• 한국지진공학회논문집
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• 제22권3호
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• pp.201-210
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• 2018

The improvement in computing systems and sensor technologies devotes to conduct data-driven structural health monitoring algorithms for existing civil infrastructures. Despite of the development of techniques, the uncertainty oriented from the measurement results in the discrepancy to the actual structural parameters and let engineers or decision makers hesitate to adopt such techniques. Many studies have shown that the modal identification results can be affected by the uncertainties due to the applied methods and the types of loading. This paper aims to compare the performance of modal identification methods using Structural Modal Identification Toolsuite (SMIT) which has been developed to facilitate multiple identification methods with a user-friendly designed platform. The data fed into SMIT processes three stages for the comprehensive identification including preprocessing, eigenvalue estimation, and post-processing. The seismic and white noise response for shear frame model was obtained from numerical simulation. The identified modal parameters is compared to the actual modal parameters. In order to improve the quality of coherence in identified modal parameters, several hurdles including modal phase collinearity and extended modal amplitude coherence were introduced. Numerical simulation conducted on the 5 dof shear frame model were used to validate the effectiveness of using these parameters.

• International Journal of Fluid Machinery and Systems
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• 제2권4호
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• pp.278-285
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• 2009

Operational modal analysis (OMA) allows modal parameters, such as natural frequencies and damping, to be estimated solely from data collected during operation. However, a main shortcoming of these methods resides in the evaluation of the accuracy of the results. This paper will explore the uncertainty and possible variations in the estimates of modal parameters for different operating conditions. Two algorithms based on the Least Square Complex Exponential (LSCE) method will be used to estimate the modal parameters. The uncertainties will be calculated using a Monte-Carlo approach with the hypothesis of constant modal parameters at a given operating condition. In collaboration with Andritz-Hydro Ltd, data collected on two different stay vanes from an Andritz-Hydro Ltd Francis turbine will be used. This paper will present an overview of the procedure and the results obtained.

• Smart Structures and Systems
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• 제23권1호
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• pp.15-29
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• 2019

This paper addresses the problem of damage detection in suspension bridge hangers, with an emphasis on the modal flexibility method. It aims at evaluating the capability and the accuracy of the modal flexibility method to detect and locate single and multiple damages in suspension bridge hangers, with different level of severity and various locations. The study is conducted numerically and experimentally on a laboratory suspension bridge mock-up. First, the covariance-driven stochastic subspace identification is used to extract the modal parameters of the bridge from experimental data, using only output measurements data from ambient vibration. Then, the method is demonstrated for several damage scenarios and compared against other classical methods, such as: Coordinate Modal Assurance Criterion (COMAC), Enhanced Coordinate Modal Assurance Criterion (ECOMAC), Mode Shape Curvature (MSC) and Modal Strain Energy (MSE). The paper demonstrates the relative merits and shortcomings of these methods which play a significant role in the damage detection ofsuspension bridges.

• Earthquakes and Structures
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• 제23권1호
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• pp.1-11
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• 2022

This study implements a hybrid Genetic Algorithm to detect, locate, and quantify structural damage for multistory shear buildings using partial modal data. Measuring modal responses at multiple locations on a structure is both challenging and expensive in practice. The proposed method's objective function is based on the building's dynamic properties and can also be employed with partial modal information. This method includes initial residuals between the numerical and experimental model and a damage penalization term to avoid false damages. To test the proposed method, a numerical example of a ten-story shear building with noisy and partial modal information was explored. The obtained results were in agreement with the previously published research. The proposed method's performance was also verified using experimental modal data of an 8-DOF spring-mass system and a five-story shear building. The predicted results for numerical and experimental examples indicated that the proposed method is reliable in identifying the damage for multistory shear buildings.

• 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.

• Structural Engineering and Mechanics
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• 제61권2호
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• pp.267-274
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• 2017

In this study was investigated of possibility using the recorded micro tremor data on ground level as ambient vibration input excitation data for investigation and application Operational Modal Analysis (OMA) on the bench-scale earthquake simulator (The Quanser Shake Table) for model steel structures. As known OMA methods (such as EFDD, SSI and so on) are supposed to deal with the ambient responses. For this purpose, analytical and experimental modal analysis of a model steel structure for dynamic characteristics was evaluated. 3D Finite element model of the building was evaluated for the model steel structure based on the design drawing. Ambient excitation was provided by shake table from the recorded micro tremor ambient vibration data on ground level. Enhanced Frequency Domain Decomposition is used for the output only modal identification. From this study, best correlation is found between mode shapes. Natural frequencies and analytical frequencies in average (only) 2.8% are differences.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.258-261
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• 2006

The structure of small launch vehicle can be divided into engine section and payload section. This paper introduces modal test of the payload section of small launch vehicle which is composed to satellite, PLA (Payload Adapter), VEB (Vehicle Equipment Bay), KMS (Kick Motor Support) and KM (Kick Motor). From this test, dynamic properties of the 2nd stage structure of small launch vehicle can be obtained. In this test, to simulate free-free boundary condition, test object was hung by 4 bungee cords and excited by using impact hammer Modal test data are analyzed by using TDAS(Test Data Analysis Software). As the result, modal parameters and mode shapes below 100Hz of the 2nd stage of small launch vehicle were identified.

• 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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• 제15권3호
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• pp.717-733
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• 2015

Modal parameters of a structure are commonly used quantities for system identification and damage detection. With a limited number of studies on the statistics assessment of modal parameters, this paper presents procedures to properly account for the uncertainties present in the process of extracting modal parameters. Particularly, this paper focuses on how to deal with the measurement error in an ambient vibration test and the modeling error resulting from a modal parameter extraction process. A bootstrap approach is adopted, when an ensemble of a limited number of noised time-history response recordings is available. To estimate the modeling error associated with the extraction process, a model prediction expansion approach is adopted where the modeling error is considered as an "adjustment" to the prediction obtained from the extraction process. The proposed procedures can be further incorporated into the probabilistic analysis of applications where the modal parameters are used. This study considers the effects of the measurement and modeling errors and can provide guidance in allocating resources to improve the estimation accuracy of the modal data. As an illustration, the proposed procedures are applied to extract the modal data of a damaged beam, and the extracted modal data are used to detect potential damage locations using a damage detection method. It is shown that the variability in the modal parameters can be considered to be quite low due to the measurement and modeling errors; however, this low variability has a significant impact on the damage detection results for the studied beam.

• Structural Engineering and Mechanics
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• 제19권2호
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• pp.123-139
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• 2005

An automatic modal identification program is developed for continuous extraction of modal parameters of three cable-supported bridges in Hong Kong which are instrumented with a long-term monitoring system. The program employs the Complex Modal Indication Function (CMIF) algorithm for identifying modal properties from continuous ambient vibration measurements in an on-line manner. By using the LabVIEW graphical programming language, the software realizes the algorithm in Virtual Instrument (VI) style. The applicability and implementation issues of the developed software are demonstrated by using one-year measurement data acquired from 67 channels of accelerometers permanently installed on the cable-stayed Ting Kau Bridge. With the continuously identified results, variability in modal vectors due to varying environmental conditions and measurement errors is observed. Such an observation is very helpful for selection of appropriate measured modal vectors for structural health monitoring use.