Affiliation:
1. State Key Laboratory of Laser Interaction with Matter, Northwest Institute of Nuclear Technology, Xi’an, Shaanxi 710024, People’s Republic of China
Abstract
Hydroxyl tagging velocimetry (HTV) technology is crucial in the velocimetry diagnosis of combustion flow fields. However, obtaining accurate HTV information in practical engineering applications is difficult because of complex flow fields and background noise interference. Therefore, for noise suppression, we proposed a generative adversarial network method for targeted network training based on the analysis of HTV image noise characteristics in a complex flow field and the construction of a high-confidence noise description model. The proposed method can effectively suppress noise in HTV experimental data, improve the signal-to-noise ratio of HTV images, and improve the accuracy of HTV measurement.
Funder
National Natural Science Foundation of China
State Key Laboratory of Laser Interaction With Matter
Sichuan Province Science and Technology Support Program
Subject
General Physics and Astronomy
Cited by
1 articles.
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