• Journal of Urban Science
• /
• v.7 no.2
• /
• pp.53-60
• /
• 2018

Digital Twin is a technology that creates a photocopy of real-world objects on a computer and analyzes the past and present operational status by fusing the structure, context, and operation of various physical systems with property information, and predicts the future society's countermeasures. In particular, 3D rendering technology (UAS, LiDAR, GNSS, etc.) is a core technology in digital twin. so, the research and application are actively performed in the industry in recent years. However, UAS (Unmanned Aerial System) and LiDAR (Light Detection And Ranging) have to be solved by compensating blind spot which is not reconstructed according to the object shape. In addition, the terrestrial LiDAR can acquire the point cloud of the object more precisely and quickly at a short distance, but a blind spot is generated at the upper part of the object, thereby imposing restrictions on the forward digital twin modeling. The UAS is capable of modeling a specific range of objects with high accuracy by using high resolution images at low altitudes, and has the advantage of generating a high density point group based on SfM (Structure-from-Motion) image analysis technology. However, It is relatively far from the target LiDAR than the terrestrial LiDAR, and it takes time to analyze the image. In particular, it is necessary to reduce the accuracy of the side part and compensate the blind spot. By re-optimizing it after fusion with UAS and Terrestrial LiDAR, the residual error of each modeling method was compensated and the mutual correction result was obtained. The accuracy of fusion-based 3D model is less than 1cm and it is expected to be useful for digital twin construction.

• Journal of Sensor Science and Technology
• /
• v.32 no.2
• /
• pp.110-117
• /
• 2023

Reconstructing underwater geometry in real time with forward-looking sonar is critical for applications such as localization, mapping, and path planning. Geometrical data must be repeatedly calculated and overwritten in real time because the reliability of the acoustic data is affected by various factors. Moreover, scattering of signal data during the coordinate conversion process may lead to geometrical errors, which lowers the accuracy of the information obtained by the sensor system. In this study, we propose a three-step data processing method with low computational cost for real-time operation. First, the number of data points to be interpolated is determined with respect to the distance between each point and the size of the data grid in a Cartesian coordinate system. Then, the data are processed with a nonlinear interpolation so that they exhibit linear properties in the coordinate system. Finally, the data are transformed based on variations in the position and orientation of the sonar over time. The results of an evaluation of our proposed approach in a simulation show that the nonlinear interpolation operation constructed a continuous underwater geometry dataset with low geometrical error.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.2D
• /
• pp.277-285
• /
• 2008

X-ray images are wildly used in medical applications, and these can be more efficiently find scoliosis which is appearing during the growth of human skeleton than others. This research is focused on the calibration of X-ray image and three-dimensional coordinate determination of objects. Three-dimensional coordinate of objects taken by X-ray are determined by two step procedure. Firstly, interior and exterior orientation parameters are determined by camera calibration using Primary Calibration Object (PCO) which has two sides with embedded radiopaque steel ball. Secondly, calibration cage coordinates which is composed of two acrylic sheets that are perpendicular to X-ray source are determined by the parameters. Three-dimensional coordinates of calibration cage determined by photogrammetric technique are compared with that of Coordinate Measuring Machine (CMM). Though the accuracy analysis, X direction which is parallel to X-ray source error values are relatively higher than those of Y and Z directions. But, the accuracies of Y and Z axis are approximately -3 mm to 3 mm. From the research results, it is considered that photogrammetric technique is applied to determine three-dimensional coordinates of patients or assist to make medical devices.

• Journal of Aerospace System Engineering
• /
• v.18 no.3
• /
• pp.41-47
• /
• 2024

Recently, as the practical application and commercialization of unmanned aerial vehicles (UAVs) is pursued, interest in ensuring the safety of the UAV is increasing. Because UAV accidents can result in property damage and loss of life, it is important to develop technology to prevent accidents. For this reason, a technique to detect the abnormal flight state of UAVs has been developed based on the AutoEncoder model. However, the existing detection technique is limited in terms of performance and real-time processing. In this paper, we propose a U-Net based abnormal flight detection technique. In the proposed technique, abnormal flight is detected based on the increasing rate of Mahalanobis distance for the reconstruction error obtained from the U-Net model. Through simulation experiments, it can be shown that the proposed detection technique has superior detection performance compared to the existing detection technique, and can operate in real-time in an on-board environment.

