• Journal of Sensor Science and Technology
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• v.9 no.1
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• pp.44-50
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• 2000

Every object emits some energy from its surface. The emission energy forms surface heat distribution which we can capture by using an infrared thermal imager. The infrared thermal image may include valuable information regarding to the subsurface anomaly of the object. Since a thermal image reflects surface clutter and subsurface anomaly, we have difficulty in extracting the information on the subsurface anomaly only with thermal images taken under a wavelength. Thus, we use visible wavelength images of the object surface to remove exterior clutter. We, therefore in this paper, visualize the infrared image for overlaying it with a visible wavelength image. First, we make an interpolated image from two ordinary images taken from both sides of an infrared sensor. Next, we overlay the intermediate image with an infrared image taken from the infrared camera. The technique suggested in this paper can be utilized for analyzing the infrared images on non-destructive inspection against disaster and for safety.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.3
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• pp.200-205
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• 2015

An ultra-precise infrared microscope consisting of a high-resolution infrared objective lens and infrared sensors is utilized successfully to obtain location information on the plane and depth of local heat sources causing defects in a semiconductor device. In this study, multi-layer semiconductor chips are analyzed for the positional information of heat sources by using a lock-in infrared microscope. Optimal conditions such as focal position, integration time, current and lock-in frequency for measuring the accurate depth of the heat sources are studied by lock-in thermography. The location indicated by the results of the depth estimate, according to the change in distance between the infrared objective lens and the specimen is analyzed under these optimal conditions.

• Publications of The Korean Astronomical Society
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• v.27 no.5
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• pp.391-397
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• 2012

The SPICA (SPace Infrared Telescope for Cosmology & Astrophysics) project is a next-generation infrared space telescope optimized for mid- and far-infrared observation with a cryogenically cooled 3m-class telescope. It will achieve the high resolution as well as the unprecedented sensitivity from mid to far-infrared range. The FPC (Focal Plane Camera) proposed by KASI as an international collaboration is a near-infrared instrument. The FPC-S and FPC-G are responsible for the scientific observation in the near-infrared and the fine guiding, respectively. The FPC-G will significantly reduce pointing error down to below 0.075 arcsec through the observation of guiding stars in the focal plane. We analyzed the pointing requirement from the focal plane instruments as well as the error factors affecting the pointing stability. We also obtained the expected performance in operation modes. We concluded that the FPC-G can achieve the pointing stability below 0.075 arcsec which is the requirement from the focal plane instruments.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.27 no.1
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• pp.39-44
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• 2014

Silicon nitride thin film deposited with Plasma Enhanced Chemical Vapor Deposition was treated by a nitrogen plasma generated by Inductively Coupled Plasma at room temperature. The treatment was investigated by Fourier Transform Infrared Spectroscopy and Atomic Force Microscopy on the surface at various RF source powers at two RF bias powers. The amount of hydrogen was reduced and the surface roughness of the films was decreased remarkably after the plasma treatment. In order to understand the causes, we analyzed the plasma diagnostics by Optical Emission Spectroscopy and Double Langmuir Probe. Based on these analysis results, we show that the nitrogen plasma treatment was effective in the improving of the properties silicon nitride thin film for flexible display.

• Journal of Biosystems Engineering
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• v.23 no.6
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• pp.561-570
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• 1998

The MLR(Multiple Linear Regression) models to estimate soluble solids content non-destructively were presented to make a selection of optimal photosensor utilized to measure the soluble solids content of apples. Visible and NIR absorbance in the 400 to 2498 nanometer(nm) wavelength region, soluble solids content(sugar content), hardness, and weight were measured for 400 apples(gala). Spectrophotometer with fiber optic probe was utilized for spectrum measurement and digital refractometer was used for soluble solids content. Correlation between absorbance spectrum and soluble solids content was analyzed to pick out the optimal wavelengths and to develop corresponding prediction model by means of MLR. For the coefficient of determination($R^2$) to be over 0.92, the MLR models out of the original absorbance were built based on 7 wavelengths of 992, 904, 1096, 1032, 880, 824, 1048nm, and the ones of the second derivative absorbance based on 5 wavelengths of 784, 1056, 992, 808, 872nm. The best model of the second derivative absorbance spectrum had $R^2$=0.91, bias= -0.02bx, SEP=0.28bx for unknown samples.

