Towards an automatic spectral and modal identification from operational modal analysis

Experimental characterization and validation of skin components in aircraft entails multiple evaluations (structural, aerodynamic, acoustic, etc.) and expensive campaigns. They require different rigs and equipment to perform the necessary tests. Two of the main dynamic characterizations include the energy absorption under impact forcing and the identification of modal parameters through the vibration response under any broadband excitation, which also includes impacts. This work exploits the response of a stiffened aircraft composite panel submitted to a multi-impact excitation, which is intended for impact and energy absorption analysis. Based on the high stiffness of composite materials, the study worked under the assumption that the global response to the multi-impact excitation is linear with small strains, neglecting the nonlinear behavior produced by local damage generation. Then, modal identification could be performed. The vibration after the impact was measured by high-speed 3D digital image correlation and employed for full-field operational modal analysis. Multiple modes were characterized in a wide spectrum, exploiting the advantages of the full-field noninvasive techniques. These results described a consistent modal behavior of the panel along with good indicators of mode separation given by the auto modal assurance criterion (Auto-MAC). Hence, it illustrates the possibility of performing these dynamic characterizations in a single test, offering additional information while reducing time and investment during the validation of these structures.

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Looseness localization for bolted joints using Bayesian operational modal analysis and modal strain energy

Advances in Mechanical Engineering ◽

10.1177/1687814018808698 ◽

2018 ◽

Vol 10 (11) ◽

pp. 168781401880869 ◽

Cited By ~ 3

Author(s):

Yu-Jia Hu ◽

Wei-Gong Guo ◽

Cheng Jiang ◽

Yun-Lai Zhou ◽

Weidong Zhu

Keyword(s):

Modal Analysis ◽

Strain Energy ◽

Damage Index ◽

Operational Modal Analysis ◽

Modal Identification ◽

Bolted Joints ◽

Mode Shapes ◽

Bolted Connections ◽

Modal Strain Energy ◽

Beam Structures

Bayesian operational modal analysis and modal strain energy are employed for determining the damage and looseness of bolted joints in beam structures under ambient excitation. With this ambient modal identification technique, mode shapes of a damaged beam structure with loosened bolted connections are obtained based on Bayesian theory. Then, the corresponding modal strain energy can be calculated based on the mode shapes. The modal strain energy of the structure with loosened bolted connections is compared with the theoretical one without bolted joints to define a damage index. This approach uses vibration-based nondestructive testing of locations and looseness of bolted joints in beam structures with different boundary conditions by first obtaining modal parameters from ambient vibration data. The damage index is then used to identify locations and looseness of bolted joints in beam structures with single or multiple bolted joints. Furthermore, the comparison between damage indexes due to different looseness levels of bolted connections demonstrates a qualitatively proportional relationship.

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Identification of Historical Veziragasi Aqueduct Using the Operational Modal Analysis

The Scientific World JOURNAL ◽

10.1155/2014/518608 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8 ◽

Cited By ~ 8

Author(s):

E. Ercan ◽

A. Nuhoglu

Keyword(s):

Modal Analysis ◽

Natural Frequencies ◽

Model Updating ◽

Dynamic Properties ◽

Dynamic Test ◽

Element Model ◽

Operational Modal Analysis ◽

Modal Identification ◽

Ambient Vibration ◽

Mode Shapes

This paper describes the results of a model updating study conducted on a historical aqueduct, called Veziragasi, in Turkey. The output-only modal identification results obtained from ambient vibration measurements of the structure were used to update a finite element model of the structure. For the purposes of developing a solid model of the structure, the dimensions of the structure, defects, and material degradations in the structure were determined in detail by making a measurement survey. For evaluation of the material properties of the structure, nondestructive and destructive testing methods were applied. The modal analysis of the structure was calculated by FEM. Then, a nondestructive dynamic test as well as operational modal analysis was carried out and dynamic properties were extracted. The natural frequencies and corresponding mode shapes were determined from both theoretical and experimental modal analyses and compared with each other. A good harmony was attained between mode shapes, but there were some differences between natural frequencies. The sources of the differences were introduced and the FEM model was updated by changing material parameters and boundary conditions. Finally, the real analytical model of the aqueduct was put forward and the results were discussed.

