• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.33-42
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• 2010

This research propose a practical guidance system considering ocean currents in real sea operation. Optimality of generated path is not an issue in this paper. Way-points from start point to possible goal positions are selected by experienced human supervisors considering major ocean current axis. This paper also describes the implementation of a precise underwater navigation solution using multi-sensor fusion technique based on USBL, GPS, DVL and AHRS measurements in detail. To implement the precise, accurate and frequent underwater navigation solution, three strategies are chosen. The first one is the heading alignment angle identification to enhance the performance of standalone dead-reckoning algorithm. The second one is that absolute position is fused timely to prevent accumulation of integration error, where the absolute position can be selected between USBL and GPS considering sensor status. The third one is introduction of effective outlier rejection algorithm. The performance of the developed algorithm is verified with experimental data of mine disposal vehicle and deep-sea ROV.

• Structural Engineering and Mechanics
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• v.57 no.2
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• pp.327-355
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• 2016

A new analytical derivation of the elastodynamic point load solutions for an isotropic multi-layered half-space is presented by means of the precise integration method (PIM) and the approach of dual vector. The time-harmonic external load is prescribed either on the external boundary or in the interior of the solid medium. Starting with the axisymmetric governing motion equations in a cylindrical coordinate system, a second order ordinary differential matrix equation can be gained by making use of the Hankel integral transform. Employing the technique of dual vector, the second order ordinary differential matrix equation can be simplified into a first-order one. The approach of PIM is implemented to obtain the solutions of the ordinary differential matrix equation in the Hankel integral transform domain. The PIM is a highly accurate algorithm to solve sets of first-order ordinary differential equations and any desired accuracy of the dynamic point load solutions can be achieved. The numerical simulation is based on algebraic matrix operation. As a result, the computational effort is reduced to a great extent and the computation is unconditionally stable. Selected numerical trials are given to validate the accuracy and applicability of the proposed approach. More examples are discussed to portray the dependence of the load-displacement response on the isotropic parameters of the multi-layered media, the depth of external load and the frequency of excitation.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.8
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• pp.798-804
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• 2006

To overcome the limited relative uncertainty and work range of the existing planar stage and the bulk structure of the contact-less motor for rotation, the novel operating principle to realize the precise rotation is suggested. It uses the two-axial vector forces, normal force and thrust force, of three-induction type of axial motors located $120^{\circ}$ apart, resulting in the contact-free rotation of the mover. Firstly in this paper, the magnetic forces across the air gap are modeled and simulated under the various conditions. It clarifies the feasible range of the derived solution. And the algorithm compensating the strong cross couple between the forces and the control inputs; generally AC magnitude and slip frequency, is given to realize the independent control of six axes. Finally, for the successfully implemented system, the round test and the micro step test results are given.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.153-156
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• 2006

The vibration isolation system is a system that attenuates the vibration transmitted from surroundings by using external energy supply like electricity and feedback and/or feedforward functions. Such a system needs stiff structure to make precise positioning without ripple within a certain bandwidth. So, a horizontal and rotary arrangement of the actuation module is suggested by using lever linkage. Modeling and kinematic formulation are completed and system identification is accomplished to tune the design variables accurately. The vibration isolation control is performed by mu-synthesis with the uncertainties in design variables. Low frequency signal enhancement circuit and saturation proof integration algorithm are devised to use seismic sensors for displacement control. This overall system shows good disturbance rejection performance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.397-402
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• 2019

Recently, with the emergence of autonomous vehicles and the increasing interest in safety, a variety of research has been being actively conducted to precisely estimate the position of a vehicle by fusing sensors. Previously, researches were conducted to determine the location of moving objects using GNSS (Global Navigation Satellite Systems) and/or IMU (Inertial Measurement Unit). However, precise positioning of a moving vehicle has lately been performed by fusing data obtained from various sensors, such as LiDAR (Light Detection and Ranging), on-board vehicle sensors, and cameras. This study is designed to enhance kinematic vehicle positioning performance by using feature-based recognition. Therefore, an analysis of the required precision of the observations obtained from the images has carried out in this study. Velocity and attitude observations, which are assumed to be obtained from images, were generated by simulation. Various magnitudes of errors were added to the generated velocities and attitudes. By applying these observations to the positioning algorithm, the effects of the additional velocity and attitude information on positioning accuracy in GNSS signal blockages were analyzed based on Kalman filter. The results have shown that yaw information with a precision smaller than 0.5 degrees should be used to improve existing positioning algorithms by more than 10%.

• Geomechanics and Engineering
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• v.36 no.2
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• pp.111-119
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• 2024

