDM). For this we develop cooperative sequential detection algorithms that use the autocorrelation property of cyclic prefix (CP) used in OFDM systems. We study the effect of timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power. We also modify the detector to mitigate the effects of these impairments. The performance of the proposed algorithms is studied via simulations. We show that sequential detection can significantly improve the performance over a fixed sample size detector.
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GC-MS study of two fatty oil fractions from Artabotrys odoratissimus (leaves) indicated the presence of fifteen compounds namely, nonanoic acid; methyl phenyl propanoate; decanoic acid; diethyl phthalate; dibutyl phthalate; 2 - amino-3-ethyl biphenyl; 5-methyl-9-phenylnonan-3-ol; hexadeca-2,7,11-triene; 2,6-dimethyl-1-phenylhepta-1-one; 2,5-dimethyltetradecahydrophenenthrene; 1-phenylundecane; 1-isopropyl-4,6-dimethyl naphthalene; 5-(2-butyl phenyl)pent-3-en-2-ol; 1-phenyideca-1-one and 1-phenylundecan-1-one. Some of the compounds are rare occurring and biologically active.
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A steel disc is cut using a single point tool. The coefficient of friction of the nascent cut surface is measured by a spherical steel pin situated in close proximity of the point of cutting. The tool, disc and the friction pin are immersed in an oil in water emulsion bath during the experiment. The purpose of the experiments conducted here is to record the effect of hydrophilic/lypophilic balance (HLB) of the emulsifier on the lubricity experienced in the cutting operation. The more lypophilic emulsifiers were found to give greater lubricity than what is recorded when the emulsifier is more hydrophilic. XPS and FTIR spectroscopy are used to explore the tribofilm generated on the nascent cut surface to indicate a possible rationale for the effect. (C) 2011 Elsevier B.V. All rights reserved.
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Nanocrystalline tin oxide powder was prepared using a solution precipitation technique after adding the surfactant sodium bis (2-ethylhexyl) sulfosuccinate (AOT). Powders were characterized using X-ray diffraction (XRD), surface area (BET) and transmission electron microscopy (TEM). The gas sensitivity for surfactant added powders increased for liquid petroleum gas (LPG) as well as compressed natural gas (CNG), due to the decreased particle size and the increased surface area. The LPG gas sensitivity increased several times using phosphorus treated surfactant AOT.
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A new family of castor oil based biodegradable polyesters was synthesized by catalyst free melt condensation reaction between two different diacids and castor oil with D-mannitol. The polymers synthesized were characterized by NMR spectroscopy, FF-IR and the thermal properties were analysed by DSC. The results of DSC show that the polymer is rubbery in physiological conditions. The contact angle measurement and hydration test results indicate that the surface of the polymer is hydrophilic. The mechanical properties, evaluated in the tensile mode, shows that the polymer has characteristics of a soft material. In vitro degradation of polymer in PBS solution carried out at physiological conditions indicates that the degradation goes to completion within 21 days and it was also found that the rate of degradation can be tuned by varying the curing conditions. (C) 2011 Elsevier Ltd. All rights reserved.
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A pi-electron rich supramolecular polymer as an efficient fluorescent sensor for electron deficient nitroaromatic explosives has been synthesized, and the role of H-bonding in dramatic amplification of sensitivity/fluorescence quenching efficiency in the solid state has been established.
Resumo:
With extensive use of dynamic voltage scaling (DVS) there is increasing need for voltage scalable models. Similarly, leakage being very sensitive to temperature motivates the need for a temperature scalable model as well. We characterize standard cell libraries for statistical leakage analysis based on models for transistor stacks. Modeling stacks has the advantage of using a single model across many gates there by reducing the number of models that need to be characterized. Our experiments on 15 different gates show that we needed only 23 models to predict the leakage across 126 input vector combinations. We investigate the use of neural networks for the combined PVT model, for the stacks, which can capture the effect of inter die, intra gate variations, supply voltage(0.6-1.2 V) and temperature (0 - 100degC) on leakage. Results show that neural network based stack models can predict the PDF of leakage current across supply voltage and temperature accurately with the average error in mean being less than 2% and that in standard deviation being less than 5% across a range of voltage, temperature.