scholarly journals Output-Only Modal Estimation Using Eigensystem Realization Algorithm with Nonstationary Data Correlation

2021 ◽  
Vol 11 (7) ◽  
pp. 3088
Author(s):  
Chang-Sheng Lin ◽  
Ming-Hsien Lin
Keyword(s):  
Nonstationary Process ◽  
Modal Identification ◽  
Structural System ◽  
Modal Parameter ◽  
Data Correlation ◽  
Eigensystem Realization Algorithm ◽  
Product Model ◽  
Modal Assurance Criterion ◽  
Stabilization Diagram ◽  
Output Only

The conventional eigensystem realization algorithm with data correlation (ERA/DC) combines the impulse response or free response data of a structural system with the concept of correlation function to identify the modal parameter of the structural system. Previous studies have shown that the modal parameters of structural systems subjected to stationary white noise excitation can be estimated by ERA/DC from the ambient response without excitation data. This concept is extended in this paper for output-only modal identification for the structural system with complex modes under ambient excitation as a nonstationary process in the form of a product model. Numerical simulations and experimental verification are used to validate the effectiveness of the proposed method for response-only modal estimation, and the stabilization diagram is used with modal assurance criterion (MAC) to distinguish structural modes from fictitious modes.

scholarly journals A new automated procedure of modal identification in operational conditions

2018 ◽  
Vol 211 ◽  
pp. 21003 ◽  
Author(s):  
Gabriele Marrongelli ◽  
Carmelo Gentile
Keyword(s):  
Parametric Identification ◽  
Modal Identification ◽  
Mode Shapes ◽  
Parameter Estimates ◽  
Reference List ◽  
Modal Parameter ◽  
Operational Conditions ◽  
Historic Masonry ◽  
Stabilization Diagram ◽  
Using Data

Structural Health Monitoring (SHM) strategies are aimed at the assessment of structural performance, using data acquired by sensing systems. Among the different available approaches, vibration-based methods - involving the automation of the modal parameter estimation (MPE) and modal tracking (MT) procedures - are receiving increasing attention. In the context of vibration-based monitoring, this paper presents an automated procedure of modal identification in operational conditions. The presented algorithms can be used to effectively manage the results obtained by any parametric identification method that involves the construction and the interpretation of stabilization diagrams. The implemented approach introduces improvements related to both the MPE and the MT tasks. The MPE procedure consists of three key steps aimed at: (1) filtering a high number of spurious poles in the stabilization diagram; (2) clustering the remaining poles that share same characteristics in term of modal parameters; (3) improving the accuracy of the modal parameter estimates. In the MT procedure the use of a simple statistical approach to define adaptive thresholds together with continuously updated dynamic reference list guarantee an efficient tracking of the most representative structural modes. The advantages obtained through the proposed procedures are exemplified using data continuously collected on the historic masonry tower of San Gottardo in Corte, located in the centre of Milan, Italy. In addition, the ability of the automated algorithms to identify contributions inherent to different vibration modes, even if they are characterized by closely-spaced frequencies and a low discriminant between mode shapes, will be described in details.

scholarly journals OUTPUT-ONLY MODAL IDENTIFICATION OF TENSEGRITY STRUCTURES

2016 ◽  
Vol 8 (2) ◽  
pp. 52-64 ◽  
Author(s):  
Miniar Attig ◽  
Maher Abdelghani ◽  
Nabil ben Kahla
Keyword(s):  
Natural Frequencies ◽  
Modal Identification ◽  
Mode Shapes ◽  
Subspace Identification ◽  
Balanced Realization ◽  
Stochastic Subspace Identification ◽  
Tensegrity Systems ◽  
Stabilization Diagram ◽  
Subspace Algorithms ◽  
Output Only

Tensegrity systems are a special class of spatial reticulated structures that are composed of struts in compression and cables in tension. In this paper, the performance of stochastic subspace algorithms for modal identification of complex tensegrity systems is investigated. A sub-class algorithm of the Stochastic Subspace Identification family: the Balanced Realization Algorithm is investigated for modal identification of a tripod simplex structure and a Geiger dome. The presented algorithm is combined with a stabilization diagram with combined criteria (frequency, damping and mode shapes). It is shown that although the studied structures present closely spaced modes, the Balanced Realization Algorithm performs well and guarantees separation between closely-spaced natural frequencies. Modal identification results are validated through comparisons of the correlations (empirical vs. model based) showing effectiveness of the proposed methodology.