• The Korean Journal of Applied Statistics
• /
• v.37 no.2
• /
• pp.191-207
• /
• 2024

Many studies have been conducted to quickly detect out-of-control situations in autocorrelated processes. The most traditionally used method is a residual control chart, which uses residuals calculated from a fitted time series model. However, many procedures for monitoring autocorrelated processes using statistical learning methods have recently been proposed. In this paper, we propose a monitoring procedure using the latent vector of LSTM Autoencoder, a deep learning-based unsupervised learning method. We compare the performance of this procedure with the LSTM Autoencoder procedure based on the reconstruction error, the RNN classification procedure, and the residual charting procedure through simulation studies. Simulation results show that the performance of the proposed procedure and the RNN classification procedure are similar, but the proposed procedure has the advantage of being useful in processes where sufficient out-of-control data cannot be obtained, because it does not require out-of-control data for training.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.3
• /
• pp.130-139
• /
• 2024

Artificial intelligence models are being used to detect facility anomalies using physics data such as vibration, current, and temperature for predictive maintenance in the manufacturing industry. Since the types of facility anomalies, such as facility defects and failures, anomaly detection methods using autoencoder-based unsupervised learning models have been mainly applied. Normal or abnormal facility conditions can be effectively classified using the reconstruction error of the autoencoder, but there is a limit to identifying facility anomalies specifically. When facility anomalies such as unbalance, misalignment, and looseness occur, the facility vibration frequency shows a pattern different from the normal state in a specific frequency range. This paper presents an N-segmentation anomaly detection method that performs anomaly detection by dividing the entire vibration frequency range into N regions. Experiments on nine kinds of anomaly data with different frequencies and amplitudes using vibration data from a compressor showed better performance when N-segmentation was applied. The proposed method helps materialize them after detecting facility anomalies.

• Journal of Broadcast Engineering
• /
• v.1 no.2
• /
• pp.176-187
• /
• 1996

This paper deals with the accurate estimation of 3- D pose (position and orientation) of a moving object with reference to the world frame (or robot base frame), based on a sequence of stereo images taken by cameras mounted on the end - effector of a robot manipulator. This work is an extension of the previous work[1]. Emphasis is given to the 3-D pose estimation relative to the world (or robot base) frame under the presence of not only the measurement noise in 2 - D images[ 1] but also the camera position errors due to the random noise involved in joint angles of a robot manipulator. To this end, a new set of discrete linear Kalman filter equations is derived, based on the following: 1) the orientation error of the object frame due to measurement noise in 2 - D images is modeled with reference to the camera frame by analyzing the noise propagation through 3- D reconstruction; 2) an extended Jacobian matrix is formulated by combining the result of 1) and the orientation error of the end-effector frame due to joint angle errors through robot differential kinematics; and 3) the rotational motion of an object, which is nonlinear in nature, is linearized based on quaternions. Motion parameters are computed from the estimated quaternions based on the iterated least-squares method. Simulation results show the significant reduction of estimation errors and also demonstrate an accurate convergence of the actual motion parameters to the true values.

