… a low accuracy of fault diagnosis for nonlinear and non-stationary dynamic signals of rotating
machinery. In this paper, we propose an effective fault diagnosis method based on multi-…

… citations in this section are limited to papers in the field of rotating machinery fault diagnosis.
… time-frequency analysis of rotating machinery fault diagnosis are divided into three stages …

… This paper presents a Digital Twin reference model for rotating machinery fault diagnosis.
The requirements for constructing the Digital Twin model are discussed, and a model updating …

… Considering those above-mentioned problems, this paper presents a novel rotating
machinery fault diagnosis method based on LGDNN (Local-Global Deep Neural Network). The …

… diagnosis. Condition-based maintenance … fault diagnosis of rotating machinery. Resonance
demodulation technology is the one fault diagnosis technology widely used in the machinery …

… algorithm is proposed for early fault diagnosis of rotating machinery. First, sigmoid function
is developed to the generalized form to improve the fault representation ability of the objective …

… This paper proposes a deep learning-based domain generalization method for rotating
machinery fault diagnosis. In order to expand the training dataset, a domain augmentation …

… In this section, a new intelligent fault diagnosis method is proposed based on the GNSF
algorithm for rotating machinery and the performance of the proposed method is discussed. The …

… In summary, rotating machinery fault diagnosis is an engineering problem traditionally …
features from raw vibration signals for fault diagnosis of rotating machinery. This goal has been …

… fault features in a deep network construction remains a challenge for intelligent fault diagnosis
of rotating machinery… for intelligent gear and bearing fault diagnosis. An improved three-…