… This section details the approach of the proposed methods for rotating machinery fault
diagnosis, as shown in Figure 2. First, the vibration data is divided into samples by a seg…

… end fault diagnostics model based on a convolutional neural network for rotating machinery
… has a good robustness for rotating machinery fault diagnostics with high accuracies for all …

… fault diagnosis under varying working conditions is proposed by using modified convolutional
neural network (CNN… Pecht, “A rotating machinery fault diagnosis method based on feature …

… Moreover, the information enhancement technology is still not applied into 1-D CNN
when deal with the machinery fault diagnosis. Therefore, it is necessary to design a self-adaptive …

… the above drawbacks, convolutional neural networks (CNN) may provide effective solutions
for intelligent information fusion and fault diagnosis. CNN is a model of deep learning, which …

… This section develops the proposed method into a real-world complex equipment fault
diagnosis case with imbalanced data. The task of this case is to detect the rotor-off fault. To …

… the diagnosis methods of rotating machinery based on convolutional neural network (CNN)
have achieved great success, they generally assume the number of normal and fault …

… learning approach has sustained many attentions in machinery fault diagnosis [1–4]. …
utilization of convolutional neural network (CNN) in diagnosing bearing fault diagnosis is reviewed. …

… features for fault diagnosis. In this article, a novel three-step intelligent fault diagnosis method
is … based on CNN and Bayesian Gaussian mixture (BGM) for rotating machinery. In the …

… the capability of fault diagnosis model. This paper proposes a new fault diagnosis method
… ) with a designed parallel multi-fusion convolutional neural network (MFCNN) Specifically, a …