Research of Electronic Equipment Fault Diagnosis Algorithm Based on RBF Neural Network

Lei Yuan, Heming Zhao
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引用次数: 1

Abstract

This paper proposes an algorithm of failure diagnosis for electronic device. This algorithm can train existed failure diagnosis parameter sample sets, analysis internal relationship of diagnosis parameters and obtain the final result for device diagnosis, which achieves diagnosis adaptation about further sample parameter of device failure diagnosis. The advantage of algorithm is to optimize training process and control result of empirical function due to considering the prediction accuracy and training time of RBF in the constructing process.
基于RBF神经网络的电子设备故障诊断算法研究
提出了一种电子设备故障诊断算法。该算法可以训练已有的故障诊断参数样本集,分析诊断参数之间的内在关系,得到设备诊断的最终结果,从而实现对设备故障诊断的进一步样本参数的诊断自适应。该算法的优点是在构造过程中考虑了RBF的预测精度和训练时间,优化了经验函数的训练过程和控制结果。
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