Abstract. There are many factors affecting dam deformation, and the time series of deformation data is directly modeled without considering the seasonality and periodicity of each influencing factor, the Ensemble Empirical Mode Decomposition (EEMD) and the Seasonal Autoregressive Integrated Moving Average (SARIMA) is proposed for prediction in this paper. Firstly, the time series of deformation data is decomposed by EEMD, which weakens its volatility to some extent, and decomposes various factors affecting dam deformation, so as to obtain a series of Intrinsic Mode Function (IMF) with different frequencies; secondly, according to the seasonal characteristics and periodic characteristics of each IMF, the SARIMA model was established respectively for rolling prediction; thirdly, the final forecast results can be obtained by superimposing the forecast results of each IMF. It is verified by experiments and compared with Gray Model, Kalman Filter Model and SARIMA model that EEMD-SARIMA model has higher prediction accuracy, and it has better fitting degree, which means that it is an effective method for dam deformation prediction.
Tunneling work, including the construction of municipal tunnels and metro lines, may disturb the structural health of aging buildings in densely built urban areas. Deformation monitoring and risk assessments of aging buildings are crucial to mitigate incidents and prevent losses of people’s lives and properties. Time-series InSAR reveals spatio-temporal information about observed targets by extracting persistent scatterers of the structures, which can achieve the wide-range monitoring of buildings and infrastructure. However, solely relying on InSAR-derived general parameters (deformation rates and time series of specific points) cannot objectively assess the safety conditions of buildings. To address this issue, this study proposes an InSAR Nonuniform Settlement Index. First, the point targets of buildings are extracted through time-series InSAR processing. Then, using the points as inputs, the Nonuniform Settlement Index calculates the 3D settlement plane and the inclination angle of the plane corresponding to each building. In this way, the proposed Nonuniform Settlement Index acts as a subsequent analysis method of time-series InSAR to characterize the safety statuses of buildings. In our study, 147 scenes of COSMO-SkyMed images from 2013 to 2022 were used to inverse the nine-year deformation evolution of the tested area. After time-series InSAR processing and index analysis based on the above SAR datasets, cross-validation was implemented with static-level and manual investigation data. The approach was to use one aging, collapsed building affected by tunneling work, as well as the eight adjacent aging buildings. The results showed high consistency with the in situ data, which proves the efficiency of the proposed approach.
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