• Journal of Sensor Science and Technology
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• v.32 no.1
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• pp.55-61
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• 2023

The objective of this study is to determine the concentrations of mixed gases by establishing a diagnosis method of a transformer using tunable-wavelength optical infrared sensors. Absorption of infrared light by methane, acetylene, and ethylene gases injected is measured from the outputs of the infrared sensors. Regression analysis equations of the gas concentrations are acquired from their respective measured absorption. The obtained concentrations are as follows: -3-9 % errors above 600 ppm(methane), 3 % errors above 1200 ppm(acetylene), and 10 % errors above 500 ppm(ethylene). The concentration inference equations obtained using the individual gases are applicable when the absorption wavelength bands do not overlap. The results of the fault analysis of a transformer using the Duval triangle method and the tunable infrared gas sensors are as follows: temperature faults with -1-1% errors and energy faults with -7-7 % errors.

• Journal of Sensor Science and Technology
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• v.5 no.1
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• pp.23-29
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• 1996

Thick film type gas sensors with parallel Pt heaters were fabricated by screen printing process and investigated sensitivities for methane gas. The TR7905 was selected as Pt paste for heater by characterization the properties of TCRs and thick film microstructures. The average resistance of parallel Pt heaters was $1.8{\Omega}$, and the best TCR obtained was $3685\;ppm/^{\circ}C$. On the top of the Pt heaters, a sensing layer added with Pt and Pd as catalyst paste was screen printed and heat treated. The sensitivity of the sensor was 4.3mV/1000ppm for methane. The power consumption of the sensors was 2.12watts.

• Journal of Sensor Science and Technology
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• v.6 no.6
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• pp.445-450
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• 1997

An ammonia gas sensor with high sensitivity using thick-film technology were fabricated and examined. The material for sensing the ammonia gas was the mixture of oxide semiconductor, $FeO_{x}-WO_{3}-SnO_{2}$. The sensor exhibits resistance increase upon exposure to low concentration of ammonia gas. The resistance of the sensor is decreased, on the other hand, for exposure to reducing gases such as ethyl alcohol, methane, propane and carbon monoxide. A novel method for detecting ammonia gas quite selectively utilizing a sensor array consisting of an ammonia gas sensor and a compensation element were proposed and developed. The compensation element is a Pt-doped $WO_{3}-SnO_{2}$ gas sensor which shows opposite direction of resistance change in comparison with that of the ammonia gas sensor upon exposure to ammonia gas. Excellent selectivity has been achieved using the sensor array having two sensing elements.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.07b
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• pp.865-868
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• 2002

$SnO_2$ powders were prepare by precipitating $Sn(OH)_4$ from an aqueous solution of $SnCl_4{\cdot}5H_2O$, pH 9.5. The effects of stability and sensitivity of $SnO_2$ thick film sensors added with various amounts, $SiO_2$, $Al_2O_3$, $ZrO_2$, $TiO_2$ have been investigated. It is shown that the 3wt% $Al_2O_3$ or $SiO_2$ can improve the stability of $SnO_2$ gas sensor at an operating temperature of $350^{\circ}C$.

• Journal of the Korean Institute of Gas
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• v.12 no.2
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• pp.48-52
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• 2008

According to extremely industrial growth, gas facilities, equipments and chemical plants are gradually increased due to incremental demands of annual amount of gases. The safety management of gases, however, is still far from their requirements. Methane, the principal ingredient of natural gas, is inflammable and explosive and is much used in factories and houses. Therefore, these gas safety management is essential. So, we, with a program of the gas safety management, hope to develop the detection system of methane gas leak using mid-infrared ray LED and PD with $3.2\;{\mu}m$. The cryogenic cooling device is indispensible at laser but needless at LED driven on the room temperature if manufacturing optical sensor with $3.2\;{\mu}m$. It, consequently, is not only possible to implement for subminiature and portable type but also able to speedily detect methane of extremely small quantities because the $CH_4$ absorption intensity at $3.2\;{\mu}m$ is stronger than that at $1.67\;{\mu}m$. Our objective of research is to prevent gas leak accidents from occurring previously and to minimize the extent of damage from them.

