Distinct feature extraction methods are simultaneously used to describe bearing faults. This
approach produces a large number of heterogeneous features that augment discriminative …

Rolling element bearing defects are among the main reasons for the breakdown of electrical
machines, and therefore, early diagnosis of these is necessary to avoid more catastrophic …

Abstract Master River Multiple Creeks Intelligent Water Drops (MRMC-IWD) is an ensemble
model of the intelligent water drop, whereby a divide-and-conquer strategy is utilized to …

Effectiveness of online bearing status monitoring (OBSM) depends deeply on the online
data processing ability and the sensitivity of data features used to recognize the mechanical …

Reliable fault diagnosis of rolling bearings is an important issue for the normal operation of
many rotating machines. Information about the structure dynamics is always hidden in the …

The thickness of an oil film lubricant can contribute to less gear tooth wear and surface
failure. The purpose of this research is to use artificial neural network (ANN) computational …

This paper presents a new approach for predicting the element rolling bearing defects. A set
of fault scenarios (Outer race, inner race and ball rolling element) are designed and tested …

A new approach is proposed to construct a reasonable prediction model for prognostic. The
Gaussian mixture model-based health indicator is used for degradation performance and …

In this paper, a hybrid approach is proposed for detecting and classifying the vibration signal
of induction motor. The proposed hybrid technique is the combination of S-transformation …

Robust fault analysis (FA) including the diagnosis of faults and predicting their level of
severity is necessary to optimise maintenance and improve reliability of Aircraft. Early …