Recognition of mineralogical and technological varieties of iron ore on the basis of ultrasound backscatter spectrograms

• Published in: IOP conference series. Earth and environmental science 2023-10, Vol.1254 (1), p.12071
• Main Authors: Morkun, V, Morkun, N, Tron, V, Serdiuk, O, Bobrov, Y, Haponenko, A
• Format: Article
• Language: English
• Subjects: Adaptive systems; Artificial neural networks; Backscattering; Fuzzy logic; Hematite; Iron; Iron compounds; Iron ores; Linear functions; Magnetite; Mathematical models; Mineralogy; Nondestructive testing; Probability theory; Recognition; Siderite; Spectral analysis; Spectrograms; Spectrum analysis; Statistical analysis; Statistical methods; Wave propagation
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/1254/1/012071

The research is aimed to the analysis and modeling of the process of propagation of ultrasonic waves in iron ore samples to assess its mineralogical varieties. The paper analyzes domestic and foreign experience in modeling of ultrasonic waves propagation; methods of mathematical and computer modeling were used, as well as methods of mathematical statistics and probability theory for analysis of the results. Scientific novelty consists in developing and substantiating a method for recognizing the mineralogical and technological varieties of iron ore of a developed deposit based on spectrograms of a backscattered ultrasonic probing signal. Practical valueconsists in developing a methodology for non-contact non-destructive mineralogical analysis of iron ore to improve the efficiency and quality of its further processing and preparation for metallurgical processing. results. As measurable characteristic estimates of textural and structural features of iron ore varieties the results of spectral analysis of the reversed radiant ultrasonic signal were used. To implement the measurement results classification procedure, Adaptive Neuro-Fuzzy Inference System is used. At the vector of parameters of membership functions of terms of input variables and the vector of coefficients of linear functions in the conclusions of the rules was formed based on the characteristics of the processed ore and the spectrograms of the backscattered ultrasonic signal. The average accuracy of recognition of magnetite, chlorite-carbonate-magnetite, hematite-magnetite, magnetite-cummngtonite-chlorite-siderite mineral varieties of iron ore of the studied deposit was 93%.