• Smart Structures and Systems
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• 제26권4호
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• pp.419-433
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• 2020

Investigation of structural integrity has been a critical issue in the field of civil engineering for years. Visual inspection is one of the most available methods to explore deteriorative components in structures. Still, this method is not applicable to invisible damage of structures. Alternatively, system identification methods are capable of tracking modal properties of structures over time. The deviation of these dynamic properties can serve as indicators to access structural integrity. In this study, a modal tracking technique using frequency-domain system identification from seismic responses of structures is proposed. The method first segments the measured signals into overlapped sequential portions and then establishes multiple Hankel matrices. Each Hankel matrix is then converted to the frequency domain, and a temporal-average frequency-domain Hankel matrix can be calculated. This study also proposes the frequency band selection that can divide the frequency-domain Hankel matrix into several portions in accordance with referenced natural frequencies. Once these referenced natural frequencies are unavailable, the first few right singular vectors by the singular value decomposition can offer these references. Finally, the frequency-domain stochastic subspace identification tracks the natural frequencies and mode shapes of structures through quick stabilization diagrams. To evaluate performance of the proposed method, a numerical study is carried out. Moreover, the long-term monitoring strong motion records at a specific site are exploited to assess the tracking performance. As seen in results, the proposed method is capable of tracking modal properties through seismic responses of structures.

• International Journal of Aeronautical and Space Sciences
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• 제17권2호
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• pp.184-194
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• 2016

In existing identification methods for on-orbit spacecraft, such as eigensystem realization algorithm (ERA) and subspace method identification (SMI), singular value decomposition (SVD) is used frequently to estimate the modal parameters. However, these identification methods are often used to process the linear time-invariant system, and there is a lower computation efficiency using the SVD when the system order of spacecraft is high. In this study, to improve the computational efficiency in identifying time-varying modal parameters of large spacecraft, a faster recursive algorithm called fast approximated power iteration (FAPI) is employed. This approach avoids the SVD and can be provided as an alternative spacecraft identification method, and the latest modal parameters obtained can be applied for updating the controller parameters timely (e.g. the self-adaptive control problem). In numerical simulations, two large flexible spacecraft models, the Engineering Test Satellite-VIII (ETS-VIII) and Soil Moisture Active/Passive (SMAP) satellite, are established. The identification results show that this recursive algorithm can obtain the time-varying modal parameters, and the computation time is reduced significantly.

• Structural Engineering and Mechanics
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• 제52권5호
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• pp.903-918
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• 2014

Large space structures may have resonant low eigenvalues and often these appear with closely-spaced natural frequencies. Owing to the coupling among modes with closely-spaced natural frequencies, each eigenvector corresponding to closely-spaced eigenvalues is ill-conditioned that may cause structural instability. The subspace to an invariant subspace corresponding to closely-spaced eigenvalues is well-conditioned, so a method is presented to design the feedback control law of intelligent structures with closely-spaced eigenvalues in this paper. The main steps are as follows: firstly, the system with closely-spaced eigenvalues is transformed into that with repeated eigenvalues by the spectral decomposition method; secondly, the computation for the linear combination of eigenvectors corresponding to repeated eigenvalues is obtained; thirdly, the feedback control law is designed on the basis of the system with repeated eigenvalues; fourthly, the system with closely-spaced eigenvalues is regarded as perturbed system on the basis of the system with repeated eigenvalues; finally, the feedback control law is applied to the original system, the first order perturbations of eigenvalues are discussed when the parameter modifications of the system are introduced. Numerical examples are given to demonstrate the application of the present method.

• 정보보호학회논문지
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• 제17권3호
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• pp.27-33
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• 2007

최근 M.Yoshida 등에 의해 2차원 벡터 공간상의 벡터 분해 문제 (vector decomposition problem 또는 VDP) 가 제안되었고, 그것은 어떤 특별한 조건하에서는 최소한 1차원 부분공간상의 계산적 Diffie-Hellman 문제 (CDHP) 보다 어렵다는 것이 증명되었다. 하지만 그들의 증명이, VDP를 암호학적 프로토콜 설계에 적용하려면 필요한 조건인 벡터 공간상의 주어진 기저에 관한 임의의 벡터의 벡터 분해 문제가 어렵다는 것을 보이는 것은 아니다. 본 논문에서는 비록 어떤 2차원 벡터 공간이 M.Yoshida 등이 제안한 특별한 조건을 만족한다 할지라도, 특정한 모양의 기저에 관해서는 벡터 분해 문제가 다항식 시간 안에 해결될 수 있다는 것을 보여준다. 또한 우리는 다른 구조를 갖는 어떠한 기저들에 대해서는 그 2차원 벡터 공간 상의 임의의 벡터에 대한 벡터 분해 문제가 적어도 CBHP 만큼 어렵다는 것을 증명한다. 그러므로 벡터 분해 문제를 기반이 되는 어려운 문제로 하는 암호학적인 프로토콜을 수행할 때는 기저를 주의하여 선택하여야 한다.

