Modal parameter extraction from measured signal by frequency domain decomposition (FDD) technique

2019 ◽  
Vol 11 (2) ◽  
pp. 324-337
Author(s):  
Sk Abdul Kaium ◽  
Sayed Abul Hossain ◽  
Jafar Sadak Ali

Purpose The purpose of this paper is to highlight that the need for improved system identification methods within the domain of modal analysis increases under the impulse of the broadening field of applications, e.g., damage detection and vibro-acoustics, and the increased complexity of today’s structures. Although significant research efforts during the last two decades have resulted in an extensive number of parametric identification algorithms, most of them are certainly not directly applicable for modal parameter extraction. So, based on this, the aim of the present work is to develop a technique for modal parameter extraction from the measured signal. Design/methodology/approach A survey and classification of the different modal analysis methods are made; however, the focus of this thesis is placed on modal parameter extraction from measured time signal. Some of the methods are examined in detail, including both single-degree-of-freedom and multi-degree-of-freedom approaches using single and global frequency-response analysis concepts. The theory behind each of these various analysis methods is presented in depth, together with the development of computer programs, theoretical and experimental examples and discussion, in order to evaluate the capabilities of those methods. The problem of identifying properties of structures that possess close modes is treated in particular detail, as this is a difficult situation to handle and yet a very common one in many structures. It is essential to obtain a good model for the behavior of the structure in order to pursue various applications of experimental modal analysis (EMA), namely: updating of finite element models, structural modification, subsystem-coupling and calculation of real modes from complex modes, to name a few. This last topic is particularly important for the validation of finite element models, and for this reason, a number of different methods to calculate real modes from complex modes are presented and discussed in this paper. Findings In this paper, Modal parameters like mode shapes and natural frequencies are extracted using an FFT analyzer and with the help of ARTeMiS, and subsequently, an algorithm has been developed based on frequency domain decomposition (FDD) technique to check the accuracy of the results as obtained from ARTeMiS. It is observed that the frequency domain-based algorithm shows good agreement with the extracted results. Hence the following conclusion may be drawn: among several frequency domain-based algorithms for modal parameter extraction, the FDD technique is more reliable and it shows a very good agreement with the experimental results. Research limitations/implications In the case of extraction techniques using measured data in the frequency domain, it is reported that the model using derivatives of modal parameters performed better in many situations. Lack of accurate and repeatable dynamic response measurements on complex structures in a real-life situation is a challenging problem to analyze exact modal parameters. Practical implications During the last two decades, there has been a growing interest in the domain of modal analysis. Evolved from a simple technique for troubleshooting, modal analysis has become an established technique to analyze the dynamical behavior of complex mechanical structures. Important examples are found in the automotive (cars, trucks, motorcycles), railway, maritime, aerospace (aircrafts, satellites, space shuttle), civil (bridges, buildings, offshore platforms) and heavy equipment industry. Social implications Presently structural health monitoring has become a significantly important issue in the area of structural engineering particularly in the context of safety and future usefulness of a structure. A lot of research is being carried out in this area incorporating the modern sophisticated instrumentations and efficient numerical techniques. The dynamic approach is mostly employed to detect structural damage, due to its inherent advantage of having global and location-independent responses. EMA has been attempted by many researchers in a controlled laboratory environment. However, measuring input excitation force(s) seems to be very expensive and difficult for the health assessment of an existing real-life structure. So Ambient Vibration Analysis is a good alternative to overcome those difficulties associated with the measurement of input excitation force. Originality/value Three single bay two storey frame structure has been chosen for the experiment. The frame has been divided into six small elements. An algorithm has been developed to determine the natural frequency of those frame structures of which one is undamaged and the rest two damages in single element and double element, respectively. The experimental results from ARTeMIS and from developed algorithm have been compared to verify the effectiveness of the developed algorithm. Modal parameters like mode shapes and natural frequencies are extracted using an FFT analyzer and with the help of ARTeMiS, and subsequently, an algorithm has been programmed in MATLAB based on the FDD technique to check the accuracy of the results as obtained from ARTeMiS. Using singular value decomposition, the power Spectral density function matrix is decomposed using the MATLAB program. It is observed that the frequency domain-based algorithm shows good consistency with the extracted results.

