• 제목/요약/키워드: Load identification

검색결과 351건 처리시간 0.028초

신경회로망을 이용한 복합재료 원통쉘의 하중특성 추론에 관한 연구 (A Study on the Prediction of the Loaded Location of the Composite Laminated Shell by Using Neural Networks)

  • 명창문;이영신;류충현
    • Composites Research
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    • 제14권5호
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    • pp.26-37
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    • 2001
  • 본 연구에서는 복합재료 원통쉘의 구조해석을 통하여 구해진 원통쉘 경사면의 10등분 등간격 9지점의 변형율을 신경회로망의 입력패턴으로 활용하여 원통쉘에 가해진 중격하중 특성을 동시에 추론하였다. 적용된 신경회로망은 Momentum Backpropagation 알고리즘이며, 모멘텀 계수 및 학습율이 학습도에 따라 가변적으로 조정될 수 있도록 프로그램을 개발 적용하였다 Backpropagation 신경회로망의 은닉층은 1층에서 3층까지 별도 프로그램을 개발하여 충격하중 특성추론 학습을 시도하였다. 개발된 신경회로망 프로그램을 적용하여 원통쉘의 충격하중 특성추론 정확도는 1%이내로 학습에 성공하였다. 본 연구 결과 신경회로망을 이용한 복합재료 원통쉘의 충격하중 특성을 추론할 수 있는 역문제 해석이 가능해졌다.

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SWS 490A 강의 용접 열영향부 음향방출 특성에 대한 연구(2) (A Study on the Acoustic Emission Characteristics of Weld Heat Affected Zone in SWS 490A Steel(2))

  • 이장규;우창기
    • 한국공작기계학회논문집
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    • 제15권5호
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    • pp.104-113
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    • 2006
  • The main objective of this study is to investigate the effect of compounded welding by using acoustic emission (AE) signals and doing a source location for weld heat affected zone (HAZ) through tensile testing. This study was carried out an SWS 490A high strength steel for electric shield metal arc welding, SMAW; $CO_2$ gas metal arc welding, GMAW($CO_2$); and gas tungsten arc welding, GTAW/TIG. Data displays are based on the measured parameters of the AE signals, along with environmental variables such as time and load. For instance, Gutenberg-Richter magnitude-frequency relationship (G-R MFR) offers useful b-value in data analysis. Namely event identification, source location gives the X- and Y-coordinates of the AE source. And K-means clustering analysis by Euclidean distance confirmed that was powerful to source location. Generally, strength of welded metal zone was stronger than strength of base metal. As the result, confirmed certainly that fracture is produced in HAZ instead of welded metal zone from source location.

산업용 로봇의 기어소음 특성 고찰 (Identification of Gear Noise for Industrial Robots)

  • 김동해;이종문
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2002년도 추계학술대회논문집
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    • pp.152-155
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    • 2002
  • An industrial robot noise has various noise sources such as gears, motors, bearings, and controller fans. Among these, gears are the most dominant source for noise. The gear noise, caused by tooth profile, elastic deformation, machining error and wear, is directly correlated with the transmission error of mating gear. Due to the fact that has several axis and many gears, it is difficult to understand the characteristics of the vibration and noise of robots. In this study, some advanced analysis techniques based on digital signal processing such as power spectrum, time spectral map, RPM map, and etc., were applied for locating the dominant frequency components of the robot noises and identifying their sources. In addition, sound quality analysis was performed in order to evaluate the operator's annoyance. The noise and vibration measurements were carried out at several points during the operation of each axis considering the effect of load and posture of the robot. Eased on the results, proper countermeasures to reduce excessive noise level have been suggested considering the characteristics of sources.