scholarly journals Cluster Analysis for Automated Operational Modal Analysis: A Review

2019 ◽  
Vol 255 ◽  
pp. 02012 ◽  
Author(s):  
M. Danial A. Hasan ◽  
Z. A. B. Ahmad ◽  
M. Salman Leong ◽  
L. M. Hee ◽  
M. Haffizzi Md. Idris
Keyword(s):  
Cluster Analysis ◽  
Modal Analysis ◽  
Clustering Algorithm ◽  
Operational Modal Analysis ◽  
Modal Identification ◽  
Modal Parameter ◽  
Essential Information ◽  
Clustering Techniques ◽  
Stabilization Diagram ◽  
Recent Developments

Recent developments in the field of modal-based damage detection and vibration-based monitoring have led to a renewed interest in automated procedures for the operational modal analysis (OMA). The development of automated operational modal analysis (OMA) procedures marked a fundamental step towards the elimination of any user intervention since traditional modal identification requires a lot of interaction by an expert user. A key for effective automation of OMA is depended on well- defined modal indicators for a clear indication about which modes are to be selected as the physical modes. In all modal analysis, the construction of stabilization diagrams is necessary in order to illustrate, and decide, if a mode is physical or not for predefined range of the model order. On the other hand, the use of stabilization diagram tools involves a large amount of user interaction, costly, time-consuming process and certainly unsuited for online applications. Therefore, the development of automatic procedures for the analysis of stabilization diagrams by resembling decision-making process of a human has been carried out in recent years. For the sake of clearness, the automation of the interpretation of stabilization diagrams can generally be divided into two steps in order to speed up the process: a) elimination of noise modes and b) clustering of physical modes in order to obtain the most representative values of the estimated parameters of each clustered mode. In recent years, several alternative procedures have been proposed for clustering techniques. Therefore, this review aims to provide relevant essential information on the recent developments of cluster analysis in automated OMA. A literature review of existing clustering algorithm has been carried out to find best practice criteria for automated modal parameter identification which involving the general concepts of these techniques as well as the pro and cons of applying these clustering techniques are also discussed and summarised.

scholarly journals Perspectives of Second-Order Blind Identification for Operational Modal Analysis of Civil Structures

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
C. Rainieri
Keyword(s):  
Modal Analysis ◽  
Second Order ◽  
Modal Identification ◽  
Computational Time ◽  
Parameter Estimates ◽  
Blind Identification ◽  
Modal Parameter ◽  
Civil Structures ◽  
Key Issues ◽  
Output Only

Innovative methods for output-only estimation of the modal properties of civil structures are based on blind source separation techniques. In the present paper attention is focused on the second-order blind identification (SOBI) algorithm and the influence of its analysis parameters on computational time and accuracy of modal parameter estimates. These represent key issues in view of the automation of the algorithm and its integration within vibration-based monitoring systems. The herein reported analyses and results provide useful hints for reduction of computational time and control of accuracy of estimates. The latter topic is of interest in the case of single modal identification tests, too. A criterion for extraction of accurate modal parameter estimates is identified and applied to selected experimental case studies. They are representative of the different levels of complexity that can be encountered during real modal tests. The obtained results point out that SOBI can provide accurate estimates and it can also be automated, confirming that it represents a profitable alternative for output-only modal analysis and vibration-based monitoring of civil structures.

Comparative Study of Output-Based Modal Identification Methods Using Measured Signals From an Offshore Platform

2010 ◽  
Author(s):  
S. Q. Wang ◽  
Y. T. Zhang ◽  
Y. X. Feng
Keyword(s):  
Damage Identification ◽  
Moving Average ◽  
Laboratory Data ◽  
Field Measurements ◽  
Comparative Investigation ◽  
Offshore Platform ◽  
Modal Identification ◽  
Modal Parameter ◽  
Identification Methods ◽  
Output Only

Research on vibration based damage identification using changes of modal parameters has been expanding rapidly over the last decades. And modal parameter identification methods are essentially important since these parameters directly affect the damage detection results. Many modal identification methods have been proposed and further verified based on numerical and laboratory data. However, few papers are reported on comparative investigation of several output-only modal identification methods, especially based on measured signals from offshore platform in service. The main objective of the present paper is to investigate the effectiveness and applicability of several output-only modal identification methods, including Ibrahim Time Domain(ITD), Eigensystem Realization Algorithm(ERA), Auto-Regressive Moving Average method(ARMA) and Stochastic Subspace Identification(SSI) methods. First the four modal identification methods are briefly reviewed. Field measurements are conducted and vibration signals are recorded for modal identification. The effectiveness is compared for the four identification methods. Useful results could be obtained.

