Abstract

A concrete dam is an important water-retaining hydraulic structure that stops or restricts the flow of water or underground streams. It can be regarded as a constantly changing complex system. The deformation of a concrete dam can reflect its operation behaviors most directly among all the effect quantities. However, due to the change of the external environment, the failure of monitoring instruments, and the existence of human errors, the obtained deformation monitoring data usually miss pieces, and sometimes the missing pieces are so critical that the remaining data fail to fully reflect the actual deformation patterns. In this paper, the composition, characteristics, and contamination of the concrete dam deformation monitoring information are analyzed. From the single-value missing data completion method based on the nonlocal average method, a multi-value missing data completion method using BP (back propagation) mapping of spatial adjacent points is proposed to improve the accuracy of analysis and pattern prediction of concrete dam deformation behaviors. A case study is performed to validate the proposed method.

Highlights

  • A multi-value missing data completion method using BP mapping of spatial adjacent points is proposed to improve the accuracy on analysis and pattern prediction of concrete dam deformation behaviors

  • A concrete dam has many factors and links that affect its deformation behaviors. These factors and links are the information sources of the concrete dam deformation monitoring. It can be seen from the composition of concrete dam deformation monitoring information in the previous section that the information sources have the following characteristics

  • From the characteristics of deformation monitoring information, it can be seen that the acquisition of concrete dam deformation information is affected by multiple factors

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Summary

A Completion Method for Missing

School of Logistics Engineering, Wuhan University of Technology, Wuhan 430063, China State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai

Literature Reviews
Monitoring Data Characteristics
Multi-Systematic
Multi-Level
Uncertainty
Monitoring Data Contamination
Traditional Interpolation Completion Methods
Completion Strategy for Multi Missing Values
Nonlinear Regression Analysis
Spatial Adjacent Point Regression
BP Mapping of Spatial Adjacent Points
Case Study
Single-Value Missing
Multi-Value Missing Data Completion
Method lation polation terpolation lation
Conclusions
Full Text
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