• 제목/요약/키워드: Smart Particle

검색결과 125건 처리시간 0.022초

An Innovative Fast Relay Coordination Method to Bypass the Time Consumption of Optimization Algorithms in Relay Protection Coordination

  • Kheshti, Mostafa;Kang, Xiaoning;Jiao, Zaibin
    • Journal of Electrical Engineering and Technology
    • /
    • 제12권2호
    • /
    • pp.612-620
    • /
    • 2017
  • Relay coordination in power system is a complex problem and so far, meta-heuristic algorithms and other methods as an alternative approach may not properly deal with large scale relay coordination due to their huge time consuming computation. In some cases the relay coordination could be unachievable. As the urgency for a proper approach is essential, in this paper an innovative and simple relay coordination method is introduced that is able to be applied on optimization algorithms for relay protection coordination. The objective function equation of operating time of relays are divided into two separate functions with less constraints. As the analytical results show here, this equivalent method has a remarkable speed with high accuracy to coordinate directional relays. Two distribution systems including directional overcurrent relays are studied in DigSILENT software and the collected data are examined in MATLAB. The relay settings of this method are compared with particle swarm optimization and genetic algorithm. The analytical results show the correctness of this mathematical and practical approach. This fast coordination method has a proper velocity of convergence with low iteration that can be used in large scale systems in practice and also to provide a feasible solution for protection coordination in smart grids as online or offline protection coordination.

3D Non-Rigid Registration for Abdominal PET-CT and MR Images Using Mutual Information and Independent Component Analysis

  • Lee, Hakjae;Chun, Jaehee;Lee, Kisung;Kim, Kyeong Min
    • IEIE Transactions on Smart Processing and Computing
    • /
    • 제4권5호
    • /
    • pp.311-317
    • /
    • 2015
  • The aim of this study is to develop a 3D registration algorithm for positron emission tomography/computed tomography (PET/CT) and magnetic resonance (MR) images acquired from independent PET/CT and MR imaging systems. Combined PET/CT images provide anatomic and functional information, and MR images have high resolution for soft tissue. With the registration technique, the strengths of each modality image can be combined to achieve higher performance in diagnosis and radiotherapy planning. The proposed method consists of two stages: normalized mutual information (NMI)-based global matching and independent component analysis (ICA)-based refinement. In global matching, the field of view of the CT and MR images are adjusted to the same size in the preprocessing step. Then, the target image is geometrically transformed, and the similarities between the two images are measured with NMI. The optimization step updates the transformation parameters to efficiently find the best matched parameter set. In the refinement stage, ICA planes from the windowed image slices are extracted and the similarity between the images is measured to determine the transformation parameters of the control points. B-spline. based freeform deformation is performed for the geometric transformation. The results show good agreement between PET/CT and MR images.

Performance of multiple tuned mass dampers-inerters for structures under harmonic ground acceleration

  • Cao, Liyuan;Li, Chunxiang;Chen, Xu
    • Smart Structures and Systems
    • /
    • 제26권1호
    • /
    • pp.49-61
    • /
    • 2020
  • This paper proposes a novel high performance vibration control device, multiple tuned mass dampers-inerters (MTMDI), to suppress the oscillatory motions of structures. The MTMDI, similar to the MTMD, involves multiple tuned mass damper-inerter (TMDI) units. In order to reveal the basic performance of the MTMDI, it is installed on a single degree-of-freedom (SDOF) structure excited by the ground acceleration, and the dynamic magnification factors (DMF) of the structure-MTMDI system are formulated. The optimization criterion is determined as the minimization of maximum values of the relative displacement's DMF for the controlled structure. Based on the particle swarm optimization (PSO) algorithm to tune the optimum parameters of the MTMDI, its performance has been investigated and evaluated in terms of control effectiveness, strokes, stiffness and damping coefficient, inerter element force, and robustness in frequency domain. Meanwhile, further comparison between the MTMDI with MTMD has been conducted. Numerical results clearly demonstrate the MTMDI outperforms the MTMD in control effectiveness and strokes of mass blocks. Additionally, in the aspects of frequency perturbations on both earthquake excitations and structures, the robustness of the MTMDI is also better than the MTMD.

