• 제목, 요약, 키워드: recursive subspace algorithm

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A novel recursive stochastic subspace identification algorithm with its application in long-term structural health monitoring of office buildings

  • Wu, Wen-Hwa;Jhou, Jhe-Wei;Chen, Chien-Chou;Lai, Gwolong
    • Smart Structures and Systems
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    • v.24 no.4
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    • pp.459-474
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    • 2019
  • This study develops a novel recursive algorithm to significantly enhance the computation efficiency of a recently proposed stochastic subspace identification (SSI) methodology based on an alternative stabilization diagram. Exemplified by the measurements taken from the two investigated office buildings, it is first demonstrated that merely one sixth of computation time and one fifth of computer memory are required with the new recursive algorithm. Such a progress would enable the realization of on-line and almost real-time monitoring for these two steel framed structures. This recursive SSI algorithm is further applied to analyze 20 months of monitoring data and comprehensively assess the environmental effects. It is certified that the root-mean-square (RMS) response can be utilized as an excellent index to represent most of the environmental effects and its variation strongly correlates with that of the modal frequency. More detailed examination by comparing the monthly correlation coefficient discloses that larger variations in modal frequency induced by greater RMS responses would typically lead to a higher correlation.

Recursive State Space Model Identification Algorithms Using Subspace Extraction via Schur Complement

  • Takei, Yoshinori;Imai, Jun;Wada, Kiyoshi
    • 제어로봇시스템학회:학술대회논문집
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    • pp.525-525
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    • 2000
  • In this paper, we present recursive algorithms for state space model identification using subspace extraction via Schur complement. It is shown that an estimate of the extended observability matrix can be obtained by subspace extraction via Schur complement. A relationship between the least squares residual and the Schur complement matrix obtained from input-output data is shown, and the recursive algorithms for the subspace-based state-space model identification (4SID) methods are developed. We also proposed the above algorithm for an instrumental variable (IV) based 4SID method. Finally, a numerical example of the application of the algorithms is illustrated.

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신호부공간 추정 성능 향상을 위한 전후방 상관과 제곱근행렬 갱신을 이용한 COPAST(correlation-based projection approximation for subspace-tracking) 알고리즘 연구 (A Square-Root Forward Backward Correlation-based Projection Approximation for Subspace Tracking)

  • 임준석;편용국
    • 전자공학회논문지 IE
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    • v.48 no.1
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    • pp.7-15
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    • 2011
  • 본 논문에서는 상관계수를 바탕으로 신호부공간을 추정하는 COPAST(correlation-based projection approximation subspace tracking)의 성능을 향상시키기 위하여 상관계수를 구하는 부분을 순방향 신호 벡터로부터 상관계수를 구하고 동시에 역방향 신호 벡터에서도 상관계수를 구하여 신호 부공간을 추정하는 방법을 제안한다. 또 매번 갱신되는 상관행렬의 안정성을 도모하고자 제곱근 행렬 갱신을 하도록 하였다. 컴퓨터 모의 실험을 통해서 제안된 방법이 기존의 COPAST에 비해서 약 5dB의 신호 부공간 추정 정확도에 향상이 있었음을 확인하였다.

Time-varying modal parameters identification of large flexible spacecraft using a recursive algorithm

  • Ni, Zhiyu;Wu, Zhigang;Wu, Shunan
    • International Journal of Aeronautical and Space Sciences
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    • v.17 no.2
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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.

Application of recursive SSA as data pre-processing filter for stochastic subspace identification

  • Loh, Chin-Hsiung;Liu, Yi-Cheng
    • Smart Structures and Systems
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    • v.11 no.1
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    • pp.19-34
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    • 2013
  • The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified $1^{st}$ mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of $2^{nd}$ mode slope ratio could be used as another feature to indicate imminent pier settlement.

Structural Topology Optimization for the Natural Frequency of a Designated Mode

  • Lim, O-Kaung;Lee, Jin-Sik
    • Journal of Mechanical Science and Technology
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    • v.14 no.3
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    • pp.306-313
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    • 2000
  • The homogenization method and the density function method are common approaches to evaluate the equivalent material properties for design cells composed of matter and void. In this research, using a new topology optimization method based on the homogenized material with a penalty factor and the chessboard prevention strategy, we obtain the optimal layout of a structure for the natural frequency of a designated mode. The volume fraction of nodes of each finite element is chosen as the design variable and a total material usage constraint is imposed. In this paper, the subspace method is used to evaluate the eigenvalue and its corresponding eigenvector of the structure for the designated mode and the recursive quadratic programming algorithm, PLBA algorithm, is used to solve the topology optimization problem.

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평균 제곱 투영 오차의 기울기에 기반한 가변 망각 인자 FAPI 알고리즘 (Mean Square Projection Error Gradient-based Variable Forgetting Factor FAPI Algorithm)

  • 서영광;신종우;서원기;김형남
    • 전자공학회논문지
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    • v.51 no.5
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    • pp.177-187
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    • 2014
  • 본 논문에서는 고속 부공간 추적 기법인 FAPI (Fast Approsimated Power Iteration)에 GVFF RLS (Gradient-based Variable Forgetting Factor Recursive Least Square Error)를 적용한 GVFF FAPI 를 제안한다. 기존의 FAPI는 신호의 공분산 행렬을 추정하기 위해 고정 망각 인자를 사용하기에, 부공간이 지속적으로 변하는 비정재 환경에 적용하기 여려운 단점이 있다. 이러한 문제점을 해결하기 위해, GVFF FAPI는 개선된 MSE (Mean Square Error)의 분석으로부터 유도된 MSE의 기울기 기반의 시변 망각 인자를 사용한다. 또한 GVFF RLS의 망각 인자 업데이트 식을 개선하여 부공간이 지속적으로 변하는 비정재 환경에서 부공간 에러를 줄인다. 개선된 망각 인자 업데이트 식은 MSE의 기울기가 양수이면 망각 인자를 빠르게 감소하게 하고 MSE의 기울기가 음수이면 망각 인자를 천천히 증가시킨다. 모의실험을 통해서 도래각이 지속적으로 변하는 환경에서 GVFF FAPI 알고리즘이 기존의 FAPI 알고리즘보다 작은 부공간 에러를 가지는 것을 보이고, 추적된 부공간을 도래각 추정기법에 적용하였을 때 추적된 도래각의 RMSE (Root Mean Square Error)가 더 작은 것을 확인한다.

Moving Object Detection Using Sparse Approximation and Sparse Coding Migration

  • Li, Shufang;Hu, Zhengping;Zhao, Mengyao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.5
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    • pp.2141-2155
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    • 2020
  • In order to meet the requirements of background change, illumination variation, moving shadow interference and high accuracy in object detection of moving camera, and strive for real-time and high efficiency, this paper presents an object detection algorithm based on sparse approximation recursion and sparse coding migration in subspace. First, low-rank sparse decomposition is used to reduce the dimension of the data. Combining with dictionary sparse representation, the computational model is established by the recursive formula of sparse approximation with the video sequences taken as subspace sets. And the moving object is calculated by the background difference method, which effectively reduces the computational complexity and running time. According to the idea of sparse coding migration, the above operations are carried out in the down-sampling space to further reduce the requirements of computational complexity and memory storage, and this will be adapt to multi-scale target objects and overcome the impact of large anomaly areas. Finally, experiments are carried out on VDAO datasets containing 59 sets of videos. The experimental results show that the algorithm can detect moving object effectively in the moving camera with uniform speed, not only in terms of low computational complexity but also in terms of low storage requirements, so that our proposed algorithm is suitable for detection systems with high real-time requirements.