Use of backscattering ultrasound parameters for iron ore varieties recognition
/ 0
- Details
- Category: Content №6 2023
- Last Updated on 23 December 2023
- Published on 30 November -0001
- Hits: 1908
Authors:
V.S.Morkun*, orcid.org/0000-0003-1506-9759, Kryvyi Rih National University, Kryvyi Rih, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
N.V.Morkun, orcid.org/0000-0002-1261-1170, Bayreuth University, Bayreuth, the Federal Republic of Germany, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
V.V.Tron, orcid.org/0000-0002-6149-5794, Kryvyi Rih National University, Kryvyi Rih, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
O.Y.Serdiuk, orcid.org/0000-0003-1244-7689, Kryvyi Rih National University, Kryvyi Rih, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
A.Haponenko, orcid.org/0000-0003-1128-5163, Kryvyi Rih National University, Kryvyi Rih, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2023, (6): 019 - 024
https://doi.org/10.33271/nvngu/2023-6/019
Abstract:
Purpose. Development of the method for recognizing the main mineral-technological varieties of iron ore in the deposits being developed by selecting an analytical model for the spectral characteristics of the received ultrasonic echo signals and quantitative assessment of their parameters.
Methodology. The work uses methods for modeling the processes of propagation of ultrasonic waves in a randomly heterogeneous medium. The process of backscattering of ultrasound in mineral structures formed by inclusions of iron ore of various varieties and associated rock was considered. The estimated parameters of the spectral characteristics of the inversely scattered probing ultrasound pulse were studied.
Findings. A method for recognizing the main mineral and technological varieties of iron ore of the deposit being developed, based on the parameters of the propagation of ultrasonic waves in the studied samples, was proposed. This is achieved by selecting an analytical model for the spectral characteristics of the received echo signals and quantifying their parameters. The amplitude of the echo signal and its spectral properties depends on the size and concentration of the scatterers, i.e., the structural and textural features of the iron ore sample under study. Taking into account these factors, the extracted parameters of the model were used to identify the main mineralogical and technological varieties of iron ore of the studied deposit.
Originality. The proposed method for recognizing mineral-technological varieties of iron ore differs from the known ones in that the amplitude, central frequency, and bandwidth of the amplitude spectrum of the Gaussian parametric model of the measured echo signals are used as evaluation parameters.
Practical value. The proposed scientific and technical solution allows for operational non-destructive control of the main mineralogical and technological types of iron ore in the process of its extraction and processing.
Keywords: ultrasonic analysis, backscattering, iron, mineral varieties
References.
1. Porkuian, O., Morkun, V., Morkun, N., & Serdyuk, O. (2019). Predictive control of the iron ore beneficiation process based on the Hammerstein hybrid model. Acta Mechanica et Automatica, 13(4), 262-270. https://doi.org/10.2478/ama-2019-0036.
2. Kotov, I., Suvorov, O., & Serdiuk, O. (2019). Development of methods for structural and logical model unification of metaknowledge for ontologies evolution managing of intelligent systems. Eastern-European Journal of Enterprise Technologies, 2(4-98), 38-47. https://doi.org/10.15587/1729-4061.2019.155410.
3. Tishchenko, S., Eremenko, G., Kukharenko, O., Pikilnyak, A., & Gaponenko, I. (2015). Definition of the destruction zone boundaries and particle size distribution of blasted rock mass in the explosion of a single explosive charge in an inorganic medium. Metallurgical and Mining Industry, 7(8), 564-567.
4. Golik, V., Morkun, V., Morkun, N., & Gaponenko, I. (2018). Improvement of hole drilling technology for ore drawing intensification. Mining of Mineral Deposits, 12(3), 63-70. https://doi.org/10.15407/mining12.03.063.
5. de Hoop, H., Yoon, H., Kubelick, K., & Emelianov, S. (2018). Photoacoustic speckle tracking for motion estimation and flow analysis. Journal of biomedical optics, 23(9), 1-9. https://doi.org/10.1117/1.JBO.23.9.096001.
6. Liu, W.W., & Li, P.C.J. (2020). Photoacoustic imaging of cells in a three-dimensional microenvironment. Journal of Biomedical Science, 27(1), 3. https://doi.org/10.1186/s12929-019-0594-x.
7. Choe, J.H., Lee, K.S., Choy, I., & Cho, W. (2018). Model of received signal based on system dynamic model of ultrasonic transducers. ultrasonic distance measurement method by using the envelope. Journal of Electrical Engineering and Technology, 13(2), 981-988. https://doi.org/10.5370/JEET.2018.13.2.981.
8. Lina, F., Cristeaa, A., Cacharda, C., & Basseta, O. (2015). Tissue characterization on ultrasound harmonic signals using Nakagami statistics. International Congress on Ultrasonics, Physics Procedia, 70, 1165-1168. https://doi.org/10.1016/j.phpro.2015.08.250.
9. Klimonda, Z., Litniewski, J., Piotr, K., & Nowicki, A. (2015). Spatial and frequency compounding in application to attenuation estimation in Tissue. Archives of Acoustics, 39. https://doi.org/10.2478/aoa-2014-0056.