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Shape Study of Wear Debris in Oil-Lubricated System with Neural Network

  • Park, Heung-Sik;Seo, Young-Baek;Cho, Yon-Sang
    • KSTLE International Journal
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    • 제2권1호
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    • pp.65-70
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    • 2001
  • The wear debris is fall off the moving surfaces in oil-lubricated systems and its morphology is directly related to the damage and failure to the interacting surfaces. The morphology of the wear particles are therefore directly indicative of wear processes occurring in tribological system. The computer image processing and artificial neural network was applied to shape study and identify wear debris generated from the lubricated moving system. In order to describe the characteristics of various wear particles, four representative parameter (50% volumetric diameter, aspect, roundness and reflectivity) from computer image analysis for groups of randomly sampled wear particles, are used as inputs to the network and learned the friction condition of five values (material 3, applied load 1, sliding distance 1). It is shown that identification results depend on the ranges of these shape parameters learned. The three kinds of the wear debris had a different pattern characteristics and recognized the friction condition and materials very well by neural network. We discuss how these approach can be applied to condition diagnosis of the oil-lubricated tribological system.

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강 거더교의 수직보강재 응답을 이용한 주행차량의 특성 추정 (Identification of Running Vehicle Properties by Vertical Stiffener Response of Steel Girder Bridge)

  • 이희현;전준창;정민선;경갑수
    • 한국안전학회지
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    • 제27권1호
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    • pp.86-95
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    • 2012
  • The BWIM(Bridge Weigh-In-Motion) is a technology to identify vehicle properties, such as weight, speed, axle spacing and running lane, passing over a bridge by using dynamic response of bridge member. Such information will be used for assessing durability and establishing a maintenance strategy of roadway structures. In this paper, as a first step for developing BWIM system, analytical and experimental studies were conducted in order to verify whether the response of vertical stiffener in steel girder bridge can be used to identify vehicle properties running on the bridge. It was known from this study that such vehicle information could be estimated reasonably by using strain time history curve of a vertical stiffener due to running vehicles. It is because the effect of each axle-load of vehicle appears definitely in the curve. However, as the magnitude of strain of vertical stiffener is effected by running pattern of vehicles, further study is necessary to reduce error when estimating vehicle weight.

Computational methodology to determine the strength of reinforced concrete joint

  • Sasmal, Saptarshi;Vishnu Pradeesh, L.;Devi, A. Kanchana;Ramanjaneyulu, K.
    • Advances in Computational Design
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    • 제1권1호
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    • pp.61-77
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    • 2016
  • Seismic performance of structures depends on the force flow mechanism inside the structure. Discontinuity regions, like beam-column joints, are often affected during earthquake event due to the complex and discontinuous load paths. The evaluation of shear strength and identification of failure mode of the joint region are helpful to (i) define the strength hierarchy of the beam-column sub-assemblage, (ii) quantify the influence of different parameters on the behaviour of beam-column joint and, (iii) develop suitable and adequate strengthening scheme for the joints, if required, to obtain the desired strength hierarchy. In view of this, it is very important to estimate the joint shear strength and identify the failure modes of the joint region as it is the most critical part in any beam-column sub-assemblage. One of the most effective models is softened strut and tie model which was developed by incorporating force equilibrium, strain compatibility and constitutive laws of cracked reinforced concrete. In this study, softened strut and tie model, which incorporates force equilibrium equations, compatibility conditions and material constitutive relation of the cracked concrete, are used to simulate the shear strength behaviour and to identify failure mechanisms of the beam-column joints. The observations of the present study will be helpful to arrive at the design strategy of the joints to ensure the desired failure mechanism and strength hierarchy to achieve sustainability of structural systems under seismic loading.

진화론적 파라미터 동정에 기반한 자기구성 퍼지 다항식 뉴럴 네트워크의 새로운 설계 (A New design of Self Organizing Fuzzy Polynomial Neural Network Based on Evolutionary parameter identification)

  • 박호성;이영일;오성권
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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    • pp.2891-2893
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    • 2005
  • In this paper, we introduce a new category of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) that is based on a genetically optimized multi-layer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. The conventional SOFPNN algorithm leads to a tendency to produce overly complex networks as well as a repetitive computation load by the trial and error method and/or the a repetitive parameter adjustment by designer. In order to generate a structurally and parametrically optimized network, such parameters need to be optimal. In this study, in solving the problems with the conventional SOFPNN, we introduce a new design approach of evolutionary optimized SOFPNN. Optimal parameters design available within FPN (viz. the no. of input variables, the order of the polynomial, input variables, and the no. of membership function) lead to structurally and parametrically optimized network which is more flexible as well as simpler architecture than the conventional SOFPNN. In addition, we determine the initial apexes of membership functions by genetic algorithm.

