Detection method for dam deformation of tailing pond based on fault diagnosis algorithm | Zendy

Xiaoli Meng | Zendy

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Detection method for dam deformation of tailing pond based on fault diagnosis algorithm

Author(s) -

Xiaoli Meng

Publication year - 2020

Publication title -

thermal science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.339

H-Index - 43

eISSN - 2334-7163

pISSN - 0354-9836

DOI - 10.2298/tsci190609013m

Subject(s) - tailings dam , tailings , deformation (meteorology) , deformation monitoring , fault (geology) , sequence (biology) , algorithm , feature (linguistics) , geology , geotechnical engineering , computer science , artificial intelligence , seismology , materials science , linguistics , oceanography , philosophy , biology , metallurgy , genetics

The existing methods of dam deformation detection of tailings reservoir have the problems of poor accuracy and slow speed. Therefore, a fault diagnosis algorithm based on tailing dam deformation detection method is proposed. The grey theory is used to accumulate the original feature sequence, and the first cumulative sequence is obtained. Based on this, the grey detection model is constructed, and then the concrete deformation of tailings dam body is accurately detected by precision test. Experimental results show that the method has high accuracy, high speed and practicability.

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