Dynamic analysis and modal test of long-span cable-stayed bridge based on ambient excitation

To study the stiffness distribution of girder and the method to identify modal parameters of cable-stayed bridge, a simplified dynamical finite element method model named three beams model was established for the girder with double ribs. Based on the simplified model four stiffness formulae were deduced according to Hamilton principle. These formulae reflect well the contribution of the flexural, shearing, free torsion and restricted torsion deformation, respectively. An identification method about modal parameters was put forward by combining method of peak value and power spectral density according to modal test under ambient excitation. The dynamic finite element method analysis and modal test were carried out in a long-span concrete cable-stayed bridge. The results show that the errors of frequencies between theoretical analysis and test results are less than 10% mostly, and the most important modal parameters for cable-stayed bridge are determined to be the longitudinal floating mode, the first vertical flexural mode and the first torsional mode, which demonstrate that the method of stiffness distribution for three beams model is accurate and method to identify modal parameters is effective under ambient excitation modal test.

Monitoring the Modal Frequency and Velocity Variations of Bridges under Ambient Excitation

We conducted a long-term monitoring experiment on the Lutuanxilu Bridge located in Changping District of Beijing, employing our recently developed real-time bridge monitoring system based on the Guralp CMG-6TD broadband seismometer. We identified the modal parameters with the stochastic subspace identification( SSI) algorithm,and continuously monitored the temporal velocity variation with coda wave interferometry.The results show that:( 1) the highly sensitive Guralp CMG-6TD broadband seismometer,which records the three-component vibration signal within broad frequency range,is well suited for long-term bridge health monitoring.( 2) With the continuous vibration signal from ambient excitation,the stochastic subspace algorithm can robustly identify the low-order modal parameters and the coda wave interferometry can accurately monitor the tiny velocity variation.( 3) The elastic modulus of bridge materials changes significantly associated with varying temperature,leading to diurnal velocity variation with amplitude of approximately 1%. The velocity variation shows strong negative correlation with temperature fluctuation. Meanwhile,the modal frequencies remain quite stable,suggesting that the velocity variation may be a more sensitive quantitative damage index.( 4) While the modal frequencies reflect the integrated health status of the bridge,the velocity variation can be utilized to monitor the local elastic modulus. Therefore,it is crucial for bridge health monitoring to continuously monitor the two key damage indexes under ambient excitation.

EXTRACTING MODAL PARAMETERS FROM STRUCTURES UNDERGOING AMBIENT EXCITATION

On Line Parameter Identification Technique (OLPIT) was presented according to ambient excitation characteristics and the response cross-correlation function that is a sum of decaying sinusoids of the same form as the impulse response function of the original system. OLPIT is a new method of identification modal parameters from response of structures under ambient excitation. OLPIT is different from NExT (natural excitation technique) based on ITD method in four aspects: ① The algorithm is improved by the singular-value decomposition (SVD). ② Multi-value of b r in the Ibrahim Time Domain (ITD) is avoided. ③ OLPIT is used in both SIMO (single input, multi-output) and MIMO (multi input, multi-output). ④ The precision of modal parameter identificatioin is improved. The simulation studies demonstrate that the method is effective in identifying complex modes even with close frequencies and is robust to measurement noise.

Modal Analysis Using Operating Modal Identification Method

Sometimes it is very difficult for some large-scale operating structures tomeasure the input forces. Modal parameters must be estimated on response-only. A poly-referencetime-domain operating modal identification complex exponential method is presented sincecross-correlation functions have the same form as impulse response functions. Then a poly-referencefrequency-domain operating modal identification method is proposed in this paper. An experiment onan aircraft model is performed to verify the proposed schemes. The results show that both outlinedschemes can extract the parameters from output-only and the modal parameters extracted by proposedfrequency-domain method are more accurate than those by presented time-domain complex exponentialmethod.

An Operational Modal Analysis Experimental Technique for Self-propelled Gun

The experimental modal analysis of the selected self-propelled gun was completed to obtain its modal frequency distribution and modes by using an operational modal analysis experimental technique.The result obtained by the method was compared with that obtained by the traditional method.It indicates that the two results are in good agreement.

Modal Parameters Identification of A Real Offshore Platform From the Response Excited by Natural Ice Loading

This paper investigates the possibility of utilizing response from natural ice loading for modal parameter identification of real offshore platforms.The test platform is the JZ20-2 MUQ jacket platform located in the Liaodong Bay,China.A field experiment is carried out in winter season,as the platform is excited by floating ices.The feasibility is demonstrated by the acceleration response of two different segments.By the SSI-data method,the modal frequencies and damping ratios of four structural modes can be successfully identified from both segments.The estimated information from both segments is almost identical,which demonstrates that the modal identification is trustworthy.Furthermore,by taking the Jacket platform as a benchmark,the numerical performance of five popular time-domain EMA methods is systematically compared from different viewpoints.The comparisons are categorized as:(1)stochastic methods versus deterministic methods;(2)high-order methods versus low-order methods;(3)data-driven versus covariance-driven stochastic subspace identification methods.