| 1. |
- Aroutiounian, Vladimir M., et al.
(författare)
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Noise spectroscopy of gas sensors
- 2008
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Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 8:5-6, s. 786-790
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Tidskriftsartikel (refereegranskat)abstract
- We study current-voltages and low-frequency noise characteristics of the metal-porous silicon-silicon single crystal-metal structure with 50% and 73% porosity of porous silicon. The study is performed in dry air and in a mix of dry air with carbon monoxide of different concentrations. The Hooge noise parameter alpha(H) and the parameter gamma in the frequency dependence of the noise voltage spectral density S-U (f) were determined from experimental data. High sensitivity of spectral dependence of noise to gas concentration allows offering powerful method for determination of gas concentration in the air or environment.
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| 2. |
- Gingl, Zoltan, et al.
(författare)
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Fluctuation-Enhanced Sensing With Zero-Crossing Analysis for High-Speed and Low-Power Applications
- 2010
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Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 10:3, s. 492-497
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Tidskriftsartikel (refereegranskat)abstract
- A new method to generate fingerprints of chemical agents has been introduced in this paper. The method is based on the use of the zero-crossing statistics at fluctuation-enhanced sensing. It is a new version of Ben Kedem's original method based on low-pass filters. To improve computation time and energy efficiency, high-pass filtering is used, and in doing this in the simplest possible way, local zero levels for short-time subwindows are defined and a zero-crossing counting by the use of such windows is carried out. The method turns out to be an effective tool to identify noise processes with different spectra or amplitude distribution, with at least 1000 times less calculation and correspondingly lower energy need than that of the Kedem or the fast Fourier transform methods. We demonstrate the usability of the method by the analysis and recognition of different stochastic processes with similar and different spectra.
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| 3. |
- Kwan, Chiman, et al.
(författare)
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Advanced agent identification with fluctuation-enhanced sensing
- 2008
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Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 8:5-6, s. 706-713
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Tidskriftsartikel (refereegranskat)abstract
- Conventional agent sensing methods normally use the steady state sensor values for agent classification. Many sensing elements (Hines et al., 1999, Ryan et al., 2004, Young et al.,, 2003, Qian et al., 2004, Qian et al.,, 2006, Carmel et ad., 2003) are needed in order to correctly classify multiple agents in mixtures. Fluctuation-enhanced sensing (FES) looks beyond the steady-state values and extracts agent information from spectra and bispectra. As a result, it is possible to use a single sensor to perform multiple agent classification. This paper summarizes the application of some advanced algorithms that can classify and estimate concentrations of different chemical agents. Our tool involves two steps. First, spectral and bispectral features will be extracted from the sensor signals. The features contain unique agent characteristics. Second, the features are fed into a hyperspectral signal processing algorithm for agent, classification and concentration estimation. The basic idea here is to use the spectral/bispectral shape information to perform agent classification. Extensive simulations have been performed by using simulated nanosensor data, as well as actual experimental data using commercial sensor (Taguchi). It was observed that our algorithms are able to accurately classify different agents, and also can estimate the concentration of the agents. Bispectra contain more information than spectra at the expense of high-computational costs. Specific nanostructured sensor model data yielded excellent performance because the agent responses are additive with this type of sensor. Moreover, for measured conventional sensor outputs, our algorithms also showed reasonable performance in terms of agent classification.
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| 4. |
- Schmera, Gabor, et al.
(författare)
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Separating Chemical Signals of Adsorption-Desorption and Diffusive Processes
- 2010
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Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 10:3, s. 461-464
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Tidskriftsartikel (refereegranskat)abstract
- We present a new sensor signal processing method that improves selectivity, sensitivity, and processing speed in systems, using fluctuation-enhanced sensing. We consider the output signal of a symmetric two-sensor arrangement and generate two independent output spectra by separating the adsorption-desorption signal component from the diffusion signal component. We demonstrate the key features of our method by computer modeling and simulation.
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| 5. |
- Trawka, Maciej Pawel, et al.
(författare)
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UV-Light-Induced Fluctuation Enhanced Sensing by WO3-Based Gas Sensors
- 2016
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Ingår i: IEEE Sensors Journal. - 1530-437X .- 1558-1748. ; 16:13, s. 5152-5159
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Tidskriftsartikel (refereegranskat)abstract
- WO3-based gas sensors were investigated under UV-light irradiation and at different working temperatures with the object of achieving superior sensitivity and selectivity. Resistance fluctuations in the WO3 layer were studied together with dc resistance measurements. The data were taken in synthetic air, ethanol, nitrogen dioxide, and mixtures of these gases. We conclude that UV irradiation can easily be applied to enhance the gas sensing properties of a WO3 layer.
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