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 …

This paper presents an up-to-date review of data-driven condition monitoring of industrial
equipment with the focus on three commonly used equipment: motors, pumps, and bearings …

This paper proposes a method for classification of fault and prediction of degradation of
components and machines in manufacturing system. The analysis is focused on the …

Induction motors are among the most important components of modern machinery and
industrial equipment. Therefore, it is necessary to develop a fault diagnosis system that …

Induction motors are critical components for most industries and the condition monitoring
has become necessary to detect faults. There are several techniques for fault diagnosis of …

Intelligent predictive maintenance (IPdM) is a maintenance strategy that makes maintenance
decisions automatically and dynamically based on Artificial Intelligence and Data mining …

As the need to improve reliability, availability and safety of technical systems increases, a
large number of proactive maintenance strategies have been proposed. Of greater interest is …

Piezoelectric transducers are used in a wide range of applications. Reliability of these
transducers is an important aspect in their application. Prognostics, which involve …

Condition-based Maintenance (CBM) is a maintenance policy that take maintenance action
just when need arises with real-time condition monitoring. Intelligent CBM means a CBM …

The diagnosis and monitoring of industrial machinery faults is crucial to the Industrial
Revolution but is frequently difficult and labor-intensive. Due to its quick computation …