A rolling bearing fault diagnosis method based on whale gray wolf optimization algorithm-
variational mode decomposition-support vector machine (WGWOA-VMD-SVM) was …

A single sensor's blade damage identification is difficult because of the complex noise
environment. At the same time, the multi-source signals include complete information of fault …

Rolling element bearings are key and also vulnerable machine elements in rotating
machinery. Fault diagnosis of rolling element bearings is significant for guaranteeing …

Abstract Blade Tip Timing (BTT) method is increasingly implemented for rotating blade
health monitoring for its non-contact property. However, the BTT data is usually highly …

Rolling bearings are important supporting components widely used in rotating machinery
and are prone to failure, it is thus important to perform fault detection of rolling bearing …

We propose a new fault diagnosis model for rolling bearings based on a hybrid kernel
support vector machine (SVM) and Bayesian optimization (BO). The model uses discrete …

The development of AI has enabled the fault detection of industrial components to be
achieved through the combination with deep learning. A detection method combined with …

Blade health monitoring (BHM) is an important technology to ensure safe operation of
turbine machinery. The blade tip timing (BTT) method is a non-contact approach of vibration …

Rotor blade health monitoring based on the non-contact blade tip timing (BTT) technique
has already been proved to be an alternative method to the classical contact strain …

Large-scale centrifugal compressor is an essential fluid machinery in modern industry. The
blades, a critical part of compressors, always work under severe and harsh conditions and …