In this paper, leakage characteristics of a sealing structure with damage holes are measured, combining super-resolution algorithms with infrared thermography technology. First, leakage tests of a sealing structure with a single-hole and double-hole are conducted, and some original infrared images are operated to locate the leakage position and calculate the leakage rate. Second, different types of super-resolution algorithms are introduced to generate different high-resolution (HR) infrared images. Finally, the results of the leakage location and leakage rate measured by different HR infrared images of different super-resolution algorithms are compared and discussed, revealing that the machine learning algorithm has the best overall performance. The super-resolution algorithm reduces the measurement error of the leakage rate by 40% and improves the sensitivity of the positioning test by five to ten times. The result indicates that super-resolution infrared thermography is of significant help in ensuring the accuracy of the multiple-hole leakage test.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.