It is meaningful to automatically learn the valuable features from the raw vibration data and
provide accurate fault diagnosis results. In this paper, an enhancement deep feature fusion …

The advent of digitization has brought about new technologies that enable advanced
condition monitoring and fault diagnosis under the Industry 4.0 paradigm. While vibration …

New sensorless observers (ie, from stator currents/voltages measurements only), to be
included into a simple observer-based sensorless control for the tracking of non-definitely …

Induction motors (IM) are key components of any industrial process; hence, it is important to
carry out continuous monitoring to detect incipient faults in them in order to avoid …

In the paper, a fault diagnosis of the induction motor (IM) at closed loop is presented, and the
fault considered in the machine is the adjacent broken rotor bars. The technique of control …

Most industrial processes are run by induction machines (IMs). Condition monitoring of IM
assures their continuity of service, and it may avoid highly costly breakdowns. Among the …

Fault diagnosis of induction machines (IMs) requires a fast model of the machine, for
adjusting fault thresholds in data-driven diagnostic methods, for computing the residuals in …

The roller is an important part of the belt conveyor in sand carrier at sea. A good fault
diagnosis method of the rollers provides an effective guarantee for the system's optimal …

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction
machines working in the transient regime, when time-frequency analysis tools are used. The …

This paper presents an advanced strategy combining fuzzy logic and artificial neural
networks (ANNs) for direct torque control (DTC) and broken‐bar fault diagnosis in induction …