The past decade has witnessed the adoption of artificial intelligence (AI) in various
applications. It is of no exception in the area of prognostics and health management (PHM) …

The objective of this paper is to present a comprehensive review of the contemporary
techniques for fault detection, diagnosis, and prognosis of rolling element bearings (REBs) …

This paper presents the results of acoustic emission (AE) investigation for monitoring
lubrication conditions of a journal bearing under various operating conditions …

Purpose This work under consideration makes use of support vector machines (SVM) for
regression and genetic algorithms (GA) which may be referred to as SVMGA, to classify …

This paper uses Bayesian robust new hidden Markov modeling (BRNHMM) for bearing fault
detection and diagnosis based on its acoustic emission signal. A variational Bayesian …

Journal bearings are widely used to support the shafts in industrial machinery involving
heavy loads, such as compressors, turbines and centrifugal pumps. The major problem that …

Almost all machines having rotating parts contain rolling element bearings to support the
rotating parts during power transmission. Bearing failure is a major cause of the breakdown …

In this paper, the rolling bearing is detected by the PLC-based remote fault diagnosis
system. This system carries out remote system bearing fault diagnosis and maintenance …

As mechanical facilities are interacting with each other, the failure of some equipment can
affect the entire system, so it is necessary to quickly detect and diagnose the abnormality of …

This study aims at developing a novel method for condition monitoring technique for
detection and classification of developing faults and increase the working life of continuous …