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 …

Bearing fault diagnosis at early stage is very significant to ensure seamless operation of
induction motors in industrial environment. The identification and classification of faults …

In recent years, artificial intelligence technology has been widely used in fault prediction and
health management (PHM). The machine learning algorithm is widely used in the condition …

Induction machines (IMs) play a critical role in various industrial processes but are
susceptible to degenerative failures, such as broken rotor bars. Effective diagnostic …

In the motor current signal, the characteristic frequency of broken rotor bar (BRB) fault is
modulated by the supply frequency and it decreases with the decrease of the load, resulting …

Detecting the initial damage of the engine precisely is conducive to finding out the failure
symptom timely and ensuring the reliable operation of the engine for avoiding malignant …

Cyclostationary analysis has been strongly recognized as an effective demodulation tool in
identifying fault features of rotating machinery based on vibration signature analysis. This …

For mixture component identification, the methods based on deep learning are becoming
prevalent due to their end-to-end characteristic, being completely data-driven and reducing …

In the light of the significance of the rotating machinery and the possible severe losses
resulted from its unexpected defects, it is vital and meaningful to exploit the effective and …

Motor current signature analysis (MCSA) is a fault diagnosis method for induction machines
(IMs) that has attracted wide industrial interest in recent years. It is based on the detection of …