Sparse decomposition has been widely used in gear local fault diagnosis due to its
outstanding performance in feature extraction. The extraction results depend heavily on the …

Bearing failures in the industry are a recurring problem that can cause permanent damage
to machines and interrupt production in important sectors of a factory. For this reason, over …

This article describes the development of a fiber Bragg grating (FBG) sensor encapsulated
in carbon-fiber reinforced polymer to detect faults in rotating electrical machine bearings …

The sparse representation, which is based on the orthogonal matching pursuit (OMP)
algorithm, is a useful technique for identifying defect characteristics in rolling element …

For the sake of addressing the issue of extracting multiple features embedded in a noise-
heavy vibration signal for bearing compound fault diagnosis, a novel model based on …

Aiming at the problem of insufficient bearing fault samples in practical engineering, an
unsupervised bearing fault diagnosis method with double frame twin network is proposed in …

Bearing fault is a common factor leading to machine failures. How to extract the periodic
transient signal due to bearing faults submerged in strong noise is a challenging problem for …

Periodic impulse features caused by damage to rotating mechanical components are often
overwhelmed by redundant components, which seriously affect the fault detection and …

针对轴承信号稀疏分解方法中因轴承个性化振动行为导致稀疏分解字典与故障信号适配性差,
以及因字典参数设置, 选取不当而使其在实际应用中稀疏分解效果不佳的问题 …

Fisher discriminant dictionary learning (FDDL) is an effective classification method that has
achieved excellent results in image processing. However, there are still some shortcomings …