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Study of a Compton backscattering wall defects detection device using the Monte Carlo method

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In view of the shortcomings of traditional wall defect detection methods, such as small detection range, poor accuracy, non-portable device, and so on, a wall defects detection device based on Compton backscattering technology is designed by Monte Carlo method, which is mainly used to detect the size and location information of defects in concrete walls. It mainly consists of two parts, the source container and the detection system: first, through the simulation and analysis of the parameters such as the receiving angle of thebackscattered particles and the rear collimating material of the detector, the influence of the fluorescent X-ray peak of the detector collimating material on the backscattered particle counts is eliminated and the detected error is reduced; second, the ring array detector design, compared with single array detector and surface array detector, can facilitate real-time detection of defect orientation, expanding the single scan range and improving the detection efficiency. After simulation and comparative analysis, the relevant optimal parameters are obtained: the object is detected using a Cs-137 γ-ray source with an activity of 6 mCi, and a ring detector consisting of four 0.5-inch cube-shaped CsI scintillator detectors is placed at 150° to receive the backscattered photons. The simulation analysis using the Monte Carlo FLUKA program showed that the maximum depth of wall defect detection is 8 cm, the maximum error fl uctuation range of defect depth and thickness is ±1 cm, the overall device weight is <20 kg, and the measurement time is <5 min.
Czasopismo
Rocznik
Strony
57--63
Opis fizyczny
Bibliogr. 22 poz., rys.
Twórcy
autor
  • Chengdu University of Technology Chengdu, Sichuan 610059, China
autor
  • Chengdu University of Technology Chengdu, Sichuan 610059, China
  • Sichuan University of Science & Engineering Zigong, Sichuan 643000, China
autor
  • Xichang University Xichang, Sichuan 615000, China
autor
  • Chengdu University of Technology Chengdu, Sichuan 610059, China
autor
  • Chengdu University of Technology Chengdu, Sichuan 610059, China
autor
  • Chengdu University of Technology Chengdu, Sichuan 610059, China
autor
  • Sichuan University of Science & Engineering Zigong, Sichuan 643000, China
Bibliografia
  • 1. Ge, J. Y., & Hou, J. L. (2021). Research on defects of building exterior wall based on infrared thermal imaging technology. In 27th Annual Academic Conference of Beijing Society of Theoretical and Applied Mechanics, 16 January 2021 (pp. 1122–1124). Beijing, China:Beijing Society of Theoretical and Applied Mechanics. (in Chinese).
  • 2. Jin, H., & Zou, L. L. (2021). Detection of hidden disease of concrete bridge based on infrared thermal imaging. J. Phys.-Conf. Series, 1748(4), 042041. DOI:10.1088/1742-6596/1748/4/042041.
  • 3. Yao, F., Lu, X. Q., & Chen, G. Y. (2021). Experimental and signal processing research on concrete-rock structural defects by impact-echo method. Journal of Railway Science and Engineering, 18(9), 2316–2323.DOI: 10.19713/j.cnki.43-1423/u.T20200974. (in Chinese).
  • 4. Yeh, P. L., Liu, P. L., & Hsu, Y. Y. (2018). Parametric analysis of the impact-echo phase method in the differentiation of reinforcing bar and crack signals. Constr. Build. Mater., 180, 375–381. DOI: 10.1016/j.conbuildmat.2018.05.243.
  • 5. Zheng, H., & Kappatos, V. (2015). Defect detection in concrete pile using impulse response measurements with sine sweep excitations. In International Symposium Non-Destructive Testing in Civil Engineering, 15–17 September 2015 (pp. 1–4). Berlin, Germany: Federal Institute for Materials Research and Testing.
  • 6. Lee, T., & Lee, J. (2020). Setting time and compressive strength prediction model of concrete by nondestructive ultrasonic pulse velocity testing at early age. Constr. Build. Mater., 252, 119027. DOI: 10.1016/j.conbuildmat.2020.119027.
  • 7. Yang, H. L. (2022). Feasibility study on detecting internal damage of concrete after fire by impact echo method. Industrial Technology & Vocational Education, 20(1), 11–16. DOI: 10.16825/j.cnki.cn13-1400/tb.2022.01.003. (in Chinese).
  • 8. Niu, C. (2017). Principle study on detection of void condition behind tunnel lining by hammering method. Masteral dissertation, Beijing Jiaotong University, Beijing, China. (in Chinese).
