机译:改进的具有多尺度信息的深度卷积神经网络用于轴承故障诊断
Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China;
Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China;
Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China;
Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China;
Deep learning; Convolutional neural network; Multi-scale cascade; Rolling bearing; Fault diagnosis;
机译:一种改进的深度卷积神经网络,具有用于轴承故障诊断的多尺度信息
机译:深度多尺度卷积转移学习网络:可变工作条件与域下滚动轴承智能故障诊断的新方法
机译:使用1-D深卷积神经网络的智能故障诊断rolling-元件轴承
机译:基于一维多尺度深度卷积神经网络的健康状态分类的滚动轴承智能故障诊断
机译:基于轴承故障诊断的深度信仰网络
机译:具有改进的D-S证据融合的集成深度卷积神经网络模型用于轴承故障诊断
机译:基于改进D-s证据融合的集合深度卷积神经网络模型在轴承故障诊断中的应用