Method of improving safe operation of mining machinery electrics by forecasting insulation resistance

Authors: Бабокин Г. И., Шпрехер Д. М., Колесников Е. Б.

The method is proposed to increase safe and efficient operation of mining machinery electrics. The use of this method in control and forecasting of electrics insulation resistance allows sufficiently accurate estimate of critical insulation resistance for a preset time period and, thus, provides failure prediction. It is proposed to solve this problem using digital technologies based on the artificial intelligence, in particular, neural networks. The implementation algorithm is based on the direct distribution neural network. The results of the insulation resistance forecasting are presented. The analysis of the obtained diagrams suggests acceptability of the results: the forecasting accuracy makes 95 %. The introduction of the proposed insulation resistance forecasting and control method will enhance electrical safety of mining equipment handling due to elimination of electric traumas of personnel in case of the current leakage protection malfunction. At the same time, this method can enhance efficiency of mining equipment through the reduced damage because of sudden outages of normally running mining machinery.

Keywords: Mining machines, electrical safety, insulation resistance, reliability, failure, protection equipment, prediction, neural network.
For citation:

Babokin G. I., Shprekher D. M., Kolesnikov E. B. Method of improving safe operation of mining machinery electrics by forecasting insulation resistance. MIAB. Mining Inf. Anal. Bull. 2020;(2):34-45. [In Russ]. DOI: 10.25018/0236-1493-2020-2-0-34-45.

Acknowledgements:
Issue number: 2
Year: 2020
Page number: 34-45
ISBN: 0236-1493
UDK: 621.313: 631.371
DOI: 10.25018/0236-1493-2020-2-0-34-45
Article receipt date: 13.02.2019
Date of review receipt: 08.11.2019
Date of the editorial board′s decision on the article′s publishing: 20.01.2020
About authors:

G.I. Babokin, Dr. Sci. (Eng.), Professor, e-mail: babokinginov@yandex.ru, Mining Institute, National University of Science and Technology «MISiS», 119049, Moscow, Russia,
D.M. Shprekher, Dr. Sci. (Eng.), Assistant Professor, Tula State University, 300012, Tula, Russia, e-mail: shpreher-d@yandex.ru,
E.B. Kolesnikov, Cand. Sci. (Eng.), Assistant Professor, Novomoskovsk Institute (branch) of D. Mendeleev University of Chemical Technology of Russia, 301650, Novomoskovsk, Russia, e-mail: kolesnikov55@mail.ru.

 

For contacts:

D.M. Shprekher, e-mail: shpreher-d@yandex.ru.

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