• Title/Summary/Keyword: dynamic prediction method

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Measurement of Static and Dynamic Displacement by Image Processing and Study for Prediction Method of Velocity and Acceleration (영상처리를 이용한 정적·동적 변위 계측과 속도·가속도 추산방식 연구)

  • Heo, Seok;Lee, Bum-Ho;Jang, Il-Young
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.21 no.2
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    • pp.112-119
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    • 2011
  • This paper is concerned with the measurement of static and dynamic displacement by image processing(IP) and study for prediction method of velocity and acceleration. To measure the displacement visually, the measurement system consists of a telephoto zoom camera, CCD(charge coupled device) image device and a computer. The specific target on the white board is used to calculate the displacement of the structure. The captured image is then converted into a pixel-based data and then analyzed numerically. The limitation of the system depends on the image capturing speed and the pixel-size of image. In this paper, we developed for the displacement measurement using the image processing method. The proposed method enables us to measure the vibration displacement, velocity and acceleration directly without any contact. The current resolution for the displacement measurement can be seen from the results.

The Simulation Method for the Driving Characteristics of Washing Machine using BLDC Motor (가정용 BLDC 전동기 세탁기의 운전특성 시뮬레이션)

  • Kim, Hoe-Cheon;Jung, Tae-Uk
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.7
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    • pp.974-981
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    • 2012
  • This paper studied about the measurement method of the instantaneous dynamic load characteristics. this experimental study, we derived the instantaneous washing load characteristics and inertial moment characteristics according to the amount of laundry and water level. Also, this studied about the dynamic driving characteristics simulation method for the prediction of washing performance based on this load characteristics analysis. For this study, the design parameters of the driving motor are obtained by FEM analysis and the experiment. By using theses motor parameters and load characteristics, the instantaneous driving characteristics simulation is accomplished and it is verified with the experimental result of various driving conditions. The results of this paper would be very useful to the prediction of washing mode operation characteristics, and it can be also utilized to the washer motor control algorithm design for the washing performance improvement.

Flow Prediction-Based Dynamic Clustering Method for Traffic Distribution in Edge Computing (엣지 컴퓨팅에서 트래픽 분산을 위한 흐름 예측 기반 동적 클러스터링 기법)

  • Lee, Chang Woo
    • Journal of Korea Multimedia Society
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    • v.25 no.8
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    • pp.1136-1140
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    • 2022
  • This paper is a method for efficient traffic prediction in mobile edge computing, where many studies have recently been conducted. For distributed processing in mobile edge computing, tasks offloading from each mobile edge must be processed within the limited computing power of the edge. As a result, in the mobile nodes, it is necessary to efficiently select the surrounding edge server in consideration of performance dynamically. This paper aims to suggest the efficient clustering method by selecting edges in a cloud environment and predicting mobile traffic. Then, our dynamic clustering method is to reduce offloading overload to the edge server when offloading required by mobile terminals affects the performance of the edge server compared with the existing offloading schemes.

Dynamic Stress Analysis of Vehicle Frame Using a Nonlinear Finite Element Method

  • Kim, Gyu-Ha;Cho, Kyu-Zong;Chyun, In-Bum;Park, Seob
    • Journal of Mechanical Science and Technology
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    • v.17 no.10
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    • pp.1450-1457
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    • 2003
  • Structural integrity of either a passenger car or a light truck is one of the basic requirements for a full vehicle engineering and development program. The results of the vehicle product performance are measured in terms of durability, noise/vibration/harshness (NVH), crashworthiness and passenger safety. The level of performance of a vehicle directly affects the marketability, profitability and, most importantly, the future of the automobile manufacturer. In this study, we used the Virtual Proving Ground (VPG) approach for obtaining the dynamic stress or strain history and distribution. The VPG uses a nonlinear, dynamic, finite element code (LS-DYNA) which expands the application boundary outside classic linear, static assumptions. The VPG approach also uses realistic boundary conditions of tire/road surface interactions. To verify the predicted dynamic stress and fatigue critical region, a single bump run test, road load simulation, and field test have been performed. The prediction results were compared with experimental results, and the feasibility of the integrated life prediction methodology was verified.

A Controller Design for the Prediction of Optimal Heating Load (최적 난방부하 예측 제어기 설계)

  • 정기철;양해원
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.6
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    • pp.441-446
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    • 2000
  • This paper presents an approach for the prediction of optimal heating load using a diagonal recurrent neural networks(DRNN) and data base system of outdoor temperature. In the DRNN, a dynamic backpropagation(DBP) with delta-bar-delta teaming method is used to train an optimal heating load identifier. And the data base system is utilized for outdoor temperature prediction. Compared to other kinds of methods, the proposed method gives better prediction performance of heating load. Also a hardware for the controller is developed using a microprocessor. The experimental results show that prediction enhancement for heating load can be achieved with the proposed method regardless of the its inherent nonlinearity and large time constant.

