The bearing fault information is often interfered or lost in the background noise after the
vibration signal being transferred complicatedly, which will make it very difficult to extract …

In practice, due to the influence of rotational speed fluctuation, structural resonance, load
distribution, and so on, the impulse response signals caused by partial faults of rolling …

In the signal processing domain, there has been growing interest in sparse coding with a
learned dictionary instead of a predefined one, which is advocated as an effective …

In the early fault diagnosis of rolling bearing, the vibration signal is mixed with a lot of noise,
resulting in the difficulties in analysis of early weak fault signal. This article introduces …

It is significant to detect the fault type and assess the fault level as early as possible for
avoiding catastrophic accidents. In the early fault diagnosis of rolling bearing, the vibration …

Identification of rolling bearing fault patterns, especially for the compound faults, has
attracted notable attention and is still a challenge in fault diagnosis. Intelligent diagnosis …

Aiming at the problem that the vibration signals of rolling bearings working in a harsh
environment are mixed with many harmonic components and noise signals, while the …

Rolling element bearing is a vital but also an easily damageable part for rotating machinery.
In this paper, sparse representation-based classification is introduced in the method of fault …

In the early stage of bearing failure, the transient features are not obvious. It is a big
challenge to extract the weak transient features under strong background noise. The sparse …

Sparse representation is one of the effective approaches for bearing fault diagnosis.
Conventional sparse representation only focuses on fault feature extraction from bearing …