• Title/Summary/Keyword: mathematical performances

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Micro-positioning of a Smart Structure Using an Enhanced Stick-slip Model (향상된 스틱-슬립 마찰 모델을 이용한 스마트 구조물의 마이크로 위치제어)

  • Lee, Chul-Hee;Jang, Min-Gyu;Choi, Seung-Bok
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.18 no.11
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    • pp.1134-1142
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    • 2008
  • In this paper, a model-based stick-slip compensation for the micro-positioning is proposed using an enhanced stick-slip model based on statistical rough surface contact model. The smart structure is comprised with PZT(lead (Pb) zirconia(Zr) Titanate(Ti)) based stack actuator incorporating with the PID(proportional-integral-derivative) control algorithm, mechanical displacement amplifier and positioning devices. For the stick-slip compensation, the elastic-plastic static friction model is used considering the elastic-plastic asperity contact in the rough surfaces statistically. Mathematical model of system for the positioning apparatus was derived from the dynamic behaviors of structural parts. PID feedback control algorithms with the developed stick-slip model as well as feedforward friction compensator are formulated for achieving the accurate positioning performance. Experimental results are provided to show the performances of friction control using the developed positioning apparatus.

Optimal Design of Tooth Profile for High-Efficiency Gerotor Oil Pump (지로터 오일 펌프의 성능 향상을 위한 치형의 최적 설계)

  • Kim Jae Hun;Park Joon Hong;Jung Sung Yuen;Son Jin Hyuk;Kim Chul
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.5 s.170
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    • pp.28-36
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    • 2005
  • A gerotor pump is suitable for oil hydraulics of machine tools, automotive engines, compressors, constructions and other various applications, which are highly accepted by designers. Especially the pump is an essential machine element of an automotive engine to feed lubricant oil. However, related industries do not have necessary technology to design and optimize the pump and paid royalties of rotor profile on an advanced country. Also, gerotor pumps with unsettled design parameters have not been sufficiently analyzed from a theoretical view of design. Therefore, it is still very difficult for the pump designer and manufacturer to decide the specifications for the required gerotor pump by users. In this study, the design optimization has been carried out to determine the design parameters that maximize the specific flow rate and minimize the flow rate irregularity. Theoretical analyses and optimal design of the gerotor oil pump have been performed by mathematical base, numerical method and knowledge of kinematics. An automated design system of the tooth profile has been developed through Auto LISP language and CAD method considering various design parameters. Finally, an optimally designed model for a general type of a gerotor pump has been generated and experimentally verified for the pump performances.

Design, Analysis and Evaluation of A New Energy Conserving MAC Protocol for Wireless Sensor Networks

  • Lim, Sangsoon;Kang, Young-Myoung;Jeong, Jiwoong;Kim, Chong-Kwon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.12
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    • pp.3046-3060
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    • 2012
  • Low power listening (LPL) MAC protocols based on duty-cycling mechanism have been studied extensively to achieve ultra low energy consumption in wireless sensor networks (WSNs). Especially, recent ACK-based LPL schemes such as X-MAC employ strobe preambles and an early ACK, and show fair performances in communications and energy efficiencies. However, the state-of-the-art ACK-based LPL scheme still suffers from collision problems due to the protocol incompleteness. These collision effects are not trivial and make WSNs unstable, aggravate energy consumptions. In this paper, we propose two novel schemes; (i) ${\tau}$-duration CCA to mitigate the collision problem in ACK-based LPL MAC protocols. (ii) Short Preamble Counter (SPC) to conserve more energy by reducing unnecessary overhearing. We demonstrate the performance improvement of our scheme via a mathematical analysis and real-time experiments. Both analysis and experimental results confirm that our proposed scheme saves energy by up to 36% compared to the naive ACK-based LPL MAC protocol thanks to ${\tau}$-duration CCA and SPC.

