Results 161 to 170 of about 28,524 (229)

Fast online implementation of covariance-driven stochastic subspace identification

Mechanical Systems and Signal Processing, 2023
Siyuan Sun, Bin Yang, Qilin Zhang, Roland Wüchner, Licheng Pan, Haitao Zhu   +5 more
openaire   +2 more sources

Detection of Anomalous Behavior of a Scaled Laboratory Structure Based on Stochastic Subspace Identification Method

International Conference on Robotics and Mechatronics, 2022
Structural health monitoring (SHM) system is an essential part of large structures to allow for early detection of possible damages or defects and avoid human or economic losses.
Ali Mashhadireza, Narges Dehghani Dehnavi, A. Sadighi, M. Bitaraf   +3 more
semanticscholar   +1 more source

Stochastic subspace identification via "LQ decomposition"

42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475), 2004
A new stochastic subspace identification algorithm is developed with the help of a stochastic realization on a finite interval. First, a finite-interval realization algorithm is re-derived via "block-LDL decomposition" for a finite string of complete covariance sequence.
H. Tanaka, T. Katayama
openaire   +1 more source

Enhancing the performance of stochastic subspace identification method via energy-oriented categorization of modal components

, 2021
As an advanced modal identification method, Stochastic Subspace Identification (SSI) technique has been widely used in the engineering field in recent years.
Y. He, Zhengliang Li, Jiyang Fu, J. R. Wu, C. Ng   +4 more
semanticscholar   +1 more source

Subspace Identification of Pure Stochastic Systems

2006 IEEE International Conference on Automation, Quality and Testing, Robotics, 2006
In this paper we treat the subspace identification of pure stochastic systems with no external input. The stochastic identification problem consists of computing the stochastic system matrices from given output data only. We show how this can be done using geometric operations as orthogonal projections.
D. Sendrescu, D. Popescu, E. Bobasu, E. Petre   +3 more
openaire   +1 more source

Stochastic realization with exogenous inputs and ‘subspace-methods’ identification

Signal Processing, 1996
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
PICCI, GIORGIO, KATAYAMA T.
openaire   +2 more sources

Subspace algorithms for the stochastic identification problem

[1991] Proceedings of the 30th IEEE Conference on Decision and Control, 1993
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Van Overschee, Peter, De Moor, Bart
openaire   +1 more source

Polynomial extension of linear subspace algorithms for stochastic identification

2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601), 2004
Among the algorithms of linear models identification from input/output data, the N4SID (numerical sub-space state space system identification) plays an important role due to its simplicity and effectiveness. It is known that N4SDD gives good results for system identification in a Gaussian setting.
Di Loreto C, GERMANI, Alfredo, MANES, COSTANZO   +2 more
openaire   +4 more sources

Electromechanical mode estimation using recursive adaptive stochastic subspace identification

2014 IEEE PES T&D Conference and Exposition, 2014
Measurement based algorithms for estimating low-frequency electromechanical modes serve as useful practical methods to monitor the modal properties of power system oscillations in real-time. This paper proposes a recursive adaptive stochastic subspace identification (RASSI) algorithm for online monitoring of power system modes using wide-area ...
S. A. Nezam Sarmadi, Vaithianathan Venkatasubramanian   +1 more
openaire   +1 more source

Modal identification of arch dams using balanced stochastic subspace identification

Journal of Vibration and Control, 2016
Dynamic characteristics extracted from ambient and forced vibration tests are always associated with some level of uncertainties because of unknown nature of applied forces, existence of ambient noises as well as measurement errors. Stochastic Subspace Methods are among the most accurate and consistent methods within the domain of operational modal ...
Reza Tarinejad, Mehran Pourgholi
openaire   +1 more source