The development of non-linear dynamic theory brought a new method for recognising and
predicting the complex non-linear dynamic behaviour. Fractal dimension can quantitatively …

A novel method based on wavelet leaders multifractal features for rolling element bearing
fault diagnosis is proposed. The multifractal features, combined with scaling exponents …

To effectively extract the fault feature information of rolling bearings and improve the
performance of fault diagnosis, a fault diagnosis method based on principal component …

Sensitive feature extraction from the raw vibration signal is still a great challenge for
intelligent fault diagnosis of rolling bearing. Current fault classification framework generally …

In modern manufacturing processes, requirements for automatic fault diagnosis have been
growing increasingly as it plays a vitally important role in the reliability and safety of …

Previous bearing fault diagnosis models show either low accuracy or long iterations, which
are not suitable for real-time production quality control scenarios lacking computing …

The goal of the paper is to present a solution to improve the fault detection accuracy of
rolling bearings. The method is based on variational mode decomposition (VMD), multiscale …

The rolling bearing is the key component of rotating machinery, and fault diagnosis for
rolling bearings can ensure the safe operation of rotating machinery. Fault diagnosis …

In order to improve the diagnosis accuracy and generalization of bearing faults, an
integrated vision transformer (ViT) model based on wavelet transform and the soft voting …

The primary task of rotating machinery fault diagnosis is to extract more fault feature
information from the measured signals, so that its diagnostic result is more accurate and …