Dynamic deflection monitoring of high-speed railway bridges with the optimal inclinometer sensor placement

  • Li, Shunlong;Wang, Xin;Liu, Hongzhan;Zhuo, Yi;Su, Wei;Di, Hao
    • Smart Structures and Systems
    • /
    • 제26권5호
    • /
    • pp.591-603
    • /
    • 2020
  • Dynamic deflection monitoring is an essential and critical part of structural health monitoring for high-speed railway bridges. Two critical problems need to be addressed when using inclinometer sensors for such applications. These include constructing a general representation model of inclination-deflection and addressing the ill-posed inverse problem to obtain the accurate dynamic deflection. This paper provides a dynamic deflection monitoring method with the placement of optimal inclinometer sensors for high-speed railway bridges. The deflection shapes are reconstructed using the inclination-deflection transformation model based on the differential relationship between the inclination and displacement mode shape matrix. The proposed optimal sensor configuration can be used to select inclination-deflection transformation models that meet the required accuracy and stability from all possible sensor locations. In this study, the condition number and information entropy are employed to measure the ill-condition of the selected mode shape matrix and evaluate the prediction performance of different sensor configurations. The particle swarm optimization algorithm, genetic algorithm, and artificial fish swarm algorithm are used to optimize the sensor position placement. Numerical simulation and experimental validation results of a 5-span high-speed railway bridge show that the reconstructed deflection shapes agree well with those of the real bridge.

Numerical simulation of shear mechanism of concrete specimens containing two coplanar flaws under biaxial loading

  • Sarfarazi, Vahab;Haeri, Hadi;Bagheri, Kourosh
    • Smart Structures and Systems
    • /
    • 제22권4호
    • /
    • pp.459-468
    • /
    • 2018
  • In this paper, the effect of non-persistent joints was determined on the behavior of concrete specimens subjected to biaxial loading through numerical modeling using particle flow code in two dimensions (PFC2D). Firstly, a numerical model was calibrated by uniaxial, Brazilian and triaxial experimental results to ensure the conformity of the simulated numerical model's response. Secondly, sixteen rectangular models with dimension of 100 mm by 100 mm were developed. Each model contains two non-persistent joints with lengths of 40 mm and 20 mm, respectively. The angularity of the larger joint changes from $30^{\circ}$ to $90^{\circ}$. In each configuration, the small joint angularity changes from $0^{\circ}$ to $90^{\circ}$ in $30^{\circ}$ increments. All of the models were under confining stress of 1 MPa. By using of the biaxial test configuration, the failure process was visually observed. Discrete element simulations demonstrated that macro shear fractures in models are because of microscopic tensile breakage of a large number of bonded discs. The failure pattern in Rock Bridge is mostly affected by joint overlapping whereas the biaxial strength is closely related to the failure pattern.

Functionally upgraded passive devices for seismic response reduction

  • Chen, Genda;Lu, Lyan-Ywan
    • Smart Structures and Systems
    • /
    • 제4권6호
    • /
    • pp.741-757
    • /
    • 2008
  • The research field of structural control has evolved from the development of passive devices since 1970s, through the intensive investigation on active systems in 1980s, to the recent studies of semi-active control systems in 1990s. Currently semi-active control is considered most promising in civil engineering applications. However, actual implementation of semi-active devices is still limited due mainly to their system maintenance and associated long-term reliability as a result of power requirement. In this paper, the concept of functionally upgraded passive devices is introduced to streamline some of the state-of-the-art researches and guide the development of new passive devices that can mimic the function of their corresponding semi-active control devices for various applications. The general characteristics of this special group of passive devices are discussed and representative examples are summarized. Their superior performances are illustrated with cyclic and shake table tests of two example devices: mass-variable tuned liquid damper and friction-pendulum bearing with a variable sliding surface curvature.

