The use of deep neural networks to detect alarms in mines

Описание

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Scientific Conference on Applied Physics, Information Technologies and Engineering (APITECH) / 2-nd International Scientific and Practical Conference on Borisov's Readings; Siberian Fed Univ, Polytechn Inst, Krasnoyarsk, RUSSIA; Siberian Fed Univ, Polytechn Inst, Krasnoyarsk, RUSSIA

Год издания: 2019

Идентификатор DOI: 10.1088/1742-6596/1399/3/033104

Аннотация: The article discusses the problem of detecting signals against a background of noise for alarms for miners in underground mine workings in case of emergency. The theoretical aspects of linear and non-linear filtering of alarms are given, the solution to the problem of constructing a non-linear filter based on deep neural network (DПоказать полностьюNN) is described. The simulation results are presented and a comparative analysis of the performance of an individual miner receiver using the methods of linear coherent reception and a DNN filter is made. Neural network training was carried out on model and experimental data obtained at an existing underground mine. © Published under licence by IOP Publishing Ltd.

Ссылки на полный текст

Издание

Журнал: Journal of Physics: Conference Series

Выпуск журнала: Vol. 1399, Is. 3

Номера страниц: 33104

ISSN журнала: 17426588

Издатель: Institute of Physics Publishing

Персоны

  • Kudinov D.S. (Siberian Fed Univ, 79 Svobodny Ave, Krasnoyarsk, Russia)
  • Kokhonkova E.A. (Siberian Fed Univ, 79 Svobodny Ave, Krasnoyarsk, Russia)