• Title/Summary/Keyword: Inverse modeling

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Dynamic Modeling for 6-DOF Parallel Machine Tool (6 자유도 병렬 공작기계를 위한 동역학 모델링)

  • 조한상;김종원
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.10a
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    • pp.1013-1016
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    • 1995
  • This paper deals with dynamics and control of a PRP6-DOF parallel manipulator. Dynamic modeling includes the effect of inertia of all links in the mechanism to increase modeling accuracy. Kinematic analysis about forward and inverse kinematics is also explained. Using Lagrange-D' Alambert method we get equations of motions in a link space which fully represent 6DOF motions of the manipulator.

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Numerical Quadrature Techniques for Inverse Fourier Transform in Two-Dimensional Resistivity Modeling (2차원 전기비저항 모델링에서 후리에역변환의 수치구적법)

  • Kim, Hee Joon
    • Economic and Environmental Geology
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    • v.25 no.1
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    • pp.73-77
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    • 1992
  • This paper compares numerical quadrature techniques for computing an inverse Fourier transform integral in two-dimensional resistivity modeling. The quadrature techniques using exponential and cubic spline interpolations are examined for the case of a homogeneous earth model. In both methods the integral over the interval from 0 to ${\lambda}_{min}$, where ${\lambda}_{min}$, is the minimum sampling spatial wavenumber, is calculated by approximating Fourier transformed potentials to a logarithmic function. This scheme greatly reduces the inverse Fourier transform error associated with the logarithmic discontinuity at ${\lambda}=0$. Numrical results show that, if the sampling intervals are adequate, the cubic spline interpolation method is more accurate than the exponential interpolation method.

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Fine dust(PM10) emission calculated of Dong-Hae harbor around area using inverse modeling technique (역모델링 기법을 이용한 동해항 주변지역 미세먼지 배출량 산출)

  • Kim, Ji-Hyun;Park, Young-Koo
    • Journal of the Korean Applied Science and Technology
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    • v.32 no.4
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    • pp.649-660
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    • 2015
  • Data obtained from the Calpuff inverse modeling estimate the emission amount of pollutants, and enable to establish the aim for reduction through the comparison of various cases. This study pursued to accumulate the fundamental data by the Calpuff inverse modeling for five areas in the vicinity of Donghae harbor, which focused on reduction of atmospheric fine dust. As a result of evaluation of the allowed emission amount for local sites, site-D required the most reduction, $4.95{\mu}g/m^2{\cdot}S$, based on the atmospheric guideline, $50{\mu}g/m^3$. The theoretical mitigation could decrease the average concentration of PM10 to $42.6{\mu}g/m^3$ for the study field (Donghae waste water treatment plant). Modeling only for site-A emission showed the potential concentration around the residential area of Donghae harbor, $40{\sim}50{\mu}g/m^3$. However, it will rise over $50{\mu}g/m^3$ with the addition of background level. Therefore no more emission would be allowed. Site-B including commercial area and unpaved field required the reduction of $0.11{\mu}g/m^2{\cdot}S$ due to vehicles and fugitive dust. Site-C and E did not emit additional pollutants.

Patch-based Cortical Source Modeling for EEG/MEG Distributed Source Imaging: A Simulation Study

  • Im Chang-Hwan
    • Journal of Biomedical Engineering Research
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    • v.27 no.2
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    • pp.64-72
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    • 2006
  • The present study introduces a new cortical patch-based source model for EEG/MEG cortical source imaging to consider anatomical constraints more precisely. Conventional source models for EEG/MEG cortical source imaging have used coarse cortical surface mesh or sampled small number of vertices from fine surface mesh, and thus they failed to utilize full anatomical information which nowadays we can get with sub-millimeter modeling accuracy. Conventional ones placed a single dipolar source on each cortical patch and estimated its intensity by means of various inverse algorithms; whereas the suggested cortical patch-based model integrates whole cortical area to construct lead field matrix and estimates current density that is assumed to be constant in each cortical patch. We applied the proposed and conventional models to realistic EEG data and compared the results quantitatively. The quantitative comparisons showed that the proposed model can provide more precise spatial descriptions of neuronal source distribution.

Digital Active Noise Control System Used Inverse Model (역모델을 이용한 디지털 능동 소음제어 시스템)

  • 정찬수;이강욱;정양응
    • The Journal of the Acoustical Society of Korea
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    • v.11 no.1E
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    • pp.56-63
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    • 1992
  • The poblem of active oise control has been analysed using a adaptive signal processing technique. In this methods, the adaptive signal processor or model predicts the primary sound wave travelling along the acoustic plant and generates the secondary source 180° out of phase which attempts to attempts to attenuate the undesired noise by destructive interference. In the solutions presented here, acoustic propagation delay is considered as a part of the model which used the FIR filter. The effects of error path and auxiliary path transfer functioin are anayzed and a new on=-line technique for error path modeling, adaptive delayed inverse modeling is presented. In this study, using these new concepts, our system can more reduce the noise level in duct to 5dB-15dB than only using LMS algorithm system.

