A New Prediction Model of Dam Deformation and Successful Application
In most dam deformation monitoring practices, some single-point models do not consider the spatial correlation, and the traditional regression models do not consider the nonlinear relationship between the environmental quantity and the deformation quantity, resulting in poor prediction accuracy. In...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Buildings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-5309/15/5/818 |
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| Summary: | In most dam deformation monitoring practices, some single-point models do not consider the spatial correlation, and the traditional regression models do not consider the nonlinear relationship between the environmental quantity and the deformation quantity, resulting in poor prediction accuracy. In view of the poor accuracy of the monitoring data, which reflect the overall deformation response in the current dam monitoring practices, this paper proposes an innovative solution of ensemble empirical mode decomposition and a wavelet noise reduction method. A high-precision prediction model considering spatial correlation is constructed. By studying the measured deformation data of an arch dam and comparing the performance parameters of various models, the superiority and universality of the proposed method are verified. Dam deformation monitoring data are of great significance to describe the operation behavior of dams. It is significant for us to optimize the health monitoring of dam safety structures and ensure dam safety and realize social harmony in our country. |
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| ISSN: | 2075-5309 |