The occurrence of bearing faults is often accompanied by noise signals, and noise sensors
have the characteristics of non-contact and flexible arrangement; hence, this paper …

Increasing reports indicated that multiscale entropy (MSE) is an efficient approach to
investigate various physical and physiological states, especially effective for cardiac …

In this study, an effective model for wind speed prediction in a coupled wind-fire scenario is
proposed.(a) The original wind speed sequence is decomposed using the variational mode …

The extraction of nonlinear dynamic fault features is a key scientific problem in the condition
monitoring and fault diagnosis of diesel fuel injectors. In order to obtain effective fault …

Railway point machines are the key equipment that controls the train route and affects the
safety of train operation. Complex and harsh working environments lead to frequent failures …

The health condition of bearings was related to the operation status of mechanical
equipment, and there were relatively few methods to recognize the severity of bearing faults …

Complexity measures typically represented by entropy are capable of detecting and
characterizing underlying dynamic changes in a system, and they have been considerably …

Feature extraction from vibration signals plays a vital role in rotating machinery fault
diagnosis. The noise contained in the signals will interfere with the fault feature extraction …

To address the challenge of low fault diagnosis accuracy due to insufficient bearing fault
data collected by single-sensor, a rolling bearing fault diagnosis method based on multi …

Enhancing the operational reliability of rotary machinery relies significantly on the effective
diagnosis of faults in rolling bearings. This study introduces an innovative method to improve …