2007 ◽  
Vol 353-358 ◽  
pp. 1195-1198 ◽  
Author(s):  
Y.B. Chen ◽  
J.G. Han ◽  
D.Q. Yang

Structural operating conditions may significantly differ from those applied during laboratory tests where the structure is well known, well installed and properly excited. For structures under their natural loading conditions, or excited by random forces, excitations cannot be measured and are usually non stationary. Hence, an improvement operational modal analysis is a useful complement to the traditional modal analysis approach. The aim of this paper is to present the application of a new identification procedure, named wavelet-based identification technique of structural modal parameters. Wavelet-based identification that works in time-frequency domain is used to identify the dynamic characteristics of the structural system in terms of natural frequencies, damping coefficients and mode shapes. The paper has shown how the amplitude and the phase of the wavelet transform of operational vibration measurements are related to eigenfrequencies and damping coefficients, and the wavelet-based spectrum analysis is used to identify the mode shapes of the structure. Those modal parameters can be used to detect damage of structures. A simulation example has demonstrated that current identified results are comparable with those previously obtained from the peak pick method in frequency domain and stochastic subspace identification in time domain.


Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5664
Author(s):  
Jiqiao Zhang ◽  
Zhihua Wu ◽  
Gongfa Chen ◽  
Qiang Liang

This paper proposes a differential filtering method for the identification of modal parameters of bridges from unmanned aerial vehicle (UAV) measurement. The determination of the modal parameters of bridges is a key issue in bridge damage detection. Accelerometers and fixed cameras have disadvantages of deployment difficulty. Hence, the actual displacement of a bridge may be obtained by using the digital image correlation (DIC) technology from the images collected by a UAV. As drone movement introduces false displacement into the collected images, the homography transformation is commonly used to achieve geometric correction of the images and obtain the true displacement of the bridge. The homography transformation is not always applicable as it is based on at least four static reference points on the plane of target points. The proposed differential filtering method does not request any reference points and will greatly accelerate the identification of the modal parameters. The displacement of the points of interest is tracked by the DIC technology, and the obtained time history curves are processed by differential filtering. The filtered signals are input into the modal analysis system, and the basic modal parameters of the bridge model are obtained by the operational modal analysis (OMA) method. In this paper, the power spectral density (PSD) is used to identify the natural frequencies; the mode shapes are determined by the ratio of the PSD transmissibility (PSDT). The identification results of three types of signals are compared: UAV measurement with differential filtering, UAV measurement with homography transformation, and accelerometer-based measurement. It is found that the natural frequencies recognized by these three methods are almost the same. This paper demonstrates the feasibility of UAV-differential filtering method in obtaining the bridge modal parameters; the problems and challenges in UAV measurement are also discussed.


2004 ◽  
Vol 11 (3-4) ◽  
pp. 395-409 ◽  
Author(s):  
Bart Peeters ◽  
Herman Van der Auweraer ◽  
Patrick Guillaume ◽  
Jan Leuridan

Recently, a new non-iterative frequency-domain parameter estimation method was proposed. It is based on a (weighted) least-squares approach and uses multiple-input-multiple-output frequency response functions as primary data. This so-called “PolyMAX” or polyreference least-squares complex frequency-domain method can be implemented in a very similar way as the industry standard polyreference (time-domain) least-squares complex exponential method: in a first step a stabilisation diagram is constructed containing frequency, damping and participation information. Next, the mode shapes are found in a second least-squares step, based on the user selection of stable poles. One of the specific advantages of the technique lies in the very stable identification of the system poles and participation factors as a function of the specified system order, leading to easy-to-interpret stabilisation diagrams. This implies a potential for automating the method and to apply it to “difficult” estimation cases such as high-order and/or highly damped systems with large modal overlap. Some real-life automotive and aerospace case studies are discussed. PolyMAX is compared with classical methods concerning stability, accuracy of the estimated modal parameters and quality of the frequency response function synthesis.


2021 ◽  
Vol 11 (21) ◽  
pp. 9963
Author(s):  
Rafael A. Figueroa-Díaz ◽  
Pedro Cruz-Alcantar ◽  
Antonio de J. Balvantín-García

In the area of modal balancing, it is essential to identify the vibration modes to be balanced in order to obtain the different modal parameters that will allow knowing the correction weight and its position in the balance planes. However, in some cases, a single mode is apparently observed in the polar response diagrams used for this process, which actually contains at least two modes and which, when added vectorially, shows only one apparent mode. In these cases, in addition to the intrinsic errors when using a modal parameter extraction tool, there will be errors in determining the correction weight for the modes, as well as for the placement angle. In this work, an identification methodology is presented which, through the use of coordinate transformation and a modal parameter extraction tool, allows identifying characteristic patterns of close modes in frequency and which, when applied in the study of a system in the field, offers robustness and applicability.


