• Smart Structures and Systems
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• 제25권2호
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• pp.123-133
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• 2020

Compressive sensing (CS) is a newly developed data acquisition and processing technique that takes advantage of the sparse structure in signals. Normally signals in their primitive space or format are reconstructed from their compressed measurements for further treatments, such as modal analysis for vibration data. This approach causes problems such as leakage, loss of fidelity, etc., and the computation of reconstruction itself is costly as well. Therefore, it is appealing to directly work on the compressed data without prior reconstruction of the original data. In this paper, a direct approach for modal analysis of damped systems is proposed by decomposing the compressed measurements with an appropriate dictionary. The damped free vibration function is adopted to form atoms in the dictionary for the following sparse decomposition. Compared with the normally used Fourier bases, the damped free vibration function spans a space with both the frequency and damping as the control variables. In order to efficiently search the enormous two-dimension dictionary with frequency and damping as variables, a two-step strategy is implemented combined with the Orthogonal Matching Pursuit (OMP) to determine the optimal atom in the dictionary, which greatly reduces the computation of the sparse decomposition. The performance of the proposed method is demonstrated by a numerical and an experimental example, and advantages of the method are revealed by comparison with another such kind method using POD technique.

• Smart Structures and Systems
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• 제13권2호
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• pp.257-280
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• 2014

In this paper, a novel PARAllel FACtor (PARAFAC) decomposition based Blind Source Separation (BSS) algorithm is proposed for modal identification of structures equipped with tuned mass dampers. Tuned mass dampers (TMDs) are extremely effective vibration absorbers in tall flexible structures, but prone to get de-tuned due to accidental changes in structural properties, alteration in operating conditions, and incorrect design forecasts. Presence of closely spaced modes in structures coupled with TMDs renders output-only modal identification difficult. Over the last decade, second-order BSS algorithms have shown significant promise in the area of ambient modal identification. These methods employ joint diagonalization of covariance matrices of measurements to estimate the mixing matrix (mode shape coefficients) and sources (modal responses). Recently, PARAFAC BSS model has evolved as a powerful multi-linear algebra tool for decomposing an $n^{th}$ order tensor into a number of rank-1 tensors. This method is utilized in the context of modal identification in the present study. Covariance matrices of measurements at several lags are used to form a $3^{rd}$ order tensor and then PARAFAC decomposition is employed to obtain the desired number of components, comprising of modal responses and the mixing matrix. The strong uniqueness properties of PARAFAC models enable direct source separation with fine spectral resolution even in cases where the number of sensor observations is less compared to the number of target modes, i.e., the underdetermined case. This capability is exploited to separate closely spaced modes of the TMDs using partial measurements, and subsequently to estimate modal parameters. The proposed method is validated using extensive numerical studies comprising of multi-degree-of-freedom simulation models equipped with TMDs, as well as with an experimental set-up.

• Smart Structures and Systems
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• 제17권3호
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• pp.413-429
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• 2016

The recent research on proper orthogonal decomposition (POD) has revealed the linkage between proper orthogonal modes and linear normal modes. This paper presents an investigation into the modal identifiability of an instrumented cable-stayed bridge using an adapted POD technique with a band-pass filtering scheme. The band-pass POD method is applied to the datasets available for this benchmark study, aiming to identify the vibration modes of the bridge and find out the so-called deficient modes which are unidentifiable under normal excitation conditions. It turns out that the second mode of the bridge cannot be stably identified under weak wind conditions and is therefore regarded as a deficient mode. To judge if the deficient mode is due to its low contribution to the structural response under weak wind conditions, modal coordinates are derived for different modes by the band-pass POD technique and an energy participation factor is defined to evaluate the energy participation of each vibration mode under different wind excitation conditions. From the non-blind datasets, it is found that the vibration modes can be reliably identified only when the energy participation factor exceeds a certain threshold value. With the identified threshold value, modal identifiability in use of the blind datasets from the same structure is examined.

