This paper surveys neuro fuzzy systems (NFS) development using classification and
literature review of articles for the last decade (2002–2012) to explore how various NFS …

The fault monitoring and diagnosis of industrial machineries are very significant in Industry
4.0 revolution but are often complicated and labour intensive. The application of artificial …

A reliable machine fault prognostic system can be used to forecast damage propagation
trend in rotary machinery and to provide an alarm before a fault reaches critical levels …

The strategic and monetary value of the civil infrastructure worldwide necessitates the
development of structural health monitoring (SHM) systems that can accurately monitor …

The present study attempts to diagnose severity of faults in ball bearings using various
machine learning techniques, like support vector machine (SVM) and artificial neural …

Prognostics and health management has become a significant part of component life-cycle
in modern industries. The prognostics and health management framework is implemented in …

This paper investigates the analysis and design of a vibration-based energy harvester for
rotary motion applications. The energy harvester consists of a cantilever beam with a tip …

Both fuzzy logic, as the basis of many inference systems, and Neural Networks, as a
powerful computational model for classification and estimation, have been used in many …

A reliable predictor is very useful to a wide array of industries to forecast the behaviour of
dynamic systems. In this paper, an adaptive multi-step predictor is developed based on a …

Various approaches for prognostics have been developed, and data-driven methods are
increasingly applied. The training step of these methods generally requires huge datasets to …