Identifying the Modal Parameters of a Structure from Ambient Vibration Data via the Stationary Wavelet Packet

2014 ◽  
Vol 29 (10) ◽  
pp. 738-757 ◽  
Author(s):  
W. C. Su ◽  
C. S. Huang ◽  
C. H. Chen ◽  
C. Y. Liu ◽  
H. C. Huang ◽  
...  
Keyword(s):  
Wavelet Packet ◽  
Ambient Vibration ◽  
Modal Parameters ◽  
Vibration Data

Dynamic Assessment of the Iron Bridge at Paderno d’Adda (1889)

2010 ◽  
Vol 133-134 ◽  
pp. 709-714 ◽  
Author(s):  
Carmelo Gentile ◽  
Antonella Saisi
Keyword(s):  
Experimental Investigation ◽  
Modal Analysis ◽  
Dynamic Assessment ◽  
Ambient Vibration ◽  
Modal Parameters ◽  
Dynamic Tests ◽  
Operational Conditions ◽  
Vibration Data ◽  
Output Only ◽  
Identification Techniques

The paper presents the experimental modal analysis recently carried out on the historic iron bridge at Paderno d’Adda (1889). The dynamic tests were performed in operational conditions (i.e. under traffic and wind-induced excitation) between June and October 2009 and different output-only identification techniques were used to extract the modal parameters from ambient vibration data. The described tests represent the first experimental investigation carried out on the global characteristics of the bridge, since the load reception tests of 1889 and 1892.

Ambient Vibration Test, Modal Identification and Structural Model Updating Following Bayesian Framework

2015 ◽  
Vol 15 (07) ◽  
pp. 1540024 ◽  
Author(s):  
J. Yang ◽  
H. F. Lam ◽  
J. Hu
Keyword(s):  
Bayesian Model ◽  
Structural Model ◽  
Model Updating ◽  
Modal Identification ◽  
Ambient Vibration ◽  
Modal Parameters ◽  
Vibration Test ◽  
Engineering Structures ◽  
Ambient Vibration Test ◽  
Vibration Data

Structural health monitoring (SHM) of civil engineering structures based on vibration data includes three main components: ambient vibration test, modal identification and model updating. This paper discussed these three components in detail and proposes a general framework of SHM for practical application. First, a fast Bayesian modal identification method based on Fast Fourier Transform (FFT) is introduced for efficiently extracting modal parameters together with the corresponding uncertainties from ambient vibration data. A recently developed Bayesian model updating method using Markov chain Monte Carlo simulation (MCMCS) is then discussed. To illustrate the performance of the proposed modal identification and model updating methods, a scale-down transmission tower is investigated. Ambient vibration test is conducted on the target structure to obtain modal parameters. By using the measured modal parameters, model updating is carried out. The MCMC-based Bayesian model updating method can efficiently evaluate the posterior marginal PDFs of the uncertain parameters without calculating high-dimension numerical integration, which provides posterior uncertainties for the target systems.

scholarly journals Dynamic Study of a Rooftop Vertical Axis Wind Turbine Tower Based on an Automated Vibration Data Processing Algorithm

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3135 ◽  
Author(s):  
Ying Wang ◽  
Wensheng Lu ◽  
Kaoshan Dai ◽  
Miaomiao Yuan ◽  
Shen-En Chen
Keyword(s):  
Wind Turbine ◽  
Vertical Axis ◽  
Dynamic Responses ◽  
Ambient Vibration ◽  
Structural Vibration ◽  
Vertical Axis Wind Turbine ◽  
Mode Identification ◽  
Stochastic Subspace Identification ◽  
Vibration Data ◽  
Vibration Responses

When constructed on tall building rooftops, the vertical axis wind turbine (VAWT) has the potential of power generation in highly urbanized areas. In this paper, the ambient dynamic responses of a rooftop VAWT were investigated. The dynamic analysis was based on ambient measurements of the structural vibration of the VAWT (including the supporting structure), which resides on the top of a 24-story building. To help process the ambient vibration data, an automated algorithm based on stochastic subspace identification (SSI) with a fast clustering procedure was developed. The algorithm was applied to the vibration data for mode identification, and the results indicate interesting modal responses that may be affected by the building vibration, which have significant implications for the condition monitoring strategy for the VAWT. The environmental effects on the ambient vibration data were also investigated. It was found that the blade rotation speed contributes the most to the vibration responses.

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