… deep learning based fault diagnosis methods and learning rate selection for deep learning.
… [7] surveyed the artificial intelligent methods for fault diagnosis of rotating machinery. Qin et …

… fault diagnosis method, based on 2D map representations of Cyclic Spectral Coherence (CSCoh)
and Convolutional Neural Networks (… failure usually leads to equipment breakdown, to …

… AE signals were recorded using a self-designed machinery fault simulator that simulates
different fault conditions using a cylindrical roller element bearing (FAG NJ206-E-TVP2), as …

… fault diagnosis methods is very serious. In this paper, a new model based on deep learning
is proposed to address the problem… Failure of these machines could cause great economical …

… equipment [7]. In order to achieve this purpose, the rolling bearing fault diagnosis method is
… However, the condition monitoring and fault diagnosis of mechanical equipment are mostly …

… of deep learning on the fault diagnosis problems. The diagnostic knowledge learned by the
deep neural network is … mechanism of deep learning on rotating machinery fault diagnosis …

… convolutional neural network is designed to extract discriminating features and provide
diagnosis … encoder information based intelligent method for fault diagnosis of rotating machinery. …

… bearing health status, and it may assist in the fault diagnosis step and better maintenance
of machines. A smart fault diagnosis method typically consists of four steps as follows: data …

… ble convolutional neural network (EnCNN) for the intelligent fault diagnosis of machines … In
the proposed EnCNN, a convolutional neural network is used as the base classifier, as shown …

… Early fault detection and diagnosis can increase the stability, reliability and safety of
manufacturing equipment… Recently, fault diagnosis (FD) methods based on deep learning (DL) …