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 …

In this paper, the idea of using a convolutional neural network (CNN) for the detection and
classification of induction motor stator winding faults is presented. The diagnosis inference …

In recent days, tendency of composite materials uses in transmission tower structure is
increasing tremendously over conventional zinc galvanized steel materials because of some …

The diagnosis of mechanical and electrical faults of induction motors (IMs) has been
performed using artificial neural networks (ANN) for similar, interpolated and extrapolated …

Risk, Reliability and Safety contains papers describing innovations in theory and practice
contributed to the scientific programme of the European Safety and Reliability conference …

This paper presents a simple and reliable improved method based on the three-phase
current intersection signal (TPCIS), for induction motor rotor fault diagnosis. This method …

The spindle comprises elements such as a shaft, bearings, a motor, a preload mechanism, a
tool holder, and a cutting tool. The shaft is supported by front and rear-pair angular contact …

In this study, a turn‐to‐turn short circuit of motor stator fault diagnosis system based on deep
auto‐encoder and soft‐max classifier is proposed. It is also considered in the proposed …

This paper presents a comparative study on the application of different neural network
structures to early detection of electrical faults in induction motor drives. The diagnosis …

This paper describes an Artificial Neural Network (ANN) based fault diagnosis methodology
for Induction Motors (IM) operating under the same conditions for various speeds and loads …