• 대한전자공학회논문지SP
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• 제43권2호
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• pp.82-86
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• 2006

패턴인식 시스템은 일반적으로 데이터의 전처리, 특징 추출, 학습단계의 과정을 거쳐서 개발되어 진다. 그중에서도 특징 추출 과정은 다차원 공간을 가진 입력 데이터의 복잡도를 줄여서 다음 단계인 학습단계에서 계산 복잡도와 인식률을 향상시키는 역할을 한다. 패턴인식에서 특징 추출 기법으로써 principal component analysis, factor analysis, linear discriminant analysis 같은 방법들이 널리 사용되어져 왔다. 이 논문에서는 singular value decomposition (SVD) 방법이 패턴인식 시스템의 특징 추출과정에 유용하게 사용될 수 있음을 보인다. 특징 추출단계에서 SVD 기법의 유용성을 검증하기 위하여 원격탐사 응용에 적용하였는데, 실험결과는 널리 쓰이는 PCA에 비해 약 25%의 인식률의 향상을 가져온다는 것을 알 수 있다.

• Journal of applied mathematics & informatics
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• 제41권4호
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• pp.861-868
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• 2023

Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x_(a,b)→ax²+bx² = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X_(a,b) ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.

• 전자공학회논문지B
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• 제33B권4호
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• pp.164-173
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• 1996

This paper presents an alternative technique for DOA (direction-of-arrival) estimation. For generating a weight vector orthogonal to the signal subspace, a modified version of MES (minimum eigenvalue searching ) method is introduced. The performance of the proposed technique is compared to that of the conventional ED (eigen decomposition) method in terms of angle resolution for a number of snapshots during agiven observation period as well as various SNR's. In addition, the superiority of the suggested technique is shown, by analyzing the required computational load of the proposed MES and conventional ED method. A novel procedure of simplifying the MES proposed in [1] is presented on that purpose. Another advnatage of the proposed technique is that it is performed independently of the detection of the number of signal components, which makes it possible to estimate the DOA's of clusters consisting of infinite number of inseparable signal components.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제13권4호
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• pp.267-280
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• 2009

In this paper we investigate a simple two-level additive Schwarz preconditioner for the P1 symmetric interior penalty Galerkin method of the Poisson equation on rectangular meshes. The construction is based on the decomposition of the global space of piecewise linear polynomials into the sum of local subspaces, each of which corresponds to an element of the underlying mesh, and the global coarse subspace consisting of piecewise constants. This preconditioner is a direct combination of the block Jacobi iteration and the cell-centered finite difference method, and thus very easy to implement. Explicit upper and lower bounds for the maximum and minimum eigenvalues of the preconditioned matrix system are derived and confirmed by some numerical experiments.

• Smart Structures and Systems
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• 제10권4_5호
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• pp.459-470
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• 2012

This paper summarizes a study for the modal analysis and model updating conducted using the monitoring data obtained from the Canton Tower of 610 m tall, which was established as an international benchmark problem by the Hong Kong Polytechnic University. Modal properties of the tower were successfully identified using frequency domain decomposition and stochastic subspace identification methods. Finite element model updating using the measurement data was further performed to reduce the modal property differences between the measurements and those of the finite element model. Over-fitting during the model updating was avoided by using an optimization scheme with a regularization term.

• Smart Structures and Systems
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• 제10권4_5호
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• pp.393-410
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• 2012

The 610 m high Canton Tower (formerly named Guangzhou New Television Tower) is currently considered as a benchmark problem for structural health monitoring (SHM) of high-rise slender structures. In the benchmark study task I, a set of 24-hour ambient vibration measurement data has been available for the output-only system identification study. In this paper, the vector autoregressive models (ARV) method is adopted in the operational modal analysis (OMA) for this TV tower. The identified natural frequencies, damping ratios and mode shapes are presented and compared with the available results from some other research groups which used different methods, e.g., the data-driven stochastic subspace identification (SSI-DATA) method, the enhanced frequency domain decomposition (EFDD) algorithm, and an improved modal identification method based on NExT-ERA technique. Furthermore, the environmental effects on the estimated modal parameters are also discussed.