• Structural Monitoring and Maintenance
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• 제7권4호
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• pp.283-294
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• 2020

In this paper, an adaptive MEMD based modal identification technique for linear time-invariant systems is proposed employing multiple vibration measurements. Traditional empirical mode decomposition (EMD) suffers from mode-mixing during sifting operations to identify intrinsic mode functions (IMF). MEMD performs better in this context as it considers multi-channel data and projects them into a n-dimensional hypercube to evaluate the IMFs. Using this technique, modal parameters of the structural system are identified. It is observed that MEMD has superior performance compared to its traditional counterpart. However, it still suffers from mild mode-mixing in higher modes where the energy contents are low. To avoid this problem, an adaptive filtering scheme is proposed to decompose the interfering modes. The Proposed modified scheme is then applied to vibrations of a reinforced concrete road bridge. Results presented in this study show that the proposed MEMD based approach coupled with the filtering technique can effectively identify the parameters of the dominant modes present in the structural response with a significant level of accuracy.

• 소음진동
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• 제9권1호
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• pp.163-173
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• 1999

Precise and reasonable modelling is necessary and indispensable to the analysis of dynamic characteristics of mechanical structures. Also. the effective prediction of the change of modal properties due to the variation of design parameters is required especially for the application of finite element method to the structural dynamics problems. To meet those necessity and requirement, three model updating algorithms are proposed for finite element methods. Those algorithms are based on sensitivity analysis of the modal data obtained from experimental modal analysis(EMA) and analytical modal analysis(AMA). The adapted sensitivity analysis methods of the algorithms are 1)eigensensitivity(EGNS) method. 2)frequency response function sensitivity(FRFS) method. 3)sensitivity based element-by-element method (SBEEM), Singular value decomposition(SVD) is used for performing eigenanalysis and parameter estimation in the updating process. Those algorithms are applied to finite element of a plate and the updating capability of each algorithm is compared in terms of accuracy. reliability and stability of the updating process. It is shown that the model updating method using frequency response function is superior to the other methods in view of various updating capabilities.

• Structural Monitoring and Maintenance
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• 제2권1호
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• pp.1-18
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• 2015

Traditionally, it is not easy to carry out tests to identify modal parameters from existing railway bridges because of the testing conditions and complicated nature of civil structures. A six year (2007-2012) research program was conducted to monitor a group of 25 railway bridges. One of the tasks was to devise guidelines for identifying their modal parameters. This paper presents the experience acquired from such identification. The modal analysis of four representative bridges of this group is reported, which include B5, B15, B20 and B58A, crossing the Caraj$\acute{a}$s railway in northern Brazil using three different excitations sources: drop weight, free vibration after train passage, and ambient conditions. To extract the dynamic parameters from the recorded data, Stochastic Subspace Identification and Frequency Domain Decomposition methods were used. Finite-element models were constructed to facilitate the dynamic measurements. The results show good agreement between the measured and computed natural frequencies and mode shapes. The findings provide some guidelines on methods of excitation, record length of time, methods of modal analysis including the use of projected channel and harmonic detection, helping researchers and maintenance teams obtain good dynamic characteristics from measurement data.

• 비파괴검사학회지
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• 제30권4호
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• pp.359-366
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• 2010

램파를 구조물 안전진단(structural health monitoring, 이하 SMH) 기법에 효과적으로 적용하기 위해서 구조물의 손상과 램파간의 물리적 특성 및 상호관계를 정확히 이해하는 것이 중요하다. 본 연구에서는 modal decomposition 방법을 이용하여 비대칭 불연속면에서 램파의 투과와 반사, 모드 변이를 모사하고, 그 진폭 비율을 불연속면의 깊이에 따라 예측하였다. 또한 이론적으로 예측된 결과를 압전센서(PZT)를 모사한 유한요소법(FEM) 모델과 실험을 통해 검증하였다. 그 결과, modal decomposition 방법을 이용한 이론적 예측이 압전센서를 이용한 유한요소 해석 및 실험 결과와 근접한 것을 확인하였으며, 불연속면의 깊이에 따른 램파의 반사와 투과, 모드 변이의 양을 이용하여 손상의 크기를 정량적으로 측정할 수 있는 방법을 제안하였다.

