Driven by the ongoing migration towards Industry 4.0, the increasing adoption of artificial
intelligence (AI) has empowered smart manufacturing and digital transformation. AI …

Recent developments in maintenance modelling fueled by data-based approaches such as
machine learning (ML), have enabled a broad range of applications. In the automotive …

Contemporary research has shown impetus in the diagnostics of permanent magnet (PM)
type machines. The manufacturers are now more interested in building diagnostics features …

This study presents a new roller bearing fault diagnosis algorithm based on a sparsity and
neighborhood preserving deep extreme learning machine (SNP-DELM) and motor current …

This paper presents a study on vibration‐based fault diagnosis techniques of a commutator
motor (CM). Proposed techniques used vibration signals and signal processing methods …

Smart and water-saving systems recommended for agricultural irrigation are of great
importance for countries and regions with limited water resources. Thus, it is aimed to …

This paper addresses the critical issue of reducing the downtime of vehicles by using
machine learning (ML) techniques and full life cycle data. The study tests the failure …

Electro-mobility plays a key role to achieve climate neutrality. Electric vehicles, partially
powered by vehicle-integrated photovoltaics, are now emerging in the market. This study …

In order to detect hearing loss more efficiently and accurately, this study proposed a new
method based on fractional Fourier transform (FRFT). Three-dimensional volumetric …

Increase of energy efficiency and level of information system development of rotor machines
in general requires improvement of theoretical approaches to research. In the present paper …