| 000 | 03687nlm0a2200481 4500 | ||
|---|---|---|---|
| 001 | 652361 | ||
| 005 | 20231030041136.0 | ||
| 035 | _a(RuTPU)RU\TPU\network\17645 | ||
| 035 | _aRU\TPU\network\16028 | ||
| 090 | _a652361 | ||
| 100 | _a20161220d2016 k y0engy50 ba | ||
| 101 | 0 | _aeng | |
| 102 | _aFX | ||
| 105 | _ay z 101zy | ||
| 135 | _adrcn ---uucaa | ||
| 181 | 0 | _ai | |
| 182 | 0 | _ab | |
| 200 | 1 |
_aComputer system for electric drives fault diagnosis of mining shovels _fV. G. Kashirskikh, A. N. Gargaev, V. M. Zavyalov, I. Y. Semykina |
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| 203 |
_aText _celectronic |
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| 300 | _aTitle screen | ||
| 320 | _a[References: 33 tit.] | ||
| 330 | _aIt is proposed to conduct fault diagnostic test on electric drives of mining shovels based on the results of monitoring the current values of electromagnetic and mechanical parameters and variables of electric drives obtained in the course of their operation using the modern computer technology. The structure of the developed system of functional diagnostics, allowing to monitor the status of the drive and identify emerging fault is shown in the paper. To determine in real time the current parameters and variables of DC motor which can't be measured during their operation, the dynamic identification was used based on the measured current and voltage of the motor windings, and mathematical estimation methods. Parameters of the mechanical subsystem of electric drive are identified by a mobile measuring system. The authors also give the structure and characteristics of the one-step neural network predictor of current, used to predict the current values in the armature and field windings of motor. The analysis of the technical state of the electric drive by a set of attributes is performed in a special analyzer, built on the basis of pre-trained artificial neural network. The results of these studies support the possibility of creating a diagnostic system for the main electric drives of mining shovels using the estimation methods and apparatus of artificial neural networks. | ||
| 333 | _aРежим доступа: по договору с организацией-держателем ресурса | ||
| 463 |
_tCoal in the 21st Century: Mining, Processing and Safety _oThe 8th Russian-Chinese Symposium, Kemerovo, Russia, 10-12 oct., 2016 г. _fKuzSTU ; ed. A. V. Zykov _v[P. 274-279] _o[proceedings] _d2016 |
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| 610 | 1 | _aтруды учёных ТПУ | |
| 610 | 1 | _aэлектронный ресурс | |
| 610 | 1 | _aelectric drive | |
| 610 | 1 | _adiagnosis | |
| 610 | 1 | _aestimation | |
| 610 | 1 | _aэлектроприводы | |
| 610 | 1 | _aдвигатели постоянного тока | |
| 610 | 1 | _aдиагностика | |
| 610 | 1 | _aидентификация | |
| 610 | 1 | _aоценка | |
| 610 | 1 | _aискусственные нейронные сети | |
| 701 | 1 |
_aKashirskikh _bV. G. _gVeniamin Georgievich |
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| 701 | 1 |
_aGargaev _bA. N. _gAndrey Nikolaevich |
|
| 701 | 1 |
_aZavyalov _bV. M. _cspecialist in the field of electrical engineering _cProfessor of Tomsk Polytechnic University, Doctor of technical sciences _f1974- _gValery Mikhailovich _2stltpush _3(RuTPU)RU\TPU\pers\35746 |
|
| 701 | 1 |
_aSemykina _bI. Y. _gIrina Yurjevna |
|
| 712 | 0 | 2 |
_aНациональный исследовательский Томский политехнический университет (ТПУ) _bЭнергетический институт (ЭНИН) _bКафедра электропривода и электрооборудования (ЭПЭО) _h178 _2stltpush _3(RuTPU)RU\TPU\col\18674 |
| 801 | 2 |
_aRU _b63413507 _c20210212 _gRCR |
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| 856 | 4 | _uhttp://elibrary.ru/item.asp?id=26773114 | |
| 942 | _cCF | ||