Abstract: Induction motors are the dominant components in industrial processes involving electromechanical energy conversion. Safety, reliability and efficiency are major concerns in modern induction motor applications. Since detecting faults on time could avoid costly unscheduled shutdowns, in recent years there has been an increased interest in induction motor fault detection and diagnosis. I...

A fault diagnosis system based on pattern recognition techniques is developed for cage induction machine broken bar detection. The developed algorithm uses the stator current and, if available, motor speed as input data. Several features are extracted from the Frequency spectrum of the current signal derived using the Fast Fourier Transform. The relevance of the features for the purpose of faul...

Induction motors (IMs) are commonly used in various industrial applications. A spectrum synch (SS) technique is proposed in this chapter for early IM defect detection using electric current signals; fault detection in this work will focus on defects in rolling element bearings and rotor bars, which together account for more than half of IM imperfections. In bearing fault detection, the proposed...

Quality control is applied in production process. The good condition of electrical machines can be obtained by using diagnostics. There are a lot of methods that can be used for diagnostics of electrical machines. In the literature, standard methods are based on a study of electrical signals. This project work start with a novel automated practical implementation for non contiguous rotor side b...

Winding function method (WFM) provides a detailed and rather simple analytical modeling and simulation technique for analyzing performance of faulty squirrel-cage induction motors (SCIMs). Such analysis is mainly applicable for designing on-line fault diagnosis techniques. In this paper, WFM is extended to include variable degree of magnetic saturation by applying an appropriate air gap functio...

Broken rotor bars in induction motors can be detected by monitoring any abnormality of the spectrum amplitudes at certain frequencies in the motor current spectrum. Broken rotor bar fault detection schemes should rely on multiple signatures in order to overcome or reduce the effect of any misinterpretation of the signatures that are obscured by factors such as measurement noises and different l...

In this paper, we propose an adaptive statistical time-frequency method to detect broken bars using digital torque estimation. The key idea in the proposed method is to transform motor current into a time-frequency spectrum to capture the time variation of the frequency components and to analyze the spectrum statistically to distinguish fault conditions from the normal operating conditions of t...

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 a method based on neural networks to detect broken rotor bars and end rings in squirrel cage induction motors. In the first part, detection methods are reviewed and traditional methods of fault detection as well as dynamic&#10model of induction motors are introduced using the winding function method. In this method, all stator and rotor bars are considered independently in o...