Detection of squirrel cage induction motor (SCIM) broken bars has long been an important but difficult job in the detection area of motor faults. Early detection of this abnormality in the motor would help to avoid costly breakdowns. A new detection method based on particle swarm optimization (PSO) is presented in this paper. Stator current in an induction motor will be measured and characteris...

This paper presents an intelligent fault detection based on adaptive continuous wavelet transform of broken rotor bars for Induction Motor (IM). Broken rotor bars, bearing decay, eccentricity, as motor faults appears as different frequencies in the stator current signals. The stator current and speed signals at deferent operation conditions obtained from the winding function are analysed throug...

Natural selection theory suggests that there should be fitness consequences for animals that possess morphological abnormalities such as missing or deformed appendages and other structures. As these characters are expected to be detrimental, morphological abnormalities could be considered ‘‘handicaps’’. However, little information exists about the nature, prevalence or consequences of naturally...

*Correspondence: [email protected] Département de Génie Electrique, Université 20 Août 1955-Skikda, Skikda, Algeria Abstract In this study we investigate the possibility of broken bar fault detection in an induction machine rotor using spectral analysis of the stator currents. The numerical method, presented in this work, based on the Hilbert transform shows the possibility of improving the dete...

Induction motors are prime component in the industries. Hence, condition monitoring and fault diagnosis of induction motor important to avoid shutdowns unplanned maintenance. A technique based on time-domain grayscale current signal imaging (TDGCI) convolutional neural network (CNN) is proposed for intelligent detection broken rotor bar an motor. The standard dataset made available by Aline Ell...

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 current signal during the motor startup was acquired from a healthy motor and a faulty motor with a broken rotor bar fault. We extracted 13 statistical time domain features from the startup transient current signal, and used the...

When an induction motor is running at stable speed and low slip, the fault signal of motor’s broken bar faults are easily submerged by power frequency (50 Hz) signal. Thus, it difficult to extract characteristics. The left-side harmonic component representing characteristics can be distinguished from owing V-shaped trajectory in time-frequency (t-f) domain during startup. This article proposed ...

Different alternatives to detect and diagnose faults in induction machines have been proposed and implemented in the last years. The technology of artificial neural networks has been successfully used to solve the motor incipient fault detection problem. The characteristics, obtained by this technique, distinguish them from the traditional ones, which, in most cases, need that the machine which...

Abstract: This article presents a fault detection scheme for the case of a broken bar occurrence in a three phase induction motor. The proposed scheme relies on Set Membership Identification (SMI) and novel proposed boundary violation rules for the identified motor’s parameters. The model of the three phase induction motor is being transformed into an equivalent two phase model, described in th...