• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.710-718
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• 2000

In this paper we described an approach to automation of visual inspection of solder joint defects of SMC(Surface Mounted Components) on PCBs(Printed Circuit Board) by using neural network and fuzzy rule-based classification method. Inherently the surface of the solder joints is curved tiny and specular reflective it induces difficulty of taking good image of the solder joints. And the shape of the solder joints tends to greatly vary with the soldering condition and the shapes are not identical to each other even though the solder joints belong to a set of the same soldering quality. This problem makes it difficult to classify the solder joints according to their qualities. Neural network and fuzzy rule-based classification method is proposed to effi-ciently make human-like classification criteria of the solder joint shapes. The performance of the proposed approach is tested on numerous samples of commercial computer PCB boards and compared with the results of the human inspector performance and the conventional Kohonen network.

• Journal of Power Electronics
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• v.13 no.5
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• pp.861-876
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• 2013

Instead of extracting every selected harmonic component, the current reference of selective active power filter (APF) can be also obtained by filtering out the fundamental component from distorted load current for computation efficiency. This type of mixed current reference contains kinds of harmonic components and easily involves noises. In this condition, selective harmonic compensation must be realized by the current controller. With regard that selectivity is the most significant feature of controller, this paper presents specific comparison analysis between two types of resonant controllers: proportional-resonant (PR) controller and vector-resonant (VR) controller. The comparison analysis covers the relations, performances, and stability of both controllers. Analysis results conclude that the poorer selectivity of the PR controller could be relatively improved, but limitations from system stability make the improvement hardly realized. By contrast, the VR controller exhibits excellent selectivity and is more suitable for selective APF with mixed current reference. Experimental results from laboratory prototype validate the reasonability of analysis. And the features of each resonant controller are concluded.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1523-1534
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• 2017

A Current Error Space Phasor (CESP) based hysteresis controller with online computation of the boundary for two-level inverter fed Induction Motor (IM) drives is presented in this paper. The stator voltages estimated along the ${\alpha}$-and ${\beta}$-axes and the orthogonal current error components of the motor are used in the online computation of the hysteresis boundary. All of the inherent benefits of space phasor based hysteresis controllers such as its quick dynamic response and nearby voltage vector switching are present in the proposed scheme with the added benefit of suppressing switching frequency variations. The similarity in the frequency spectrum of the phase voltage obtained at the output of the inverter using the proposed scheme and Bus Clamping Pulse Width Modulation (BCPWM) based drive is justified with the help of extensive MATLAB SIMULINK simulations. The controller is experimentally verified with a three phase, 2.2 kW IM drive for steady state and transient conditions and the obtained results match the simulation results.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.510-517
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• 2019

Increasing proliferation resistance of plutonium by way of increased $^{238}Pu$ content is of interest to the nuclear nonproliferation and international safeguards community. Considering the high alpha decay heat of $^{238}Pu$, increasing the isotopic fraction leads to a noticeably higher amount of heat generation within the plutonium. High heat generation is especially unattractive in the scenario of weaponization. Upon weaponization of the plutonium, the plutonium may generate enough heat to elevate the temperature in the high explosives to above its self-explosion temperature, rendering the weapon useless. In addition, elevated temperatures will cause thermal expansion in the components of a nuclear explosive device that may produce thermal stresses high enough to produce failure in the materials, reducing the effectiveness of the weapon. Understanding the technical limit of $^{238}Pu$ required to reduce the possibility of weaponization is key to reducing the current limit on safeguarded plutonium (greater than 80 at. % $^{238}Pu$). The plutonium vector evaluated in this study was found by simulating public information on Lightbridge's fuel design for pressurized water reactors. This study explores the temperature profile and maximum stress within a simple (first generation design) hypothetical nuclear explosive device of four unique scenarios over time. Analyzing the transient development of both the temperature profile and maximum stress not only establishes a technical limit on the $^{238}Pu$ content, but also establishes a time limit for which each scenario would be useable.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.9-12
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• 1999

This paper presents the development of a control architecture for the autonomous underwater vehicle (AUV) with VARIVEC (variable vector) propeller. Moreover this paper also describes the new technique of controlling the servomotors using the Field Programmable Gate Array (FPGA). The AUVs are being currently used fur various work assignments. For the daily measuring task, conventional AUV are too large and too heavy. A small AUV will be necessary for efficient exploration and investigation of a wide range of a sea. AUVs are in the phase of research and development at present and there are still many problems to be solved such as power resources and underwater data transmission. Further, another important task is to make them smaller and lighter for excellent maneuverability and low power. Our goal is to develop a compact and light AUV having the intelligent capabilities. We employed the VARIVEC propeller system utilizing the radio control helicopter elements, which are swash plate and DC servomotors. The VARIVEC propeller can generate six components including thrust, lateral force and moment by changing periodically the blade angle of the propeller during one revolution. It is possible to reduce the number of propellers, mechanism and hence power sources. Our control tests were carried out in an anechoic tank which suppress the reflecting effects of the wall surface. We tested the developed AUV with required performance. Experimental results indicate the effectiveness of our approach. Control of VARIVEC propeller was realized without any difficulty.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.143-148
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• 1998

