Paper
7 March 2022 Research on intelligent recognition system of launch vehicle test site based on computer vision
Dan Wang, Xue Yang, Zhihong Chen, Changchun Lv, Guannan Liu, Li Xu
Author Affiliations +
Proceedings Volume 12167, Third International Conference on Electronics and Communication; Network and Computer Technology (ECNCT 2021); 1216726 (2022) https://doi.org/10.1117/12.2628840
Event: 2021 Third International Conference on Electronics and Communication, Network and Computer Technology, 2021, Harbin, China
Abstract
The new generation of launch vehicle has the characteristics of more complex system functions and more complicated interfaces, so it is very important to fully and comprehensively test on the ground. At present, the monitoring parameters of some equipment in the front end of the test site still rely on manual observation for judgment, and the test efficiency and effectiveness as well as the safety of personnel need to be improved. This paper uses computer vision technology for real-time monitoring and intelligent recognition of instruments and meters, using target recognition technology based on Faster R-CNN and image processing technology based on OpenCV+PyTorvh to effectively judge the status and data of the instruments. The identification results can be transmitted to the back-end for storage and interpretation in real time through the existing test network, so that the test problems can be traced and reproduced. According to the test, the system's recognition accuracy rate reaches 100%. Compared with manual monitoring readings, the data record is more complete and the recognition efficiency is higher. The system is able to improve the test efficiency, ensure the test reliability, and provide a solution for unattended rocket test.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dan Wang, Xue Yang, Zhihong Chen, Changchun Lv, Guannan Liu, and Li Xu "Research on intelligent recognition system of launch vehicle test site based on computer vision", Proc. SPIE 12167, Third International Conference on Electronics and Communication; Network and Computer Technology (ECNCT 2021), 1216726 (7 March 2022); https://doi.org/10.1117/12.2628840
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KEYWORDS
Image processing

Intelligence systems

Computer vision technology

Cameras

Computing systems

Image filtering

Machine vision

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