Efficient Screen Splitting Methods - A Case Study in Block-wise Motion Detection

  • Layek, Md. Abu;Chung, TaeChoong;Huh, Eui-Nam
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.10
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    • pp.5074-5094
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    • 2016
  • Screen splitting is one of the fundamental tasks in different methods including video and image compression, screen classification, screen content coding and the like. These methods in turn support various applications in data communications, remote screen sharing, remote desktop delivery to assist teaching-learning, telemedicine, Desktop as a Service etc. In the literature we find systems requiring splitting assumes a fixed size split that do not change dynamically, also there is no analysis why that split is chosen in terms of performance. By doing mathematical analysis this paper first finds the efficient splitting schemes that can be easily automated to make a system adaptive. Thereafter, taking the screen motion detection as a case study, it demonstrates the effects of various splitting methods on motion detection performance. The simulation results clearly shows how classification performances varies with different splitting which will facilitate to choose the best splitting for a specific application scenario as well as making the system adaptive by providing dynamic splitting.

MPEG-4 Video Rate Control Algorithm using SOFM-Based Neural Classifier (SOFM 신경망 분류기를 이용한 MPEG-4 비디오 전송률 제어)

  • Park, Gwang-Hoon;Lee, Yoon-Jin
    • Journal of KIISE:Software and Applications
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    • v.29 no.7
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    • pp.425-435
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    • 2002
  • This paper introduces a macroblock-based rate control algorithm using the neural classifier based in Self Organization feature Maps (SOFM). In contrast to the conventional rate control methods based on the mathematical rate distortion (RD) model and the feedback regression, proposed method can actively adapt to the rapid-varying image characteristics by establishing the global model for bitrate control and by using the SOFM based neural classifier to manage that model. Proposed rate control algorithm has 0.2 dB ~ 0.6 dB better performances than MPEG-4 macroblock-based rate control algorithm by evaluating with the encoded Peak Signal to Noise Ratios while maintaining similar overall computational complexity.

Design of multiphase carbon fiber reinforcement of crack existing concrete structures using topology optimization

  • Nguyen, Anh P.;Banh, Thanh T.;Lee, Dongkyu;Lee, Jaehong;Kang, Joowon;Shin, Soomi
    • Steel and Composite Structures
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    • v.29 no.5
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    • pp.635-645
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    • 2018
  • Beam-column joints play a significant role in static and dynamic performances of reinforced concrete frame structures. This study contributes a numerical approach of topologically optimal design of carbon fiber reinforced plastics (CFRP) to retrofit existing beam-column connections with crack patterns. In recent, CFRP is used commonly in the rehabilitation and strengthening of concrete members due to the remarkable properties, such as lightweight, anti-corrosion and simplicity to execute construction. With the target to provide an optimal CFRP configuration to effectively retrofit the beam-column connection under semi-failure situation such as given cracks, extended finite element method (X-FEM) is used by combining with multi-material topology optimization (MTO) as a mechanical description approach for strong discontinuity state to mechanically model cracked structures. The well founded mathematical formulation of topology optimization problem for cracked structures by using multiple materials is described in detail in this study. In addition, moved and regularized Heaviside functions (MRHF), that have the role of a filter in multiple materials case, is also considered. The numerical example results illustrated in two cases of beam-column joints with stationary cracks verify the validity, benefit and supremacy of the proposed method.

Model-Reference Adaptive Pitch Attitude Control of Fixed-Wing UAV (고정익 무인 항공기 피치 자세의 모델-참조 적응 제어)

  • Kim, Byung-Wook;Park, Sang-Hyuk
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.47 no.7
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    • pp.499-507
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    • 2019
  • Despite the well-known mathematical model of fixed-wing aircraft, there are various studies to meet desired performances by considering the modeling errors in the extended flight envelope. This paper proposes a new adaptation mechanism of model-reference adaptive control, which applies the Levenberg-Marquardt algorithm to the pitch attitude control of fixed-wing UAV. In addition, reference model in the adaptation law is set by referring to the dynamic properties of the plant model. The performance of the proposed adaptive control law is verified through simulations and flight tests.

