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Study on an Intelligent Inference Engine in Early-Warning System of Dam Health

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  • Huaizhi Su
  • Zhiping Wen
  • Zhongru Wu

Abstract

With systems engineering and artificial intelligent methods, an early-warning system of dam health (EWSDH) is developed. This system consists of integration control module, intelligent inference engine (IIE), support base cluster, information management and input/output modules. As a central processing unit of EWSDH, IIE is a decision support system for monitoring the operation characteristics and diagnosing unexpected behaviour of dam health. With the time-frequency domain localization properties and self-learning ability of wavelet networks based on wavelet frames, IIE builds some new monitoring models of dam health. The models are used to approximate and forecast the operation characteristics of dam. The methods of attributions reduction in rough sets theory are presented to diagnose adaptively the unexpected behaviour. The proposed system has been used to monitor dam health successfully. Copyright Springer Science+Business Media B.V. 2011

Suggested Citation

  • Huaizhi Su & Zhiping Wen & Zhongru Wu, 2011. "Study on an Intelligent Inference Engine in Early-Warning System of Dam Health," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(6), pages 1545-1563, April.
    • Handle: RePEc:spr:waterr:v:25:y:2011:i:6:p:1545-1563
    DOI: 10.1007/s11269-010-9760-3
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    References listed on IDEAS

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    1. Saman Razavi & Shahab Araghinejad, 2009. "Reservoir Inflow Modeling Using Temporal Neural Networks with Forgetting Factor Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(1), pages 39-55, January.
    2. Salvatore Barbagallo & Simona Consoli & Nello Pappalardo & Salvatore Greco & Santo Zimbone, 2006. "Discovering Reservoir Operating Rules by a Rough Set Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(1), pages 19-36, February.
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    Cited by:

    1. Huaizhi Su & Meng Yang & Yeyuan Kang, 2016. "Comprehensive Evaluation Model of Debris Flow Risk in Hydropower Projects," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1151-1163, February.
    2. Huaizhi Su & Peng Qin & Zhihai Qin, 2013. "A Method for Evaluating Sea Dike Safety," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(15), pages 5157-5170, December.
    3. Huaizhi Su & Xiaoqun Yan & Hongping Liu & Zhiping Wen, 2017. "Integrated Multi-Level Control Value and Variation Trend Early-Warning Approach for Deformation Safety of Arch Dam," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(6), pages 2025-2045, April.

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