This paper is intended as a tutorial overview of induction motors signature analysis as a
medium for fault detection. The purpose is to introduce in a concise manner the fundamental …

Timely and accurate bearing fault detection and diagnosis is important for reliable and safe
operation of industrial systems. In this study, performance of a generic real-time induction …

Early detection of the motor faults is essential and artificial neural networks are widely used
for this purpose. The typical systems usually encapsulate two distinct blocks: feature …

Bearing faults are the biggest single source of motor failures. Artificial Neural Networks
(ANNs) and other decision support systems are widely used for early detection of bearing …

In recent years, marked improvement has been achieved in the design and manufacture of
stator winding. However, motors driven by solid-state inverters undergo severe voltage …

This paper develops a winding-function-based method for modeling polyphase cage
induction motors with inter-turn short circuits in the machine stator winding. Analytical …

Various applications of artificial neural networks (ANNs) presented in the literature prove
that such technique is well suited to cope with online fault diagnosis in induction motors. The …

Bibliography on Induction Motors Faults Detection and Diagnosis Page 1 HAL Id: hal-01052297
https://hal.science/hal-01052297 Submitted on 25 Jul 2014 HAL is a multi-disciplinary open …

Feature extraction from a time sequence signal without manual information is an important
part for bearing intelligent diagnosis. With the merits of signal information and feature …

Electric motors are widely used in many industrial applications on account of stability,
solidity and ease of use. Mechanical bearing faults have the highest statistical occurrence …