This paper proposes a multiscale slope feature extraction method using wavelet-based
multiresolution analysis for rotating machinery fault diagnosis. The new method mainly …

The fault diagnosis of rotating machinery has attracted considerable research attention in
recent years because such components as bearings and gears frequently suffer failure …

Empirical wavelet transform (EWT) based on the scale space method has been widely used
in rolling bearing fault diagnosis. However, using the scale space method to divide the …

This paper presents a novel method for fault diagnosis based on an improved wavelet
package transform (IWPT), a distance evaluation technique and the support vector machines …

Vibration signals of rolling element bearings faults are usually immersed in background
noise, which makes it difficult to detect the faults. Wavelet‐based methods being used …

This paper presents a hybrid technique to enhance health diagnosis of rotating machines
under varying speed conditions. This is achieved through the integration of complex wavelet …

As one of the most critical components in rotating machinery, it is essential to determine the
health of rolling bearings on time. The effective feature extraction method is considered …

Wavelet transform has been widely used for vibration-based machine fault diagnosis.
However, it is a difficult task to choose or design appropriate wavelet or wavelets for a given …

Defect faults on the surface of rolling bearing elements are the most frequent cause of
malfunctions and breakages of electrical machines. Due to increasing demands for quality …

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