• Journal of Sensor Science and Technology
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• v.17 no.6
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• pp.406-413
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• 2008

We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.

• Journal of Sensor Science and Technology
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• v.14 no.2
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• pp.69-77
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• 2005

The electronic nose (e-nose) has been used in food industry and quality controls in plastic packaging. Recently it finds its applications in medical diagnosis, specifically on detection of diabetes, pulmonary or gastrointestinal problem, or infections by examining odors in the breath or tissues with its odor characterizing ability. Moreover, the use of portable e-nose enables the on-site measurements and analysis of vapors without extra gas-sampling units. This is expected to widen the application of the e-nose in various fields including point-of-care-test or e-health. In this study, a PDA-based portable e-nose was developed using micro-machined gas sensor array and miniaturized electronic interfaces. The rich capacities of the PDA in its computing power and various interfaces are expected to provide the rapid and application specific development of the diagnostic devices, and easy connection to other facilities through information technology (IT) infra. For performance verification of the developed portable e-nose system, Six different vapors were measured using the system. Seven different carbon-black polymer composites were used for the sensor array. The results showed the reproducibility of the measured data and the distinguishable patterns between the vapor species. Additionally, the application of two typical pattern recognition algorithms verified the possibility of the automatic vapor recognition from the portable measurements. These validated the portable e-nose based on PDA developed in this study.

• Korean Journal of Materials Research
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• v.33 no.5
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• pp.195-204
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• 2023

Micro-electronic gas sensor devices were developed for the detection of carbon monoxide (CO), nitrogen oxides (NO_x), ammonia (NH₃), and formaldehyde (HCHO), as well as binary mixed-gas systems. Four gas sensing materials for different target gases, Pd-SnO₂ for CO, In₂O₃ for NO_x, Ru-WO₃ for NH₃, and SnO₂-ZnO for HCHO, were synthesized using a sol-gel method, and sensor devices were then fabricated using a micro sensor platform. The gas sensing behavior and sensor response to the gas mixture were examined for six mixed gas systems using the experimental data in MEMS gas sensor arrays in sole gases and their mixtures. The gas sensing behavior with the mixed gas system suggests that specific adsorption and selective activation of the adsorption sites might occur in gas mixtures, and allow selectivity for the adsorption of a particular gas. The careful pattern recognition of sensing data obtained by the sensor array made it possible to distinguish a gas species from a gas mixture and to measure its concentration.

• Journal of Sensor Science and Technology
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• v.21 no.6
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• pp.402-407
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• 2012

We report a Fabry-Perot interferometer (FPI)-based multi-channel micro-spectrometer used for multi-gas measurement in the spectral range of $3-5{\mu}m$ and its gas sensing performance. The fabricated infrared (IR) spectrometer consists of two parts: an FPI on the top side for selective IR filtering and a $V_2O_5$-based IR detector array on the bottom side for the detection of the filtered IR. Experimental results show that the FPI-based multi-channel gas sensor has reliability and selectivity for simultaneously detecting environmentally harmful gases such as $CH_4$, $CO_2$, $N_2O$ and CO in the spectral range of $3-5{\mu}m$. The fabricated FPI-based multi-channel gas sensor also demonstrated that a reliable and selective detection of gas concentrations ranging from 0 to 500 ppm is feasible. In addition, the electrical characteristics demonstrate a superior response performance in regards to the selectivity in the multi-target gases.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.329-334
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• 2004

The electronic nose (E-nose) recently finds its applications in medical diagnosis, specifically on detection of diabetes, pulmonary or gastrointestinal problem, or infections by examining odors in the breath or tissues with its odor characterizing ability. The odor recognition performance of E-nose can be improved by manipulating the sensor array responses of vapors in time-profile forms. The different chemical interactions between the sensor materials and the volatile organic compounds (VOC's) leave unique marks in the signal profiles giving more information than collection of the conventional piecemal features, i.e., maximum sensitivity, signal slopes, rising time. In this study, to use them in vapor recognition task conveniently, a novel time-profile method was proposed, which is adopted from digital image pattern matching. The degrees of matching between 8 different vapors were evaluated by using the proposed method. The test vapors are measured by the silicon-based gas sensor array with 16 CB-polymer composites installed in membrane structure. The results by the proposed method showed clear discrimination of vapor species than by the conventional method.

• Journal of Sensor Science and Technology
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• v.24 no.6
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• pp.379-384
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• 2015

An infrared image sensor is a core device in a thermal imaging system. The fabrication method of a focal plane array (FPA) is a key technology for a high resolution infrared image sensor. Each pixels in the FPA have $Si_3N_4/SiO_2$ membranes including legs to deposit bolometric materials and electrodes on Si readout circuits (ROIC). Instead of polyimide used to form a sacrificial layer, the feasibility of an amorphous silicon (${\alpha}-Si$) was verified experimentally in a $8{\times}8$ micro-bolometer array with a $50{\mu}m$ pitch. The elimination of the polyimide sacrificial layer hardened by a following plasma assisted deposition process is sometimes far from perfect, and thus requires longer plasma ashing times leading to the deformation of the membrane and leg. Since the amorphous Si could be removed in $XeF_2$ gas at room temperature, however, the fabricated micro-bolomertic structure was not damaged seriously. A radio frequency (RF) sputtered nickel oxide film was grown on a $Si_3N_4/SiO_2$ membrane fabricated using a low stress silicon nitride (LSSiN) technology with a LPCVD system. The deformation of the membrane was effectively reduced by a combining the ${\alpha}-Si$ and LSSiN process for a nickel oxide micro-bolometer.