Selection of data on drilling-and-blasting in creation of databases of machine learning algorithms

The article offers a structured analysis of methods for processing and verification of data obtained during drilling-and-blasting, with the description of features of collecting pure data to create a mother database to be used in machine learning algorithms. The main objective of the study is to create a machine learning algorithm which, based on the pure inputs concerned with specific conditions, can correlate, select and process data obtained from detectors of drilling parameters, for the further calculation of different characteristics of rocks, prediction of optimal drilling-and-blasting parameters and blasting results. In this article, the measured drilling parameters are analyzed with a view to define response, if any, to change of the type or kind of rocks, as well as to intersection of zones of structural damage and discontinuity in rock mass. The comparison of geological information of slope scanning after perimeter blasting and video image endoscopy data from blastholes with the drilling energy consumption data is presented in the article. Based on the results, the article identifies some trends of the future studies aimed to create learning algorithms of particle size distribution in broken rock disintegration with regard to factors connected both with drilling-and-blasting and rock mass condition.

Keywords: mineral mining, drilling, rock property, monitoring, MWD system, data verification, data filtration, drilling energy consumption, block model.
For citation:

Isheyskiy V. A., Martinyskin E. A., Vasilyev A. S., Smirnov S. A. Selection of data on drilling-and-blasting in creation of databases of machine learning algorithms. MIAB. Mining Inf. Anal. Bull. 2022;(4):116-133. [In Russ]. DOI: 10.25018/0236_1493_2022_4_0_116.


The team of the authors is grateful to the Council for Grants of the President of the Russian Federation for young Russian scientist and leading scientific schools for the research project support in the framework of the governmental sponsorship of young Russian candidates of sciences, Grant MK-3770.2021.4.

Issue number: 4
Year: 2022
Page number: 116-133
ISBN: 0236-1493
UDK: 622.233
DOI: 10.25018/0236_1493_2022_4_0_116
Article receipt date: 11.01.2022
Date of review receipt: 17.01.2022
Date of the editorial board′s decision on the article′s publishing: 10.03.2022
About authors:

V.A. Isheyskiy1, Cand. Sci. (Eng.), Assistant Professor, e-mail:,ORCID ID: 0000-0003-1007-6562,
E.A. Martinyskin, Technical Director, OOO «VZRYV GRUPP», 652707, Kiselevsk, Russia, e-mail:,
A.S. Vasilyev1, Graduate Student, e-mail:,
S.A. Smirnov, Technical Director, ООО «Resurs», 654007, Novokuznetsk, Russia, e-mail:,
1 Saint-Petersburg Mining University, 199106, Saint-Petersburg, Russia.


For contacts:

V.A. Isheyskiy, e-mail:


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