• 제목/요약/키워드: Q algorithm

검색결과 690건 처리시간 0.035초

Calculus of the defect severity with EMATs by analysing the attenuation curves of the guided waves

  • Gomez, Carlos Q.;Garcia, Fausto P.;Arcos, Alfredo;Cheng, Liang;Kogia, Maria;Papelias, Mayorkinos
    • Smart Structures and Systems
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    • 제19권2호
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    • pp.195-202
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    • 2017
  • The aim of this paper is to develop a novel method to determine the severity of a damage in a thin plate. This paper presents a novel fault detection and diagnosis approach employing a new electromagnetic acoustic transducer, called EMAT, together with a complex signal processing method. The method consists in the recognition of a fault that exists within the structure, the fault location, i.e. the identification of the geometric position of damage, and the determining the significance of the damage, which indicates the importance or severity of the defect. The main scientific novelties presented in this paper is: to develop of a new type of electromagnetic acoustic transducer; to incorporate wavelet transforms for signal representation enhancements; to investigate multi-parametric analysis for noise identification and defect classification; to study attenuation curves properties for defect localization improvement; flaw sizing and location algorithm development.

Three-Phase Reference Current Generator Employing with Kalman Filter for Shunt Active Power Filter

  • Hasim, Ahmad Shukri Abu;Ibrahim, Zulkifilie;Talib, Md. Hairul Nizam;Dardin, Syed Mohd. Fairuz Syed Mohd.
    • Journal of Electrical Engineering and Technology
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    • 제12권1호
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    • pp.151-160
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    • 2017
  • This paper presents a new technique of reference current generator based on Kalman filter (KF) estimator for three-phase shunt active power filter (APF). The stationary reference frame (d-q algorithm) is used to transform the load currents into DC component. The harmonics of load currents are extracted and the three-phase reference currents are generated using KF estimator. The work is simulated using Matlab/Simulink platform. To validate the simulation results, an experimental test-rig have been perform using real-time control dSPACE DS1104. In addition, hysteresis current control was used to generate the switching signal for the correction of the harmonics in the system. The non-linear load were constructed with three-phase rectifier which connected in series with inductor and parallel with resistor and capacitor. The results shows that the new technique of shunt APF embedded with KF is proven to eliminate the harmonics created by the non-linear load with some improvement on the total harmonics distortion (THD).

A High-Performance Sensorless Control System of Reluctance Synchronous Motor with Direct Torque Control

  • Kim Min-Huei;Kim Nam-Hun;Choi Kyeong-Ho;Kim Dong-Hee;Hwang Dong-Ha
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2001년도 Proceedings ICPE 01 2001 International Conference on Power Electronics
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    • pp.355-359
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    • 2001
  • This paper presents an implementation of digital control system of speed sensorless for Reluctance Synchronous Motor (RSM) drives with DTC. The control system consists of stator flux observer, rotor position/speed/torque estimator, two hysteresis band controllers, an optimal switching look-up table, IGBT voltage source inverter, and TMS320C31 DSP controller by using fully integrated control software. The stator flux observer is based on the combined voltage and current model with stator flux feedback adaptive control that inputs are current and voltage sensing of motor terminal with estimated rotor angle for wide speed range. The rotor position is estimated by observed stator flux-linkage space vector. The estimated rotor speed is determined by differentiation of the rotor position used only in the current model part of the flux observer for a low speed operating area. It does not require the knowledge of any motor parameters, nor particular care for motor starting, In order to prove the suggested control algorithm, we have a simulation and testing at actual experimental system. The developed sensorless control system is shown a good speed control response characteristic results and high performance features in 50/1000 rpm with 1.0Kw RSM having 2.57 ratio of d/q reluctance.

