• Journal of the Korea Institute of Military Science and Technology
• /
• v.21 no.6
• /
• pp.744-751
• /
• 2018

In this paper, we propose a fast detection and identification algorithm of chemical gases with a passive FTIR spectrometer. We use a pre-detection algorithm that can reduce the spatial region effectively for gas detection and the candidates of the target. It is possible to remove background spectra effectively from measured spectra with the least-squares method. The CC(Correlation Coefficients) and the SNR(Signal-to-Noise Ratio) methods are used for the detection of target gases. The proposed pre-detection algorithm allows the total process of chemical gas detection to be performed with lower complexity compared with the conventional algorithms. This paper can help developing real-time chemical detection instruments and various applications of FTIR spectrometers.

• Journal of the Korean Institute of Gas
• /
• v.20 no.5
• /
• pp.40-49
• /
• 2016

When a leak occurs in the buried pipelines, The leak locations are able to detected by using the vibration sensors. These leak detection system, intended for incompressible fluid, such as water, are of using the wave propagation velocity and a signal arrival time delay between the sensors. In this paper, to develop a leak location detection system for a compressible fluid such as gas, the conventional detection methods have been studied, improved, and verified through the experiment using the compressed air. It confirmed that it is possible to detect the leak location for compressible fluid in the buried pipelines and to be applicable to the development of a leak location detection system in buried pipelines for gas.

• 한국가스학회:학술대회논문집
• /
• 2007.04a
• /
• pp.92-97
• /
• 2007

• Journal of Sensor Science and Technology
• /
• v.17 no.3
• /
• pp.183-187
• /
• 2008

A sub-ppm level MEMS gas sensor that can be used for the detection of formaldehyde (HCHO) is presented. It is realized by using a zinc oxide (ZnO) thin-film material with a Ni-seed layer as a sensing material and by bulk micromachining technology. To enhance sensitivity of the MEMS gas sensor with Ni-seed layer was embedded with ZnO sensing material and sensing electrodes. As experimental results, the changed sensor resistance ratio for HCHO gas was 9.65 % for 10 ppb, 18.06 % for 100 ppb, and 35.7 % for 1 ppm, respectively. In addition, the minimum detection level of the fabricated MEMS gas sensor was 10 ppb for the HCHO gas. And the measured output voltage was about 0.94 V for 10 ppb HCHO gas concentration. The noise level of the fabricated MEMS gas sensor was about 50 mV. The response and recovery times were 3 and 5 min, respectively. The consumption power of the Pt micro-heater under sensor testing was 184 mW and its operating temperature was $400^{\circ}C$.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.24 no.4
• /
• pp.290-296
• /
• 2011

Carbon nanotubes (CNTs) have excellent electrical, chemical stability, mechanical and thermal properties. In this paper, networks of Multi-walled carbon nanotube (MWCNT) materials were investigated as a resistive gas sensors for the $H_2$ gas detection. Sensor films were fabricated by the air spray method using the multi-walled CNTs dispersion solution on the glass substrates cured with plasma and nitrocellulose. Sensors were characterized by the resistance measurements in the self-fabricated oven in order to find the optimum detection properties for the hydrogen gas molecular. The sensitivity and the linearity of the MWVNT sensors using the glass substrate cured with plasma for the $H_2$ gas concentration of 0.06~0.6 ppm are 0.013~0.097%/sec and 0.131~0.959%FS, respectively. The MWCNT film was excellent in the response for the hydrogen gas moleculars and its reaction speed was very fast, which could be using as hydrogen gas sensor. The resistance of the fabricated sensors decreases when the sensors are exposed to $H_2$ gas.

• KSBB Journal
• /
• v.13 no.5
• /
• pp.477-482
• /
• 1998

A biosensor with PZT piezoelectric ceramic crystal was developed for the detection of formaldehyde gas. Poled PZT piezoelectric ceramic disk was made from ZrO2, TiO2 and Nb2O5, together with the addition of PbO and polyvinyl alcohol, through various processes of mixing, calcination drying, crushing, forming, sintering, polishing, ion coating and poling. Oscillator circuit of sensor was made of operational amplifier(AD811AN). Formaldehyde dehydrogenase was immobilized onto a piezoelectic ceramic crystal, together with the cofactors, reduced glutathione and nicotinamide adenine dinucleotide. The effect of flow rate on the sensitivity was determined by varing the flow rate of carrier gas from 24.7mL/min to 111.7mL/min through detector cell. The results indicated that as the flow rate was increased, the recovery rate was increased. And a significant increase in the sensitivity was observed in enhanced flow rate of carrier gas. Frequency difference(ΔF) of immobilized PZT piezoelectic disk increased proportionally to the concentration gas and reproduced to repeated exposures of formaldehyde gas(28ppm, Δ68Hz).

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2009.06a
• /
• pp.365-366
• /
• 2009

• Transactions on Electrical and Electronic Materials
• /
• v.14 no.5
• /
• pp.254-257
• /
• 2013

In-situ optical emission spectroscopy (OES) is employed for PECVD chamber monitoring. OES is used as an addon sensor to monitoring and cleaning end point detection (EPD). On monitoring plasma chemistry using OES, the process gas and by-product gas are simultaneously monitored. Principal component analysis (PCA) enhances the capability of end point detection using OES data. Through chamber cleaning monitoring using OES, cleaning time is reduced by 53%, in general. Therefore, the gas usage of fluorine is also reduced, so satisfying Green Fab challenge in semiconductor manufacturing.

• Smart Structures and Systems
• /
• v.23 no.4
• /
• pp.393-403
• /
• 2019

Applying more features gives us better accuracy in modeling; however, increasing the inputs causes the curse of dimensions. In this paper, a new structure has been proposed for fault detecting and identifying (FDI) of high-dimensional systems. This structure consist of two structure. The first part includes Auto-Encoders (AE) as Deep Neural Networks (DNNs) to produce feature engineering process and summarize the features. The second part consists of the Local Model Networks (LMNs) with LOcally LInear MOdel Tree (LOLIMOT) algorithm to model outputs (multiple models). The fault detection is based on these multiple models. Hence the residuals generated by comparing the system output and multiple models have been used to alarm the faults. To show the effectiveness of the proposed structure, it is tested on single-shaft industrial gas turbine prototype model. Finally, a brief comparison between the simulated results and several related works is presented and the well performance of the proposed structure has been illustrated.

• Proceedings of the IEEK Conference
• /
• 2007.07a
• /
• pp.479-480
• /
• 2007

It is study about implementation of the home network system that used an ubiquitous sensor network and an embedded system in this paper. PXA270 and CC2420 were used, and the home server of a wireless sensor home network system composed it. A wireless control system is composed of a gas valve, a DC motor, a lamp and a door rock. A wireless detection system is composed of a gas detection sensor, a movement detection sensor, an extension detection sensor The wireless detection system that was an environment sensing system was composed of temperature, humidity, mic, illuminance, a speed-up, infrared rays temperature sensing module, and modular, other RFID established an USB camera, and an ubiquitous home network was composed.