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CLC number: TV3

On-line Access: 2012-08-30

Received: 2012-05-07

Revision Accepted: 2012-08-13

Crosschecked: 2012-08-17

Cited: 4

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Citations:  Bibtex RefMan EndNote GB/T7714

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Journal of Zhejiang University SCIENCE A 2012 Vol.13 No.9 P.687-699


Information fusion diagnosis and early-warning method for monitoring the long-term service safety of high dams

Author(s):  Xing Liu, Zhong-ru Wu, Yang Yang, Jiang Hu, Bo Xu

Affiliation(s):  State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China; more

Corresponding email(s):   zrwu@hhu.edu.cn

Key Words:  Dam monitoring, Diagnosis, Early-warning, Multi-source information fusion, Information entropy

Xing Liu, Zhong-ru Wu, Yang Yang, Jiang Hu, Bo Xu. Information fusion diagnosis and early-warning method for monitoring the long-term service safety of high dams[J]. Journal of Zhejiang University Science A, 2012, 13(9): 687-699.

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author="Xing Liu, Zhong-ru Wu, Yang Yang, Jiang Hu, Bo Xu",
journal="Journal of Zhejiang University Science A",
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%T Information fusion diagnosis and early-warning method for monitoring the long-term service safety of high dams
%A Xing Liu
%A Zhong-ru Wu
%A Yang Yang
%A Jiang Hu
%A Bo Xu
%J Journal of Zhejiang University SCIENCE A
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1200122

T1 - Information fusion diagnosis and early-warning method for monitoring the long-term service safety of high dams
A1 - Xing Liu
A1 - Zhong-ru Wu
A1 - Yang Yang
A1 - Jiang Hu
A1 - Bo Xu
J0 - Journal of Zhejiang University Science A
VL - 13
IS - 9
SP - 687
EP - 699
%@ 1673-565X
Y1 - 2012
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A1200122

Analyzing the service behavior of high dams and establishing early-warning systems for them have become increasingly important in ensuring their long-term service. Current analysis methods used to obtain safety monitoring data are suited only to single survey point data. Unreliable or even paradoxical results are inevitably obtained when processing large amounts of monitoring data, thereby causing difficulty in acquiring precise conclusions. Therefore, we have developed a new method based on multi-source information fusion for conducting a comprehensive analysis of prototype monitoring data of high dams. In addition, we propose the use of decision information entropy analysis for building a diagnosis and early-warning system for the long-term service of high dams. Data metrics reduction is achieved using information fusion at the data level. A Bayesian information fusion is then conducted at the decision level to obtain a comprehensive diagnosis. early-warning outcomes can be released after sorting analysis results from multi-positions in the dam according to importance. A case study indicates that the new method can effectively handle large amounts of monitoring data from numerous survey points. It can likewise obtain precise real-time results and export comprehensive early-warning outcomes from multi-positions of high dams.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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