scholarly journals Compressive power spectrum sensing for vibration-based output-only system identification of structural systems in the presence of noise

2015 ◽  
Author(s):  
Bamrung Tau Siesakul ◽  
Kyriaki Gkoktsi ◽  
Agathoklis Giaralis
Keyword(s):  
System Identification ◽  
Power Spectrum ◽  
Spectrum Sensing ◽  
Structural Systems ◽  
Output Only

Nonlinear subspace system identification based on output-only measurements

2020 ◽  
Vol 357 (17) ◽  
pp. 12904-12937 ◽  
Author(s):  
Amirali Sadeqi ◽  
Shapour Moradi ◽  
Kourosh Heidari Shirazi
Keyword(s):  
System Identification ◽  
Output Only ◽  
Subspace System Identification

Stochastic System Identification for Operational Modal Analysis: A Review

2001 ◽  
Vol 123 (4) ◽  
pp. 659-667 ◽  
Author(s):  
Bart Peeters ◽  
Guido De Roeck
Keyword(s):  
System Identification ◽  
Stochastic System ◽  
Instrumental Variable ◽  
Subspace Identification ◽  
Response Functions ◽  
Impulse Responses ◽  
Identification Methods ◽  
Operational Conditions ◽  
Stochastic Subspace Identification ◽  
Output Only

This paper reviews stochastic system identification methods that have been used to estimate the modal parameters of vibrating structures in operational conditions. It is found that many classical input-output methods have an output-only counterpart. For instance, the Complex Mode Indication Function (CMIF) can be applied both to Frequency Response Functions and output power and cross spectra. The Polyreference Time Domain (PTD) method applied to impulse responses is similar to the Instrumental Variable (IV) method applied to output covariances. The Eigensystem Realization Algorithm (ERA) is equivalent to stochastic subspace identification.

scholarly journals ESTIMATION OF STRUCTURAL DYNAMICS OF A MODEL BOOM OF DRAGLINE DRE-23 BY OUTPUT-ONLY SYSTEM IDENTIFICATION METHODS

2011 ◽  
Author(s):  
Zakir Faruquee ◽  
Hal Gurgenci
Keyword(s):  
System Identification ◽  
Modal Analysis ◽  
Damping Ratio ◽  
Canonical Variate ◽  
Identification Methods ◽  
Analysis Methods ◽  
Electrodynamic Shaker ◽  
Simulated Field ◽  
Output Only ◽  
Frequency Domain Decomposition

Two output -only system identification methods namely Canonical Variate Analysis (CVA) and Frequency Domain Decomposition (FDD) were used to estimate the dynamics (Mode shape, natural frequency and damping ratio) of the model boom of the dragline DRE 23. The boom was excited separately with an impulse hammer and with an electrodynamic shaker with chirp, random and simulated field excitations. In all cases, the excitations as well as the responses of the model boom were measured. The dynamics were obtained from the response measurements using Output-Only methods as well as from both the excitations and responses using conventional modal analysis methods. In all cases, the estimations of the dynamics by Output-Only methods were comparable if not better than those estimates obtained by the convention modal analysis methods.

Quadrotor aircraft intelligent system identification experiment design

2019 ◽  
Vol 233 (13) ◽  
pp. 4911-4925
Author(s):  
Mohammed Alabsi ◽  
Travis Fields
Keyword(s):  
System Identification ◽  
Power Spectrum ◽  
Intelligent System ◽  
Model Development ◽  
Experiment Design ◽  
Input Power ◽  
Unmanned Aircraft ◽  
Input Design ◽  
Spectrum Optimization ◽  
Aircraft System

Aircraft prototyping and modeling is usually associated with resource expensive techniques and significant post flight analysis. The NASA Learn-To-Fly concept targets the replacement of the conventional ground-based aircraft model development and prototyping approaches with an efficient real time paradigm. The work presented herein describes the development of an intelligent excitation input design technique that determines excitation frequencies based on predefined rotational motion dynamic model. The input design is then evaluated on quadcopter unmanned aircraft that utilizes the new multisine input design. In order to minimize flight excursions without compromising the modeling capabilities, multisine input power spectrum is optimized based on the vehicle’s frequency response. The proposed methodology emphasizes excitation of modal frequencies which yields flight data rich information content. The generated optimized multisine input design is utilized for a quadcopter aircraft system identification and the performance is compared to conventional uniform amplitudes design. Simulation results show highly accurate model estimation in all identification results in addition to reduction of induced perturbations and power consumption. Additionally, the generated model prediction capabilities are not compromised after power spectrum optimization. Overall, the proposed technique introduces an efficient and intelligent system identification experiment design that can minimize the time and effort spent during excitation input design.

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