Field measurements of typhoon effects on a transmission tower and its modal parameter identification

Li, Hong‐Nan; Fu, Xing; Ren, Liang; Zhang, Qing

doi:10.1177/1369433219898103

Cited by 16 publications

(7 citation statements)

References 33 publications

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“…The SSI method based on data-driven is more applicable for the actual structure under long-term environmental load 33 , 34 . The strain mode shapes of the structure can be ultimately obtained as follows via the identification of the system matrix and : where represents the strain mode of the structure; is the eigenvector; is the diagonal eigenvalue matrix.…”

Section: Displacement Reconstruction Methods From Multi-rate Datamentioning

confidence: 99%

Theoretical derivation and experimental investigation of dynamic displacement reconstruction based on data fusion for beam structures

Ren

Zhang

2022

Sci Rep

Self Cite

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Accurately obtaining the dynamic displacement response of the beam structure is of great significance. However, it is difficult to directly measure the dynamic displacement for large structures due to the low measurement accuracy or the installation difficulty of the sensor. Therefore, it is urgent to develop an indirect measurement method for displacement based on measurable physical quantities. Since acceleration and strain contain high and low frequency displacement information respectively, this paper proposes a displacement reconstruction algorithm that can realize the data fusion of the two, which is very helpful for the research of structural health monitoring. Firstly, the stochastic subspace identification (SSI) method is adopted to calculate the strain mode, and then the displacement is derived via the mode shape superposition method. Afterwards, the strain-derived displacement and acceleration are combined by the proposed algorithm to reconstruct the dynamic displacement. Both the numerical simulation and model experiment are conducted to verify the effectiveness of the proposed algorithm. Furthermore, the influences of noise, sampling rate ratio and measurement point position are analyzed. The results show that the proposed algorithm can accurately reconstruct both high-frequency and pseudo-static displacements, and the displacement reconstructed error in the model experiment is within 5%.

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Section: Displacement Reconstruction Methods From Multi-rate Datamentioning

confidence: 99%

Theoretical derivation and experimental investigation of dynamic displacement reconstruction based on data fusion for beam structures

Ren

Zhang

2022

Sci Rep

Self Cite

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“…Modal identification technique is essential to identify accurately the structural vibration characteristics from measured dynamic responses for health monitoring of engineering structures. The identified vibration characteristics can be used for structural damage detection, condition assessment, and long-term monitoring (Beck et al, 2001; Nagarajaiah and Yang, 2017; Li et al, 2020; Sun et al, 2020; Hou et al, 2022). In terms of engineering applications, it is very difficult to measure the dynamic external excitations applied to the structures.…”

Section: Introductionmentioning

confidence: 99%

Operational modal identification of structures based on improved empirical wavelet transform

Xia,

Li,

et al. 2023

Advances in Structural Engineering

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When empirical wavelet transform (EWT) is used to identify the modal parameters of civil engineering structures, the frequency band division is generally not accurate due to the noise effect on the Fourier spectrum. This phenomenon will lead to modal mixing and false modes in the analysis results. Therefore, this article establishes a signal frequency band division method by taking advantages of maximal spectrum technique and spectral skewness index. Combining the random decrement technique (RDT) and the least square method of single component modal parameter identification, an adaptive approach based on the improved EWT for operational modal parameter identification of civil engineering structures under stationary environmental excitations is proposed. The traditional frequency band division method based on EWT can not completely and effectively divide the meaningful frequency bands. While the proposed frequency band division technology based on the spectral skewness index can prevent the phenomenon of insufficient division and excessive division and realize adaptive frequency band division. The effectiveness of the proposed approach is validated by a numerical three-story frame and a field three-span concrete box girder bridge under ambient vibrations. The modal identification results from both numerical and experimental validations demonstrate that the proposed approach can effectively and accurately decompose the vibration responses and identify the structural modal parameters under operational conditions.

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“…In vibration-based structural health monitoring, the careful choice and examination of fault features play a pivotal role. Signal processing techniques widely utilized include the peak value method [6], stochastic subspace identification [7], and variational mode decomposition [8], which are employed to extract distinctive parameters. These parameters are then compared under different working conditions to diagnose faults.…”

Section: Introductionmentioning

confidence: 99%

A Monitoring Method for Transmission Tower Foots Displacement Based on Wind-Induced Vibration Response

Liu,

Zhao,

Wen

et al. 2023

SDHM

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The displacement of transmission tower feet can seriously affect the safe operation of the tower, and the accuracy of structural health monitoring methods is limited at the present stage. The application of deep learning method provides new ideas for structural health monitoring of towers, but the current amount of tower vibration fault data is restricted to provide adequate training data for Deep Learning (DL). In this paper, we propose a DT-DL based tower foot displacement monitoring method, which firstly simulates the wind-induced vibration response data of the tower under each fault condition by finite element method. Then the vibration signal visualization and Data Transfer (DT) are used to add tower fault data samples to solve the problem of insufficient actual data quantity. Subsequently, the dynamic response test is carried out under different tower fault states, and the tower fault monitoring is carried out by the DL method. Finally, the proposed method is compared with the traditional online monitoring method, and it is found that this method can significantly improve the rate of convergence and recognition accuracy in the recognition process. The results show that the method can effectively identify the tower foot displacement state, which can greatly reduce the accidents that occurred due to the tower foot displacement.

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Field measurements of typhoon effects on a transmission tower and its modal parameter identification

Cited by 16 publications

References 33 publications

Theoretical derivation and experimental investigation of dynamic displacement reconstruction based on data fusion for beam structures

Theoretical derivation and experimental investigation of dynamic displacement reconstruction based on data fusion for beam structures

Operational modal identification of structures based on improved empirical wavelet transform

A Monitoring Method for Transmission Tower Foots Displacement Based on Wind-Induced Vibration Response

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