A simplified deformation forewarning method for longitudinal structural performance of existing shield tunnels based on Fast Fourier Transform

Fu, Yiming; Wang, Fudao; Hong, Chengyu; Wen, Junsheng; Zeng, Deqi

doi:10.1016/j.tust.2022.104813

Cited by 5 publications

(2 citation statements)

References 30 publications

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“…The longitudinal variation of the tunnel can have an impact on the use of the tunnel structure. Fu et al [13] designed a defect early warning method based on the measured settlement data of the tunnel. Using Timoshenko beams to simulate the longitudinal mechanical response of tunnel structures under surrounding rock loads, and using Fourier transform to solve the data, the dichotomy method can better achieve the analysis of deformation index sensitivity.…”

Section: Related Workmentioning

confidence: 99%

Longitudinal deformation of Shield tunnel based on construction monitoring data

Yao¹

2023

J. vibroeng.

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The rapid development of urbanization has changed the traffic and transportation in the central area. The change of the surrounding rock and structural stress state of the project under construction caused by the tunnel construction in the same period has caused great harm to its safe use and casualties. Shield construction technology can achieve safe excavation and lining, with high degree of automation. And it is a relatively common construction method at present. But its adaptability to section size and section environmental conditions is poor. In view of this, from the analysis of construction monitoring data, the study established a longitudinal model considering lateral effects from the perspective of lateral characteristics. It also achieved stress assessment and improvement through lateral deformation calculation, segment ring bolt calculation and formula correction. The experimental results showed that the opening at the circumferential seam of the right line of the test tunnel under this method is 8.9 mm. The radius of curvature is 758 mm, and the safety assessment level of longitudinal deformation is 3. This method can effectively guarantee the safety of shield tunnel construction and has good guiding value for tunnel management and maintenance.

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Section: Related Workmentioning

confidence: 99%

Longitudinal deformation of Shield tunnel based on construction monitoring data

Yao¹

2023

J. vibroeng.

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“…Compared to traditional DFT, where the number of complex multiplications and additions for a length of N is N 2 and N(N-1), respectively, the FFT algorithm significantly improves computational efficiency. In scenarios with large initial data volumes, the FFT offers a considerable advantage, saving significant operations [23]. The mathematical representation of the FFT algorithm is as follows:…”

Section: Introduction To Fftmentioning

confidence: 99%

Intelligence identification of tunnel surrounding rock mass grades using drilling jumbo data

Huang,

Zheng,

Zhou

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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In drill-and-blast tunnels, the recorded data from fully computerized rock drilling jumbos can reflect the tunnel face rock mass conditions. An intelligent method based on real-time drilling data was developed herein to identify tunnel rock mass grades. First, the time series of 14 drilling parameters was processed using a Fourier transform, and the maximum amplitudes of each parameter were computed. Subsequently, the means, medians, and variances of the parameter amplitudes from different blast holes on the same tunnel face were satisfied to form the original feature set. Neighborhood component analysis was used to select the key rock mass condition features. From this feature selection (FS), the top five features were selected as the final feature set. Furthermore, using the selected features, a Gaussian Process Classification (GPC)-based model was established to predict rock mass grades. The proposed method captures both the drilling data information in the time dimension and the inherent connection of different blast hole data, making it advantageous. Using field construction data from Xiwuling Tunnel, the proposed FS-GPC model performance was evaluated. It achieved an accuracy of 90% in predicting rock mass grades. The proposed method can accurately and rapidly predict rock mass grades in drill-and-blast tunnels, optimizing engineering design and construction decisions.

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