Network platform for automation of pit dump truck failure prediction
I.V. Zyryanov1, 2, M.V. Kornyakov2, K.A. Nepomnyashchikh2, A.I. Trufanov2, V.A. Khramovskikh2, A.N. Shevchenko2
1 Polytechnic Institute (branch), M.K. Ammosov North-Eastern Federal University, Mirniy, Russian Federation
2 Irkutsk National Research Technical University, Irkutsk, Russian Federation
Russian Mining Industry №3 / 2024 стр. 56-63
Abstract: The article considers the possibilities of developing an automated system for monitoring and predicting the technical condition of in-pit vehicles at the operation stage based on failure statistics and network analysis of data received from health sensors of the mining machines. This study seeks to reduce emergency downtime in the mining industry by introducing modern information and communication technologies. The applicability of existing methods to analyze digital signals received from the sensors installed on the mining equipment was assessed. A promising approach is considered, using the progress achieved in network engineering and conversion of the time series signals into the integrated networks. A sequence of operations is proposed as an innovation, including collection and analysis of data, development of network prediction models and practical implementation of the results. It is expected that using such a sequence of steps will be able to promptly notify of the need to repair equipment, thereby reducing downtime, which in turn will increase productivity and reduce the operating costs. The main stages of the study are formulated and presented, the implementation of which is aimed at predicting the health of the equipment, identifying the need for unscheduled repairs, which will lead to a decrease in the number of emergency failures or their prevention in real operating conditions of mining enterprises.
Keywords: reliability of mining machinery and equipment, digital signal, network analysis of time series, network markers of equipment operability, failure prediction, mining dump trucks, internal combustion engine
Acknowledgements: The research was partially financed by the Russian Foundation for Basic Research and the Ministry of Education, Culture, Science and Sports of Mongolia under Research Project No.20-57-44002.
For citation: Zyryanov I.V., Kornyakov M.V., Nepomnyashchikh K.A., Trufanov A.I., Khramovskikh V.A., Shevchenko A.N. Network platform for automation of pit dump truck failure prediction. Russian Mining Industry. 2024;(3):56–63. (In Russ.) https://doi.org/10.30686/1609-9192-2024-3-56-63
Article info
Received: 27.03.2024
Revised: 08.05.2024
Accepted: 12.05.2024
Information about the authors
Igor V. Zyryanov – Dr. Sci. (Eng.), Professor, Head of the Mining Department of the Polytechnic Institute (branch), M.K. Ammosov North-Eastern Federal University, Mirniy, Russian Federation; Professor the Department of Mining Machinery and Electromechanical Systems, Institute of Subsoil Use, Irkutsk National Research Technical University, Irkutsk, Russian Federation, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Mikhail V. Kornyakov – Dr. Sci. (Eng.), Associate Professor, Rector, Chairman of the Academic Council, Chairman of the Scientific and Technical Council, President of the bandy team, President of the All-Russian Student Bandy League. Institute of Subsoil Use, Irkutsk National Research Technical University, Irkutsk, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Kirill A. Nepomnyashchikh – Postgraduate Student, Assistant at the Department of Mining Machinery and Electromechanical Systems, Institute of Subsoil Use, Irkutsk National Research Technical University, Irkutsk, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Andrey I. Trufanov – Candi. Sci. (Phys. and Math.), Associate Professor, Institute of Information Technology and Data Analysis, Irkutsk National Research Technical University, Irkutsk, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Vitaly A. Khramovskikh – Cand. Sci. (Eng.), Associate Professor, Associate Professor of the Department of Mining Machines and Electromechanical Systems, Acting Head of the Department of GMiEMS, Institute of Subsoil Use, Irkutsk National Research Technical University, Irkutsk, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Alexey N. Shevchenko – Cand. Sci. (Eng.), Associate Professor, Associate Professor of the Department of Mining Machinery and Electromechanical Systems, Director of the Institute of Subsoil Use, Irkutsk National Research Technical University, Irkutsk, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
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