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DVB-S2 기반 LDPC 복호기의 멀티레벨 변조 방식 적용을 위한 디맵핑 알고리즘 (Demapping Algorithm for Applying the Multilevel Modulation Scheme to LDPC Decoding Based on DVB-S2)

  • 정지원;정진희;김민혁
    • 한국전자파학회논문지
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    • 제17권7호
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    • pp.615-622
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    • 2006
  • DVB-S2 표준안에서는 다양한 부호화율과 그에 따른 다양한 변조 방식을 지원한다. 따라서 본 논문에서는 LDPC에 8 PSK 이상의 다치 변조 방식 적용을 위해 수신단에서 비트 분리 방법을 제시한다. 수신된 I, Q 심볼만을 이용하여 세 비트 이상의 비트를 분리하기 위한 LLR 방식에 기초를 하여 LLR 방식의 단점인 복잡도를 개선하기 위해 Euclidean, MAX, Sector 방식을 제시하였다.

불연속 암반내 터널굴착의 안정성 평가 및 암반분류를 위한 인공 신경회로망 개발 (Development of Artificial Neural Networks for Stability Assessment of Tunnel Excavation in Discontinuous Rock Masses and Rock Mass Classification)

  • 문현구;이철욱
    • 터널과지하공간
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    • 제3권1호
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    • pp.63-79
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    • 1993
  • The design of tunnels in rock masses often demands more informations on geologic features and rock mass properties than acquired by usual field survey and laboratory testings. In practice, the situation that a perfect set of geological and mechanical input data is given to geomechanics design engineer is rare, while the engineers are asked to achieve a high level of reliability in their design products. This study presents an artificial neural network which is developed to resolve the difficulties encountered in conventional design techniques, particulary the problem of deteriorating the confidence of existing numerical techniques such as the finite element, boundary element and distinct element methods due to the incomplete adn vague input data. The neural network has inferring capabilities to identify the possible failure modes, support requirements and its timing for underground openings, from previous case histories. Use of the neural network has resulted in a better estimate of the correlation between systems of rock mass classifications such as the RMR and Q systems. A back propagation learning algorithm together with a multi-layer network structure is adopted to enhance the inferential accuracy and efficiency of the neural network. A series of experiments comparing the results of the neural network with the actual field observations are performed to demonstrate the abilities of the artificial neural network as a new tunnel design assistance system.

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유압 굴삭기용 폐루프 타입 MCV(Main Control Valve) (Closed loop type MCV(Main Control Valve) for Hydraulic Excavator)

  • 임태형;이홍선;양순용
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2005년도 춘계학술대회 논문집
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    • pp.864-870
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    • 2005
  • Hydraulic excavators have been popular devices in construction field because of its multi-workings and economic efficiency. The mathematical models of excavators have many nonlinearities because of nonlinear opening characteristics and dead zone of main control valve, oil temperature variation, etc. The objective of this paper is to develop a simulator for hydraulic excavator using AMESim. Components and whole circuit are expressed graphically. Parameters and nonlinear characteristics are inputted in text style. From the simulation results, fixed spring stiffness of MCV can't satisfy accuracy of spool displacement under whole P-Q diagrams. Closed loop type MCV containing proportional gain is proposed in this paper that can reduce displacement error. The ability of closed loop MCV is verified through comparing with normal type MCV using AMESim simulator. The simulator can be used to forecastexcavator behavior when new components, new mechanical attachments, hydraulic circuit changes, and new control algorithm are applied. The simulator could be a kind of development platform for various new excavators.

