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Projekt unikalnego systemu optycznego i wdrożenie systemu rentgenowskiego do badań nieniszczących rakiet na paliwo stałe
Języki publikacji
Abstrakty
One of the most important military applications in missile science is the careful X-ray examination (XRE) of solid rocket fuel samples. So that it becomes clear whether the missile fuel is made efficiently and achieves its goal or not, which is a regular combustion rate from the moment of launch to the end of its flight. The main dependency of this is to provide expenses for the real launch of missiles to ensure the work of the solid fuel that has been manufactured. In this paper, we review a visual diagnostic system with X-rays for solid fuel samples (SFS) before starting the field tests to detect manufacturing defects. An optimal design of the X-ray device was made in terms of transmission and the radiation collection system to focus it on the sample to be tested and to choose the most appropriate X-ray detector for this purpose. The metal casing of the X-ray tube (XRT), the collimator, and the mechanical equipment of the entire system were also designed and implemented, with the assembly of parts and components of the X-ray camera. The system was tested on two real samples. The first is made efficiently and does not have any manufacturing defects, while the other has air bubbles. The proposed system succeeded in giving accurate images for both samples. This made evaluating fuel performance possible without costly field experiments.
Jednym z najważniejszych zastosowań wojskowych w nauce o rakietach jest dokładne badanie rentgenowskie (XRE) próbek stałego paliwa rakietowego. Żeby było jasne, czy paliwo rakietowe jest produkowane wydajnie i osiąga swój cel, czyli równomierne spalanie od chwili wystrzelenia do końca lotu. Główną zależnością jest zapewnienie wydatków na rzeczywiste wystrzelenie rakiet, aby zapewnić pracę wyprodukowanego paliwa stałego. W tym artykule dokonujemy przeglądu wizualnego systemu diagnostyki za pomocą promieni rentgenowskich próbek paliwa stałego (SFS) przed rozpoczęciem testów terenowych w celu wykrycia wad produkcyjnych. Wykonano optymalną konstrukcję urządzenia rentgenowskiego pod względem transmisji oraz układu odbioru promieniowania, aby skupić je na badanej próbce i wybrać najwłaściwszy do tego celu detektor promieniowania rentgenowskiego. Zaprojektowano i wdrożono także metalową obudowę lampy rentgenowskiej (XRT), kolimator oraz wyposażenie mechaniczne całego układu, wraz z montażem części i podzespołów kamery rentgenowskiej. System został przetestowany na dwóch rzeczywistych próbkach. Pierwsza jest wykonana sprawnie i nie posiada wad produkcyjnych, natomiast druga posiada pęcherzyki powietrza. Zaproponowany system pozwolił uzyskać dokładne obrazy obu próbek. Umożliwiło to ocenę wydajności paliwa bez kosztownych eksperymentów w terenie.
Wydawca
Czasopismo
Rocznik
Tom
Strony
1--9
Opis fizyczny
Bibliogr. 30 poz., rys., tab.
Twórcy
autor
- Dept. of Electronics & Communication Faculty of engineering, Aswan University
autor
- Dept. of Electronics & Communication Faculty of engineering, Aswan University
autor
- Dept. of Electronics &Communication, Alexandria Higher Institute
autor
- Faculty of Science, Aswan University
autor
- Dept. of Electronic Science and Technology, Nanjing University of Aeronautics & Astronautics
autor
- Dept. of Electronics & Communication, Air Defense College
Bibliografia
- [1] L. F. Nascimento. Brief history of X-ray tube patents. World Patent Information (2014), 37, 48-53.
- [2] N. N. Azman, S. Siddiqui, R. Hart, and I.-M. Low. Effect of particle size, filler loadings and x-ray tube voltage on the transmitted x-ray transmission in tungsten oxide—epoxy composites. Applied radiation and isotopes (2013), 71, 62-67.
- [3] M. Dehairs, H. Bosmans, and N. Marshall. A study of the impact of x-ray tube performance on angiography system imaging efficiency. Physics in Medicine & Biology (2020), 65, 225028.
- [4] B. W. Pogue and B. C. Wilson. Optical and x-ray technology synergies enabling diagnostic and therapeutic applications in medicine. Journal of biomedical optics (2018), 23, 121610- 121610.
- [5] H. Wei, Y. Fang, P. Mulligan, W. Chuirazzi, H.-H. Fang, C. Wang, et al. Sensitive X-ray detectors made of methylammonium lead tribromide perovskite single crystals. Nature Photonics (2016), 10, 333-339.
- [6] T. Marshall, J. Evans, and R. Frederick. UAH Solid Propellant Characterization. in 43rd AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit (2007), 5763.
- [7] A. M. Toscana, M. R. Lato, D. Fontanarosa, and M. G. De Giorgi. Optical Diagnostics for Solid Rocket Plumes Characterization: A Review. Energies (2022), 15, 1470.
- [8] A. Yu. Krainov, V. A. Poryazov, and D. A. Krainov. Mathematical modelling on extinction of metallized composite solid propellant under a sudden drop in pressure. Propellants, Explosives, Pyrotechnics (2022), 47, e202100123.
- [9] Z. Wang, H. Xie, S. Xiang, K. Ouyang, L. Bao, R. Shen, et al. Multi-stage combustion characteristics of sodium perchlorate/lithium perchlorate-based electrically controlled solid propellant. Chemical Engineering Journal (2023), 456, 140958.
