Abstract Fault Detection and Diagnosis (FDD) of rotating machinery plays a key role in
reducing the maintenance costs of the manufacturing systems. How to improve the FDD …

Rotating machinery plays a critical role in many significant fields. However, the
unpredictable machinery faults may lead to the severe damage and losses. Hence, it is of …

The traditional intelligent diagnosis methods of rotating machinery generally require feature
extraction of the raw signals in advance. However, it is a very time-consuming and laborious …

Fault diagnosis of rotating machinery plays a significant role in the reliability and safety of
modern industrial systems. The traditional fault diagnosis methods usually need manually …

Fault diagnosis of rotating machinery is essential for maintaining system performance and
ensuring the operation safety. Deep learning (DL) has been recently developed rapidly and …

The rolling bearings play a vital role in mechanical production and transportation. However,
when it appears abnormal, the fault characteristics are weak and different to be extracted in …

Application of deep-learning techniques has been increasing, which redefines state-of-the-
art technology, especially in industrial applications such as fault diagnosis and classification …

Fault diagnosis is critical to ensure the safety and reliable operation of rotating machinery.
Most methods used in fault diagnosis of rotating machinery extract a few feature values from …

To improve the fault diagnosis performance for rotating machinery, an efficient, noise-
resistant end-to-end deep learning (DL) algorithm is proposed based on the advantages of …

Fault diagnosis in rotating machinery is significant to avoid serious accidents; thus, an
accurate and timely diagnosis method is necessary. With the breakthrough in deep learning …