Bearing fault diagnosis based on transfer learning with dual-flow manifold ResNet and improved CapsNet
Linhu Yao,
Hongwei Wang,
Lei Tao
et al.
Abstract:In intelligent fault diagnosis for rolling bearings, the variable operating conditions of rotating machinery lead to inconsistent distributions between training and testing data, inevitably decreasing fault diagnosis accuracy. To overcome this issue, we propose a bearing fault diagnosis method based on transfer learning with a dual-flow manifold residual network and improved capsule network (DMRCN). Firstly, we introduce a dual-flow manifold residual network (DMResNet) structure consisting of continuous wide-k… Show more
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