Modal Identification of Practical Engineering Structures using Second-Order Blind Identification

2021 ◽  
Author(s):  
K. Lakshmi ◽  
Varun Kasi Reddy ◽  
A. Rama Mohan Rao
Keyword(s):  
Second Order ◽  
Modal Identification ◽  
Blind Identification ◽  
Engineering Structures ◽  
Practical Engineering

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.

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.

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.

Compressed sensing based on dictionary learning for underdetermined modal identification

2020 ◽  
Vol 64 (1-4) ◽  
pp. 129-136
Author(s):  
Wei Guan ◽  
Longlei Dong ◽  
Jinxiong Zhou
Keyword(s):  
Compressed Sensing ◽  
Dictionary Learning ◽  
Engineering Application ◽  
Modal Identification ◽  
Mode Shapes ◽  
Engineering Structures ◽  
New Approach ◽  
Learned Dictionary ◽  
Complete Measurement ◽  
Practical Engineering

With the engineering structures becoming more complicated, it is difficult to obtain complete measurement responses with limited sensors. Thus, carrying out the underdetermined modal identification will have practical engineering application values. In this paper, a new approach for underdetermined blind modal identification based on dictionary learning in the framework of compressed sensing (CS) is proposed. The principal idea is to estimate modal shapes using a clustering technique, and recover modal responses combing the estimated mode shapes matrix and the learned dictionary. The experiment results on a typical cantilever beam structure illustrate that the proposed method can perform accurate dynamic parameters identification whether in underdetermined case or determined case.

Recent advances in reliability analysis of aeroengine rotor system: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xue-Qin Li ◽  
Lu-Kai Song ◽  
Guang-Chen Bai
Keyword(s):  
Reliability Analysis ◽  
Surrogate Model ◽  
Engineering Application ◽  
Rotor System ◽  
Engineering Structures ◽  
Content Type ◽  
Reliability Design ◽  
Rotor Systems ◽  
Practical Engineering ◽  
Complex Engineering

PurposeTo provide valuable information for scholars to grasp the current situations, hotspots and future development trends of reliability analysis area.Design/methodology/approachIn this paper, recent researches on efficient reliability analysis and applications in complex engineering structures like aeroengine rotor systems are reviewd.FindingsThe recent reliability analysis advances of engineering application in aeroengine rotor system are highlighted, it is worth pointing out that the surrogate model methods hold great efficiency and accuracy advantages in the complex reliability analysis of aeroengine rotor system, since its strong computing power can effectively reduce the analysis time consumption and accelerate the development procedures of aeroengine. Moreover, considering the multi-objective, multi-disciplinary, high-dimensionality and time-varying problems are the common problems in various complex engineering fields, the surrogate model methods and its developed methods also have broad application prospects in the future.Originality/valueFor the strong demand for efficient reliability design technique, this review paper may help to highlights the benefits of reliability analysis methods not only in academia but also in practical engineering application like aeroengine rotor system.

scholarly journals Fault Diagnosis of Rotating Machinery Based on Multi-Sensor Signals and Median Filter Second-Order Blind Identification (MF-SOBI)

2020 ◽  
Vol 10 (11) ◽  
pp. 3735 ◽  
Author(s):  
Feng Miao ◽  
Rongzhen Zhao ◽  
Leilei Jia ◽  
Xianli Wang
Keyword(s):  
Blind Source Separation ◽  
Impulse Noise ◽  
Median Filter ◽  
Source Separation ◽  
Rotating Machinery ◽  
Second Order ◽  
Time Signal ◽  
Blind Identification ◽  
Sensor Signals ◽  
Strong Impulse

Feature extraction plays a crucial role in the diagnosis of rotating machinery faults. However, the vibration signals measured are inherently complex and non-stationary and the features of faulty signals are often submerged by noise. The principle and method of blind source separation are introduced, and we point out that the blind source separation algorithm is invalid in an environment of strong impulse noise. In order to solve the problem of fast separation of multi-sensor signals in an environment of strong impulse noise, first, the window width of the median filter (MF) is calculated according to the sampling frequency, so that the impulse noise and part of the white noise can be effectively filtered out. Next, the filtered signals are separated by the improved second-order blind identification (SOBI) algorithm. At the same time, the method is tested on the strong pulse background noise and rub impact dataset. The results show that this method has higher efficiency and accuracy than the direct separation method. It is possible to apply the method to real-time signal analysis due to its speed and efficiency.

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