광산란 방식 실시간 미세먼지 측정 및 모니터링 시스템 개발 (Development of Detection and Monitoring by Light Scattering in Real Time)

  • 이누리;엄현욱;조현숙
    • 한국화재소방학회논문지
    • /
    • 제32권3호
    • /
    • pp.134-139
    • /
    • 2018
  • 최근 초미세먼지는 사회적 재난으로 간주될만큼 국민건강에 심각하게 영향을 미쳐 사회문제가 되고 있다. 기존의 미세먼지 측정 방식은 베타선 흡수방식을 사용하여 실시간 측정 및 소형화가 어려운 단점이 존재한다. 본 논문에서는 광산란 방식을 사용하여 소형화 및 저비용의 센싱 장치를 개발하였다. 광산란 방식을 적용한 센서는 내부에 반도체 레이저 다이오드를 사용하여 구성하였으며, 전압레벨의 신호를 주파수레벨로 변환하여 기존 방식의 한계를 극복하고 미세먼지 입자 크기별 분리가 가능하도록 구현하였다. 또한 개발 시스템은 블루투스 통신으로 스마트폰과 연결하여 미세먼를 모니터링하고, 장치를 제어할 수 있다.

Machine learning approaches for wind speed forecasting using long-term monitoring data: a comparative study

  • Ye, X.W.;Ding, Y.;Wan, H.P.
    • Smart Structures and Systems
    • /
    • 제24권6호
    • /
    • pp.733-744
    • /
    • 2019
  • Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.

A new swarm intelligent optimization algorithm: Pigeon Colony Algorithm (PCA)

  • Yi, Ting-Hua;Wen, Kai-Fang;Li, Hong-Nan
    • Smart Structures and Systems
    • /
    • 제18권3호
    • /
    • pp.425-448
    • /
    • 2016
  • In this paper, a new Pigeon Colony Algorithm (PCA) based on the features of a pigeon colony flying is proposed for solving global numerical optimization problems. The algorithm mainly consists of the take-off process, flying process and homing process, in which the take-off process is employed to homogenize the initial values and look for the direction of the optimal solution; the flying process is designed to search for the local and global optimum and improve the global worst solution; and the homing process aims to avoid having the algorithm fall into a local optimum. The impact of parameters on the PCA solution quality is investigated in detail. There are low-dimensional functions, high-dimensional functions and systems of nonlinear equations that are used to test the global optimization ability of the PCA. Finally, comparative experiments between the PCA, standard genetic algorithm and particle swarm optimization were performed. The results showed that PCA has the best global convergence, smallest cycle indexes, and strongest stability when solving high-dimensional, multi-peak and complicated problems.

SMG 유체를 이용한 전단형 댐퍼의 제어성능평가 (Control Performance Evaluation of Shear Type Damper using SMG Fluid)

  • 허광희;전승곤;서상구;김대혁
    • 한국지진공학회논문집
    • /
    • 제23권2호
    • /
    • pp.141-147
    • /
    • 2019
  • This research focuses on developing the Smart material with Grease adopted as a base oil to overcome a particle deposition caused by the MR fluid consisting of a silicon, which maximizing the characteristics and advantage of the MR fluid. By adopting the SMG fluid to a shear damper, this paper aimed to evaluate the control performance of it according to the variation of intensity of electric current(0 A, 0.5 A, 1.0 A, 1.5 A, 2.0 A, 2.5 A) and frequency(0.5 Hz, 1 Hz, 2 Hz). Subsequently, the usability of the SMG damper was analyzed by comparing the dynamic model of it to that of the other types of dampers(Power(Involution) Model, Bingham Model). As a result, DR, the performance indicator of semi-active damper, shows approximately 5 in a condition of 2 Hz. Also while confirming the excellent performance like the Power and the Bingham model, it raises the possibility to exploit it as the semi-active damper.