• Journal of Biomedical Engineering Research
• /
• v.25 no.4
• /
• pp.269-275
• /
• 2004

Different biological tissues have different values of electrical resistivity. In EIT (electrical impedance tomography), we try to provide cross-sectional images of a resistivity distribution inside an electrically conducting subject such as the human body mainly for functional imaging. However, it is well known that the image reconstruction problem in EIT is ill-posed and the quality of a reconstructed image highly depends on the measurement error. This requires us to develop a high-performance EIT system. In this paper, we describe the development of a 16-channel digital EIT system including a single constant current source, 16 voltmeters, main controller, and PC. The system was designed and implemented using the FPGA-based digital technology. The current source injects 50KHz sinusoidal current with the THD (total harmonic distortion) of 0.0029% and amplitude stability of 0.022%. The single current source and switching circuit reduce the measurement error associated with imperfect matching of multiple current sources at the expense of a reduced data acquisition time. The digital voltmeter measuring the induced boundary voltage consists of a differential amplifier, ADC, and FPGA (field programmable gate array). The digital phase-sensitive demodulation technique was implemented in the voltmeter to maximize the SNR (signal-to-noise ratio). Experimental results of 16-channel digital voltmeters showed the SNR of 90dB. We used the developed EIT system to reconstruct resistivity images of a saline phantom containing banana objects. Based on the results, we suggest future improvements for a 64-channel muff-frequency EIT system for three-dimensional dynamic imaging of bio-impedance distributions inside the human body.

• Progress in Medical Physics
• /
• v.10 no.3
• /
• pp.159-168
• /
• 1999

Cardiac disease is one of the leading causes of death in Korea. In quantitative analysis of cardiac function and morphological information by three-dimensional reconstruction of magnetic resonance images, left ventricle provides an important role functionally and physiologically. However, existing procedures mostly rely on the extensive human interaction and are seldom evaluated on clinical applications. In this study, we developed a system which could perform automatic extraction of enpicardial and endocardial contour and analysis of cardiac function to evaluate reliability and stability of each system comparing with the result of ARGUS system offered 1.5T Siemens MRI system and manual method performed by clinicians. For various aspects, we investigated reliability of each system by compared with left ventricular contour, end-diastolic volume (EDV), end-systolic volume (ESV), stock volume (SV), ejection fraction (EF), cardiac output (CO) and wall thickness (WT). When comparing with manual method, extracted results of developed process using minimum error threshold (MET) method that automatically extracts contour from cardiac MR images and ARGUS system were demonstrated as successful rate 90% of the contour extraction. When calculating cardiac function parameters using MET and comparing with using correlation coefficients analysis method, the process extracts endocardial and epicardial contour using MET, values from automatic and ARGUS method agreed with manual values within :t 3% average error. It was successfully demonstrated that automatic method using threshold technique could provide high potential for assessing of each parameters with relatively high reliability compared with manual method. In this study, the method developed in this study could reduce processing time compared with ARGUS and manual method due to a simple threshold technique. This method is useful for diagnosis of cardiac disease, simulating physiological function and amount of blood flow of left ventricle. In addition, this method could be valuable in developing automatic systems in order to apply to other deformable image models.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.22 no.2
• /
• pp.45-55
• /
• 2017

Long chain alkyl diols (LCDs) have been reported in sediments from various marine environments. Rampen et al. (2012) introduced the paleo-sea surface temperature (SST) proxy, Long chain Diol Index (LDI) based on the relative abundance of $C_{30}$ 1,15-diol, $C_{28}$ 1,13-diol, and $C_{30}$ 1,13-diol. In general, CP-Sil5CB and DB-5ms columns have been used for the quantitative and qualitative analysis of LCDs with a GC-MS. In this study, we examined the effect of three different columns (CP-Sil5CB, HP-5ms and DB-5) on the quantitative analysis of LCDs using marine sediments from the East Sea of Korea and the western Arctic Ocean. In general, our study showed that the results of CP-Sil5CB differed significantly from those of HP-5ms and DB-5. However, the differences of the LDI-derived SSTs among three columns were $0.1-0.2^{\circ}C$ for the East Sea and $0.2-0.7^{\circ}C$ for the western Arctic Ocean, which were well within the calibration error range (${\pm}1{\sigma}$). Accordingly, our study showed that the use of different columns resulted in significant differences of LCDs concentrations, but its effect on the LDI was relatively insignificant. Therefore, it appears that the different columns can be used for the paleo-SST reconstruction in the East Sea and the western Arctic Ocean using the LDI proxy.