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신경회로망에 의한 철손을 고려한 SynRM의 새로운 효율 최적화 제어 (A Novel Efficiency Optimization Control of SynRM Considering Iron Loss with Neural Network)

  • 강성준;고재섭;최정식;백정우;장미금;정동화
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2009년도 제40회 하계학술대회
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    • pp.776_777
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    • 2009
  • Optimal efficiency control of synchronous reluctance motor(SynRM) is very important in the sense of energy saving and conservation of natural environment because the efficiency of the SynRM is generally lower than that of other types of AC motors. This paper is proposed a novel efficiency optimization control of SynRM considering iron loss using neural network(NN). The optimal current ratio between torque current and exciting current is analytically derived to drive SynRM at maximum efficiency. This paper is proposed an efficiency optimization control for the SynRM which minimizes the copper and iron losses. The design of the speed controller based on adaptive learning mechanism fuzzy-neural networks(ALM-FNN) controller that is implemented using fuzzy control and neural networks. The objective of the efficiency optimization control is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. The control performance of the proposed controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

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적응학습 뉴로 퍼지제어기를 이용한 유도전동기의 최대 토크 제어 (Maximum Torque Control of Induction Motor using Adaptive Learning Neuro Fuzzy Controller)

  • 고재섭;최정식;김도연;정병진;강성준;정동화
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2009년도 제40회 하계학술대회
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    • pp.778_779
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    • 2009
  • The maximum output torque developed by the machine is dependent on the allowable current rating and maximum voltage that the inverter can supply to the machine. Therefore, to use the inverter capacity fully, it is desirable to use the control scheme considering the voltage and current limit condition, which can yield the maximum torque per ampere over the entire speed range. The paper is proposed maximum torque control of induction motor drive using adaptive learning neuro fuzzy controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d, q axis current $_i_{ds}$, $i_{qs}$ for maximum torque operation is derived. The proposed control algorithm is applied to induction motor drive system controlled adaptive learning neuro fuzzy controller and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the adaptive learning neuro fuzzy controller and ANN controller.

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Differential Evolution Approach for Performance Enhancement of Field-Oriented PMSMs

  • Yun, Hong Min;Kim, Yong;Choi, Han Ho
    • Journal of Electrical Engineering and Technology
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    • 제13권6호
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    • pp.2301-2309
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    • 2018
  • In a field-oriented vector-controlled permanent magnet synchronous motor (PMSM) control system, the d-axis current control loop can offer a free degree of freedom which can be used to improve control performances. However, in the industry the desired d-axis current command is usually set as zero without using the free degree of freedom. This paper proposes a method to use the degree of freedom for control performance improvement. It is assumed that both the inner loop proportional-integral (PI) current controller and the q-axis outer loop PI speed controller are tuned by the well-known tuning rules. This paper gives an optimal d-axis reference current command generator such that some useful performance indexes are minimized and/or a tradeoff between conflicting performance criteria is made. This paper uses a differential evolution algorithm to autotune the parameter values of the optimal d-axis reference current command generator. This paper implements the proposed control system in real time on a Texas Instruments TMS320F28335 floating-point DSP. This paper also gives experimental results showing the practicality and feasibility of the proposed control system, along with simulation results.

회전자 속도보상을 이용한 센서리스 유도전동기 제어 시스템 (Speed-Sensorless Induction Motor Control System using a Rotor Speed Compensation)

  • 정강률
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제54권3호
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    • pp.154-161
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    • 2005
  • This paper proposes a speed-sensorless induction motor control system using a rotor speed compensation. To explain the proposed system, this paper describes an induction motor model in the synchronous reference frame for the vector control. The rotor flux is estimated by the rotor flux observer using the reduced-dimensional state estimator technique. The estimated rotor speed is directly obtained from the electrical frequency, the slip frequency, and the rotor speed compensation with the estimated q-axis rotor flux. The error of the rotor time constant is indirectly reflected in the rotor speed compensation using the compensation of the flux error angle. To precisely estimate the rotor flux, the actual value of the stator resistance, whose actual variation is reflected, is derived. An implementation of pulse-width modulation (PWM) pulses using an effective space vector modulation (SVM) is briefly mentioned. For fast calculation and improved performance of the proposed algorithm, all control functions are implemented in software using a digital signal processor (DSP) with its environmental circuits. Also, it is shown through experimental results that the proposed system gives good performance for the speed-sensorless induction motor control.