Modal identification of Canton Tower under uncertain environmental conditions

Ye, Xijun; Yan, Quansheng; Wang, Weifeng; Xiaolin, Yu

doi:10.12989/sss.2012.10.4_5.353

Cited by 14 publications

(12 citation statements)

References 18 publications

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“…(2) As for the relationship between the frequency and temperature, the simulated results of the FEM are consistent with the measured results in the work of Ye et al, 31 ie, the GNTVT's frequency decreases as the temperature increases and vice versa. For a high-rise structure like GNTVT, either only take the effect of temperature on the material elastic modulus into account or only consider the effect of temperature on the structural geometric stiffness, when the temperature rises, and the structural modal frequency decreases, ie, the relationship between the structural modal frequency and temperature is inversely proportional.…”

Section: Discussionsupporting

confidence: 85%

“…Refer to Ye et al, 31 it can be seen that there are 13 modal frequencies in the range of 0∼1.4 Hz in Figure 2. The first modal frequency is 0.01 Hz, which shows GNTVT is a very flexible high-rise structure.…”

Section: Output-only Modal Identificationmentioning

confidence: 65%

“…30 Using an improved multiple reference DOFs stabilization diagram method, which is based on NExT-ERA (M-NExT-ERA), the modal properties of GNTVT have been identified by Ye et al 31 frequency range of interest is less than 5 Hz, the data is band pass filtered with a fifth-order band-pass Butterworth filter in the range [0.05-2] Hz after detrending. 30 Using an improved multiple reference DOFs stabilization diagram method, which is based on NExT-ERA (M-NExT-ERA), the modal properties of GNTVT have been identified by Ye et al 31 frequency range of interest is less than 5 Hz, the data is band pass filtered with a fifth-order band-pass Butterworth filter in the range [0.05-2] Hz after detrending.…”

Section: Output-only Modal Identificationmentioning

confidence: 99%

“…At each step, the modes identified at the current system order are compared with the modes identified at the previous system order, and the modal frequency, damping ratio, and mode shape are used as criteria. 30 Using an improved multiple reference DOFs stabilization diagram method, which is based on NExT-ERA (M-NExT-ERA), the modal properties of GNTVT have been identified by Ye et al 31 The duration of signal is 24 hours. Since the frequency range of interest is less than 5 Hz, the data is band pass filtered with a fifth-order band-pass Butterworth filter in the range [0.05-2] Hz after detrending.…”

Section: Output-only Modal Identificationmentioning

confidence: 99%

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Model updating and variability analysis of modal parameters for super high‐rise structure

Chen

2018

Concurrency and Computation

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For Structural Health Monitoring (SHM), a core prerequisite is to accurately identify the modal properties. Since the dynamic characteristics of a structure change under the effects of different environmental factors such as temperature and wind, it is necessary to determine how the environmental factors affect the modal properties. This study focuses on the Guangzhou new TV tower (GNTVT), which is a 610-m high structure. Based on the measured data from GNTVT, both the varying patterns of the operational modal parameters under the effects of different environmental factors and the Finite Element Model (FEM) updating based on Genetic Algorithm (GA) had been investigated. Then, using the updated FEM, the effect of the temperature on the modal frequency had been investigated under two situations: (1) Temperature only affects the modulus of elasticity. This situation was considered to be more important because of the significant frequency change. When temperature increases by10 • C, the maximum change of modal frequencies is 1%. (2) Temperature only affects the geometric stiffness of structure. This situation was considered to be less important because the change in the frequency is very small which may be ignored.When temperature increases by10 • C, the maximum change of modal frequencies is 0.02%. The simulated results were consistent with the measured results. KEYWORDS finite element model, modal frequency, model update, super high-rise structure, temperature INTRODUCTIONUsing the vibration-based method, the primary task of Structural Health Monitoring (SHM) is to accurately identify the structural modal properties. This is because the modal properties, eg, frequency, modal shape, and damping ratio, can accurately reflect the structural properties such as stiffness and damage. 1,2 However, changes in the environmental conditions may cause changes in these modal properties. Over the past two decades, using field measurements and dynamic tests, the effects of the environmental factors, such as temperature, wind speed, and humidity on the structural modal properties have been extensively investigated. 3-17 While the vibration-based structural damage identification approaches have gained increasing attention in research, earlier studies have shown that the environmental effect is one of the main pitfalls limiting successful applications of the vibration-based damage detection methods to real structures. [18][19][20] These studies concluded that: (1) the effect of the variations in the modal properties due to the changes in the environmental factors is highly significant. The effect may be even greater than that caused by structural damage.(2) Temperature is the environmental factor that causes severe variation in modal properties.(3) The effect of the temperature on the natural frequencies can be eliminated using intelligent artificial algorithms such as Artificial Neural Networks (ANN) and Supporting Vector Machine (SVM).The studies mentioned in the preceding literature review are mostly based on the monitoring data ...

