Affiliation:
1. The National Key Laboratory of Water Disaster Prevention Hohai University Nanjing China
2. College of Water Conservancy and Hydropower Engineering Hohai University Nanjing China
3. Department of Computer Engineering Nanjing Institute of Technology Nanjing China
4. Cooperative Innovation Center for Water Safety and Hydro Science Hohai University Nanjing China
Abstract
AbstractThe pivotal role of dam infrastructure necessitates continuous health monitoring, which results in extensive sets of data. Most monitoring data‐based models in dam engineering concentrate on predicting dam behavior. However, little attention has been systematically paid to the processing of extensive monitoring data, modeling of comprehensive dam behavior, and assessment of overall dam operation status. Here, we propose a novel monitoring model comprising three main aspects: a multidimensional data mining method, a multipoint response prediction method, and a multilayer data fusion‐based assessment method. Utilizing monitoring data from a mega concrete arch dam, we evaluate and discuss the effects of data mining, modeling accuracy for dam behavior, robustness against data pollution, and sensitivity to anomalies. Comparisons with classical benchmarks demonstrate the performance of the proposed model for the dam.
Funder
National Natural Science Foundation of China
National Key Research and Development Program of China
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