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Damage identification of 2D and 3D trusses by using complete and incomplete noisy measurements

  • Rezaiee-Pajand, M.;Kazemiyan, M.S.
    • Structural Engineering and Mechanics
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    • 제52권1호
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    • pp.149-172
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    • 2014
  • Four algorithms for damage detection of trusses are presented in this paper. These approaches can detect damage by using both complete and incomplete measurements. The suggested methods are based on the minimization of the difference between the measured and analytical static responses of structures. A non-linear constrained optimization problem is established to estimate the severity and location of damage. To reach the responses, the successive quadratic method is used. Based on the objective function, the stiffness matrix of the truss should be estimated and inverted in the optimization procedure. The differences of the proposed techniques are rooted in the strategy utilized for inverting the stiffness matrix of the damaged structure. Additionally, for separating the probable damaged members, a new formulation is proposed. This scheme is employed prior to the outset of the optimization process. Furthermore, a new tactic is presented to select the appropriate load pattern. To investigate the robustness and efficiency of the authors' method, several numerical tests are performed. Moreover, Monte Carlo simulation is carried out to assess the effect of noisy measurements on the estimated parameters.

Design and Simulation of Integral Twist Control for Helicopter Vibration Reduction

  • Shin, Sang-Joon;Cesnik Carlos E. S.;Hall Steven R.
    • International Journal of Control, Automation, and Systems
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    • 제5권1호
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    • pp.24-34
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    • 2007
  • Closed-loop active twist control of integral helicopter rotor blades is investigated in this paper for reducing hub vibration induced in forward flight. A four-bladed fully articulated integral twist-actuated rotor system has been designed and tested successfully in wind tunnel in open-loop actuation. The integral twist deformation of the blades is generated using active fiber composite actuators embedded in the composite blade construction. An analytical framework is developed to examine integrally twisted helicopter blades and their aeroelastic behavior during different flight conditions. This aeroelastic model stems from a three-dimensional electroelastic beam formulation with geometrical-exactness, and is coupled with finite-state dynamic inflow aerodynamics. A system identification methodology that assumes a linear periodic system is adopted to estimate the harmonic transfer function of the rotor system. A vibration minimizing controller is designed based on this result, which implements a classical disturbance rejection algorithm with some modifications. Using the established analytical framework, the closed-loop controller is numerically simulated and the hub vibratory load reduction capability is demonstrated.

ID 검색 개선을 위한 비보호채널상의 RFID 상호인증 프로토콜 (RFID Mutual Authentication Protocol on Insecure Channel for Improvement of ID Search)

  • 박미옥;오기욱
    • 한국컴퓨터정보학회논문지
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    • 제15권10호
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    • pp.121-128
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    • 2010
  • 본 논문에서는 데이터베이스, 리더 그리고 태그 간의 모든 통신 채널이 안전하지 않은 비보호 채널(insecure channel)임을 가정하여 비보호 채널상의 안전한 RFID 상호인증 프로토콜을 제안했다. 제안한 프로토콜은 안전한 단방향 해쉬함수를 사용했고, DB에서 태그 ID를 검색하는데 걸리는 시간과 해쉬 연산량의 부담을 개선하는 것이 목적이다. 또한, RFID 상호인증 프로토콜이 보장해야 할 기본적인 보안사항들뿐만 아니라 전방향 안전성(Forward Security)도 함께 제공하며, 태그에서 난수를 생성하지 않음으로써, 태그에서의 처리량의 부담을 줄이고자 한다.