基于神经网络的轴承故障预测模型  

Prognostics Model of Bearing Fault Based on Neural Networks

作　　者：韩昕锋[1] 任立坤[2] 

机构地区：[1]海军装备部装备采购中心,北京100071 [2]海军航空工程学院7系,山东烟台264001

出　　处：《海军航空工程学院学报》2015年第3期281-285,共5页Journal of Naval Aeronautical and Astronautical University

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

关 键 词：故障预测 神经网络 状态监测 

分 类 号：TB115.2[理学—数学]