Telescope performance real-time monitoring based on machine learning
| العنوان: | Telescope performance real-time monitoring based on machine learning |
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| المؤلفون: | Xiu S. Pan, Zi H. Cao, Ying Fu, Qing Y. Zhang, Xiang Q. Cui, Yong Zhang, Ye P. Li, Tian Z. Hu |
| المصدر: | Monthly Notices of the Royal Astronomical Society. 500:388-396 |
| بيانات النشر: | Oxford University Press (OUP), 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Physics, Real-time computing, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Astrophysics::Instrumentation and Methods for Astrophysics, Astronomy and Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, 02 engineering and technology, 01 natural sciences, law.invention, Methods statistical, Telescope, Space and Planetary Science, law, 0103 physical sciences, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, 010303 astronomy & astrophysics, Astrophysics::Galaxy Astrophysics |
| الوصف: | In astronomy, the demand for high-resolution imaging and high-efficiency observation requires telescopes that are maintained at peak performance. To improve telescope performance, it is useful to conduct real-time monitoring of the telescope status and detailed recordings of the operational data of the telescope. In this paper, we provide a method based on machine learning to monitor the telescope performance in real-time. First, we use picture features and the random forest algorithm to select normal pictures captured by the acquisition camera or science camera. Next, we cut out the source image of the picture and use convolutional neural networks to recognize star shapes. Finally, we monitor the telescope performance based on the relationship between the source image shape and telescope performance. Through this method, we achieve high-performance real-time monitoring with the Large Sky Area Multi-Object Fibre Spectroscopic Telescope, including guiding system performance, focal surface defocus, submirror performance, and active optics system performance. The ultimate performance detection accuracy can reach up to 96.7 per cent. |
| تدمد: | 1365-2966 0035-8711 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_________::81f37dbb52b8367e0fc509e26cbb74f8Test https://doi.org/10.1093/mnras/staa3087Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi...........81f37dbb52b8367e0fc509e26cbb74f8 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 13652966 00358711 |
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