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Section: Discussionsupporting

confidence: 85%

Section: Output-only Modal Identificationmentioning

confidence: 65%

Section: Output-only Modal Identificationmentioning

confidence: 99%

Section: Output-only Modal Identificationmentioning

confidence: 99%

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Model updating and variability analysis of modal parameters for super high‐rise structure

Chen

2018

Concurrency and Computation

Self Cite

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“…Ni et al (2012) presented a benchmark problem to study the ambient vibration response of the Canton Tower over a whole day with the temperature and wind information measured simultaneously . Based on these data, research has been conducted all over the world, including modal identification, model updating, sensor displacement, and so on [5, 28–36]. Shi et al (2012) introduced their work on modal identification of a super tall building located in Shanghai using ambient and free vibration data.…”

Section: Introductionmentioning

confidence: 99%

Structural health monitoring of Shanghai Tower during different stages using a Bayesian approach

Zhang

Xiong

Shi

et al. 2016

Struct. Control Health Monit.

110

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The dynamic characterization of structures is essential for assessing their response when subjected to dynamic loads in structural health monitoring. It mainly comprises the modal parameters, that is, the natural frequencies, damping ratios and mode shapes. These modal properties are attracting more attention when structures are under construction or operation for the researchers, structure owner and engineers. This paper presents the work on the operational modal analysis of a super tall building-the Shanghai Tower with a height of 632 m situated in Shanghai, China. A recently developed fast Bayesian method is utilized to perform modal identification, providing an effective means to identify the modal properties and assess their accuracy. In this study, ambient vibration tests are implemented in different construction stages. The corresponding modal properties and their associated uncertainties are identified and investigated, with interesting trends observed. Finite element models are also established to obtain the modal parameters in different stages and compared with the identified results. After the main structure is completed, a field test covering the eight corners of the core wall in a typical floor is performed to investigate the mode shapes. Afterward, a 12-h measurement is performed with the information of temperature and humidity recorded simultaneously. The variation of modal properties with changing environment is studied. The results obtained will be beneficial for understanding the modal properties of this super tall building and provide a baseline for future structural health monitoring.

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Dynamic displacements-based model updating with motion capture system

Hwang

Choi

et al. 2016

Struct. Control Health Monit.

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Summary In this paper, a dynamic displacements‐based model updating method using a motion capture system (MCS) is proposed. The dynamic characteristics from MCS are used to find the parameters that minimize the difference between updated model and direct measurement. Using a multi‐objective optimization algorithm of non‐dominated sorting genetic algorithm‐II, the number of objective functions for model updating is set to the same number of modes under consideration, and all the objective function are simultaneously minimized. To consider the contribution of each mode on model updating and to avoid biased results, a rule for weighting of solutions associated to each mode based on modal participation factors is suggested and tested. Using a free vibration experimental test of a three‐story shear model, the performance of model updating method is verified by the comparison of the dynamics characteristics between the updated model and direct measurement by MCS. In addition, time histories of displacements from the updated model are compared with the direct measurement. Copyright © 2016 John Wiley & Sons, Ltd.

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Modal identification of Canton Tower under uncertain environmental conditions

Cited by 14 publications

References 18 publications

Model updating and variability analysis of modal parameters for super high‐rise structure

Model updating and variability analysis of modal parameters for super high‐rise structure

Structural health monitoring of Shanghai Tower during different stages using a Bayesian approach

Dynamic displacements-based model updating with motion capture system

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