Application of advanced statistical methods for extracting long-term trends in static monitoring data from an arch dam

被引:63
|
作者
Loh, Chin-Hsiung [1 ]
Chen, Chia-Hui [1 ]
Hsu, Ting-Yu [1 ]
机构
[1] Natl Taiwan Univ, Dept Civil Engn, Taipei 10617, Taiwan
来源
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL | 2011年 / 10卷 / 06期
关键词
singular spectral analysis; autoregressive model; auto-associate neural network; nonlinear principal component analysis; statistical analysis; VARYING ENVIRONMENTAL-CONDITIONS; PRINCIPAL COMPONENT ANALYSIS; SINGULAR SPECTRUM ANALYSIS; NEURAL NETWORKS; DIAGNOSIS; BRIDGE;
D O I
10.1177/1475921710395807
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The objective of this article is to develop methods for extracting trends from long-term structural health monitoring data and try to set an early warning threshold level based on the results of analyses. The long-term monitoring data in this study is the continuous monitoring of the dam static deformation. Two different approaches were applied to extract features of the long-term structural health monitoring data of the static deformation of the Fei-Tsui Arch Dam (Taiwan). The methods include the singular spectrum analysis with auto regressive model (SSA-AR) and the nonlinear principal component analysis (NPCA) using auto-associative neural network method (AANN). The singular spectrum analysis is a novel nonparametric technique based on principles of multi-variance statistics. An AR model is optimized for each of the principal components obtained from SSA, and the multi step predicted values are recombined to make the time series. Different from SSA method the NPCA-AANN method is also used to extract the underlying features of static deformation of the dam. By using these two different methods, the residual deformation between the estimated and the recorded data was generated, through statistical analysis, the threshold level of the dam static deformation can be determined. Discussion on the two proposed methods to the static deformation monitoring data of Fei-Tsui Arch Dam (Taiwan) is discussed.
引用
收藏
页码:587 / 601
页数:15
相关论文
共 50 条
  • [1] Long-term dam safety monitoring of Punt dal Gall arch dam in Switzerland
    M. Wieland
    G. F. Kirchen
    Frontiers of Structural and Civil Engineering, 2012, 6 (1) : 76 - 83
  • [2] Long-term dam safety monitoring of Punt dal Gall arch dam in Switzerland
    Wieland, M.
    Kirchen, G. F.
    FRONTIERS OF STRUCTURAL AND CIVIL ENGINEERING, 2012, 6 (01) : 76 - 83
  • [3] Evaluation of long-term stability for high arch dam and its application
    Liu, Y. R.
    He, Z.
    Yang, Q.
    Pan, Y. W.
    Zhang, L.
    Xue, L. J.
    COMPUTER METHODS AND RECENT ADVANCES IN GEOMECHANICS, 2015, : 1943 - 1948
  • [4] Monitoring of long-term static deformation data of Fei-Tsui arch dam using artificial neural network-based approaches
    Kao, Ching-Yun
    Loh, Chin-Hsiung
    STRUCTURAL CONTROL & HEALTH MONITORING, 2013, 20 (03): : 282 - 303
  • [5] Examining methods used in extracting long-term thermospheric density trends
    Huang, Tai-Yin
    Kane, T. J.
    JOURNAL OF ATMOSPHERIC AND SOLAR-TERRESTRIAL PHYSICS, 2013, 97 : 115 - 124
  • [6] Filling data gaps in long-term solar UV monitoring by statistical imputation methods
    Heinzl, Felix
    Lorenz, Sebastian
    Scholz-Kreisel, Peter
    Weiskopf, Daniela
    PHOTOCHEMICAL & PHOTOBIOLOGICAL SCIENCES, 2024, 23 (07) : 1265 - 1278
  • [7] Screening for long-term trends in groundwater nitrate monitoring data
    Stuart, M. E.
    Chilton, P. J.
    Kinniburgh, D. G.
    Cooper, D. M.
    QUARTERLY JOURNAL OF ENGINEERING GEOLOGY AND HYDROGEOLOGY, 2007, 40 : 361 - 376
  • [8] Statistical evaluation of wind properties based on long-term monitoring data
    Xiao-Wei Ye
    Yang Ding
    Hua-Ping Wan
    Journal of Civil Structural Health Monitoring, 2020, 10 : 987 - 1000
  • [9] Statistical evaluation of wind properties based on long-term monitoring data
    Ye, Xiao-Wei
    Ding, Yang
    Wan, Hua-Ping
    JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING, 2020, 10 (05) : 987 - 1000
  • [10] Deformation features of a long-span arch bridge based on long-term monitoring data
    Zhou, G. D.
    Liu, D. K.
    BRIDGE MAINTENANCE, SAFETY, MANAGEMENT, LIFE-CYCLE SUSTAINABILITY AND INNOVATIONS, 2021, : 2279 - 2284