Research of a Fault Prediction Method of the Electronic Equipment Based on ARMA - Elman neural network Model

被引：0
|
作者：
Liu Xiaodong [1 ]
Deng Jinyu [1 ]
Yang Jingli [1 ]
Li Yue [1 ]
机构：
[1] Harbin Inst Technol, Sch Elect Engn & Automat, Harbin, Peoples R China
来源：
2018 EIGHTH INTERNATIONAL CONFERENCE ON INSTRUMENTATION AND MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC 2018) | 2018年
关键词：
Fault Prediction; Elman Neural Network; Electronic Equipment; Combined Model; TIME-SERIES PREDICTION;
D O I：
10.1109/IMCCC.2018.00376
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
To improve the accuracy of the fault prediction of the electronic equipment, a novel fault prediction method based on ARMA-Elman neural network model is presented. The ARMA-Elman neural network model combines the fitting ability of ARMA model to linear time series with the mapping ability of Elman neural network to nonlinear time series. The forecasting model is tested by the actual data from high-voltage power supply of radar transmitter. Simulation result shows that the prediction accuracy of ARMA-Elman neural network model has better prediction accuracy than the single ARMA model and Elman neural network model. So this method is feasible and effective.
引用
收藏
页码：1827 / 1830
页数：4
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