• Journal of Biosystems Engineering
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• v.23 no.6
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• pp.571-582
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• 1998

The PLS(Partial Least Square) and ANN(Artificial Neural Network) were introduced to develop the soluble solids content prediction model of apples which is followed by making a subsequent selection of photosensor. For the optimal PLS model, number of factors needed for spectrum analysis were increased until the convergence of prediction residual error sum of squares. Analysis has shown that even part of the overall wavelength with no pretreatment may turn out better performing. The best PLS model was found in the 800 to 1,100nm wavelength region without pretreatment of second derivation, having $R^2$=0.9236, bias= -0.0198bx, SEP=0.2527bx for unknown samples. On the other hand, for the ANN model the second derivation led to higher performance. On partial range of 800 to 1,100nm wavelengh region, prediction model with second derivation for unknown samples reached $R^2$=0.9177, SEP=0.2903bx in contrast to $R^2$=0.7507, SEP =0.4622bx without pretreatment.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.713-716
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• 1991

This paper describes a methodology of mobile robot navigation which is designed to carry heavy payloads at high speeds to be used in FMS(Flexible Manufacturing System) without human control. Intelligent control scheme using fuzzy logic is applied to the navigation control. It analyzes sensor readings from multi-sensor system, which is composed of ultrasonic sensors, infrared sensors and odometer, for environment learning, planning, landmark detecting and system control. And it is implemented on a physical robot, AGV(Autonomous Guided Vehicle) which is a two-wheeled, indoor robot. An on-board control software is composed of two subsystems, i.e., AGV control subsystem and Sensor control subsystem. The results show that the navigation of the AGV is robust and flexible, and a real-time control is possible.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.888-891
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• 1991

In this paper, we have shown a new approach of neural networks for mobile robot motion control under an indoor refracted environment. The vehicle has two powered wheels and four passive casters which support a free motion. And it also uses sonar sensors, infrared sensors, Internal odometer, and contact sensors. Two experiments were conducted to demonstrate our objectives. The first one is that the vehicle executes a reflexive motor control to maintain a constant distance to the boundary. The second one is that as well as the boundary following, the vehicle makes a block obstacle avoidance during its path. Without prior knowledge of external environment. we have accomplished the tasks by employing a simple, reactive stimulus-response neural network scheme associating sensor data with the vehicle's action.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.14 no.6
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• pp.272-276
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• 2004

Inorganic materials, including gemstones, also have characteristic vibrational energies in the infrared that can be used for identification. For infrared spectroscopy, absorptions associated with the vibrations of the crystal structure (lattice vibrations) are characteristic of the given combination of atoms constituting the gemstone. Natural turquoise $CuAl_6(PO_4)_4\cdot(OH)_8\cdot 5H_2O$ can be distinguished easily from its common substitutes in the infrared range 2000~450$\textrm{cm}^{-1}$ by features in the mid-infrared. Gilson turquoise, which is a synthetic, exhibits a significantly smoother pattern when compared with natural turquoise, because of a different state of aggregation. Also, because the natural turquoise and gibbsite are so different chemically, their patterns are very different. The technique, which is infrared spectroscopy, is nondestructive and, with Fourier transform instrumentation, extremely rapid.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1127-1127
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• 2001

The transfer of predictive models using various chemometric techniques has been reported for FTNIR and scanning-grating based NIR instruments with respect relatively dry samples (<10% water). Some of the currently used transfer techniques include slope and bias correction (SBC), direct standardization (DS), piecewise direct standardization (PDS), orthogonal signal correction (OSC), finite impulse transform (FIR) and wavelet transform (WT) and application of neural networks. In a previous study (Greensill et at., 2001) on calibration transfer for wet samples (intact melons) across silicon diode array instrumentation, we reported on the performance of various techniques (SBC, DS, PDS, double window PDS (DWPDS), OSC, FIR, WT, a simple photometric response correction and wavelength interpolative method and a model updating method) in terms of RMSEP and Fearns criterion for comparison of RMSEP. In the current study, we compare these melon transfer results to a similar study employing pairs of spectrometers for non-invasive prediction of soluble solid content of peaches.