• Structural Engineering and Mechanics
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• v.39 no.5
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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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.863-868
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• 2002

Operational Modal Analysis also known as Ambient Modal Analysis has an increasing interest in mechanical engineering. Especially on big structures where the excitation and not less important the determination of the forces is most often a problem. In a structure like a wind turbine wing where the modes occur both close in frequency and hi-directional the ambient excitation has big advantages. In this paper modal parameters are identified from the wing by operational modal analysis. For the parameter identification both parametric and non-parametric techniques are used. Advantages and disadvantages are discussed and results from the different techniques are compared

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.385.1-385
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• 2002

Operational Modal Analysis also known as Ambient Modal Analysis has an increasing interest in mechanical cngineering. Especially on big structures where the excitation and not less important the determination of the forces is most often a problem. In a structure like a wind turbine wing where the modes occur both close in frequency and bi-directional the Ambient excitation has big advantages. (omitted)

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.1162-1165
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• 2001

Operational Modal Analysis also known as Output Only Modal Analysis has in the recent years been used for extracting modal parameters of civil engineering structures and is now becoming popular for mechanical structures. The advantage of the method is that no artificial excitation need to be applied to the structure or force signals to be measured. All the parameter estimation is based upon the response signals, thereby minimising the work of preparation for the test. This test case is a controlled lab set-up enabling different parameter estimation methods techniques to be used and compared to the Operational Modal Analysis. For Operational Modal Analysis two different estimation techniques are used： a non-parametric technique based on Frequency Domain Decomposition (FDD), and a parametric technique working on the raw data in time domain, a data driven Stochastic Subspace Identification (SS!) algorithm. These are compared to other methods such as traditional Modal Analysis.

• Smart Structures and Systems
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• v.20 no.2
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• pp.115-126
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• 2017

The modal identification of large civil structures such as bridges under the ambient vibrational conditions has been widely investigated during the past decade. Many operational modal analysis methods have been proposed and successfully used for identifying the dynamic characteristics of the constructed bridges in service. However, there is very limited research available on reliable criteria for the robustness of these identified modal parameters of the bridge structures. In this study, two time-domain operational modal analysis methods, the data-driven stochastic subspace identification (SSI-DATA) method and the covariance-driven stochastic subspace identification (SSI-COV) method, are employed to identify the modal parameters from field recorded ambient acceleration data. On the basis of the SSI-DATA method, the modal contribution indexes of all identified modes to the measured acceleration data are computed by using the Kalman filter, and their applicability to evaluate the robustness of identified modes is also investigated. Here, the benchmark problem, developed by Hong Kong Polytechnic University with field acceleration measurements under different excitation conditions of a cable-stayed bridge, is adopted to show the effectiveness of the proposed method. The results from the benchmark study show that the robustness of identified modes can be judged by using their modal contributions to the measured vibration data. A critical value of modal contribution index of 2% for a reliable identifiability of modal parameters is roughly suggested for the benchmark problem.

• Structural Engineering and Mechanics
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• v.37 no.6
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• pp.593-615
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• 2011

This study determines the water length effects on the modal behavior of a prototype arch dam using Operational and Analytical Modal Analyses. Achievement of this purpose involves construction of a prototype arch dam-reservoir-foundation model under laboratory conditions. In the model, reservoir length was taken to be as much as three times the dam height. To determine the experimental dynamic characteristics of the arch dam using Operational Modal Analysis, ambient vibration tests were implemented for empty reservoir and three different reservoir water lengths. In the ambient vibration tests, the dam was vibrated by natural excitations provided from small impact effects and the response signals were measured using sensitive accelerometers. Operational Modal Analysis software process signals collected from the ambient vibration tests, and Enhanced Frequency Domain Decomposition and Stochastic Subspace Identification techniques estimated modal parameters of the dams. To validate the experimental results, 3D finite element model of the prototype arch dam was modeled by ANSYS software for empty reservoir and three different reservoir water lengths, and dynamic characteristics of each model were determined analytically. At the end of the study, experimentally and analytically identified dynamic characteristics compared to each other. Also, changes on the natural frequencies along to water length are plotted as graphs. Results suggest that reservoir water complicates the modal behavior of the arch dam significantly.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.393-410
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• 2012