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Prediction of dynamic soil properties coupled with machine learning algorithms

  • Dae-Hong Min;Hyung-Koo Yoon
    • Geomechanics and Engineering
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    • v.37 no.3
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    • pp.253-262
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    • 2024
  • Dynamic properties are pivotal in soil analysis, yet their experimental determination is hampered by complex methodologies and the need for costly equipment. This study aims to predict dynamic soil properties using static properties that are relatively easier to obtain, employing machine learning techniques. The static properties considered include soil cohesion, friction angle, water content, specific gravity, and compressional strength. In contrast, the dynamic properties of interest are the velocities of compressional and shear waves. Data for this study are sourced from 26 boreholes, as detailed in a geotechnical investigation report database, comprising a total of 130 data points. An importance analysis, grounded in the random forest algorithm, is conducted to evaluate the significance of each dynamic property. This analysis informs the prediction of dynamic properties, prioritizing those static properties identified as most influential. The efficacy of these predictions is quantified using the coefficient of determination, which indicated exceptionally high reliability, with values reaching 0.99 in both training and testing phases when all input properties are considered. The conventional method is used for predicting dynamic properties through Standard Penetration Test (SPT) and compared the outcomes with this technique. The error ratio has decreased by approximately 0.95, thereby validating its reliability. This research marks a significant advancement in the indirect estimation of the relationship between static and dynamic soil properties through the application of machine learning techniques.

Use of bivariate gamma function to reconstruct dynamic behavior of laminated composite plates containing embedded delamination under impact loads

  • Lee, Sang-Youl;Jeon, Jong-Su
    • Structural Engineering and Mechanics
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    • v.70 no.1
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    • pp.1-11
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    • 2019
  • This study deals with a method based on the modified bivariate gamma function for reconstructions of dynamic behavior of delaminated composite plates subjected to impact loads. The proposed bivariate gamma function is associated with micro-genetic algorithms, which is capable of solving inverse problems to determine the stiffness reduction associated with delamination. From computing the unknown parameters, it is possible for the entire dynamic response data to develop a prediction model of the dynamic response through a regression analysis based on the measurement data. The validity of the proposed method was verified by comparing with results employing a higher-order finite element model. Parametric results revealed that the proposed method can reconstruct dynamic responses and the stiffness reduction of delaminated composite plates can be investigated for different measurements and loading locations.

Flutter Analysis of Small Aircraft using Full Airframe Dynamic FE Model (전기체 동적 유한요소 모델을 이용한 소형항공기 플러터 해석)

  • Lee, Sang-Wook;Paek, Seung-Kil;Kim, Sung-Chan;Hwang, In-Hee
    • Proceedings of the KSME Conference
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    • 2008.11a
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    • pp.424-429
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    • 2008
  • Aircraft flutter analysis model consists of dynamic FE model and aerodynamic model. Dynamic FE model is composed of stiffness and mass model, and is used for the prediction of normal mode characteristics of the structure. Since aircraft flutter analysis is normally performed in the modal domain, dynamic FE model shall be constructed to describe the modal characteristics of the structure with sufficient accuracy. In this study, dynamic FE modeling method was described using full airframe FE model and structural and system weight data for aircraft flutter analysis. In addition, full airframe dynamic FE model for composite small aircraft was constituted for normal mode and flutter analysis, and the mass modeling results were compared with the target weight data to validate the mass modeling method proposed. Finally, full airframe flutter analysis of composite small aircraft was performed with the dynamic FE model and the aerodynamic model composed.

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Implementation of low power algorithm for near distance wireless communication and RFID/USN systems

  • Kim, Song-Ju;Hwang, Moon-Soo;Kim, Young-Min
    • International Journal of Contents
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    • v.7 no.1
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    • pp.1-7
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    • 2011
  • A new power control algorithm for wireless communication which can be applied to various near distance communications and USN/RFID systems is proposed. This technique has been applied and tested to lithium coin battery operated UHF/microwave transceiver systems to show extremely long communication life time without battery exchange. The power control algorithm is based on the dynamic prediction method of arrival time for incoming packet at the receiver. We obtain 16mA current consumption in the TX module and 20mA current consumption in the RX module. The advantage provided by this method compared to others is that both master transceiver and slave transceiver can be low power consumption system.

An iterative hybrid random-interval structural reliability analysis

  • Fang, Yongfeng;Xiong, Jianbin;Tee, Kong Fah
    • Earthquakes and Structures
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    • v.7 no.6
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    • pp.1061-1070
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    • 2014
  • An iterative hybrid structural dynamic reliability prediction model has been developed under multiple-time interval loads with and without consideration of stochastic structural strength degradation. Firstly, multiple-time interval loads have been substituted by the equivalent interval load. The equivalent interval load and structural strength are assumed as random variables. For structural reliability problem with random and interval variables, the interval variables can be converted to uniformly distributed random variables. Secondly, structural reliability with interval and stochastic variables is computed iteratively using the first order second moment method according to the stress-strength interference theory. Finally, the proposed method is verified by three examples which show that the method is practicable, rational and gives accurate prediction.