… valuable features from the raw vibration data and provide accurate fault diagnosis results. In
this paper, an enhancement deep feature fusion method is developed for rotating machinery …

… A new feature fusion … for rotating machinery fault diagnosis. For multi-source data, some
data sources are extracted with empirical features and others are extracted with hidden features. …

… multi-feature fusion scheme and … feature fusion scheme is adopted to fuse the spectral
samples with different working conditions, which uses multi-branch convolution layers as feature …

… The DNN method based on the differential geometric feature fusion proposed in this
paper can provide an efficient means of online fault diagnosis by extracting potential features …

… of the rotating machinery … feature dimension and conduct feature fusion [33]. DBN, as a
deep learning method, is a kind of generative neural network with powerful unsupervised feature …

… feature sample, which realizes the feature-level fusion of the multi-sensor signal. Next, a
DNN based on SAEs is constructed to enhance the feature learning and deep feature fusion. …

… of an improved ResNets model for rotating machinery fault diagnosis to solve the issues
mentioned above. Firstly, a novel multi-scale feature fusion block (MSFFB) is proposed to pre-…

… fault diagnosis of rotating machines under variable working … use of features that are insensitive
to rotating speed or load is … of machine system in occasions with different rotating speed …

… To effectively address this issue, an adaptive feature fusion assisted generation adversarial
… signal input, a module for adaptive feature fusion is constructed to guide the generator to …

… key components in rotating machinery. In this paper, a new method called feature fusion deep
… several pre-trained restricted Boltzmann machines for feature learning of the raw vibration …