• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.559-569
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• 2007

In this paper, the dynamic controller design problem of a redundant planar 2-dof parallel manipulator is studied. Using the Euler-Lagrange equation, we formulate the dynamic model of the parallel manipulator in the joint space and propose an augmented PD controller with forward dynamic compensation for the parallel manipulator. By formulating the controller in the joint space, we eliminate the complex computation of the Jacobian matrix of joint angles with end-effector coordinate. So with less computation, our controller is easier to implement, and a shorter sampling period can be achieved, which makes the controller more suitable for high-speed motion control. Furthermore, with the combination of static friction model and viscous friction model, the active joint friction of the parallel manipulator is studied and compensated in the controller. Based on the dynamic parameters of the parallel manipulator evaluated by direct measurement and identification, motion control experiments are implemented. With the experiments, the validity of the dynamic model is proved and the performance of the controller is evaluated. Experiment results show that, with forward dynamic compensation, the augmented PD controller can improve the tracking performance of the parallel manipulator over the simple PD controller.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1997.10a
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• pp.17-23
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• 1997

A methodology for on-line data reconciliation and optimization has been proposed to minimize the energy cost of a utility system. As industrial data tend to be corrupted by noise or gross error, fast and robust data reconciliation technique is essential for the on-line optimization of utility system. Thus, we propose the hierarchical decomposition approach that can be applicable to on-line data reconciliation and optimization. As this approach divides whole system into several subsystems and removes the nonlinearity of constraint systematically, it handles complexity of system easily and shows good performance in accuracy and computation speed. Through case studies, we prove that this methodology is a good candidate for on-line data reconciliation and optimization.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2134-2143
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• 2018

This work introduces a fault diagnosis method for transformer based on self-powered radio frequency identification (RFID) sensor tag and improved Hilbert-Huang transform (HHT). Consisted by RFID tag chip, power management circuit, MCU and accelerometer, the developed RFID sensor tag is used to acquire and wirelessly transmit the vibration signal. A customized power management including solar panel, low dropout (LDO) voltage regulator, supercapacitor and corresponding charging circuit is presented to guarantee constant DC power for the sensor tag. An improved band restricted empirical mode decomposition (BREMD) which is optimized by quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to deal with the raw vibration signal. Compared with traditional methods, this improved BREMD method shows great superiority in reducing mode aliasing. Then, a promising fault diagnosis approach on the basis of Hilbert marginal spectrum variations is brought up. The measured results show that the presented power management circuit can generate 2.5V DC voltage for the rest of the sensor tag. The developed sensor tag can achieve a reliable communication distance of 17.8m in the test environment. Furthermore, the measurement results indicate the promising performance of fault diagnosis for transformer.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.491-494
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• 2006

Kalman filtering (KF) is hard to be applied to the SINS (Strap-down Inertial Navigation System)/RDSS (Radio Determination Satellite Service) integrated navigation system directly because the time delay of RDSS positioning in active mode is random. BP (Back-Propagation) Neuron computing as a powerful technology of Artificial Neural Network (ANN), is appropriate to solve nonlinear problems such as the random time delay of RDSS without prior knowledge about the mathematical process involved. The new algorithm betakes a BP neural network (BPNN) and velocity feedback to aid KF in order to overcome the time delay of RDSS positioning. Once the BP neural network was trained and converged, the new approach will work well for SINS/RDSS integrated navigation. Dynamic vehicle experiments were performed to evaluate the performance of the system. The experiment results demonstrate that the horizontal positioning accuracy of the new approach is 40.62 m (1 ${\sigma}$), which is better than velocity-feedback-based KF. The experimental results also show that the horizontal positioning error of the navigation system is almost linear to the positioning interval of RDSS within 5 minutes. The approach and its anti-jamming analysis will be helpful to the applications of SINS/RDSS integrated systems.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1089-1098
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• 2018

This study aims at developing and applying a hybrid model to the wind power prediction (WPP). The hybrid model for a very-short-term WPP (VSTWPP) is achieved through analytical data, multiple linear regressions and least square methods (MLR&LS). The data used in our hybrid model are based on the historical records of wind power from an offshore region. In this model, the WPP is achieved in four steps: 1) transforming historical data into ratios; 2) predicting the wind power using the ratios; 3) predicting rectification ratios by the total wind power; 4) predicting the wind power using the proposed rectification method. The proposed method includes one-step and multi-step predictions. The WPP is tested by applying different models, such as the autoregressive moving average (ARMA), support vector machine (SVM), and artificial neural network (ANN). The results of all these models confirmed the validity of the proposed hybrid model in terms of error as well as its effectiveness. Furthermore, forecasting errors are compared to depict a highly variable WPP, and the correlations between the actual and predicted wind powers are shown. Simulations are carried out to definitely prove the feasibility and excellent performance of the proposed method for the VSTWPP versus that of the SVM, ANN and ARMA models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1866-1883
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• 2019

