Dynamic Property Evaluation of a Long-Span Cable-Stayed Bridge (Sutong Bridge) by a Bayesian Method

2018 ◽  
Vol 19 (01) ◽  
pp. 1940010 ◽  
Author(s):  
Yan-Chun Ni ◽  
Qi-Wei Zhang ◽  
Jian-Feng Liu
Keyword(s):  
Natural Frequency ◽  
Dynamic Characteristics ◽  
Structural Damage ◽  
Dynamic Properties ◽  
Modal Identification ◽  
Modal Parameters ◽  
Modal Parameter ◽  
Cable Stayed Bridge ◽  
Long Span ◽  
Sutong Bridge

Modal identification aims at identifying the dynamic properties including natural frequency, damping ratio, and mode shape, which is an important step in further structural damage detection, finite element model updating, and condition assessment. This paper presents the work on the investigation of the dynamic characteristics of a long-span cable-stayed bridge-Sutong Bridge by a Bayesian modal identification method. Sutong Bridge is the second longest cable-stayed bridge in the world, situated on the Yangtze River in Jiangsu Province, China, with a total length of 2 088[Formula: see text]m. A short-term nondestructive on-site vibration test was conducted to collect the structural response and determine the actual dynamic characteristics of the bridge before it was opened to traffic. Due to the limited number of sensors, multiple setups were designed to complete the whole measurement. Based on the data collected in the field tests, modal parameters were identified by a fast Bayesian FFT method. The first three modes in both vertical and transverse directions were identified and studied. In order to obtain modal parameter variation with temperature and vibration levels, long-term tests have also been performed in different seasons. The variation of natural frequency and damping ratios with temperature and vibration level were investigated. The future distribution of the modal parameters was also predicted using these data.

Vibration Monitoring of Two Long-Span Floors Equipped with Tuned Mass Dampers

2019 ◽  
Vol 19 (09) ◽  
pp. 1950101 ◽  
Author(s):  
Pei Liu ◽  
Hai-Xin Zhu ◽  
Babak Moaveni ◽  
Wei-Guo Yang ◽  
Shu-Qiang Huang
Keyword(s):  
Natural Frequency ◽  
Dynamic Properties ◽  
Concrete Slab ◽  
Vibration Monitoring ◽  
Ambient Vibration ◽  
Mode Shapes ◽  
Modal Parameters ◽  
Tuned Mass Dampers ◽  
Long Span ◽  
Wood Flooring

This paper presents the field tests and vibration performance assessment of two long-span floors with tuned mass dampers (TMDs). The floors considered are made of steel beams and concrete slabs, as part of a gymnasium with composite floors spanning 36 m in each direction and equipped with 30 TMDs. Operational modal analysis based on ambient acceleration measurements is performed to extract the modal parameters of the floors. Ambient vibration tests were conducted at three stages of construction for each floor, namely (i) after the concrete slab was completed, (ii) after one layer over the concrete slab was added, and (iii) after the flooring (surfacing) was fully finished. The effects of the layers making up the flooring system and of the TMDs on the dynamic properties of the floors are studied. The finite element models of the floors are validated using the identified modal parameters. The effects of natural frequency of TMDs on the dynamic properties of the floors are investigated using the validated model. Finally, the effects of flooring on the vibration serviceability of the two floors are studied with TMDs in operation, when the floors were subjected to crowd-induced rhythmic loading, from which the efficiency of TMDs is assessed numerically. The results show that the coupled vibrations of the two floors with TMDs turned off occur in the first two modes, while the natural frequencies of the floors decrease with the addition of layers. The TMDs in operation break the first mode of the floor into two modes with similar mode shapes, resulting in smaller vibration response and larger damping ratios, which vary with the natural frequency of TMDs. Also, the wood flooring significantly increases the human-induced vibration of the floor, while the plastic flooring shows basically no effect.