Support vector ensemble for incipient fault diagnosis in nuclear plant components

  • Ayodeji, Abiodun;Liu, Yong-kuo
    • Nuclear Engineering and Technology
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    • v.50 no.8
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    • pp.1306-1313
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    • 2018
  • The randomness and incipient nature of certain faults in reactor systems warrant a robust and dynamic detection mechanism. Existing models and methods for fault diagnosis using different mathematical/statistical inferences lack incipient and novel faults detection capability. To this end, we propose a fault diagnosis method that utilizes the flexibility of data-driven Support Vector Machine (SVM) for component-level fault diagnosis. The technique integrates separately-built, separately-trained, specialized SVM modules capable of component-level fault diagnosis into a coherent intelligent system, with each SVM module monitoring sub-units of the reactor coolant system. To evaluate the model, marginal faults selected from the failure mode and effect analysis (FMEA) are simulated in the steam generator and pressure boundary of the Chinese CNP300 PWR (Qinshan I NPP) reactor coolant system, using a best-estimate thermal-hydraulic code, RELAP5/SCDAP Mod4.0. Multiclass SVM model is trained with component level parameters that represent the steady state and selected faults in the components. For optimization purposes, we considered and compared the performances of different multiclass models in MATLAB, using different coding matrices, as well as different kernel functions on the representative data derived from the simulation of Qinshan I NPP. An optimum predictive model - the Error Correcting Output Code (ECOC) with TenaryComplete coding matrix - was obtained from experiments, and utilized to diagnose the incipient faults. Some of the important diagnostic results and heuristic model evaluation methods are presented in this paper.

Experimental and numerical study of autopilot using Extended Kalman Filter trained neural networks for surface vessels

  • Wang, Yuanyuan;Chai, Shuhong;Nguyen, Hung Duc
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.12 no.1
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    • pp.314-324
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    • 2020
  • Due to the nonlinearity and environmental uncertainties, the design of the ship's steering controller is a long-term challenge. The purpose of this study is to design an intelligent autopilot based on Extended Kalman Filter (EKF) trained Radial Basis Function Neural Network (RBFNN) control algorithm. The newly developed free running model scaled surface vessel was employed to execute the motion control experiments. After describing the design of the EKF trained RBFNN autopilot, the performances of the proposed control system were investigated by conducting experiments using the physical model on lake and simulations using the corresponding mathematical model. The results demonstrate that the developed control system is feasible to be used for the ship's motion control in the presences of environmental disturbances. Moreover, in comparison with the Back-Propagation (BP) neural networks and Proportional-Derivative (PD) based control methods, the EKF RBFNN based control method shows better performance regarding course keeping and trajectory tracking.

A comparative study of multi-objective evolutionary metaheuristics for lattice girder design optimization

  • Talaslioglu, Tugrul
    • Structural Engineering and Mechanics
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    • v.77 no.3
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    • pp.417-439
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    • 2021
  • The geometric nonlinearity has been successfully integrated with the design of steel structural system. Thus, the tubular lattice girder, one application of steel structural systems have already been optimized to obtain an economic design following the completion of computationally expensive design procedure. In order to decrease its computing cost, this study proposes to employ five multi-objective metaheuristics for the design optimization of geometrically nonlinear tubular lattice girder. Then, the employed multi-objective optimization algorithms (MOAs), NSGAII, PESAII, SPEAII, AbYSS and MoCell are evaluated considering their computing performances. For an unbiased evaluation of their computing performance, a tubular lattice girder with varying size-shape-topology and a benchmark truss design with 17 members are not only optimized considering the geometrically nonlinear behavior, but three benchmark mathematical functions along with the four benchmark linear design problems are also included for the comparison purpose. The proposed experimental study is carried out by use of an intelligent optimization tool named JMetal v5.10. According to the quantitative results of employed quality indicators with respect to a statistical analysis test, MoCell is resulted with an achievement of showing better computing performance compared to other four MOAs. Consequently, MoCell is suggested as an optimization tool for the design of geometrically nonlinear tubular lattice girder than the other employed MOAs.