Stochastic subspace identification for output-only modal analysis: accuracy and sensitivity on modal parameter estimation

2011 ◽  
Author(s):  
Yi-Cheng Liu ◽  
Chin-Hsiung Loh
Keyword(s):  
Parameter Estimation ◽  
Modal Analysis ◽  
Subspace Identification ◽  
Modal Parameter ◽  
Stochastic Subspace Identification ◽  
Output Only ◽  
Modal Parameter Estimation

Modal Parameter Estimation for Underdamped Linear Dynamic Systems

2013 ◽  
Vol 486 ◽  
pp. 233-238
Author(s):  
Fillemon Nduvu Nangolo
Keyword(s):  
Parameter Estimation ◽  
Modal Analysis ◽  
Damping Ratio ◽  
Analytical Data ◽  
Modal Parameter ◽  
Classical Dynamic ◽  
Linear Dynamic Systems ◽  
Analysis Techniques ◽  
Vibration Parameters ◽  
Modal Parameter Estimation

Modal parameter estimation is the estimation of frequency, damping ratio, and modal coefficients from experimental data. Modal analysis techniques are a common method used to determine these properties. The Least-Squares Complex Exponential (LSCE) and the Eigensystem Realization Algorithm (ERA) are one of the popular methods of modal analysis techniques. This paper presents an experimental verification of the LSCE and ERA methods. The investigation focuses on the estimation of natural frequencies, damping ratio and modal coefficients. To investigate this, artificial analytical data were processed in MATLAB environment to estimate the modal parameters. The identified vibration parameters from the LSCE and ERA were compared with the values based on classical dynamic theory, and the natural frequency and damping ratios percent of error were calculated.

scholarly journals Experimental modal analysis in research

2017 ◽  
Vol 16 (3) ◽  
pp. 005-012 ◽  
Author(s):  
Mariusz Żółtowski ◽  
Krzysztof Napieraj
Keyword(s):  
Parameter Estimation ◽  
Modal Analysis ◽  
Civil Engineering ◽  
Experimental Modal Analysis ◽  
Impact Testing ◽  
Engineering Industry ◽  
Vibration Modes ◽  
Modal Parameter ◽  
Excitation Techniques ◽  
Modal Parameter Estimation

Experimental modal analysis has grown steadily in popularity since the advent of the digital FFT spectrum analyser in the 1970’s. This days impact testing has become widespread as a fast and economical means of finding the vibration modes of a machine or structure. Its significantly use ascending roles can be seen also in the civil engineering industry [6]. This paper reviews the main topics associated with experimental modal analysis including making FRF measurements, modal excitation techniques, and modal parameter estimation from a set of FRFs.

scholarly journals Modal Parameter Identification of Structures Using Reconstructed Displacements and Stochastic Subspace Identification

2021 ◽  
Vol 11 (23) ◽  
pp. 11432
Author(s):  
Xiangying Guo ◽  
Changkun Li ◽  
Zhong Luo ◽  
Dongxing Cao
Keyword(s):  
Parameter Identification ◽  
Modal Analysis ◽  
Moving Average ◽  
Random Fluctuation ◽  
High Frequency Component ◽  
Modal Parameters ◽  
Subspace Identification ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Stochastic Subspace Identification

A method of modal parameter identification of structures using reconstructed displacements was proposed in the present research. The proposed method was developed based on the stochastic subspace identification (SSI) approach and used reconstructed displacements of measured accelerations as inputs. These reconstructed displacements suppressed the high-frequency component of measured acceleration data. Therefore, in comparison to the acceleration-based modal analysis, the operational modal analysis obtained more reliable and stable identification parameters from displacements regardless of the model order. However, due to the difficulty of displacement measurement, different types of noise interferences occurred when an acceleration sensor was used, causing a trend term drift error in the integral displacement. A moving average low-frequency attenuation frequency-domain integral was used to reconstruct displacements, and the moving time window was used in combination with the SSI method to identify the structural modal parameters. First, measured accelerations were used to estimate displacements. Due to the interference of noise and the influence of initial conditions, the integral displacement inevitably had a drift term. The moving average method was then used in combination with a filter to effectively eliminate the random fluctuation interference in measurement data and reduce the influence of random errors. Real displacement results of a structure were obtained through multiple smoothing, filtering, and integration. Finally, using reconstructed displacements as inputs, the improved SSI method was employed to identify the modal parameters of the structure.

Sign in / Sign up

Export Citation Format

Share Document