Dynamic Characteristics of a Long-Span Cable-Stayed Bridge

2011 ◽  
Vol 480-481 ◽  
pp. 1496-1501
Author(s):  
Liu Hui
Keyword(s):  
Finite Element ◽  
Dynamic Characteristics ◽  
Iteration Method ◽  
Natural Frequencies ◽  
Element Model ◽  
Vibration Modes ◽  
Cable Stayed Bridge ◽  
Long Span ◽  
Subspace Iteration ◽  
Floating System

In order to study the dynamic characteristics of a super-long-span cable-stayed bridge which is semi-floating system, the spatial finite element model of this cable-stayed bridge was established in ANSYS based on the finite element theory.Modal solution was conducted using subspace iteration method, and natural frequencies and vibration modes were obtained.The dynamic characteristics of this super-long-span cable-stayed bridge were then analyzed.Results showed that the super-long-span cable-stayed bridge of semi-floating system has long basic cycle, low natural frequencies, dense modes and intercoupling vibration modes.

scholarly journals Noise Reduction for Modal Parameter Identification of the Measured FRFs Using the Modal Peak-Based Hankel-SVD Method

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Tianxu Zhu ◽  
Chaoping Zang ◽  
Gengbei Zhang
Keyword(s):  
Parameter Identification ◽  
Noise Reduction ◽  
Flat Plate ◽  
Modal Identification ◽  
Modal Parameters ◽  
Modal Parameter ◽  
Noise Elimination ◽  
Modal Parameter Identification ◽  
Modal Test ◽  
Svd Method

The measured frequency response functions (FRFs) in the modal test are usually contaminated with noise that significantly affects the modal parameter identification. In this paper, a modal peak-based Hankel-SVD (MPHSVD) method is proposed to eliminate the noise contaminated in the measured FRFs in order to improve the accuracy of the identification of modal parameters. This method is divided into four steps. Firstly, the measured FRF signal is transferred to the impulse response function (IRF), and the Hankel-SVD method that works better in the time domain rather than in the frequency domain is further applied for the decomposition of component signals. Secondly, the iteration of the component signal accumulation is conducted to select the component signals that cover the concerned modal features, but some component signals of the residue noise may also be selected. Thirdly, another iteration considering the narrow frequency bands near the modal peak frequencies is conducted to further eliminate the residue noise and get the noise-reduced FRF signal. Finally, the modal identification method is conducted on the noise-reduced FRF to extract the modal parameters. A simulation of the FRF of a flat plate artificially contaminated with the random Gaussian noise and the random harmonic noise is implemented to verify the proposed method. Afterwards, a modal test of a flat plate under the high-temperature condition was undertaken using scanning laser Doppler vibrometry (SLDV). The noise reduction and modal parameter identification were exploited to the measured FRFs. Results show that the reconstructed FRFs retained all of the modal features we concerned about after the noise elimination, and the modal parameters are precisely identified. It demonstrates the superiority and effectiveness of the approach.

scholarly journals A Method of Modal Parameter Identification for Wind Turbine Blade Based on Binocular Dynamic Photogrammetry

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Wenyun Wang ◽  
Xuejun Li ◽  
Anhua Chen
Keyword(s):  
Wind Turbine ◽  
Turbine Blade ◽  
Wind Turbine Blade ◽  
Modal Identification ◽  
Image Feature ◽  
Vibration Measurement ◽  
Modal Parameters ◽  
Target Point ◽  
Identification Algorithm ◽  
Modal Parameter

The identification of operational modal parameters of a wind turbine blade is fundamental for online damage detection. In this paper, we use binocular photogrammetry technology instead of traditional contact sensors to measure the vibration of blade and apply the advanced stochastic system identification technique to identify the blade modal frequencies automatically when only output data are available. Image feature extraction and target point tracking (PT) are carried out to acquire the displacement of labeled targets on the wind turbine blade. The vibration responses of the target points are obtained. The data-driven stochastic subspace identification (SSI-Data) method based on the Kalman filter prediction sequence is explored to extract modal parameters from vibration response under unknown excitation. Hankel matrixes are reconstructed with different dimensions, so different modal parameters are produced. Similarity of these modal parameters is compared and used to cluster modes into groups. Under appropriate tolerance thresholds, spurious modes can be eliminated. Experiment results show that good effects and stable accuracy can also be achieved with the presented photogrammetry vibration measurement and automatic modal identification algorithm.

scholarly journals Automated Modal Identification Based on Improved Clustering Method

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Gangrou Wu ◽  
Min He ◽  
Peng Liang ◽  
Chunsheng Ye ◽  
Yue Xu
Keyword(s):  
Structural Damage ◽  
Previous Method ◽  
Modal Identification ◽  
Modal Parameters ◽  
Clustering Method ◽  
Modal Data ◽  
Benchmark Experiment ◽  
Stabilization Diagram ◽  
Automated Modal Identification ◽  
Last Stage

