• Structural Engineering and Mechanics
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• 제39권5호
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• pp.733-750
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• 2011

Recently, identification of modal parameters using the response only data has attracted considerable attention particularly where the classic modal testing methods is difficult to conduct. One drawback of the response only data, also known as Operational Modal Analysis (OMA), is that only the unscaled mode shapes can be obtained which restricts the applications of OMA. The Mass change method is a usual way to scale the operational mode shapes. In this article a new method is proposed to optimize the additive mass for scaling of the unscaled mode shapes from OMA for which a priori knowledge of the Finite Element model of structure is required. It is shown that the total error of the scaled mode shapes is minimized using the proposed method. The method is validated using a numerical case study of a beam. Moreover, the experimental results of a clamped-clamped beam demonstrate the applicability of the method.

• Smart Structures and Systems
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• 제15권1호
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• pp.227-244
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• 2015

This study develops a two stage procedure to identify the structural damage based on the optimized artificial neural networks. Initially, the modal strain energy index (MSEI) is established to extract the damaged elements and to reduce the computational time. Then the genetic algorithm (GA) and artificial neural networks (ANNs) are combined to detect the damage severity. The input of the network is modal strain energy index and the output is the flexural stiffness of the beam elements. The principal component analysis (PCA) is utilized to reduce the input variants of the neural network. By using the genetic algorithm to optimize the parameters, the ANNs can significantly improve the accuracy and convergence of the damage identification. The influence of noise on damage identification results is also studied. The simulation and experiment on beam structures shows that the adaptive parameter selection neural network can identify the damage location and severity of beam structures with high accuracy.

• Smart Structures and Systems
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• 제17권3호
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• pp.471-489
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• 2016

Modal identification based on ambient vibration data has attracted extensive attention in the past few decades. Since the excitation for ambient vibration tests is mainly from the environmental effects such as wind and traffic loading and no artificial excitation is applied, the signal to noise (s/n) ratio of the data acquired plays an important role in mode identifiability. Under ambient vibration conditions, certain modes may not be identifiable due to a low s/n ratio. This paper presents a study on the mode identifiability of an instrumented cable-stayed bridge with the use of acceleration response data measured by a long-term structural health monitoring system. A recently developed fast Bayesian FFT method is utilized to perform output-only modal identification. In addition to identifying the most probable values (MPVs) of modal parameters, the associated posterior uncertainties can be obtained by this method. Likewise, the power spectral density of modal force can be identified, and thus it is possible to obtain the modal s/n ratio. This provides an efficient way to investigate the mode identifiability. Three groups of data are utilized in this study: the first one is 10 data sets including six collected under normal wind conditions and four collected during typhoons; the second one is three data sets with wind speeds of about 7.5 m/s; and the third one is some blind data. The first two groups of data are used to perform ambient modal identification and help to estimate a critical value of the s/n ratio above which the deficient mode is identifiable, while the third group of data is used to perform verification. A couple of fundamental modes are identified, including the ones in the vertical and transverse directions respectively and coupled in both directions. The uncertainty and s/n ratio of the deficient mode are investigated and discussed. A critical value of the modal s/n ratio is suggested to evaluate the mode identifiability of the deficient mode. The work presented in this paper could provide a base for the vibration-based condition assessment in future.

• 수산해양기술연구
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• 제29권1호
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• pp.39-55
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• 1993

Modal Analysis is the process of characterizing the dynamic properties of an elastic structure by identifying its modes of vibration. A mode of vibration is a global property of an elastic structure. That is, a mode has a specific natural frequency and damping factor which can be identified from response data at practically any point on a structure, and it has a characteristic mode shape which identifies the mode spatially over the entire structure. Modal testing is able to be performed on structural and mechanical structure in an effort to learn more about their elastic behavior. Once the dynamic properties of a structure are known its behavior can be predicted and therefore controlled or corrected. Resonant frequencies, damping factors and mode shape data can be used directly by a mechanical designer to pin point weak spots in a structure design, or this data can also be used to confirm or synthesize equations of motion for the elastic structure. These differential equations can be used to simulate structural response to know input forces and to examine the effects of pertubations in the distributed mass, stiffness and damping properties of the structure in more detail. In this paper the measurement of transfer functions in digital form, and the application of digital parameter identification techniques to identify modal parameters from the measured transfer function data are discussed. It is first shown that the transfer matrix, which is a complete dynamic model of an elastic plate structure can be written in terms of the structural modes of vibration. This special mathematical form allows one to identify the complete dynamics of the structure from a much reduced set of test data, and is the essence of the modal approach to identifying the dynamics of a structure. Finally, the application of transfer function models and identification techniques for obtaining modal parameters from the transfer function data are discussed. Characteristics on vibration response of elastic plate structure obtained from the dynamic analysis by Finite Element Method are compared with results of modal analysis.

• Structural Engineering and Mechanics
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• 제45권6호
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• pp.779-802
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• 2013

In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANNs) techniques are developed and applied to identify damage in a model steel girder bridge using dynamic parameters. The required data in the form of natural frequencies are obtained from experimental modal analysis. A comparative study is made using the ANNs and ANFIS techniques and results showed that both ANFIS and ANN present good predictions. However the proposed ANFIS architecture using hybrid learning algorithm was found to perform better than the multilayer feedforward ANN which learns using the backpropagation algorithm. This paper also highlights the concept of ANNs and ANFIS followed by the detail presentation of the experimental modal analysis for natural frequencies extraction.

