• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.525-534
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• 2023

Gas leak detection system is a key to minimize the loss of life due to the explosiveness and toxicity of gas. Most of the leak detection systems detect by gas sensors or thermal imaging cameras. To improve the performance of gas leak detection system using single-modal methods, the paper propose multimodal approach to gas sensor data and thermal camera data in developing a gas type identification model. MultimodalGasData, a multimodal open-dataset, is used to compare the performance of the four models developed through multimodal approach to gas sensors and thermal cameras with existing models. As a result, 1D CNN and GasNet models show the highest performance of 96.3% and 96.4%. The performance of the combined early fusion model of 1D CNN and GasNet reached 99.3%, 3.3% higher than the existing model. We hoped that further damage caused by gas leaks can be minimized through the gas leak detection system proposed in the study.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.1-8
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• 2000

A new method of knock detection in SI engines, using a change of ion concentration in the combustion chamber, was developed. In order to measure in-cylinder ionization current, ionization probes were installed at spark plug and cylinder head of production engine. It was found that the electric current generated by ionized gas in core burned gas region of knocking cycle is between 2 and 10 times larger than that of normal cycle, because the burned gas temperature which is the dominant parameter of a change of ion concentration increases. However, a change of ionization current in boundary region of burned gas is relatively weak. Hence a change of ion concentration in core burned gas region can be used for knock detection.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.7
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• pp.521-526
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• 2018

In particular, gas sensors require characteristics such as high speed, sensitivity, and selectivity. In this study, we fabricated a $NO_X$ gas sensor by using a multi-walled carbon nanotube (MWCNT)/zinc oxide (ZnO) composite film. The fabricated MWCNT/ZnO gas sensor was then treated by a $450^{\circ}C$ temperature process to increase its detection sensitivity for NOx gas. We compared the detection characteristics of a ZnO film gas sensor, MWCNT film gas sensor, and the MWCNT/ZnO composited film gas sensor with and without the heat-treatment process. The fabricated gas sensors were used to detect $NO_X$ gas at different concentrations. The gas sensor absorbed $NO_X$ gas molecules, exhibiting increased sensitivity. The sensitivity of the gas sensor was increased by increasing the gas concentration. Additionally, while changing the temperature inside the chamber for the MWCNT/ZnO composite film gas sensor, we obtained its sensitivity for detecting $NO_X$ gas. Compared with ZnO, the MWCNT film gas sensor is excellent for detecting $NO_X$ gas. From the experimental results, we confirmed the enhanced gas sensor sensing mechanism. The increased effect by electronic interaction between the MWCNT and ZnO films contributes to the improved sensor performance.

• Journal of the Korea Safety Management & Science
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• v.17 no.2
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• pp.129-137
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• 2015

This study is in regard to the gas detection system and gas detection method utilizing smart phone. This study includes; 1) the sensor module attached to the smart phone to detect and measure flammable gas or toxic gas; and 2) gas detection APP which is installed inside the smart phone and recognizes the user information and location information automatically by reading RFID tag indicating the user or the location to detect gas through the contact area where RFID and blue tooth reader is installed inside of the above mentioned smart phone, and then measures the combustible gas or toxic gas by operating above mentioned sensor module and obtains the data thus measured, and above mentioned smart phone is characterized by its transmission of the above mentioned user information, location information and measured data which are obtained by above mentioned gas detecting APP to operation server via communication network. With this, reliability for the location detecting gas by the user, the result of the measurement, etc. can be secured. Furthermore, this provides the effect of preventing artificial manipulation at the time of input which is associated with the identification of the user to be measured by utilizing removable sensor module and application or the mistake resulted from wrong input by the user. In addition, by transmitting the measured data from the sensor module carrying out gas detection to operation server, this provides the effect of making it possible to process the data thus collected to a specialized data for combustible gas or toxic gas.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.110-116
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• 2024

Despite the continuous advancement of science and technology, fire accidents continue to occur without decreasing over time, so there is a constant need for a system that can accurately detect fires at an early stage. However, because most existing fire detection systems detect fire in the early stage of combustion when smoke is generated, rapid fire prevention actions may be delayed. Therefore we propose an early fire detection system that can perform early fire detection at a reasonable cost using LSTM, a deep learning model based on multi-gas sensors with high selectivity in the early stage of decomposition rather than the smoke generation stage. This system combines multiple gas sensors to achieve faster detection speeds than traditional sensors. In addition, through window sliding techniques and model light-weighting, the false alarm rate is low while maintaining the same high accuracy as existing deep learning. This shows that the proposed fire early detection system is a meaningful research in the disaster and engineering fields.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.9
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• pp.1163-1169
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• 2014