• Computers and Concrete
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• 제10권3호
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• pp.277-294
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• 2012

The aim of the study is to determine the modal parameters of a prototype damaged arch dam by operational modal analysis (OMA) method for some damage scenarios. For this purpose, a prototype arch dam-reservoir-foundation model is constructed under laboratory conditions. Ambient vibration tests on the arch dam model are performed to identify the modal parameters such as natural frequency, mode shape and damping ratio. The tests are conducted for four test-case scenarios: an undamaged dam with empty reservoir, two different damaged dams with empty reservoirs, and a damaged dam with full reservoir. Loading simulating random impact effects is applied on the dam to crack. Cracks and fractures occurred at the middle of the upper part of the dams and distributed through the abutments. Sensitivity accelerometers are placed on the dams' crests to collect signals for measurements. Operational modal analysis software processes the signals collected from the ambient vibration tests, and enhanced frequency domain decomposition and stochastic subspace identification techniques are used to estimate modal parameters of the dams. The modal parameters are obtained to establish a basis for comparison of the results of two techniques for each damage case. Results show that approximately 35-40% difference exists between the natural frequencies obtained from Case 1 and Case 4. The natural frequencies of the dam considerably decrease with increasing cracks. However, observation shows that the filled reservoir slightly affected modal parameters of the dam after severe cracking. The mode shapes obtained are symmetrical and anti-symmetrical. Apparently, mode shapes in Case 1 represent the probable responses of arch dams more accurately. Also, damping ratio show an increase when cracking increases.

• Computers and Concrete
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• 제12권6호
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• pp.803-818
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• 2013

In this study, analytical and experimental modal analyses of a scaled bridge model are carried out to extract the dynamic characteristics such as natural frequency, mode shapes and damping ratios. For this purpose, a scaled bridge model is constructed in laboratory conditions. Three dimensional finite element model of the bridge is constituted and dynamic characteristics are determined, analytically. To identify the dynamic characteristics experimentally; Experimental Modal Analyses (ambient and forced vibration tests) are conducted to the bridge model. In the ambient vibration tests, natural excitations are provided and the response of the bridge model is measured. Sensitivity accelerometers are placed to collect signals from the measurements. The signals collected from the tests are processed by Operational Modal Analysis; and the dynamic characteristics of the bridge model are estimated using Enhanced Frequency Domain Decomposition and Stochastic Subspace Identification methods. In the forced vibration tests, excitation of the bridge model is induced by an impact hammer and the frequency response functions are obtained. From the finite element analyses, a total of 8 natural frequencies are attained between 28.33 and 313.5 Hz. Considering the first eight mode shapes, these modes can be classified into longitudinal, transverse and vertical modes. It is seen that the dynamic characteristics obtained from the ambient and forced vibration tests are close to each other. It can be stated that the both of Enhanced Frequency Domain Decomposition and Stochastic Subspace Identification methods are very useful to identify the dynamic characteristics of the bridge model. The first eight natural frequencies are obtained from experimental measurements between 25.00-299.5 Hz. In addition, the dynamic characteristics obtained from the finite element analyses have a good correlation with experimental frequencies and mode shapes. The MAC values obtained between 90-100% and 80-100% using experimental results and experimental-analytical results, respectively.

• Structural Engineering and Mechanics
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• 제17권3_4호
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• pp.445-466
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• 2004

In this paper, several modal identification techniques for output-only structural systems are extensively investigated. The methods considered are the power spectral method, the frequency domain decomposition method, the Ibrahim time domain method, the eigensystem realization algorithm, and the stochastic subspace identification method. Generally, the power spectral method is most widely used in practical area, however, the other methods may give better estimates particularly for the cases with closed modes and/or with large measurement noise. Example analyses were carried out on typical structural systems under three different loading cases, and the identification performances were examined throught the comparisons between the estimates by various methods.