In the realm of rock excavation projects, precise estimation of the drilling rate index stands as a pivotal factor in strategic planning and cost assessment. This study introduces and evaluates two pioneering computational intelligence models designed for the prognostication of the drilling rate index, a pivotal parameter with direct implications for cost estimation in rock excavation projects. These models, denoted as the Relevance Vector Regression (RVR) optimized with the Invasive Weed Optimization algorithm (IWO) (RVR-IWO model) and the RVR integrated with the Shuffled Frog Leaping algorithm (SFL) (RVR-SFL model), represent a groundbreaking approach to forecasting drilling rate index. The RVR-IWO and RVR-SFL models were meticulously devised to harness the capabilities of computational intelligence and optimization techniques for drilling rate index estimation. This research pioneers the integration of IWO and SFL with RVR, constituting an unprecedented effort in forecasting drilling rate index. The primary objective of this study was to gauge the precision and dependability of these models in forecasting the drilling rate index, revealing significant distinctions between the two. In terms of predictive precision, the RVR-IWO model emerged as the superior choice when compared to the RVR-SFL model, underscoring the remarkable efficacy of the Invasive Weed Optimization algorithm. The RVR-IWO model delivered noteworthy results, boasting a Variance Account for (VAF) of 0.8406, a Mean Squared Error (MSE) of 0.0114, and a Squared Correlation Coefficient (R²) of 0.9315. On the contrary, the RVR-SFL model exhibited slightly lower precision, yielding an MSE of 0.0160, a VAF of 0.8205, and an R2 of 0.9120. These findings serve to highlight the potential of the RVR-IWO model as a formidable instrument for drilling rate index prediction, particularly within the framework of rock excavation projects. This research not only makes a significant contribution to the realm of drilling engineering but also underscores the broader adaptability of the RVR-IWO model in tackling an array of challenges within the domain of rock engineering. Ultimately, this study advances the comprehension of drilling rate index estimation and imparts valuable insights into the practical implementation of computational intelligence methodologies within the realm of engineering projects.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1824-1833
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• 2016

In this paper, we propose networked airborne relay-based positioning scheme (N-ARPS) based on time division multiple access (TDMA) networks to improve the performance of relative navigation (RelNav). To integrate the ARPS into TDMA, there are three problems such as slot allocation, selection of airborne relays, and method for signal loss to be solved. A subframe of N-ARPS is designed to assign the slots for broadcast and relay of navigation signals consecutively to minimize the effect of mobility. The selection algorithm determines the optimum set of airborne relays by selecting evenly distributed nodes depending on their distances to the master station. Finally, we uses precise position location information (PPLI) messages, which are received in data transmission period, to estimate a user position when the navigation signals are missing. The simulation results indicate that N-ARPS significantly improves user accuracy over RelNav.

• Journal of Astronomy and Space Sciences
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• v.23 no.3
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• pp.259-268
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• 2006

The use of GPS receiver at outer space becomes common in low earth orbit. Recently most of satellites use GPS receiver as navigation solution for finding satellite position. However, the accuracy of navigation solution acquiring directly from GPS receiver is not enough in satellite application such as map generation. Post-processing concepts such as Precise Orbit Determination (POD) are recently applied to satellite data processing to improve satellite position accuracy. The POD uses raw measurement data instead of navigation solution of GPS receiver. The performance of raw measurement data depends on raw measurement data accuracy and tracking loop algorithm of GPS receiver. In this paper, a method for evaluating performance of raw measurement data is suggested. Test environment and procedure of the low earth orbit satellite acquiring for navigation solution of GPS receiver and navigation solution of POD are described. In addition, accuracy on navigation solution of GPS receiver, raw measurement data, and navigation solution of POD are analyzed. The proposed method can be applicable to general low earth orbit satellite.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.2
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• pp.139-148
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• 2014

State-of-charge (SOC) is one of the significant indicators to estimate the driving range of the electric vehicle and to control the alternator of the conventional engine vehicles as well. Therefore its precise estimation is crucial not only for utilizing the energy effectively but also preventing critical situations happening to the power train and lengthening the lifetime of the battery. However, lead-acid battery is time-variant, highly nonlinear, and the hysteresis phenomenon causes large errors in estimation SOC of the battery especially under the frequent discharge/charge. This paper proposes a novel estimation technique for the SOC of the Lead-Acid battery by using a well-known Extended Kalman Filter (EKF) and an electrical equivalent circuit model of the Lead-Acid battery considering diffusion and hysteresis characteristics. The diffusion is considered by the reconstruction of the open circuit voltage decay depending on the rest time and the hysteresis effect is modeled by calculating the normalized integration of the charge throughput during the partial cycle. The validity of the proposed algorithm is verified through the experiments.

• Journal of Biomedical Engineering Research
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• v.45 no.4
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• pp.139-147
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• 2024

This study enhances AI algorithms for extracting spinal regions from Whole Spine X-rays, aiming for higher accuracy while minimizing learning and detection times. Whole Spine X-rays, critical for diagnosing conditions such as scoliosis and kyphosis, necessitate precise differentiation of spinal contours. The conventional manual methodology encounters challenge due to the overlap of anatomical structures, prompting the integration of AI to overcome these limitations and enhance diagnostic precision. In this study, 1204 AP and 500 LAT Whole Spine X-ray images were meticulously labeled, spanning the third cervical to the fifth lumbar vertebrae. We based our efforts on the HR-Net algorithm, which exhibited the highest accuracy, and proceeded to simplify its network architecture and enhance the block structure for optimization. The optimized HR-Net algorithm demonstrates an improvement, increasing accuracy by 2.98% for the AP dataset and 1.59% for the LAT dataset compared to its original formulation. Additionally, the modification resulted in a substantial reduction in learning time by 70.06% for AP images and 68.43% for LAT images, along with a decrease in detection time by 47.18% for AP and 43.07% for LAT images. The time taken per image for detection was also reduced by 47.09% for AP and 43.07% for LAT images. We suggest that the application of the proposed HR-Net in this study can lead to more accurate and efficient extraction of spinal regions in Whole Spine X-ray images. This can become a crucial tool for medical professionals in the diagnosis and treatment of spinal-related conditions, and it will serve as a foundation for future research aimed at further improving the accuracy and speed of spinal region segmentation.