The Design criteria of the auxiliary resonant snubber inverter (ARSI) using a load-side circuit are discussed in relation to electric propulsion drives. In this regard, this paper attempts to develop a set of design criteria for the ARSI. First, the switching characteristics of IGBTs under soft-switching mainly in terms of dv/dt/, di/dt and switching losses are discussed and utilized for optimizing the selection of the resonant components in the system. After that, the proper control strategies of ARSIs are analyzed and simulated based on voltage space vector modulations. Later, the design, control and implementation of the auxiliary resonant circuit suitable for industrial products are analyzed and presented. And finally, other factors including power stage layout, packaging and the choice of current sensors are included. The detailed simulation and experimental results will be included based on a laboratory prototype. The proposed design criteria of the ARSI would help the implementation of an electric propulsion drive system.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.4
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• pp.699-707
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• 2015

The ice-resistance estimation technique for icebreaking ships had been studied intensively over recent years to meet the needs of designing Arctic vessels. Before testing in the ice model basin, the estimation of a ship's ice resistance with high reliability is very important to decide the delivered power necessary for level ice operation. The main idea of previous studies came from several empirical formulas, such as Poznyak and Ionov (1981), Enkvist (1972) and Shimansky (1938) methods, in which ice resistance components such as icebreaking, buoyancy and clearing resistances were represented by the integral equations along the Design Load Water Line (DLWL). The current study proposes a few modified methods not only considering the DLWL shape, but also the hull shape under the DLWL. In the proposed methodology, the DLWL shape for icebreaking resistance and the hull shape under the DLWL for buoyancy and clearing resistances can be directly considered in the calculation. Especially, when calculating clearing resistance, the flow pattern of ice particles under the DLWL of ship is assumed to be in accordance with the ice flow observed during ice model testing. This paper also deals with application examples for a few ship designs and its ice model testing programs at the AARC ice model basin. From the comparison of results of the model test and the estimation, the reliability of this estimation technique has been discussed.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.35-41
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• 2021

A rotor is a crucial component in various mechanical assemblies. Additionally, high-speed and high-efficiency components are required in the automotive industry, manufacturing industry, and turbine systems. In particular, the failure of high-speed rotating bearings has catastrophic effects on auxiliary systems. Therefore, bearing reliability and fault diagnosis are essential for bearing maintenance. In this work, we performed failure mode and effect analysis on bearing rotors and determined that corrosion is the most critical failure type. Furthermore, we conducted experiments to extract vibration characteristic data and preprocess the vibration data through principle component analysis. Finally, we applied a machine learning algorithm called support vector machine to diagnose the failure and observed a classification performance of 98%.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.345-346
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• 2023

As the shape and size of detectable objects diversifying recognition and segmentation algorithms have been developed to acquire accurate shape information. Although a high density of data captured by the repetition of scanning improves the accuracy of algorithms the high dense data decreases the efficiency due to its large size. This paper proposes standardization algorithms using the feature of structural members on indoor point cloud data to improve the process. First of all we determine the reduction rate of the density based on the features of the target objects then the data reduction algorithm compresses the data based on the reduction rate. Second the data arrangement algorithm rotates the data until the normal vector of data is aligned along the coordinate axis to allow the following algorithms to operate properly. Final the data arrangement algorithm separates the rotated data into their leaning axis. This allows reverse engineering of indoor point clouds to obtain the efficiency and accuracy of refinement processes.

• Wind and Structures
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• v.38 no.1
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• pp.75-91
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• 2024

Reliable wind signal reconstruction can be beneficial to the operational safety of long-span bridges. Non-Gaussian characteristics of wind signals make the reconstruction process challenging. In this paper, non-Gaussian wind signals are converted into a combined prediction of two kinds of features, actual wind speeds and wind angles of attack. First, two decomposition techniques, empirical mode decomposition (EMD) and variational mode decomposition (VMD), are introduced to decompose wind signals into intrinsic mode functions (IMFs) to reduce the randomness of wind signals. Their principles and applicability are also discussed. Then, four artificial intelligence (AI) algorithms are utilized for wind signal reconstruction by combining the particle swarm optimization (PSO) algorithm with back propagation neural network (BPNN), support vector regression (SVR), long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM), respectively. Measured wind signals from a bridge site in a deep-cutting gorge are taken as experimental subjects. The results showed that the reconstruction error of high-frequency components of EMD is too large. On the contrary, VMD fully extracts the multiscale rules of the signal, reduces the component complexity. The combination of VMD-PSO-Bi-LSTM is demonstrated to be the most effective among all hybrid models.