The rapid consumption of fossil fuel and increased environmental damage caused by it have
given a strong impetus to the growth and development of fuel-efficient vehicles. Hybrid …

The need to manufacture more competitive equipment, together with the emergence of the
digital technologies from the so-called Industry 4.0, have changed many paradigms of the …

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 …

Induction motor (IM) is a highly efficient prime mover in industrial applications. To maintain
an uninterrupted operation, accurate fault diagnosis system of IM is required. It can help to …

Stator/rotor winding faults are the common faults in squirrel-cage induction motor systems,
which motivates the study of incipient fault detection and isolation (IFDI) to improve the …

Fault diagnosis of electric motors is a fundamental task for production line testing, and it is
usually performed by experienced human operators. In the recent years, several methods …

In the field of reliability engineering, the gamma process plays an important role in modeling
degradation processes. However, extracting lifetime information from product degradation …

Predicting the remaining useful life of machinery, infrastructure, or other equipment can
facilitate preemptive maintenance decisions, whereby a failure is prevented through timely …

The fault detection of electrical or mechanical anomalies in induction motors has been a
challenging problem for researchers over decades to ensure the safety and economic …

Machinery fault diagnosis has progressed over the past decades with the evolution of
machineries in terms of complexity and scale. High-value machineries require condition …