The automated modal identification has been playing an important role in online structural damage detection and condition assessment. This paper proposes an improved hierarchical clustering method to identify the precise modal parameters by automatically interpreting the stabilization diagram. Two major improvements are provided in the whole clustering process. The modal uncertainty is first introduced in the first stage to eliminate as many as possible mathematical modal data to produce more precise clustering threshold, which helps to produce more precise clustering results. The boxplot is introduced in the last stage to assess the precision of the clustering results from a statistical perspective. Based on an iterative analysis of boxplot, the outliers of the clustering results are found out and eliminated and the precise modal results are finally produced. The Z24 benchmark experiment data are utilized to validate the feasibility of the proposed method, and comparison between the previous method and the improved method is also provided. From the result, it can be concluded that the modal uncertainty is more effective than the other modal criteria in distinguishing the mathematical modal data. The modal results by clustering process are not precise in statistic and the boxplot can find out the outliers of the clustering results and produce more precise modal results. The improved automated modal identification method can automatically extract the physical modal data and produce more precise modal parameters.

Simultaneous Dynamics-Based Visual Inspection Using Modal Parameter Estimation

2011 ◽  
Vol 23 (1) ◽  
pp. 180-195 ◽  
Author(s):  
Hua Yang ◽  
◽  
Takeshi Takaki ◽  
Idaku Ishii
Keyword(s):  
Parameter Estimation ◽  
Real Time ◽  
Visual Inspection ◽  
Dynamic Properties ◽  
Mode Shapes ◽  
Modal Parameters ◽  
Modal Parameter ◽  
Resonant Frequencies ◽  
Modal Parameter Estimation ◽  
Non Destructive

In this study, we introduce the concept of dynamicsbased visual inspection with High-Frame-Rate (HFR) video analysis as a novel non-destructive active sensing method for verifying dynamic properties of a vibrating object. The HFR video is used for determining the structural dynamic properties of an object, such as its resonant frequencies and mode shapes, which can be estimated as modal parameters by modal analysis only when the object is excited. By improving and implementing a fast output-only modal parameter estimation algorithm on a real-time 2000-fps vision platform, the modal parameters of an excited object are simultaneously estimated as its input-invariant dynamic properties for dynamics-based visual inspection evenwhen the objects undergo different excitation conditions. Our simultaneous 2000-fps visual inspection system can facilitate non-destructive and longterm monitoring of the structures of beam-shaped objects vibrating at dozens or hundreds of hertz, and it can detect small changes in the dynamic properties of these objects caused by internal defects such as fatigue cracks in real time, even when their static appearances are similar. To demonstrate the performance of the proposed 2000-fps simultaneous dynamics-based visual inspection approach, the resonant frequencies and mode shapes for beam-shaped cantilevers with different artificial cracks and weights, excited by human finger tapping, were estimated in real time.

scholarly journals A new modal analysis method applied to changing machine tool using clustering

2020 ◽  
Vol 12 (10) ◽  
pp. 168781402096832
Author(s):  
Xuchu Jiang ◽  
Xinyong Mao ◽  
Yingjie Chen ◽  
Caihua Hao
Keyword(s):  
Machine Tool ◽  
Modal Analysis ◽  
Natural Frequency ◽  
Efficient Method ◽  
Machine Tools ◽  
Vibration Signal ◽  
Modal Parameters ◽  
Analysis Method ◽  
Modal Parameter ◽  
The Difference

The states of the machine tool, such as the components’ position and the spindle speed, play leading roles in the change of dynamic parameters. However, the traditional modal analysis method that modal parameters manually identified from vibration signal is greatly interfered by harmonics, and the process of eliminating interference is very inefficient and subjective. At present, there is a lack of a standard and efficient method to characterize modal parameter changes in different states of machine tools. This paper proposes a new machine tool modal classification analysis method based on clustering. The characteristics related to the modal parameters are extracted from the response signal in different states, and the clustering results are used to reflect the changes of machine tool modal parameters. After the amplitude of the frequency response function is normalized, the characteristics related to the natural frequency are acquired, and the clustering results further reflect the difference of the natural frequency of the signal. The new method based on clustering can be a standard and efficient method to characterize modal parameter changes in different states of machine tools.

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