Results 41 to 50 of about 28,524 (229)
SSI improved algorithm based on zero phase filtering technology for structural parameter identification in civil engineering [PDF]
Archives of Civil EngineeringEarly damage detection and reinforcement of civil engineering structures are crucial. To ensure timely maintenance in the later stage, the civil structure is subjected to modal parameter identification.
Kai Yang, Zhenwu Wang
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Journal of Low Frequency Noise, Vibration and Active Control, 2022 This study proposes an algorithm for autonomous modal estimation to automatically eliminate false modes and quantify the uncertainty caused by the clustering algorithm and ambient factors. This algorithm belongs to the stochastic subspace identification (
Yongpeng Luo +3 more
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Journal of Manufacturing and Materials ProcessingModal analysis is a standard tool for evaluating the dynamic behaviour of machine tools. Since the dynamic behaviour can differ for operating and analysis conditions, the use of operational modal analysis for machine tools has been researched over the ...
Willy Reichert +4 more
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Automated Harmonic Signal Removal Technique Using Stochastic Subspace-Based Image Feature Extraction
Journal of Imaging, 2020 This paper presents automated harmonic removal as a desirable solution to effectively identify and discard the harmonic influence over the output signal by neglecting any user-defined parameter at start-up and automatically reconstruct back to become a ...
Muhammad Danial Bin Abu Hasan +3 more
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Model-Free Predictive Anti-Slug Control of a Well-Pipeline-Riser [PDF]
Modeling, Identification and Control, 2016 Simplified linearized discrete time dynamic state space models are developed for a 3-phase well-pipeline-riser and tested together with a high fidelity dynamic model built in K-Spice and LedaFlow. In addition the Meglio pipeline-riser model is used as an
Christer Dalen, David Di Ruscio
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Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization
AIChE Journal, EarlyView.Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed +4 more
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Subspace Identification Method for Combined Deterministic-Stochastic Bilinear Systems [PDF]
IFAC Proceedings Volumes, 2000 Abstract In this paper, a 'four-block' subspace system identification method for combined deterministic-stochastic bilinear systems is developed. Estimation of state sequences, followed by estimation of system matrices, is the central component of subspace identification methods.
Huixin Chen, Jan Maciejowski
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Journal of Modern Power Systems and Clean Energy, 2017 In this paper, a data-driven stochastic subspace identification (SSI-DATA) technique is proposed as an advanced stochastic system identification (SSI) to extract the inter-area oscillation modes of a power system from wide-area measurements. For accurate
Deyou YANG, Guowei CAI, Kevin CHAN
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Subspace System Identification of the Kalman Filter [PDF]
Modeling, Identification and Control, 2003 Some proofs concerning a subspace identification algorithm are presented. It is proved that the Kalman filter gain and the noise innovations process can be identified directly from known input and output data without explicitly solving the Riccati ...
David Di Ruscio
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Vehicle System Dynamics, 2020 Monitoring the condition of suspension systems is significant to ensure the safe operation of modern railway vehicles. For this purpose, an online modal identification scheme, denoted as Correlation Subset based Stochastic Subspace Identification (CoS ...
Fulong Liu +5 more
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