Image Analysis Based Acoustics Approach for Tank Floor Condition Evaluation
Source abstract
Abstract
An experimental program was conducted to develop a methodology to evaluate the floor condition of the aboveground storage tanks (ASTs). The proposed methodology applies image analysis to the data captured during acoustic emission (AE) monitoring conducted to assess corrosion activity on the AST floor. AE characteristics and source localization were dynamically monitored during normal AST operation. Based on geometric features of the corrosion-related AE activity map on the AST floor, a box count method was used to determine fractal dimension. The remaining thickness of the AST floor is determined relative to its thickness at fabrication as a function of AE activity intensity, which in-turn is used to estimate the total floor material loss due to corrosion. The results showed that fractal dimension values of the corroded AST floor fit well to corresponding values of material loss and therefore each can be used in conjunction with AE parameters to generate a corrosion risk index. The study provides a new approach for AE data analysis to establishing a cost-effective maintenance strategy for AST owners based on risk probability to conduct operation shut down and repairs on time before hazardous situations.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Infrastructure Maintenance and Monitoring · Non-Destructive Testing Techniques · Water Systems and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (33)
Show source-provided references
1. Shinichi, M. and Yoshihisa, Y., Quantitative risk assessment of LNG aboveground tanks based on past operating records of LNG regasification terminals and life cycle assessment, in Semantic Scholar, 2003.
2. Roberge, P.R., Handbook of Corrosion Engineering, New York: McGraw-Hill, 1999, ch. 4, p. 268.
3. Box, G.E., Hunter, J.S., and Hunter, W.G., Statistics for Experiments: Design, Innovation, and Discovery, New York: Wiley, 2005.
4. Mason, R.L., Gunst, R.F., and Hess, J.L., Statistical Design and Analysis of Experiments with Applications to Engineering and Science, New York: Wiley, 2003.10.1002/0471458503 ↗
5. Tscheliesnig, P., Lackner, G., and Jagenbrein, A., Corrosion detection by means of acoustic emission monitoring, 19th World Conf. Nondestr. Test. (Munich, 2016).
6. Tscheliesnig, P., Lackner, G., Gori, M., Vallen, H., and Herrmann, B., Inspection of flat-bottomed storage tanks by acoustical methods; classification of corrosion related signals, Acoust. Emission, 2000, vol. 18, pp. 167–173.
7. Yuyama, S., Yamada, M., Sekine, K., and Kitsukawa, S., Recommended practice for acoustic emission testing for corrosion in the bottom plate of aboveground tanks, Mater. Eval., 2007, pp. 888–892.
8. Enikeev, M., Gubaydullin, I., and Maleeva, M., Analysis of corrosion process development on metals by means of computer vision, Engineering, 2017, vol. 21, no. 4, pp. 184–192.
9. Feliciano, F.F., Leta, F.R., and Mainier, F.B., Texture digital analysis for corrosion monitoring, Corros. Sci., 2015, vol. 93, pp. 138–147.10.1016/j.corsci.2015.01.017 ↗
10. Silva, N.R., Weeën, P.V., Baets, B.D., and Bruno, O.M., Improved texture image classification through the use of a corrosion-inspired cellular automaton, Neurocomputing, 2015, vol. 149, pp. 1560–1572.10.1016/j.neucom.2014.08.036 ↗
11. Mandelbrot, B.B., Fractal Geometry of Nature, New York: Henry Holt and Co., 1983.10.1119/1.13295 ↗
12. Enikeev, M.R., Maleeva, M.A., and Gubaydulin, I.M., Research of the mechanism of development of corrosion defeats with use of elements computer vision, Middle Volga Math. Soc., vol. 15, no. 3, pp. 70–75.
