Analysis and Warning Prediction of Tunnel Deformation Based on Multifractal Theory

Author:

Yang Chengtao1ORCID,Huang Rendong1,Liu Dunwen1ORCID,Qiu Weichao2,Zhang Ruiping2,Tang Yu13ORCID

Affiliation:

1. School of Resources and Safety Engineering, Central South University, Changsha 410083, China

2. Road & Bridge North China Engineering Co., Ltd., Beijing 101100, China

3. College of Water Resources and Civil Engineering, Hunan Agricultural University, Changsha 410128, China

Abstract

To better analyze the fluctuation characteristics and development law of tunnel deformation data, multifractal theory is applied to tunnel deformation analysis. That is, the multifractal detrended fluctuation analysis (MF-DFA) model is first utilized to carry out the multifractal characterization of tunnel deformation data. Further, Mann–Kendall (M–K) analysis is utilized to construct the dual criterion (∆α indicator criterion and ∆f(α) indicator criterion) for the tunnel deformation early warning study. In addition, the particle swarm optimization long-short-term memory (PSO-LSTM) prediction model is used for predicting tunnel settlement. The results show that, in reference to the tunnel warning level criteria and based on the Z-value results of the indicator criterion, the warning level of all four sections is class II. At the same time, through the analysis of tunnel settlement predictions, the PSO-LSTM model has a better prediction effect and stability for tunnel settlement. The predicted results show a slow increase in tunnel settlement over the next 5 days. Finally, the tunnel warning level and the predicted results of tunnel settlement are analyzed in a comprehensive manner. The deformation will increase slowly in the future. Therefore, monitoring and measurement should be strengthened, and disaster preparedness plans should be prepared.

Funder

Scientific Research Fund of Hunan Provincial Education Department

Publisher

MDPI AG

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