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A Novel Imputation Model for Missing Concrete Dam Monitoring Data

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  • Xinran Cui

    (College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
    National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China
    State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China)

  • Hao Gu

    (College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
    State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China)

  • Chongshi Gu

    (College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
    National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China
    State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China)

  • Wenhan Cao

    (College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
    National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China
    State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China)

  • Jiayi Wang

    (College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China
    National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China
    State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China)

Abstract

To ensure the safety of concrete dams, a large number of monitoring instruments are embedded in the bodies and foundations of the dams. However, monitoring data are often missing due to failure of monitoring equipment, human error and other factors that cause difficulties in diagnosis of dam safety and failure to precisely predict their deformation. In this paper, a new method for imputing missing deformation data is proposed. First, since the traditional deformation increment speed distance index of the deformation similarity index does not take into account the fact that there is little change in deformations occurring in two consecutive days, the denominator of the index tends to be equal to zero. In this paper, an improved index for solving this problem is proposed. A combined weighting method for calculating the deformation similarity comprehensive index and the k -means clustering method is then proposed and used to classify deformation monitoring points. Subsequently, a panel data model that imputes different types of missing data is established. The method proposed in this paper can impute missing concrete dam deformation data more accurately; therefore, it can effectively solve the missing deformation monitoring data problem.

Suggested Citation

  • Xinran Cui & Hao Gu & Chongshi Gu & Wenhan Cao & Jiayi Wang, 2023. "A Novel Imputation Model for Missing Concrete Dam Monitoring Data," Mathematics, MDPI, vol. 11(9), pages 1-24, May.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:9:p:2178-:d:1140092
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    References listed on IDEAS

    as
    1. Wei Wei & Chongshi Gu & Xiao Fu, 2021. "Processing Method of Missing Data in Dam Safety Monitoring," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-12, July.
    2. Rebecca R. Andridge & Roderick J. A. Little, 2010. "A Review of Hot Deck Imputation for Survey Non‐response," International Statistical Review, International Statistical Institute, vol. 78(1), pages 40-64, April.
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