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:
Apr. 08, 2025

Filed:

Oct. 18, 2024
Applicant:

Nanjing Hydraulic Research Institute, Nanjing, CN;

Inventors:

Kai Zhang, Nanjing, CN;

Jinbao Sheng, Nanjing, CN;

Yan Xiang, Nanjing, CN;

Chengdong Liu, Nanjing, CN;

Fudong Chi, Nanjing, CN;

Hao Chen, Nanjing, CN;

Zhuo Li, Nanjing, CN;

Bingbing Nie, Nanjing, CN;

Bo Dai, Nanjing, CN;

Yakun Wang, Nanjing, CN;

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G01M 3/04 (2006.01);
U.S. Cl.
CPC ...
G01M 3/04 (2013.01);
Abstract

The present disclosure provides an underwater detection method for contact leakage of a tunnel joint of a dam culvert, including: obtaining an underwater image sequence of the culvert by an underwater robot; preprocessing and registering the underwater image sequence; extracting particle information appearing in the underwater image sequence based on the registered underwater image sequence; constructing a three-dimensional fluid velocity distribution map based on the particle information, and determining leakage situation according to the three-dimensional fluid velocity distribution map; and superimposing the three-dimensional fluid velocity distribution map on a preconfigured three-dimensional culvert model, and rendering and displaying it. The present disclosure can adapt to the complex and changeable underwater environment inside the culvert, it has a high sensitivity to fine leakage in the deep layer, it can realize the accurate measurement and trend prediction of leakage, and it can automate the detection process to reduce manual dependence.


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