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 …

This paper reviews the recent literature on machine learning (ML) models that have been
used for condition monitoring in wind turbines (eg blade fault detection or generator …

In recent years, deep learning technique has been used in mechanical intelligent fault
diagnosis and it has achieved much success. Among the deep learning models …

Over the last 20 years, particularly in last 10 years, great progress has been made in the
theory and applications of wavelets and many publications have been seen in the field of …

A convolutional discriminative feature learning method is presented for induction motor fault
diagnosis. The approach firstly utilizes back-propagation (BP)-based neural network to learn …

The piston pump is the key power component in the civil aircraft hydraulic system, and the
most common pump used in the aviation field is the pressure compensated variable …

This paper presents a transfer learning-based approach for bearing fault diagnosis, where
the transfer strategy is proposed to improve diagnostic performance of the bearings under …

A significant development in condition monitoring techniques has been observed over the
years. The scope of condition monitoring has been shifted from defect identification to its …

As failures in rotating machines can have serious implications, the timely detection and
diagnosis of faults in these machines is imperative for their smooth and safe operation …

Similarity-based modeling (SBM) is a technique whereby the normal operation of a system is
modeled in order to detect faults by analyzing their similarity to the normal system states …