• Smart Structures and Systems
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• 제28권6호
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• pp.827-838
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• 2021

The dynamic displacement is considered to be an important indicator of structural safety, and becomes an indispensable part of Structural Health Monitoring (SHM) system for high-speed railway bridges. This paper proposes an indirect strain based dynamic displacement reconstruction methodology for high-speed railway box girders. For the typical box girders under eccentric train load, the plane section assumption and elementary beam theory is no longer applicable due to the bend-torsion coupling effects. The monitored strain was decoupled into bend and torsion induced strain, pre-trained multi-output support vector regression (M-SVR) model was employed for such decoupling process considering the sensor layout cost and reconstruction accuracy. The decoupled strained based displacement could be reconstructed respectively using box girder plate element analysis and mode superposition principle. For the transformation modal matrix has a significant impact on the reconstructed displacement accuracy, the modal order would be optimized using particle swarm algorithm (PSO), aiming to minimize the ill conditioned degree of transformation modal matrix and the displacement reconstruction error. Numerical simulation and dynamic load testing results show that the reconstructed displacement was in good agreement with the simulated or measured results, which verifies the validity and accuracy of the algorithm proposed in this paper.

• 융합신호처리학회논문지
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• 제9권1호
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• pp.82-88
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• 2008

본 논문은 주기적 진동 문제를 연구하기 위해 Runge-Kutta(RK)-Butcher 알고리듬이 소개되었다. RK-Butcher 알고리듬을 사용하여 얻어진 시뮬레이션 결과와 고전적인 4차 RK(4) 방법을 통해 얻은 결과들을 제안한 알고리듬의 성능을 확인하기 위하여 몇몇 주기적 진동 문제들의 정확한 해와 비교하였다. RK-Butcher 알고리듬의 시뮬레이션 결과는 항상 문제의 정확한 해 RK(4) 방법보다 더 근접한 결과를 줌이 확인되었다. 정확도 측면에서 RK-Butcher 알고리듬이 RK(4) 방법과 비교해볼 때 우수함을 알 수 있다. 제안한 RK-Butcher 알고리듬은 프로그램 언어로 쉽게 구현할 수 있으며 임의 시간에 종료해도 훌륭한 근사적인 해를 얻을 수 있다. RK-Butcher 알고리듬은 짧은 시간내에 이상적인 정확한 해에 근접한 결과를 주기 때문에 궤도 와 두 물체의 문제를 연구하는데 훌륭한 수치 알고리듬으로 적용 가능하다.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2118-2126
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• 2017

The large-scale power system blackouts have indicated that conventional protection relays that based on local signals cannot fit for modern power grids with complicated setting or heavily loaded-flow transfer. In order to accurately detect various faulted lines and improve the fault-tolerance of wide-area protection, a novel multi-section weighed fault matching and detecting algorithm is proposed. The real protection vector (RPV) and expected section protection vectors (ESPVs) for five fault sections are constructed respectively. The function of multi-section weighed fault matching is established to calculate the section fault matching degrees between RPV and five ESPVs. Then the fault degree of protected line based on five section fault degrees can be obtained. Two fault detecting criterions are given to support the higher accuracy rate of detecting fault. With the enumerating method, the simulation tests illustrate the correctness and fault-tolerance of proposed algorithm. It can reach the target of 100% accuracy rate under 5 bits error of wide-area protections. The influence factors of fault-tolerance are analyzed, which include the choosing of wide-area protections, as well as the topological structures of power grid and fault threshold.

• ETRI Journal
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• 제33권6호
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• pp.857-863
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• 2011

Due to uncertainties in target motion and randomness of deployed sensor nodes, the problem of imbalance of energy consumption arises from sensor scheduling. This paper presents an energy-efficient adaptive sensor scheduling for a target monitoring algorithm in a local monitoring region of wireless sensor networks. Owing to excessive scheduling of an individual node, one node with a high value generated by a decision function is preferentially selected as a tasking node to balance the local energy consumption of a dynamic clustering, and the node with the highest value is chosen as the cluster head. Others with lower ones are in reserve. In addition, an optimization problem is derived to satisfy the problem of sensor scheduling subject to the joint detection probability for tasking sensors. Particles of the target in particle filter algorithm are resampled for a higher tracking accuracy. Simulation results show this algorithm can improve the required tracking accuracy, and nodes are efficiently scheduled. Hence, there is a 41.67% savings in energy consumption.

• Smart Structures and Systems
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• 제15권1호
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• pp.227-244
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• 2015

This study develops a two stage procedure to identify the structural damage based on the optimized artificial neural networks. Initially, the modal strain energy index (MSEI) is established to extract the damaged elements and to reduce the computational time. Then the genetic algorithm (GA) and artificial neural networks (ANNs) are combined to detect the damage severity. The input of the network is modal strain energy index and the output is the flexural stiffness of the beam elements. The principal component analysis (PCA) is utilized to reduce the input variants of the neural network. By using the genetic algorithm to optimize the parameters, the ANNs can significantly improve the accuracy and convergence of the damage identification. The influence of noise on damage identification results is also studied. The simulation and experiment on beam structures shows that the adaptive parameter selection neural network can identify the damage location and severity of beam structures with high accuracy.

