Hydraulic metal structure health diagnosis based on data mining technology

Water Science and Engineering

Guang-ming Yang¹  Xiao Feng²  Kun Yang² 

[1] College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, PR China;Dayu College, Hohai University, Nanjing 210098, PR China;

关键词: Hydraulic metal structure;    Health diagnosis;    Data mining technology;    Clustering model;    Association rule;   

DOI  :  10.1016/j.wse.2015.04.010

来源: DOAJ

【 摘 要 】

In conjunction with association rules for data mining, the connections between testing indices and strong and weak association rules were determined, and new derivative rules were obtained by further reasoning. Association rules were used to analyze correlation and check consistency between indices. This study shows that the judgment obtained by weak association rules or non-association rules is more accurate and more credible than that obtained by strong association rules. When the testing grades of two indices in the weak association rules are inconsistent, the testing grades of indices are more likely to be erroneous, and the mistakes are often caused by human factors. Clustering data mining technology was used to analyze the reliability of a diagnosis, or to perform health diagnosis directly. Analysis showed that the clustering results are related to the indices selected, and that if the indices selected are more significant, the characteristics of clustering results are also more significant, and the analysis or diagnosis is more credible. The indices and diagnosis analysis function produced by this study provide a necessary theoretical foundation and new ideas for the development of hydraulic metal structure health diagnosis technology.

【 授权许可】

Unknown