  • 9. Zhao, Q., Sang, Y., Gao, J. L., Yang, Y. Z., Sui, L. Z., & Zhu, W. Z. (2019). Summary of the research on impact-echo method to evaluate the quality of concrete. China Concrete and Cement Products, 12, 18–23. DOI: 10.19761/j.1000-4637.2019.12.018.06. (in Chinese).
  • 10. Trtnik, G., Kavčič, F., & Turk, G. (2009). Prediction of concrete strength using ultrasonic pulse velocity and artificial neural networks. Ultrasonics, 49(1), 53–60. DOI: 10.1016/j.ultras.2008.05.001.
  • 11. Solís-Carcaño, R., & Moreno, E. I. (2008). Evaluation of concrete made with crushed limestone aggregate based on ultrasonic pulse velocity. Constr. Build. Mater., 22(6), 1225–1231. DOI: 10.1016/j.conbuildmat.2007.01.014.
  • 12. Lin, D. F., Chen, Z. H., Liu, M. M., Jia, Q. L., & Liu, L. H. (2017). Application of Compton backscattering technique in SRM detection. Nondestructive Testing, 39(12), 51–53. DOI: 10.11973/wsjc201712012. (in Chinese).
  • 13. Wang, Z. L., Zhang, D. B., Li, X. M., Jiang, L. X., Chen, X. & Li, Y. S. (2020). Research on Compton back-scatter scanning detection technology for external wall thermal insulation system of existing buildings. Construction Technology, 49(9), 9–11+19.DOI: CNKI:SUN:SGJS.0.2020-09-003. (in Chinese)
  • 14. Margret, M., Menaka, M., Subramanian, V., Baskaran, R., & Venkatraman, B. (2018). Non-destructive inspection of hidden corrosion through Compton Study of a Compton backscattering wall defects detection device using the Monte Carlo method 63 backscattering technique. Radiat. Phys. Chem., 152, 158–164. DOI: 10.1016/j.radphyschem.2018.07.015.
  • 15. Chuong, H. D., Thong, N. D., Nguyen, V. H., Minh, L. H., Truc Linh, N. T., Ho, P. L., Thanh, T. T., & Van Tao, C. (2022). Non-destructive evaluation of thickness of material plates through Compton backscattering technique using Si(Li) detector. Radiat. Phys. Chem., 193, 109978. DOI: 10.1016/j.radphyschem.2022.109978.
  • 16. Jamshidi, V., & Davarnejad, R. (2021). Photon backscatter radiography application for the simulation of corrosion detection inside a pipeline: A novel proposal for 360° corrosion consideration in the pipelines. Appl. Radiat. Isot., 176, 109844. DOI: 10.1016/j.apradiso.2021.109844.
  • 17. Wu, J. Z. (2003). Portable Compton backscatter imager study. Masteral dissertation, Zhejiang University, Zhejiang, China. (in Chinese).
  • 18. Boldo, E. M., & Appoloni, C. R. (2014). Inspection of reinforced concrete samples by Compton backscattering technique. Radiat. Phys. Chem., 95, 392–395. DOI: 10.1016/j.radphyschem.2012.12.013.
  • 19. Sari, M. B., Wirawan, R., Waris, A., Kim, H. J., & Djamal, M. (2019). Simulation of void detection system using gamma-ray Compton scattering technique. J. Eng. Technol. Sci., 51(3), 369–379. DOI: 10.5614/j.eng.technol.sci.2019.51.3.5.
  • 20. Zhang, C., Yang, J., Li, R., Qiao, Y., Zhang, X., & Xu, J. (2020). Fluka simulation of PGNAA system for determining heavy metal pollution in the soil sample. Nukleonika, 65(1), 13–17. DOI: 10.2478/nuka-2020-0002.
  • 21. Ferrari, A., Sala, P. R., Fasso, A., & Ranft, J. (2005). Fluka: A multi-particle transport code. United States: U.S. Department of Energy Office of Scientific and Technical Information.
  • 22. Cao, Y. N. (2010). Compton scattering imagining technique in nondestructive test of aircraft structures research and simulation. Masteral dissertation, Civil Aviation University of China, Tianjin, China. (in Chinese).
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c176eee9-5092-49ca-8167-239734bdf655
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