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A kernel principal component analysis-based approach for determining the spatial warning domain of dam safety

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Abstract

It is important to determine the warning value of structural behavior for evaluating the service safety, identifying the potential risk and preventing the failure of dam engineering. However, more attention was paid to determining the security warning value of a single observation point on deformation, seepage or stress. And the correlation between the adjacent points or among all points in one dam section is usually lack of consideration. In this paper, the monitoring data of multi-points are taken to determine the spatial warning domain of dam safety. The warning mode of abnormal structural behavior is changed from the single point into the linked multi-points. First, the kernel principal component analysis method is adopted to identify the inherent characteristics among observation points in a dam section. Second, considering the correlation among observation points, the implementation process is proposed to determine the spatial warning domain of dam safety. Finally, an actual concrete gravity dam is taken as an example. The proposed approach is used to determine the spatial warning domains of deformation and seepage. The results, which are obtained by the proposed approach, the traditional method and the qualitative analysis for monitoring data, are compared. It is indicated that the proposed multi-points correlation-based approach is feasible and superior to determine the spatial warning domain of dam safety.

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Acknowledgements

This research has been partially supported by National Natural Science Foundation of China (SN: 51979093, 51739003, 51579083), the National Key Research and Development Program of China (SN: 2018YFC0407101, 2016YFC0401601, 2017YFC0804607), Key R&D Program of Guangxi (SN: AB17195074), Open Foundation of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering (SN: 20195025912, 20165042112).

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Authors and Affiliations

  1. State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China

    Huaizhi Su & Jie Ren

  2. College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, China

    Huaizhi Su

  3. Department of Computer Engineering, Nanjing Institute of Technology, Nanjing, China

    Zhiping Wen

  4. Geotechnical Engineering Department, Nanjing Hydraulic Research Institute, Nanjing, China

    Jie Ren

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  1. Huaizhi Su
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  2. Zhiping Wen
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Correspondence to Huaizhi Su.

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Su, H., Wen, Z. & Ren, J. A kernel principal component analysis-based approach for determining the spatial warning domain of dam safety. Soft Comput 24, 14921–14931 (2020). https://doi.org/10.1007/s00500-020-04845-4

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