As a preliminary study for detection techniques of $CO_2$ gas bubble plumes, we have conducted a comparative experiment on artificially generated $CO_2$ gas bubbles plume by using multibeam echosounder (MBES), single beam echosounder (SBES), and sub-bottom profiler (SBP). The rising speed of artificial gas bubbles is higher than references because of compulsory release of compressed gas in the tank. Compared to single beam acoustic equipments, the MBES detects wide swath coverage. It provides exact determination of the source position and 3D information on the gas bubble plumes in the water column. Therefore, it is shown that MBES can distinctly detect gas bubble plumes compared to single beam acoustic equipments. We can establish more effective complementary detection technique by simultaneous operation of MBES and SBES. Consequently, it contributes to improve qualitative and quantitative detection techniques by understanding the acoustic characteristics of the specific gas bubbles.

• Journal of the Korean Chemical Society
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• v.61 no.4
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• pp.139-142
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• 2017

Ethene ($C_2H_4$), which is produced in plants as they mature, was used to study its photoacoustic properties using photoacoustic spectroscopy. Detection of trace amounts, with $N_2$ gas, of $C_2H_4$ gas was also applied. The gas was tested in various conditions-temperature, concentration of the gas, gas cell length, and power of the laser- to determine their effect on the photoacoustic signal, the ideal conditions to detect trace gas amounts, and concentration of $C_2H_4$ produced by an avocado and a banana. A detection limit of 10 ppm was determined for pure $C_2H_4$. A detection of 5% and 13% (by volume) concentration of $C_2H_4$ was produced for a ripening avocado and banana, respectively, in closed space.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.11a
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• pp.323-324
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• 2005

To found out the degradation characteristic of transformer insulation, insulation materials and electrodes are deposited into transformer oil. They used to heated and make flashover. Due to the thermal and electrical stress added to insulation materials, the density of carbon dioxide and hydrogen included in transformer oil was increased. The gas density can measured by using the gas density detection equipment of gas sensor and air circulation method.

• Korean Journal of Materials Research
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• v.28 no.1
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• pp.1-5
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• 2018

Gas detection is necessary for various reasons, including the prevention of gas leakages and the creation of necessary environmental conditions. Among the gas detection methods, leakage of gas can be confirmed using materials that undergo color changes that are easily distinguished by the naked eye. Metal nanoparticles (NPs) experience variations in their absorption wavelengths under the localized surface plasmon effect (LSPR) with mechanical stresses, which change the distance between NPs. In this study, we attempted to detect the presence of gas utilizing the LSPR-related color change of a chain of Au NPs. The assembly of Au NPs, arranged in a chain shape, experienced a color change from dark blue to purple with a change in the distance between the NPs by applying a physical force, i.e., compression, stretching, and gas pressure. As the force of compression and the degree of stretching increased, the absorption wavelength shifted from doublet peaks at 650 and 550 nm to a singlet peak at 550 nm. Further, applying gas pressure caused an identical color change. With this result, we propose a method that could be applied to all gases that require detection based on gas pressure.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.32 no.5
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• pp.432-436
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• 2019

In this study, we produced a light, flexible, wearable gas sensor by depositing MWCNTs (Multi-walled Carbon Nanotubes) into nylon. MWCNTs are widely used as a gas sensor material due to their excellent mechanical, electrical and physical characteristics. We produced a gas sensor to detect NOx gases by depositing nylon yarn in a MWCNT solution. The MWCNT solution was made by mixing 3 mg MWCNT in 5 ml of ethanol. Nylon yarn was placed in the manufactured solution and ultrasonic waves were applied using an ultrasonicator for 3 h, resulting in MCWNT deposition. The MWCNT-deposited nylon yarn was dried at room temperature for 24 h. The MWCNT-thin-film-coated nylon yarn was masked 1 mm apart, and gold was then deposited on the masked nylon yarn to create the gas sensor. The sensor then was installed in a chamber with a controlled atmospheric environment and exposed to NOx gas. The changing signal from the sensor was amplified to analyze its gas detection characteristics.