• Electrical & Electronic Materials
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• v.8 no.3
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• pp.278-284
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• 1995

Thin fihn SnO$_{2}$ Gas Sensor was fabricated by electron-beam evaporation system and the target made by general firing method for the purpose of detecting gas components in air, especially methane gas. SnO$_{2}$ thin film was prepared on the polished alumina substrate which Pt interdigital electrode was precoated. The effects of annealing temperature and substrate temperature on the structural properties of SnO$_{2}$ thin film on glass were investigated using the X-ray diffraction. The good crystalline structure is formed when substrate temperature is 150[.deg. C] and annealing condition is 550[.deg. C], 1[hour]. And the sensing properties at various thickness of the SnO$_{2}$ thin film and the effects of PdCI$_{2}$ addition were also investigated. The good result is showed when the thickness is below 1000[.angs.] and the quantity of PdCI$_{2}$ addition is 4[wt%]. The thickness of SnO$_{2}$ thin film was measured by .alpha.-step and Elliopsometer.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1549-1552
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• 2003

Semiconductor gas sensor using tin oxide as sensing material has been used to detect gases based on the fact that impedance of the sensing material varies when the gas sensor is exposed to the gases. This variation comprises of two parts. The first one is variation in resistance of the sensing material and the other is expressed in terms of the sensor capacitance variation. Normally, only variation of the sensor resistance is considered. In this paper, using AC measurement with a capacitor-coupled inverting amplifier circuit, both changes in the sensor resistance and variations in the sensor capacitance were investigated. These characteristics were represented as magnitude gain and phase shift of AC signal at a specific frequency after passing it through the sensor and the designed circuit. A two-stage artificial neural network, which utilized the information above, was employed to identify and quantify three combustible gases: methane, propane and butane. The network outputs were approximately proportional to concentrations of test gases with reasonable level of error.

• Journal of the Korean Institute of Gas
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• v.15 no.4
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• pp.51-55
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• 2011

This paper describes the temperature compensation algorithm using thermopile detector for nondispersive infrared methane gas sensor. From the output voltage of thermistor that is attached onto the infrared detector, the ambient temperature was extracted. The effects of temperatures on the properties of sensor module (the characteristics of narrow bandpass filter, optical cavity and infrared lamp, and gas absorption coefficient times optical path length) have been introduced in order to implement the temperature compensation algorithm. Even though the measurement error of developed sensor module was in the range of $\pm$ 1,500 ppm, after programming the temperature compensation algorithm, the developed sensor module shows a high accuracy less than +180 ppm error within $20^{\circ}C$ temperature variation.

• Journal of Sensor Science and Technology
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• v.8 no.6
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• pp.461-468
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• 1999

In this paper, we have implemented a gas recognition system for classification and identification of explosive gases such as methane, propane, and butane using a sensor array and an artificial neural network. Such explosive gases which can be usually detected in the oil factory and LPG pipeline are very dangerous for a human being. We analyzed the characteristics of a multi-dimensional sensor signals obtained from the nine sensors using the principal component analysis(PCA) technique. Also, we implemented a gas pattern recognizer using a multi-layer neural network with error back propagation learning algorithm, which can classify and identify the sorts of gases and concentrations for each gas. The simulation and experimental results show that the proposed gas recognition system is effective to identify the explosive gases. And also, we used DSP board(TMS320C31) to implement the proposed gas recognition system using the neural network for real time processing.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.11
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• pp.9-17
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• 2000

A sensor array with 10 discrete sensors integrated on a substrate was developed for discriminating the kinds and quantities of explosive gases. The sensor array consisted of 10 oxide semiconductor gas sensors with $SnO_2$ as base material and had broad sensitivity to specific gas. The sensor array was designed with uniform thermal distribution and had also high sensitivity and reproductivity to low gas concentration through nano-sized sensing materials with different additives. By using the sensitivity signal of the sensor array at $400^{\circ}C$, we could reliably discriminate the kinds and quantities of explosive gases like butane, propane and methane under the lower explosion limit through the principal component analysis (PCA) method.