Research into fault diagnosis in rotating machinery with a wide range of variable loads and
speeds, such as the gearboxes of wind turbines, is of great industrial interest. Although …

The feasibility and usefulness of frequency domain fusion of data from multiple vibration
sensors installed on typical industrial rotating machines, based on coherent composite …

Fault diagnosis plays an essential role in reducing the maintenance costs of rotating
machinery manufacturing systems. In many real applications of fault detection and …

Feature selection is an important aspect under study in machine learning based diagnosis,
that aims to remove irrelevant features for reaching good performance in the diagnostic …

This research aims to bring together thermal modelling and machine learning approaches to
improve the understanding on the operation and fault detection of a wind turbine gearbox …

A growing number of wind turbines are equipped with vibration measurement systems to
enable the close monitoring and early detection of developing fault conditions. The vibration …

Fault diagnosis of rotating machines is an important task to prevent machinery downtime,
and provide verifiable support for condition-based maintenance (CBM) decision-making …

Condition monitoring (CM) of wind turbine gearbox is one of the key concerns for the reliable
operation of wind power generation. With the huge ongoing transition towards renewable …

The key to fault diagnosis of rotating machinery is to extract fault features effectively and
select the appropriate classification algorithm. As a common signal decomposition method …

Gearboxes are massively utilized in nowadays industries due to their huge importance in
power transmission; hence, their defects can heavily affect the machines performance …