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Source Identification in 2-Dimensional Scattering Field Based on Inverse Problem (역문제를 이용한 2차원 산란장에서의 소스 추정)

  • Kim, Tae Yong;Lee, Hoon-Jae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.6
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    • pp.1262-1268
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    • 2014
  • Inverse problem is very interest in the sciences and engineering, in particular for modeling and monitoring applications. By applying inverse problem, it can be widely used to exploration of mineral resources, identification of underground cables and buried pipelines, and diagnostic imaging in medical area. In this paper, we firstly consider 2-dimensional EM scattering problem and present the FDTD method to estimate unknown source. In this case, non-linear CGM technique is used to investigate unknown sources corresponding to measured data obtained from forward problem in near field. The proposed technique for solving the inverse source problem presents a reasonable agreement and can be applied to investigate an internal source signal of embedded security module.

Tool-trajectory Error at the Singular Area of Five-axis Machining - Part I: Trajectory Error Modeling - (5축 가공의 특이영역에서 공구궤적 오차 - Part I: 궤적오차 모델링 -)

  • So, Bum-Sik;Jung, Yoong-Ho;Yun, Jae-Deuk
    • Korean Journal of Computational Design and Engineering
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    • v.14 no.1
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    • pp.18-24
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    • 2009
  • This paper proposes an analytical method of evaluating the maximum error by modeling the exact tool path for the tool traverse singular region in five-axis machining. It is known that the NC data from the inverse kinematics transformation of 5-axis machining can generate singular positions where incoherent movements of the rotary axes can appear. These lead to unexpected errors and abrupt operations, resulting in scoring on the machined surface. To resolve this problem, previous methods have calculated several tool positions during a singular operation, using inverse kinematics equations to predict tool trajectory and approximate the maximum error. This type of numerical approach, configuring the tool trajectory, requires much computation time to obtain a sufficient number of tool positions in a region. We have derived an analytical equation for the tool trajectory in a singular area by modeling the tool operation into a linear and a nonlinear part that is a general form of the tool trajectory in the singular area and that is suitable for all types of five-axis machine tools. In addition, we have evaluated the maximum tool-path error exactly, using our analytical model. Our algorithm can be used to modify NC data, making the operation smoother and bringing any errors to within tolerance.

Modeling of Shear-mode Rotary MR Damper Using Multi-layer Neural Network (다층신경망을 이용한 전단모드 회전형 MR 댐퍼의 모델링)

  • Cho, Jeong-Mok;Huh, Nam;Joh, Joong-Seon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.7
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    • pp.875-880
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    • 2007
  • Scientific challenges in the field of MR(magnetorheological) fluids and devices consist in the development of MR devices, the mathematical modeling and simulation of MR devices, and the development of (optimal) control algorithm for MR device systems. To take a maximum advantage of MR fluids in control applications a reliable mathematical model, which predicts their nonlinear characteristics, is needed. A inverse model of the MR device is required to calculate current(or voltage) input of MR damper, which generates required damping force. In this paper, we implemented test a bench for shear mode rotary MR damper and laboratory tests were performed to study the characteristics of the prototype shear-mode rotary MR damper. The direct identification and inverse dynamics modeling for shear mode rotary MR dampers using multi-layer neural networks are studied.

Fashion-show Animation Generation using a Single Image to 3D Human Reconstruction Technique (이미지에서 3차원 인물복원 기법을 사용한 패션쇼 애니메이션 생성기법)

  • Ahn, Heejune;Minar, Matiur Rahman
    • Journal of Korea Society of Industrial Information Systems
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    • v.24 no.5
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    • pp.17-25
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    • 2019
  • In this paper, we introduce the technology to convert a single human image into a fashion show animation video clip. The technology can help the customers confirm the dynamic fitting result when combined with the virtual try on technique as well as the interesting experience to a normal person of being a fashion model. We developed an extended technique of full human 2D to 3D inverse modeling based on SMPLify human body inverse modeling technique, and a rigged model animation method. The 3D shape deformation of the full human from the body model was performed by 2 part deformation in the image domain and reconstruction using the estimated depth information. The quality of resultant animation videos are made to be publically available for evaluation. We consider it is a promising approach for commercial application when supplemented with the post - processing technology such as image segmentation technique, mapping technique and restoration technique of obscured area.

Positioning control of pzt actuators using neuro control with hysteresis model (ICCAS 2003)

  • Lee, Byung-Ryong;Lee, Soo-Hee;Yang, Soon-Yong;Ahn, Kyung-Kwan
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.382-385
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    • 2003
  • In this paper, in order to improve the control performance of piezoelectric actuator, an integrated control structure is proposed. The control structure consists of inverse hysteresis model , to compensate the hysteresis nonlinearty problem, and feedforward - feedback controller to give a good tracking performance. The inverse hysteresis model and neural network are used as feed-forward controller, and PID controller is used as a feedback controller. From diverse experiments it is concluded that the proposed control scheme gives good tracking performance than the classical control does.

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