… intelligent method for diagnosing the faults of rotating machinery. The effectiveness of …
datasets from rolling element bearings and planetary gearboxes. These datasets contain massive …

… fault diagnosis methods often consist of data … diagnosis (EFD) of rotating machinery has
achieved a large number of successful applications. Since the literature on this subject is huge …

… The field of mechanical fault diagnosis has entered the era of “big data”… large number of
methods and technology. In terms of fault mechanism, the fault mechanism of rotating machinery …

… Due to large-size monitoring data of equipment conditions, deep … datasets and self-collected
data to verify the proposed method. Table 1 shows the public datasets of rotating machinery …

… have published work related to fault diagnosis in rotating machines, mainly exploring a single
type of fault. However, if we have to take complete advantage of Big Data, it is essential to …

… fault diagnosis. However, due to the difficulty of collecting and labeling machine fault data,
the datasets in some practical applications are relatively much smaller than the other big data …

… review of AI algorithms in rotating machinery fault diagnosis, from both the views of …
spectrum data fusion method is proposed for rotating machines fault … Low efficiency for big data …

… Once massive useful training samples are available by data augmentation, multiple residual
blocks can be potentially stacked in the network for better feature extraction through the …

… of systems and cause huge losses. … diagnosis method for rotating machinery based on
GRU is proposed. Our method attempts to fully exploit temporal information of time-series data …

… Lu, “Deep neural networks: A promising tool for fault characteristic mining and intelligent
diagnosis of rotating machinery with massive data,” Mech. Syst. Signal Process, vol. …