The 610 m high Canton Tower (formerly named Guangzhou New Television Tower) is currently considered as a benchmark problem for structural health monitoring (SHM) of high-rise slender structures. In the benchmark study task I, a set of 24-hour ambient vibration measurement data has been available for the output-only system identification study. In this paper, the vector autoregressive models (ARV) method is adopted in the operational modal analysis (OMA) for this TV tower. The identified natural frequencies, damping ratios and mode shapes are presented and compared with the available results from some other research groups which used different methods, e.g., the data-driven stochastic subspace identification (SSI-DATA) method, the enhanced frequency domain decomposition (EFDD) algorithm, and an improved modal identification method based on NExT-ERA technique. Furthermore, the environmental effects on the estimated modal parameters are also discussed.

• Earthquakes and Structures
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• v.15 no.3
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• pp.263-273
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• 2018

Operational modal analysis is being widely used in aerospace, mechanical and civil engineering. Common research fields include optimal design and rehabilitation under dynamic loads, structural health monitoring, modification and control of dynamic response and analytical model updating. In many practical cases, influence of noise contamination in the recorded data makes it difficult to identify the modal parameters accurately. In this paper, an improved frequency domain method called Enhanced Least Square Complex Frequency (eLSCF) is developed to extract modal parameters from noisy recorded data. The proposed method makes the use of pre-defined approximate mode shape vectors to refine the cross-power spectral density matrix and extract fundamental frequency for the mode of interest. The efficiency of the proposed method is illustrated using an example five story shear frame loaded by random excitation and different noise signals.

• Smart Structures and Systems
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• v.31 no.2
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• pp.171-181
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• 2023

Using the most up-to-date system identification methods in both time and frequency domains, the dynamic monitoring data from the reinforced concrete Egebaekvej Bridge near Holte, Denmark, is examined in this investigation. The bridge was erected in the 1960s and was still standing during test campaign before demolishing. The ARTeMIS Modal was adopted to derive the modal parameters from ambient vibration data. Several Operational Modal Analysis (OMA) approaches were applied, including Enhanced Frequency Domain Decomposition (EFDD), Curve-fit Frequency Domain Decomposition (CFDD), and Frequency Domain Decomposition (FDD). Afterward, Principal Component (SSI-PC), Unweighted Principal Component (SSI-UPC) Stochastic Subspace Identification methods were utilized. Danish engineering consulting company, COWI with the allowance of the bridge contractor BARSLUND, allow the researcher for this experimental test to demonstrate the impact of OMA applications.

• Earthquakes and Structures
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• v.8 no.4
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• pp.859-887
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• 2015

Structural health monitoring (SHM) has gained in popularity in recent years since it can assess the performance and condition of instrumented structures in real time and provide valuable information to the asset's manager and owner. Operational modal analysis plays an important role in SHM and it involves the determination of natural frequencies, damping ratios and mode shapes of a constructed structure based on measured dynamic data. This paper presents the operational modal analysis and seismic response characterization of the Tsing Ma Suspension Bridge of 2,160 m long subjected to different earthquake events. Three kinds of events, i.e., short-distance, middle-distance and long-distance earthquakes are taken into account. A fast Bayesian modal identification method is used to carry out the operational modal analysis. The modal properties of the bridge are identified and compared by use of the field monitoring data acquired before and after the earthquake for each type of the events. Research emphasis is given on identifying the predominant modes of the seismic responses in the deck during short-distance, middle-distance and long-distance earthquakes, respectively, and characterizing the response pattern of various structural portions (deck, towers, main cables, etc.) under different types of earthquakes. Since the bridge is over 2,000 m long, the seismic wave would arrive at the tower/anchorage basements of the two side spans at different time instants. The behaviors of structural dynamic responses on the Tsing Yi side span and on the Ma Wan side span under each type of the earthquake events are compared. The results obtained from this study would be beneficial to the seismic design of future long-span bridges to be built around Hong Kong (e.g., the Hong Kong-Zhuhai-Macau Bridge).