• Wind and Structures
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• 제27권5호
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• pp.283-291
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• 2018

This study presents the reliability assessment of a 100.5 m tall reinforced concrete chimney at a glass factory under wind loading by using vibration-based identified modal values. Ambient vibration measurements were recorded and modal values such as frequencies, shapes and damping ratios were identified by using Enhanced Frequency Domain Decomposition (EFDD) method. Afterwards, Finite Element Model (FEM) of the chimney was verified based on identified modal parameters. Reliability assessment of the chimney under wind loading was performed by obtaining the exceedance probability of demand to capacity distribution. Demand distribution of the chimney was developed under repetitive seeds of multivariate stochastic wind fields generated along the height of chimney. Capacity distribution of the chimney was developed by Monte Carlo simulation. Finally, it was found that reliability of the chimney is lower than code suggested limit values.

• Structural Engineering and Mechanics
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• 제7권4호
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• pp.387-400
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• 1999

Damage detection in civil engineering structures using the change in dynamic system parameters has gained a lot of scientific interest during the last decade. By repeating a dynamic test on a structure after a certain time of use, the change in modal parameters can be used to quantify and qualify damages. To be able to use the modal parameters confidentially for damage evaluation, the effect of other parameters such as excitation type, ambient conditions,... should be considered. In this paper, the influence of excitation type on the dynamic system parameters of a highway prestressed concrete bridge is investigated. The bridge, B13, lies between the villages Vilvoorde and Melsbroek and crosses the highway E19 between Brussels and Antwerpen in Belgium. A drop weight and ambient vibration are used to excite the bridge and the response at selected points is recorded. A finite element model is constructed to support and verify the dynamic measurements. It is found that the difference between the natural frequencies measured using impact weight and ambient vibration is in general less than 1%.

• Structural Engineering and Mechanics
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• 제67권4호
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• pp.359-368
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• 2018

In this paper, a method is presented to identify the physical and modal parameters of multistory shear building based on substructural technique using block pulse generalized operational matrix and genetic algorithm. The substructure approach divides a complete structure into several substructures in order to significantly reduce the number of unknown parameters for each substructure so that identification processes can be independently conducted on each substructure. Block pulse functions are set of orthogonal functions that have been used in recent years as useful tools in signal characterization. Assuming that the input-outputs data of the system are known, their original BP coefficients can be calculated using numerical method. By using generalized BP operational matrices, substructural dynamic vibration equations can be converted into algebraic equations and based on BP coefficient for each story can be estimated. A cost function can be defined for each story based on original and estimated BP coefficients and physical parameters such as mass, stiffness and damping can be obtained by minimizing cost functions with genetic algorithm. Then, the modal parameters can be computed based on physical parameters. This method does not require that all floors are equipped with sensor simultaneously. To prove the validity, numerical simulation of a shear building excited by two different normally distributed random signals is presented. To evaluate the noise effect, measurement random white noise is added to the noise-free structural responses. The results reveal the proposed method can be beneficial in structural identification with less computational expenses and high accuracy.

• 대한기계학회논문집
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• 제14권2호
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• pp.339-348
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• 1990

Techniques which are able to predict and control dynamic characteristics, not affecting the vibrational characteristics on the modification of structural design, are being studied. As one of these techniques, experimental modal analysis is widely applied by many researchers. In this study, modal analysis is performed using transfer matrix method by a macro computer. The developed program would estimate the structural modal parameters precisely, and the validity of this program is certified by comparing with the experimental results of .GAMMA A. structure. Estimated modal parameters(natural frequency, vibrational mode, equivalent mass, etc.) are in accord with the experimental results. Also, the optimal location of the additive mass is determined by the evaluation of the vibrational mode and the equivalent mass. The relation between the additive mass and the equivalent mass is specified, and we come to know that the ratio of equivalent mass to additive mass alter linearly within the range of 20%.

• Smart Structures and Systems
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• 제4권1호
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• pp.47-66
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• 2008

The present work utilizes system identification technique for health monitoring of shear building, wherein Parametric State Space modeling has been adopted. The method requires input excitation to the structure and also output acceleration responses of both undamaged and damaged structure obtained from numerically simulated model. Modal parameters like eigen frequencies and eigen vectors have been extracted from the State Space model after introducing appropriate transformation. Least square technique has been utilized for the evaluation of the stiffness matrix after having obtained the modal matrix for the entire structure. Highly accurate values of stiffness of the structure could be evaluated corresponding to both the undamaged as well as damaged state of a structure, while considering noise in the simulated output response analogous to real time scenario. The damaged floor could also be located very conveniently and accurately by this adopted strategy. This method of damage detection can be applied in case of output acceleration responses recorded by sensors from the actual structure. Further, in case of even limited availability of sensors along the height of a multi-storeyed building, the methodology could yield very accurate information related to structural stiffness.