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Cluster Analysis for Automated Operational Modal Analysis: A Review

MATEC Web of Conferences ◽

10.1051/matecconf/201925502012 ◽

2019 ◽

Vol 255 ◽

pp. 02012 ◽

Cited By ~ 1

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.

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A frequency domain blind identification method for operational modal analysis using a limited number of sensors

Journal of Vibration and Control ◽

10.1177/1077546319897218 ◽

2020 ◽

Vol 26 (17-18) ◽

pp. 1383-1398

Author(s):

Xinhui Li ◽

Jerome Antoni ◽

Michael J Brennan ◽

Tiejun Yang ◽

Zhigang Liu

Keyword(s):

Modal Analysis ◽

Frequency Domain ◽

Blind Source Separation ◽

Source Separation ◽

Operating Conditions ◽

Operational Modal Analysis ◽

Modal Identification ◽

Frequency Range ◽

Vibration Data ◽

Spatial Aliasing

Operational modal analysis is an experimental modal analysis approach, which uses vibration data collected when the structure is under operating conditions. Amongst the methods for operational modal analysis, blind source separation–based methods have been shown to be efficient and powerful. The existing blind source separation modal identification methods, however, require the number of sensors to be at least equal to the number of modes in the frequency range of interest to avoid spatial aliasing. In this article, a frequency domain algorithm that overcomes this problem is proposed, which is based on the joint diagonalization of a set of weighted covariance matrices. In the proposed approach, the frequency range of interest is partitioned into several frequency ranges in which the number of active modes in each band is less than the number of sensors. Numerical simulations and an experimental example demonstrate the efficacy of the method.

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A review of operational modal analysis techniques for in-service modal identification

Journal of the Brazilian Society of Mechanical Sciences and Engineering ◽

10.1007/s40430-020-02470-8 ◽

2020 ◽

Vol 42 (8) ◽

Author(s):

Fahad Bin Zahid ◽

Zhi Chao Ong ◽

Shin Yee Khoo

Keyword(s):

Modal Analysis ◽

Operational Modal Analysis ◽

Modal Identification ◽

Analysis Techniques

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A New Online Operational Modal Analysis Method for Vibration Control for Linear Time-Varying Structure

Applied Sciences ◽

10.3390/app10010048 ◽

2019 ◽

Vol 10 (1) ◽

pp. 48 ◽

Cited By ~ 1

Author(s):

Cheng Wang ◽

Haiyang Huang ◽

Xiongming Lai ◽

Jianwei Chen

Keyword(s):

Vibration Control ◽

Modal Analysis ◽

Natural Frequencies ◽

Linear Time ◽

Vibration Response ◽

Operational Modal Analysis ◽

Modal Identification ◽

Modal Parameters ◽

Time Varying ◽

Forgetting Factor

From the viewpoint of vibration control, if the amplitude of the main frequencies of the vibration response can be reduced, the vibration energy of the structure is greatly reduced. Modal parameters, including modal shapes, natural frequencies, and damping ratios, can reflect the dynamics of the structure and can be used to control the vibration. This paper integrates the idea of “forgetting factor weighting” into eigenvector recursive principal component analysis, and then proposes an operational modal analysis (OMA) method that uses eigenvector recursive PCA with a forgetting factor (ERPCAWF). The proposed method can identify the transient natural frequencies and transient modal shapes online and realtime using only nonstationary vibration response signals. The identified modal parameters are also suitable for online, real-time health monitoring and fault diagnosis. Finally, the modal identification results from a three-degree-of-freedom weakly damped linear time-varying structure shows that the ERPCAWF-based OMA method can effectively identify transient modal parameters online using only nonstationary response signals. The results also show that the ERPCAWF-based approach is faster, requires less memory space, and achieves higher identification accuracy and greater stability than autocorrelation matrix recursive PCA with a forgetting factor-based OMA.

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