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.

Predicting the variability of natural frequencies and its causes by Second-Order Blind Identification

2018 ◽  
Vol 18 (2) ◽  
pp. 486-507 ◽  
Author(s):  
Carlo Rainieri ◽  
Filipe Magalhaes ◽  
Danilo Gargaro ◽  
Giovanni Fabbrocino ◽  
Alvaro Cunha
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Second Order ◽  
Parameter Estimates ◽  
Blind Identification ◽  
Modal Parameter ◽  
Civil Structures ◽  
Structural Health ◽  
Operational Variables

Structural aging, degradation phenomena, and damage due to hazardous events are common causes of failure in civil structures and infrastructures. The increasing need of extending the structure lifespan for sustainability and economic reasons motivated the rapid development of remote, fully automated structural health monitoring systems. Different approaches have been developed for damage detection based on the incoming data. Modal-based damage detection is probably one of the most popular procedures for structural health monitoring of civil structures, also thanks to the development of robust automated operational modal analysis algorithms in the last decade. However, the sensitivity of modal parameter estimates and the associated damage features to environmental and operational factors represents a significant drawback to the extensive application of this technology. Thus, effective damage detection cannot skip the preliminary compensation of the effect of those variables on modal properties. Different approaches to compensate the environmental influence on modal property estimates are reported in the literature. In this article, the use of Second-Order Blind Identification is proposed. It is applied to a number of case studies in order to validate its effectiveness in the presence of one or more environmental or operational variables. Results demonstrate that it can model the variability of natural frequency estimates in operational conditions and, above all, it can give a fundamental insight in determining the causes of such variability.

Second-Order Blind Identification for Operational Modal Analysis

2007 ◽  
Author(s):  
F. Poncelet ◽  
G. Kerschen ◽  
J. C. Golinval ◽  
F. Marin
Keyword(s):  
Modal Analysis ◽  
Operational Modal Analysis ◽  
Blind Identification ◽  
Modal Parameter ◽  
Engineering Structures ◽  
Experimental Application ◽  
Large Structures ◽  
Output Only ◽  
Modal Parameter Estimation ◽  
Source Signals

For modal analysis of large structures, it is unpractical and expensive to use artificial excitation (e.g., shakers). However, engineering structures are most often subject to ambient loads (e.g., traffic and wind) that can be exploited for modal parameter estimation. One difficulty is that the actual loading conditions cannot generally be measured, and output-only measurements are available. This paper proposes to explore the utility of blind source separation (BSS) techniques for operational modal analysis. The basic idea of BSS is to recover unobserved source signals from their observed mixtures. The feasibility and practicality of the proposed method are demonstrated using an experimental application.

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.

Research on Modal Identification of Structures Using Robust Second-Order Blind Identification Technique

2013 ◽  
Vol 389 ◽  
pp. 712-720
Author(s):  
Jian Hua Du ◽  
Hong Wu Huang ◽  
Dian Dian Lan
Keyword(s):  
Second Order ◽  
Modal Identification ◽  
Mode Shapes ◽  
Blind Identification ◽  
Separation Algorithm ◽  
Single Degree Of Freedom ◽  
Second Order Statistics ◽  
Single Degree ◽  
Identification Technique ◽  
Simulation Results

The paper discusses the basic principle of blind source separation algorithm applying in structural modal identification. By improving the signal-whitening method, a robust second-order blind identification (RSOBI) algorithm is established on the basis of second-order statistics. The modal responses and mode shapes can be obtained using the RSOBI algorithm from the observed data of structures in time domain. Frequency and damping are estimated from the modal responses by traditional single degree of freedom methods. The simulation results show that the RSOBI algorithm has good performance in modal identification of structures.

scholarly journals Comparison of Different Independent Component Analysis Algorithms for Output-Only Modal Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-25 ◽  
Author(s):  
Jianying Wang ◽  
Cheng Wang ◽  
Tianshu Zhang ◽  
Bineng Zhong
Keyword(s):  
Independent Component Analysis ◽  
Parameter Identification ◽  
Modal Analysis ◽  
Optimization Methods ◽  
Component Analysis ◽  
Independent Component ◽  
Modal Parameter ◽  
Modal Parameter Identification ◽  
Modal Parameters Identification ◽  
Output Only

From the principle of independent component analysis (ICA) and the uncertainty of amplitude, order, and number of source signals, this paper expounds the root reasons for modal energy uncertainty, identified order uncertainty, and modal missing in output-only modal analysis based on ICA methods. Aiming at the problem of lack of comparison and evaluation of different ICA algorithms for output-only modal analysis, this paper studies the different objective functions and optimization methods of ICA for output-only modal parameter identification. Simulation results on simply supported beam verify the effectiveness, robustness, and convergence rate of five different ICA algorithms for output-only modal parameters identification and show that maximization negentropy with quasi-Newton iterative of ICA method is more suitable for modal parameter identification.

Extending Blind Modal Identification to the Underdetermined Case for Ambient Vibration

2012 ◽  
Author(s):  
Scot McNeill
Keyword(s):  
Natural Frequencies ◽  
Second Order ◽  
Modal Identification ◽  
Ambient Vibration ◽  
Mode Shapes ◽  
Frequency Domain Method ◽  
Blind Identification ◽  
Vibration Data ◽  
Modal Damping ◽  
Six Dof

The modal identification framework known as Blind Modal Identification (BMID) has recently been developed, drawing on techniques from Blind Source Separation (BSS). Therein, a BSS algorithm known as Second Order Blind Identification (SOBI) was adapted to solve the Modal IDentification (MID) problem. One of the drawbacks of the technique is that the number of modes identified must be less than the number of sensors used to measure the vibration of the equipment or structure. In this paper, an extension of the BMID method is presented for the underdetermined case, where the number of sensors is less than the number of modes to be identified. The analytic signal formed from measured vibration data is formed and the Second Order Blind Identification of Underdetermined Mixtures (SOBIUM) algorithm is applied to estimate the complex-valued modes and modal response autocorrelation functions. The natural frequencies and modal damping ratios are then estimated from the corresponding modal auto spectral density functions using a simple Single Degree Of Freedom (SDOF), frequency-domain method. Theoretical limitations on the number of modes identified given the number of sensors are provided. The method is demonstrated using a simulated six DOF mass-spring-dashpot system excited by white noise, where displacement at four of the six DOF is measured. All six modes are successfully identified using data from only four sensors. The method is also applied to a more realistic simulation of ambient building vibration. Seven modes in the bandwidth of interest are successfully identified using acceleration data from only five DOF. In both examples, the identified modal parameters (natural frequencies, mode shapes, modal damping ratios) are compared to the analytical parameters and are demonstrated to be of good quality.

Development and some Key Issues of Modal Parameter Identification in Bridges

2013 ◽  
Vol 574 ◽  
pp. 193-198
Author(s):  
Guo Hai Hu ◽  
Cheng Ma ◽  
Chang Xi Yang ◽  
Yang Liu
Keyword(s):  
Parameter Identification ◽  
Working Condition ◽  
Modal Identification ◽  
Modal Parameter ◽  
Fundamental Idea ◽  
Modal Parameter Identification ◽  
Identification Methods ◽  
Identification Technique ◽  
Key Issues ◽  
Ambient Excitation

In this study, the modal identification methods based on time and frequency domain are summarized, and the working condition, identified accuracy and some fundamental idea of these approaches are discussed. By comparing the characteristic of different identification method, the identification technique based on ambient excitation is promising in bridges since it is difficult to measure the excitation information. Some challenge and key issues of modal identification of bridges are pointed out in the last part.

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