- [10] L. Jie-Yao, Y. Su-Lan, W. Shixi, T. Gen, Y. Wenming, and Y. Qi-Long. Burning rate modulation for composite propellants by interfacial control of Al@ AP with precise catalysis of CuO. Combustion and Flame (2022), 240, 112029.
- [11] H. Tian, Z. Wang, Z. Guo, R. Yu, G. Cai, and Y. Zhang. Effect of metal and metalloid solid-fuel additives on performance and nozzle ablation in a hydroxy-terminated polybutadiene based hybrid rocket motor. Aerospace Science and Technology (2022), 123, 107493.
- [12] W. Pang, V. Abrukov, D. Anufrieva, and D. Chen. Burning Rate Prediction of Solid Rocket Propellant (SRP) with High-Energy Materials Genome (HEMG). Crystals (2023), 13, 237.
- [13] L. Li, J. Ren, P. Wang, Z. Lü, X. Li, and M. Sun. An adaptive false-color enhancement algorithm for super-8-bit high grayscale X-ray defect image of solid rocket engine shell. Mechanical Systems and Signal Processing (2022), 179, 109398.
- [14] L. Li, J. Ren, P. Wang, H. Gao, M. Sun, B. Sha, et al. A pixel-level weak supervision segmentation method for typical defect images in X-ray inspection of solid rocket motors combustion chamber. Measurement (2023), 112497.
- [15] L. Xue, J. Hei, Y. Wang, Q. Li, Y. Lu, and W. Liu. A high efficiency deep learning method for the x-ray image defect detection of casting parts. Measurement Science and Technology (2022), 33, 095015.
- [16] P. Maken and A. Gupta. 2D-to-3D: A Review for Computational 3D Image Reconstruction from x-ray Images. Archives of Computational Methods in Engineering (2023), 30, 85-114.
- [17] C. Neubüser, T. Corradino, G.-F. Dalla Betta, S. Mattiazzo, L. Pancheri, and A. Collaboration. First characterization results of ARCADIA FD-MAPS after X-ray irradiation. Journal of Instrumentation (2023), 18, C01066.
- [18] P. Skrzypiec and R. Szczygieł. Readout chip with RISC-V microprocessor for hybrid pixel detectors. Journal of Instrumentation (2023), 18, C01030.
- [19] J. Quercia, F. Mele, D. Macera, B. Arcaini, B. Garavelli, and G. Bertuccio. Experimental characterization of a fast X-ray spectroscopic imager module using the ALTAIR P3 ASIC for real-time contaminants detection. Journal of Instrumentation (2023), 18, C01064.
- [20] H. O. Dávila, S. Martinez-Ovalle, and H. Vega-Carrillo. Study of X-ray scattered in a phantom as function of its maximum energy during bimodal PET/CT imaging. Applied Radiation and Isotopes (2019), 148, 1-6.
- [21] B.-B. Zhang, E.-W. Liang, and B. Zhang. A comprehensive analysis of Swift XRT data. I. Apparent spectral evolution of gamma-ray burst X-ray tails. The Astrophysical Journal (2007), 666, 1002.
- [22] D. Gamdha, S. Unnikrishnakurup, K. J. Rose, M. Surekha, P. Purushothaman, B. Ghose, et al. Automated defect recognition on X-ray radiographs of solid propellant using deep learning based on convolutional neural networks. Journal of Nondestructive Evaluation (2021), 40, 1-13.
- [23] L. Li, J. Ren, P. Wang, H. Gao, M. Sun, B. Sha, et al. A pixel-level weak supervision segmentation method for typical defect images in X-ray inspection of solid rocket motors combustion chamber. Measurement (2023), 112497.
- [24] S. M. P. Kalaiselvi, E. Tang, H. Moser, M. Breese, S. P. Turaga, H. Kasi, et al. Wafer scale manufacturing of high precision micro-optical components through X-ray lithography yielding 1800 Gray Levels in a fingertip sized chip. Scientific reports (2022), 12, 1-12.
- [25] M. Hossein, S. M. Reza, and S.-N. Jamshid. Image quality and dose assessment of collimator slit width effect in SLOT-SCAN X-ray imaging system. Applied Radiation and Isotopes (2021), 171, 109642.
- [26] B. Whelan, S. Trovati, J. Wang, R. Fahrig, P. G. Maxim, A. Hanuka, et al. Bayesian optimization to design a novel x-ray shaping device. Medical Physics (2022), 49, 7623-7637.
- [27] S. Stoupin, A. MacPhee, N. Ose, M. MacDonald, L. Masse, D. Rusby, et al. A Monte Carlo technique to model performance of streak camera-based time-resolving x-ray spectrometers. Review of Scientific Instruments (2022), 93, 093510.
- [28] E. Kalemci, O. Turhan, İ. Kuvvetli, S. Schanne, M. Hernanz, P. Orleański, et al. The instrument control unit processing hardware and software of the wide field monitor on eXTP. in Space Telescopes and Instrumentation: Ultraviolet to Gamma Ray (2022), 1592-1604.
- [29] J. Reiffers, S. Albrecht, O. Hälker, A. Lederhuber, B. Mican, and F. J. Veredas. Hardware development of Athena WFI frame processing module. in Space Telescopes and Instrumentation: Ultraviolet to Gamma Ray (2022), 948-958.
- [30] M. Edwards. Designing a Hybrid Digital/Analog Quantum Physics Emulator as Open Hardware. arXiv preprint arXiv (2023), 2302.00821.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e846b7f6-272b-466a-9a9e-e77a1dc4a338
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