Improving the reliability of engineered systems is a crucial problem in many applications in
various engineering fields, such as aerospace, nuclear energy, and water declination …

The availability of computational power in the domain of Prognostics and Health
Management (PHM) with deep learning (DL) applications has attracted researchers …

To assess health conditions of rotating machinery efficiently, multiple accelerometers are
mounted on different locations to acquire a variety of possible faults signals. The statistical …

Fault diagnosis methods based on dimensionless indicators have long been studied for
rotating machinery. However, traditional dimensionless indicators frequently suffer a low …

This paper proposes a new approach to diagnose broken rotor bar failure in a line start-
permanent magnet synchronous motor (LS-PMSM) using random forests. The transient …

Accurate detection of mechanical components faults is an essential step for reduction of
repair cost, human injury probability and loss of production. Using intelligent fault diagnosis …

Gearboxes and bearings play an important role in industries for motion and torque
transmission machines. Therefore, early diagnoses are sought to avoid unplanned …

The mining industry contributes to the expansion of the global economy by generating vital
commodities. For continuous production, the industry relies significantly on machinery and …

Features extracted from real world applications increase dramatically, while machine
learning methods decrease their performance given the previous scenario, and feature …

Fault detection and diagnosis is the most important technology in condition-based
maintenance (CBM) system for rotating machinery. This paper experimentally explores the …