13. Itzhak, D., Dinstein, I., and Zilberberg, T., Pitting corrosion evaluation by computer image processing, Corros. Sci., 1981, vol. 21, no. 1, pp. 17–22.10.1016/0010-938X(81)90059-7 ↗
14. Quin, M.J., Bailey, M.G., Ikeda, B.M., and Shoesmith, D.W., Image Analysis Techniques for Investigating Localized Corrosion Processes, Chalk River: Atom.Energy Can., 1993, pp. 1–52.
15. Feigenbaum, M.J., Quantitative universality for a class of nonlinear transformations, Stat. Phys., 1978, vol. 19, pp. 25–33.10.1007/BF01020332 ↗
16. Caldarelli, G., Castellano, C., and Vespignani, A., Fractal and topological properties of directed fractures, Phys. Rev., 1994, vol. 49, no. 4, pp. 2673–2679.
17. Schroeder, M., Physics. Fractals, Chaos, Power Laws: Minutes from an Infinite Paradise, W.H. Freeman, 1992.
18. Barabási, A.L. and Stanley, H.E., Fractal Concepts in Surface Growth, New York: Cambridge Univ. Press, 1995.10.1017/CBO9780511599798 ↗
19. Angel, F.C., Fractal effect of corrosion on 1 mechanical behavior of unprotected structural steel, Develop. Corros. Prot., IntechOpen, 2014.
20. Benoit, Fractal Analysis Software, 2012. http://www.trusoft.international.com.
21. ASTM E2374, Standard guide for acoustic emission system performance verification, 2016.
22. ASTM E976, Standard guide for determining the reproducibility of acoustic emission sensor response, 2015.
23. Li, Z.W., Yuyama, S., Yamada, M., Sekine, K., Kitsukawa, S., Maruyama, H., and Konno, S., Investigation on AE signal/noise processing in corrosion damage evaluation of tank bottom, Acoust. Emission, 2005, vol. 23, pp. 233–242.
24. Bayray, M., Acoustic emission due to cyclic pressurization of vessels with partially penetrated longitudinal seams, Acoust. Emission, 2000, vol. 18, pp. 131–137.
25. Han, Z., Luo, H., and Wang, H., Effects of strain rate and notch on acoustic emission during the tensile deformation of a discontinuous yielding material, Mater. Sci. Eng., 2011, vol. 528, no. 13, pp. 4372–4380.10.1016/j.msea.2011.02.042 ↗
26. Zohora, F., Evaluation of material crack using acoustic emission technique, M. Sci. Thesis, Queensland Univ. Technol., 2016.
27. ASME Boiler & Pressure Vessel Code, Sec.V: Nondestructive examination, 2010, pp. 246, 251.
28. Souza, P.V.S., Alves, R.L., and Balthazar, W.F., A simple and didactic method to calculate the fractal dimension—An interdisciplinary tool, 2018. . arXiv:1804.01038v1 [physics.ed-ph].
29. Liu, Z., Zhang, N., and Yan, G., Pitting corrosion morphology characteristics of 7B04 aluminum alloys in airport environment based on fractal theory, 3rd Int. Conf. Autom. Mech. Control Comput. Eng., 2018, vol. 166, pp. 614–618.10.2991/amcce-18.2018.105 ↗
30. Saether, E. and Ta’asan, S., Hierarchical Approach to Fracture Mechanics, NASA/TM-2004-213499, 2004.
31. Prateepasen, A., Pitting Corrosion Monitoring Using Acoustic Emission, ch. 3 of Pitting Corrosion, IntechOpen, 2012, pp. 43–60. https://doi.org/10.5772/3312710.5772/33127 ↗
32. Lackner, G. and Tscheliesnig, P., Field testing of flat bottomed storage tanks with acoustic emission – A review on the gained experience, Acoust. Emission, 2004, vol. 22, pp. 201–207.
33. Yuyama, S., Yamada, M., Sekine, K., and Kitsukawa, S., Recommended practice for acoustic emission testing for corrosion in the bottom plate of aboveground tanks, Mater. Eval., 2007, pp. 888–892.