Rolling bearings are critical components that are prone to faults in the operation of rotating
equipment. Therefore, it is of utmost importance to accurately diagnose the state of rolling …

This paper proposes a new signal feature extraction and fault diagnosis method for fault
diagnosis of low-speed machinery. Statistic filter (SF) and wavelet package transform (WPT) …

Purpose To maintain machinery operations smoothly, Rolling-Element Bearings (REBs) are
utilized so that the entire equipment's safety is ensured. Sometimes, the safety of the …

The vibration signal analysis is a popular method for extracting sensitive fault features. The
vibration signals are usually contaminated by noise, and therefore the extracted features …

This paper presents a novel vibration signal fusion algorithm using improved empirical
wavelet transform and variance contribution rate to fuse three-channel vibration signals for …

Vibration signals are widely used in monitoring and diagnosing of rolling bearing faults.
These signals are usually noisy and masked by other sources, which may therefore result in …

Signal processing is a widely used tool in the field of monitoring and diagnosis of rolling
bearing faults. The vibration signals of rolling bearing contain important information which …

A comprehensive fault diagnosis method of rolling bearing about noise interference, fault
feature extraction, and identification was proposed. Based on complete ensemble empirical …

Bearing vibration signals exhibit instantaneous modulation features under variable rotating
frequency, making it difficult to identify the characteristic frequency components. As such, a …

The acquired hob vibration signals are inevitably contaminated by noise in the industrial
environment, which changes the vibration signal frequency distribution and reduces the …