2018 ◽  
Vol 7 (4.27) ◽  
pp. 78
Author(s):  
M. Fadhil Shazmir ◽  
N. Ayuni Safari ◽  
M. Azhan Anuar ◽  
A. A.Mat Isa ◽  
Zamri A.R

Obtaining a good experimental modal data is essential in modal analysis in order to ensure accurate extraction of modal parameters. The parameters are compared with other extraction methods to ascertain its consistency and validity. This paper demonstrates the extraction of modal parameters using various identification algorithms in Operational Modal Analysis (OMA) on a 3D scaled model of a 3-storey aluminium structure. Algorithms such as Frequency Domain Decomposition (FDD), Enhanced Frequency Domain Decomposition (EFDD) and Stochastic Subspace Identification (SSI) are applied in this study to obtain modal parameters. The model test structure is fabricated of aluminium and assembled using bolts and nuts. Accelerometers were used to collect the responses and the commercial post processing software was used to obtain the modal parameters. The resulting natural frequencies and mode shapes using FDD method are then compared with other OMA parametric technique such as EFDD and SSI algorithm by comparing the natural frequencies and Modal Assurance Criterion (MAC). Comparison of these techniques will be shown to justify the validity of each technique used and hence confirming the accuracy of the measurement taken.    


1998 ◽  
Vol 120 (2) ◽  
pp. 378-383
Author(s):  
T. P. Runarsson ◽  
M. T. Jonsson ◽  
G. R. Jonsson

This paper describes a nonlinear deterministic estimator based on cumulants for the extraction of modal parameters. The signal analysed is composed of multiple exponentially damped real sinusoids in unknown additive noise. Cumulants reduce significantly the effects of noise and are also an efficient way of compressing the sampled data. In modal analysis a sensor may be unable to detect some modes of vibration due to its location. Cumulants estimated from real data sampled at different locations and instances are added directly together. This average cumulant function will contain the eigenvalues for all excited modes of vibration. Finding the frequencies and corresponding damping factors is therefore reduced to solving a single average cumulant function. The performance of the proposed estimator is examined and compared with the Eigensystem Realization Algorithm via simulations.


Author(s):  
Marina Latinović ◽  
Zoran Mišković ◽  
Marko Popović

This paper presents a dynamic behavior analysis of an old cable-stayed footbridge over river Vrbasin Banja Luka. Identification of modal parameters, of this prone to vibrations footbridge structure,was performed using Operational Modal Analysis with Frequency Domain Decomposition method.Experimental test setups and obtained results, compared to the numerical values obtained by FEmodel updating, are shown. Modal Assurance Criterion was used for the confirmation of theuniqueness of experimentally obtained mode shapes, and also for the comparison of FE model modeshapes to the experimentally obtained ones, in the locations of measurement.


2015 ◽  
Vol 39 (1) ◽  
pp. 145-149 ◽  
Author(s):  
Ewa B. Skrodzka ◽  
Bogumił B.J. Linde ◽  
Antoni Krupa

Abstract Experimental modal analysis of a violin with three different tensions of a bass bar has been performed. The bass bar tension is the only intentionally introduced modification of the instrument. The aim of the study was to find differences and similarities between top plate modal parameters determined by a bass bar perfectly fitting the shape of the top plate, the bass bar with a tension usually applied by luthiers (normal), and the tension higher than the normal value. In the modal analysis four signature modes are taken into account. Bass bar tension does not change the sequence of mode shapes. Changes in modal damping are insignificant. An increase in bass bar tension causes an increase in modal frequencies A0 and B(1+) and does not change the frequencies of modes CBR and B(1-).


Crystals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 311
Author(s):  
Chan-Jung Kim

Previous studies have demonstrated the sensitivity of the dynamic behavior of carbon-fiber-reinforced plastic (CFRP) material over the carbon fiber direction by performing uniaxial excitation tests on a simple specimen. However, the variations in modal parameters (damping coefficient and resonance frequency) over the direction of carbon fiber have been partially explained in previous studies because all modal parameters have only been calculated using the representative summed frequency response function without modal analysis. In this study, the dynamic behavior of CFRP specimens was identified from experimental modal analysis and compared five CFRP specimens (carbon fiber direction: 0°, 30°, 45°, 60°, and 90°) and an isotropic SCS13A specimen using the modal assurance criterion. The first four modes were derived from the SCS13A specimen; they were used as reference modes after verifying with the analysis results from a finite element model. Most of the four mode shapes were found in all CFRP specimens, and the similarity increased when the carbon fiber direction was more than 45°. The anisotropic nature was dominant in three cases of carbon fiber, from 0° to 45°, and the most sensitive case was found in Specimen #3.


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