10. Hoseini, M. R., Wang, X., & Zuo, M. J. (2012). Estimating ultrasonic time of flight using envelope and quasi maximum likelihood method for damage detection and assessment. Measurement, 45(8), 2072-2080. https://doi.org/10.1016/j.measurement.2012.05.008.
11. Bevans, R. (2022). Akaike Information Criterion | When & How to Use It (Example). Retrieved from https://www.scribbr.com/statistics/akaike-information-criterion/.
12. Dobrovolskij, D., & Schladitz, K. (2022). Simulation of Ultrasonic Backscattering in Polycrystalline Microstructures. Acoustics, 4(1), 139-167. https://doi.org/10.3390/acoustics4010010.
13. Jia, N., Su, M., & Cai, X. (2019). Particle size distribution measurement based on ultrasonic attenuation spectra using burst superposed wave. Results in Physics, 13, 102273. https://doi.org/10.1016/j.rinp.2019.102273.
14. Kim, Y., Park, J., & Kim, H. H. (2020). Signal-Processing Framework for Ultrasound Compressed Sensing Data: Envelope Detection and Spectral Analysis. Applied Sciences, 10(19), 6956. https://doi.org/10.3390/app10196956.
15. Tron, V., Haponenko, A., Haponenko, I., & Paranyuk, D. (2020). Borehole logging based on ultrasonic measurements. E3S Web of Conferences, 201, 01025. https://doi.org/10.1051/e3sconf/202020101025.
16. Mercado, K. P., Radhakrishnan, K., Stewart, K., Snider, L., Ryan, D., & Haworth, K. J. (2016). Size-isolation of ultrasound-mediated phase change perfluorocarbon droplets using differential centrifugation. Journal of the Acoustical Society of America, 139(5), EL142–EL148. https://doi.org/10.1121/1.4946831.
17. Gambin, B., Byra, M., Kruglenko, E., Nowicki, A., & Doubrovina, O. (2016). Ultrasonic measurement of temperature rise in breast cyst and in surroundings regions. Archives of Acoustics, 41(4), 791-798.
18. Song, Y., Kube, C. M., Peng, Z., Turner, J. M. W., & Li, X. (2019). Flaw detection with ultrasonic backscatter signal envelopes. The Journal of the Acoustical Society of America, 145(2), EL142–EL148. https://doi.org/10.1121/1.5089826.
19. Daba, J. S., & Dubois, J. P. (2015). Statistical Modeling of Local Area Fading Channels Based on Triply Stochastic Filtered Marked Poisson Point Processes. Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.1110109.
20. Chen, F., He, A., Fu, S., Liu, X., Liu, Y., & Qu, X. (2019). A method to locate spatial distribution of scattering centers from ultrasonic backscatter signal. Journal of the Acoustical Society of America. https://doi.org/10.1121/1.5098947.
21. Tsui, P. (2013). Dependency of Ultrasonic Nakagami Images on The Mechanical Properties of Scattering Medium. Journal of Medical and Biological Engineering, 33(1), 95. https://doi.org/10.5405/jmbe.1101.
22. Kim, Y., Park, J., & Kim, H. H. (2020). Signal-Processing Framework for Ultrasound Compressed Sensing Data: Envelope Detection and Spectral Analysis. Applied Sciences, 10(19), 6956. https://doi.org/10.3390/app10196956.
23. Vogt, M., & Deilmann, M. (2019). 5.3.3 Parametric spectrum analysis of backscattered ultrasound signals for the characterization of particles in suspensions. https://doi.org/10.5162/sensoren2019/5.3.3.
24. Klimonda, Z., Litniewski, J., Karwat, P., & Nowicki, A. (2015). Spatial and Frequency Compounding in Application to Attenuation Estimation in Tissue. Archives of Acoustics, 39(4), 519-527. https://doi.org/10.2478/aoa-2014-0056.
25. Valada, A., & Burgard, W. (2017). Deep spatiotemporal models for robust proprioceptive terrain classification. The International Journal of Robotics Research, 36(13-14), 1521-1539. https://doi.org/10.1177/0278364917727062.
Newer news items:
- Study of leakage current in underground mine power network: a case study in mining in Vietnam - 23/12/2023 01:29
- A methodological approach to assessing the durability of welded structures of screens using SolidWorks Simulation software - 23/12/2023 01:29
- Mathematical models for determining and analyzing thermal regimes in mining industry mechanism structures - 23/12/2023 01:29
- Efficiency and seismic safety of constructing underground structures in complex rock masses - 23/12/2023 01:29
- Analysis and prediction of surface settlements during the digging of underground mining works (Algeria) - 23/12/2023 01:29
- Problems of operating heating boilers of increased environmental efficiency - 23/12/2023 01:29
- Recycling of barite ore tailings into porcelain: microstructure and dielectric properties - 23/12/2023 01:29
- Data analysis solutions to improve blasting efficiency in mining - 23/12/2023 01:29
- Mathematical substantiation and creation of information tools for optimal control of drilling and blasting in open-pit mine - 23/12/2023 01:29
- Managing the process of underground coal gasification - 23/12/2023 01:29
Archive