Recent progress on intelligent fault diagnosis (IFD) has greatly depended on deep
representation learning and plenty of labeled data. However, machines often operate with …

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 …

Fault detection and diagnosis of gear systems using vibration measurements play an
important role in ensuring their functional reliability and safety. Computational intelligence …

The success of intelligent fault diagnosis of machines relies on the following two conditions:
1) labeled data with fault information are available; and 2) the training and testing data are …

Gear transmissions are an integral part of most rotation machinery. Their abnormalities can
affect the reliable operation of the equipment. Most sensors that monitor gear transmissions …

Efficient fault diagnosis of electrical and mechanical anomalies in induction motors (IMs) is
challenging but necessary to ensure safety and economical operation in industries …

With the increase in the amount of data captured during the manufacturing process,
monitoring systems are becoming important factors in decision making for management …

In recent years, deep learning techniques have been proved a promising tool for bearing
fault diagnosis. However, to extract deep features with better representative ability, how to …

Automatic and accurate identification of rolling bearings fault categories, especially for the
fault severities and fault orientations, is still a major challenge in rotating machinery fault …

Deep learning has gained a great achievement in the intelligent fault diagnosis of rotating
machineries. However, the labeled data is scarce in actual engineering and the marginal …