基于神经网络的轴承故障预测模型

Prognostics Model of Bearing Fault Based on Neural Networks

摘要:

利用在故障预测领域广泛应用的神经网络模型,对轴承监测数据的特征提取与建模,挖掘出监测数据与剩余寿命间内在关联,从而对轴承剩余寿命做出评估。在轴承全寿命数据的实际实验中,证实了该模型的有效性。

Abstract:

In this paper, neural networks were used to estimate the remaining useful life of the bearings. Through the featureextraction and modeling process, the intrinsic connection between monitoring data and remaining useful life was dig out, soas to evaluate the residual life of bearing. In the experiment, the effectiveness of the model was verified.