US 12,467,859 B2
Method for constructing infrared imaging dataset of gas leakage based on computational fluid dynamics
Huiling Tai, Sichuan (CN); Yu Zhang, Sichuan (CN); Yadong Jiang, Sichuan (CN); Wenjie Lai, Sichuan (CN); and Yuanming Wu, Sichuan (CN)
Assigned to University of Electronic Science and Technology of China, Chengdu (CN)
Filed by University of Electronic Science and Technology of China, Sichuan (CN)
Filed on May 21, 2025, as Appl. No. 19/215,245.
Claims priority of application No. 202410639497.5 (CN), filed on May 22, 2024.
Prior Publication US 2025/0297952 A1, Sep. 25, 2025
Int. Cl. G01N 21/35 (2014.01); G01N 21/3504 (2014.01); G06F 30/28 (2020.01); G06F 113/08 (2020.01)
CPC G01N 21/3504 (2013.01) [G06F 30/28 (2020.01); G06F 2113/08 (2020.01)] 6 Claims
OG exemplary drawing
 
1. A method for constructing an infrared imaging dataset of gas leakage based on computational fluid dynamics, comprising steps of:
S1: in a gas leakage field scene, collecting a geometric structure of a pipeline and a leakage aperture, so as to establish a three-dimensional physical model of the gas leakage field scene;
S2: meshing the three-dimensional physical model, and determining an inlet surface, an outlet surface and a wall surface of the three-dimensional physical model;
S3: based on the computational fluid dynamics, simulating with the meshed three-dimensional physical model; setting at least one inlet velocity of the inlet surface to obtain leaking gas mole fractions of each mesh under time steps, and constituting three-dimensional gas concentration data corresponding to each frame;
wherein during simulating, constructing a component transportation equation based on components of a leaking gas and an ambient gas determined from the gas leakage field scene, and selecting a turbulence model based on the geometric structure of the pipeline and a flow rate of the leaking gas;
S4: using optical gas imaging based on a pinhole camera model, imaging the three-dimensional gas concentration data to obtain initial images, and calculating gas concentration path-lengths corresponding to pixel points in each frame of the initial images; and
S5: performing maximum-minimum value normalization on the gas concentration path-lengths corresponding to all the pixel points in the initial images, and generating grayscale images according to normalization results; and constructing the infrared imaging dataset of the gas leakage based on the grayscale images and the gas concentration path-lengths corresponding to the pixel points in the grayscale images.