A comparative study on in-flight modal identification of an aircraft using time- and frequency-domain techniques

2020 ◽  
Vol 26 (21-22) ◽  
pp. 1920-1934
Author(s):  
Cagri Kocan
Keyword(s):  
Frequency Domain ◽  
Flight Test ◽  
Modal Identification ◽  
Modal Parameters ◽  
Modal Parameter ◽  
Operational Conditions ◽  
Stochastic Subspace Identification ◽  
Vibration Data ◽  
Output Only ◽  
Frequency Domain Decomposition

In this study, in-flight modal identification analyses are made based on vibration data collected during a flight test of an aircraft, by using two different output-only identification techniques: frequency domain decomposition and data-driven stochastic subspace identification. The purpose of this study was to evaluate and compare the efficacy of the two methods in modal parameter estimation and to validate their capability in dealing with some challenging tasks such as time tracking of modal parameters and estimating modal damping ratios. In addition, the effects of different environmental conditions and maneuvers are investigated by separating the flight-test data, such as static engine start, taxi, takeoff, cruise, roll, climb, descend, and yaw maneuvers. It is demonstrated that the selection of operational conditions and maneuvers plays a crucial role in identifying the modal parameters of the aircraft.

A Study on Structural System Identification and Damage Detection for Free Vibration Response Using the Wavelet Transform

2015 ◽  
Vol 752-753 ◽  
pp. 1029-1034
Author(s):  
Asnizah Sahekhaini ◽  
Pauziah Muhamad ◽  
Masayuki Kohiyama ◽  
Aminuddin Abu ◽  
Lee Kee Quen ◽  
...  
Keyword(s):  
Free Vibration ◽  
Damage Detection ◽  
Vibration Response ◽  
Structural System ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Complex Morlet Wavelet ◽  
Structural System Identification ◽  
Free Vibration Response ◽  
Energy Components

This paper presents a wavelet-based method of identification modal parameter and damage detection in a free vibration response. An algorithm for modal parameter identification and damage detection is purposed and complex Morlet wavelet is chosen as an analysis wavelet function. This paper only focuses on identification of natural frequencies of the structural system. The method utilizes both undamaged and damage experiment data of free vibration response of the truss structure system. Wavelet scalogram is utilizes for damage detection. The change of energy components for undamaged and damage structure is investigated from the plot of wavelet scalogram which corresponded to the detection of damage.

Dynamic Property Evaluation of a Long-Span Cable-Stayed Bridge (Sutong Bridge) by a Bayesian Method

2018 ◽  
Vol 19 (01) ◽  
pp. 1940010 ◽  
Author(s):  
Yan-Chun Ni ◽  
Qi-Wei Zhang ◽  
Jian-Feng Liu
Keyword(s):  
Natural Frequency ◽  
Dynamic Characteristics ◽  
Structural Damage ◽  
Dynamic Properties ◽  
Modal Identification ◽  
Modal Parameters ◽  
Modal Parameter ◽  
Cable Stayed Bridge ◽  
Long Span ◽  
Sutong Bridge

Modal identification aims at identifying the dynamic properties including natural frequency, damping ratio, and mode shape, which is an important step in further structural damage detection, finite element model updating, and condition assessment. This paper presents the work on the investigation of the dynamic characteristics of a long-span cable-stayed bridge-Sutong Bridge by a Bayesian modal identification method. Sutong Bridge is the second longest cable-stayed bridge in the world, situated on the Yangtze River in Jiangsu Province, China, with a total length of 2 088[Formula: see text]m. A short-term nondestructive on-site vibration test was conducted to collect the structural response and determine the actual dynamic characteristics of the bridge before it was opened to traffic. Due to the limited number of sensors, multiple setups were designed to complete the whole measurement. Based on the data collected in the field tests, modal parameters were identified by a fast Bayesian FFT method. The first three modes in both vertical and transverse directions were identified and studied. In order to obtain modal parameter variation with temperature and vibration levels, long-term tests have also been performed in different seasons. The variation of natural frequency and damping ratios with temperature and vibration level were investigated. The future distribution of the modal parameters was also predicted using these data.

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