… Machinery failure can cause significant financial loss as well as … , data was generated using
data augmentation techniques that are good for application to two types of time series data. …

… a fault detection approach based on data augmentation for roller … data augmentation was
achieved by the simulated signals generated by the dynamic model, and based on this, a fault …

… Experimental results of gearbox and bearing datasets show that the DAESPN model has
strong feasibility to carry out data augmentation for fault diagnosis of rotating machines under …

… eg, industrial process data, some more data augment methods are needed… data augmentation
to increase the numbers of input data samples in low-data domain of the imbalanced data …

… network method for intelligent rolling equipment fault diagnosis. The data generation and
fault diagnosis process is as follows: 1) Collect bearing fault datasets from different models and …

… on two rotating machinery datasets, the data-driven fault diagnostic model can significantly
… proposed data augmentation method is promising for fault diagnostic tasks with imbalanced …

… role in process monitoring and fault diagnosis. While the online monitoring system uses
sensors to obtain measurement data of mechanical equipment and industrial processes which …

… Deep learning algorithms for diagnosing machinery faults have become prevalent owing to
their robustness and capacity for adaptation. Deep architectures of computational layers and …

… This article reviews the research results of data-driven fault diagnosis methods of recent
years, and it includes the application status and research progress of machinery fault diagnosis …

… To the best of our knowledge, in the field of rotating machinery fault diagnosis, early work …
state of equipment. In real practice, however, it is common to face the issue that the equipments …