As the youngest branch of information hiding, network covert timing channels conceal the existence of secret messages by manipulating the timing information of the overt traffic. The popular model-based framework for constructing covert timing channels always utilizes cumulative distribution function (CDF) of the inter-packet delays (IPDs) to modulate secret messages, whereas discards high-order statistics of the IPDs completely. The consequence is the vulnerability to high-order statistical tests, e.g., entropy test. In this study, a rich security model of covert timing channels is established based on IPD chains, which can be used to measure the distortion of multi-order timing statistics of a covert timing channel. To achieve rich security, we propose two types of covert timing channels based on nested lattices. The CDF of the IPDs is used to construct dot-lattice and interval-lattice for quantization, which can ensure the cell density of the lattice consistent with the joint distribution of the IPDs. Furthermore, compensative quantization and guard band strategy are employed to eliminate the regularity and enhance the robustness, respectively. Experimental results on real traffic show that the proposed schemes are rich-secure, and robust to channel interference, whereas some state-of-the-art covert timing channels cannot evade detection under the rich security model.

• Korean Journal of Construction Engineering and Management
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• v.24 no.4
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• pp.60-73
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• 2023

The need for adopting automation technologies to improve inefficiencies in interior finishing modeling work is increasing during the Building Information Modeling (BIM) design stage. As a result, the use of visual programming languages (VPL) for practical applications is growing. However, undefined or incorrect space designations in BIM models can hinder the development of automated finishing modeling processes, resulting in erroneous corrections and rework. To address this challenge, this study first developed a rule-based automated interior finishing detailing module for floors, walls, and ceilings. In addition, an automated space integrity checking module with 86.69% ACC using the Multi-Layer Perceptron (MLP) model was developed. These modules were integrated into a design automation module for interior finishing, which was then verified for practical utility. The results showed that the automation module reduced the time required for modeling and integrity checking by 97.6% compared to manual work, confirming its utility in assisting BIM model development for interior finishing works.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.5
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• pp.87-92
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• 2005

In this study, an automation assembly jig for the automation assembly process for the ventilation grille that is used in the interior of a car Is developed. As the method that can do the automation assembly for the ventilation grille, a simple jig and air cylinder have been applied. And a solenoid valve, a filter regulator, and on-off switch have been used in controlling the system. Moreover, the timer is attached to the equipment so that a worker may control the assembly time, as fitting the quantity on demand of production. Actually with executing the assembly test productivity and performance of assembly have been verified. In case of the automation assembly work for a ventilation grille is compared to the manual work. The optimum working speed has been identified to make the process twice or three times better.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.77-82
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• 2000

In this study, an automation assembly jig for the automation assembly process for the ventilation grille that is used in the interior of a car is developed. As the method that can do the automation assembly for the ventilation grille, a simple jig and air cylinder have been applied. And a solenoid valve, a filter regulator, and on-off switch have been used in controlling the system. Moreover, the timer is attached to the equipment so that a worker may control the assembly time, as fitting the quantity on demand of production. Actually with executing the assembly test productivity and performance of assembly have been verified. In case of the automation assembly work for a ventilation grille is compared to the manual work. The optimum working speed has been identified to make the process twice or three times better.

• Transactions of Materials Processing
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• v.23 no.2
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• pp.75-81
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• 2014

Progressive dies are used for metal stamping during which multiple operations are performed in a sequence. Material is fed automatically from a coil into the press and advances from one die station to the next with each press stroke. Transfer dies are used in high-volume manufacturing for round, deep-drawn, and medium-to-large parts. Several different operations may be incorporated within a transfer die such as blanking, bending, piercing, trimming, and deep drawing. The main challenge in the current study is how to deform a seat cushion panel meeting the design specifications without any defects. A complex automation die manufacturing technology for the automotive seat cushion panel, mixing both semi-progressive die and transfer die for continuous production, was developed.