Use of neuronets in problems of forecasting the reliability of electric machines with a high degree of mean time between failures

Mykhaylo ZAGIRNYAK; Viacheslav PRUS

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Use of neuronets in problems of forecasting the reliability of electric machines with a high degree of mean time between failures

机译：在预测平均故障间隔时间较长的电机的可靠性问题中使用神经网络

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Przebadano możliwość implementacji sieci neuronowej w modelach niezawodnościowych maszyn elektrycznych z uszkodzeniami konstrukcyjnymi. Postawiono ugruntowane zadania dla sieci neuronowych podczas prognozowania uszkodzeń głównych jednostek konstrukcyjnych. Wyboru struktury sieci neuronowej dokonano w wyniku analizy najbardziej obiecujących modeli na przykładzie oceny uszkodzeń łożyska.%It was investigated the possibility to implement neuronets in reliability models of electric machines with constructive faults. It was grounded the tasks for neuronets during fomcasting the failure of main structural units and electric machines in general. The choice of neuronet structure was done as result of analysis of most promising models on the example of evaluation the bearing unit faults.

机译：研究了在具有结构损伤的电机可靠性模型中实现神经网络的可能性。确定了神经网络的既定任务，同时预测了主要结构单元的损坏。对神经网络结构的选择是通过对轴承损伤评估示例中最有希望的模型进行分析而得出的，它研究了在具有建设性故障的电机可靠性模型中实现神经网络的可能性。总的来说，在浇铸主要结构单元和电机故障期间，这是神经网络的任务基础。神经网络结构的选择是在评估轴承单元故障的实例上对大多数最有前景的模型进行分析的结果。

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来源
《Przeglad Elektrotechniczny》 |2016年第1期|132-135|共4页
作者
Mykhaylo ZAGIRNYAK; Viacheslav PRUS;
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作者单位

Kremenchuk Mykhailo Ostrohradskyi National University, vul. Pershotravneva, 20, 39600, Ukraine;

Kremenchuk Mykhailo Ostrohradskyi National University, vul. Pershotravneva, 20, 39600, Ukraine;

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正文语种 pol
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关键词
neuronet; reliability model; bearing unit;

机译：神经网络可靠性模型;轴承单元;

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Use of neuronets in problems of forecasting the reliability of electric machines with a high degree of mean time between failures

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