The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 12, 2023

Filed:

Jul. 07, 2022
Applicant:

Zhejiang University, Zhejiang, CN;

Inventors:

Zheming Tong, Zhejiang, CN;

Jiage Xin, Zhejiang, CN;

Shuiguang Tong, Zhejiang, CN;

Assignee:

Zhejiang University, Hangzhou, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
F03B 11/00 (2006.01); G06F 18/2137 (2023.01); G06F 18/243 (2023.01);
U.S. Cl.
CPC ...
F03B 11/008 (2013.01); F05B 2260/80 (2013.01); F05B 2270/305 (2013.01); F05B 2270/333 (2013.01); F05B 2270/404 (2013.01); F05B 2270/709 (2013.01); F05B 2270/80 (2013.01); G06F 18/2137 (2023.01); G06F 18/24323 (2023.01);
Abstract

The present invention provides a hydraulic turbine cavitation acoustic signal identification method based on big data machine learning. According to the method, time sequence clustering based on multiple operating conditions under the multi-output condition of the hydraulic turbine set is performed by utilizing an neural network, characteristic quantities of the hydraulic turbine set under a steady condition in a healthy state is screened; a random forest algorithm is introduced to perform feature screening of multiple measuring points under steady-state operation of the hydraulic turbine set, optimal feature measuring points and optimal feature subsets are extracted, finally a health state prediction model is constructed by using gated recurrent units; whether incipient cavitation is present in the equipment is judged. The present invention can effectively identify the occurrence of incipient cavitation in the hydraulic turbine set, reducing unnecessary shutdown of the equipment and prolonging the service life.


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