• Nuclear Engineering and Technology
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• 제55권3호
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• pp.827-838
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• 2023

Centrifugal pump is a key part of nuclear power plant systems, and its health status is critical to the safety and reliability of nuclear power plants. Therefore, fault diagnosis is required for centrifugal pump. Traditional fault diagnosis methods have difficulty extracting fault features from nonlinear and non-stationary signals, resulting in low diagnostic accuracy. In this paper, a new fault diagnosis method is proposed based on the improved particle swarm optimization (IPSO) algorithm-based variational modal decomposition (VMD) and relevance vector machine (RVM). Firstly, a simulation test bench for rotor faults is built, in which vibration displacement signals of the rotor are also collected by eddy current sensors. Then, the improved particle swarm algorithm is used to optimize the VMD to achieve adaptive decomposition of vibration displacement signals. Meanwhile, a screening criterion based on the minimum Kullback-Leibler (K-L) divergence value is established to extract the primary intrinsic modal function (IMF) component. Eventually, the factors are obtained from the primary IMF component to form a fault feature vector, and fault patterns are recognized using the RVM model. The results show that the extraction of the fault information and fault diagnosis classification have been improved, and the average accuracy could reach 97.87%.

• 전자공학회논문지
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• 제50권6호
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• pp.276-286
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• 2013

Singular Value Decomposition (SVD) 기반의 디콘볼루션 방식은 CT 관류 영상 해석에서 가장 널리 사용되는 기법이다. 이 방식에서는 잡음의 영향을 줄이기 위해 SVD 계수를 임계화하는 과정이 사용된다. 이 때 임계화 경계치로 고정된 값을 사용하거나 미리 정해진 진동 지수(Oscillation Index)에 따른 경계치가 사용된다. 이들 두 임계화 방식은 계산량과 정확도 측면에서 서로 장단점을 가지고 있다. 본 논문에서는 두 임계화 방식의 정확도를 비교하기 위한 몬테 칼로 모의 실험 방식을 제안한다. 또한 관류 해석시 사용하는 평활화 과정이 알고리즘의 정확도에 미치는 영향을 측정하기 위해 이 실험 방식을 확장하였다. 본 논문에서는 이와 같은 성능 비교를 위한 모의 실험 방식을 제시하고, 모의 데이터와 실제 CT 영상에 대한 실험 결과를 소개한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권3호
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• pp.1224-1242
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• 2018

Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.

• 한국광학회지
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• 제19권1호
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• pp.1-8
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• 2008

샥-하트만(Shack-Hartmann) 파면 측정 센서는 여러 분야에서 다양하게 사용되고 있다. 특히 적응광학은 주요 응용분야 중 하나이다. 적응광학 시스템은 실시간으로 빠르게 동작되어야 하므로 고속 파면 측정이 필수적이다. 고속 파면 측정에서는 카메라의 노출시간이 매우 작기 때문에 파면 측정시에 광자 잡음(photon noise)와 판독 잡음(readout noise)등의 잡음의 영향을 크게 받는다. 따라서 잡음에 둔감한 고속 중심점 탐색 알고리즘이 요구된다. 본 논문에서는 잡음에 둔감한 고속 중심점 탐색 알고리즘으로 다중 해상도 상관관계법이 제안되었다. 이 방법은 고속 푸리에 변환(fast Fourier transform)을 이용한 상관관계법과 비교하여 다중 해상도 이미지를 이용함으로써 계산시간을 향상시켰다. 본 논문에서는 무게중심법(center of mass method)과 상관관계법(correlation method)과 다중해상도 상관관계법(multi-resolution correlation method)의 계산시간과 측정 정확도를 비교하기 위해 전산모사 방법이 사용되었다. 제안된 방법의 정확도는 기존의 상관관계법과 유사한 것을 확인하였다.

• 제어로봇시스템학회논문지
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• 제9권6호
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• pp.435-441
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• 2003

This paper addresses that an approximation and tracking control of realtime recurrent neural networks(RTRN) using two-dimensional iterative teaming algorithm for an electro-hydraulic servo system. Two dimensional learning rule is driven in the discrete system which consists of nonlinear output fuction and linear input. In order to control the trajectory of position, two RTRN with the same network architecture were used. Simulation results show that two RTRN using 2-D learning algorithm are able to approximate the plant output and desired trajectory to a very high degree of a accuracy respectively and the control algorithm using two identical RTRN was very effective to trajectory tracking of the electro-hydraulic servo system.