• Geophysics and Geophysical Exploration
• /
• v.13 no.4
• /
• pp.364-369
• /
• 2010

Resistivity data should be edited before the inversion because resistivity data are contaminated by a lot of noise. Generally, outlier or data violating pants-leg effect in dipole-dipole array were used to be rejected in the apparent resistivity pseudo-section. For more precise data editing, normalized voltage curves are used. In this study, we analyzed the behavior of normalized voltage curves for pole-pole, pole-dipole and dipole-dipole arrays in the presence of threedimensional inhomogeneities, and finally re-examined the validity of normalized voltage curves in the editing process of resistivity data.

• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.5
• /
• pp.825-833
• /
• 2020

Currently, the K-Water uses various valves that can be remotely controlled for optimal water management. Valve system fault can be classified into rotor defects, stator defects, bearing defects, and gear defects of induction motors. If the valve cannot be operated due to a gear fault, the water management operation can be greatly affected. For effective water management, there is an urgent need for preemptive repairs to determine whether gear is damaged through failure prediction diagnosis.. Recently, deep learning algorithms are being applied for valve failure diagnosis. However, the method currently applied has a disadvantage of attaching a vibration sensor to the valve. In this paper, propose a new algorithm to determine whether a fault exists using a convolutional neural network (CNN) based on the voltage and current information of the valve without additional sensor mounting. In particular, a normalized Lisasjous diagram was used to maximize the fault classification performance in the CNN-based diagnostic system.

• Korean Chemical Engineering Research
• /
• v.44 no.5
• /
• pp.498-504
• /
• 2006

The etch rates of photoresist (PR) and the etch selectivity of $SiO_2$ to PR in a high density $CHF_3$ plasma were investigated at different ion-incident angles and bias voltages. A Faraday cage was employed for the accurate control of ion-incident angles. The ion energy was controlled by changing bias voltages. The etch rate of $SiO_2$ continuously decreased with ion-incident angles but the etch rate of PR remained constant up to the middle angle region and decreased afterwards. The etch rates of $SiO_2$ normalized to those at $0^{\circ}$ incident angle changed with the ion-incident angle following a cosine(${\theta}$) curve. On the other hand, the normalized etch rates of the PR changed showing a drastic over-cosine shape in the middle angle region. The etch selectivity of $SiO_2$ to PR decreased with an increase in the ion-incident angle because the etch yields of PR were enhanced by physical sputtering in the middle angle region compared to the case of $SiO_2$ etching. The etch selectivity of $SiO_2$ to PR decreased with an increase in the bias voltage at nearly all ion-incident angles.