A novel method to solve the rotating machinery fault diagnosis problem is proposed, which
is based on principal components analysis (PCA) to extract the characteristic features and …

Feature extraction and class discrimination are two key problems for fault diagnosis of
rotating machinery. Firstly, multi-scale higher order singular spectrum analysis (MS-HO …

Fault diagnosis methods based on dimensionless indicators have long been studied for
rotating machinery. However, traditional dimensionless indicators frequently suffer a low …

As crucial equipment during industrial manufacture, the health status of rotating machinery
affects the production efficiency and device safety. Hence, it is of great significance to …

To better equip with a non-expert to carry out the diagnosis operations, a new method for
intelligent fault identification of rotating machinery based on the empirical mode …

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 …

In order to achieve accurate diagnosis for rotating machinery automatically and considering
that test data under actual fault conditions are rather difficult to obtain, a novel fault diagnosis …

When an abnormal situation occurs in rotating machinery, fault feature information may be
scattered on multiple sensors, and fault feature extraction through a single sensor is not …

In recent years, the variational mode decomposition (VMD) method has been introduced for
rotating machinery fault diagnosis. However, the results largely depend on its parameters …

A new intelligent fault diagnosis algorithm of rotating machinery based on intrinsic
characteristic-scale decomposition (ICD), generalized composite multi-scale fuzzy entropy …