Stator Winding Fault can be detected by monitoring any abnormality of the Park’s spectrum. In this paper, a fault-detection performance comparison is presented between the Support Vector Machine (SVM) and backpropagation algorithm (BP) using experimental data for a healthy and faulty case. Support Vector Machine and Back propagation Algorithm provide environments to develop fault-detection sche...

Detection and identification of induction machine faults through the stator current signal using higher order spectra analysis is presented. This technique is known as motor current signature analysis (MCSA). This paper proposes two higher order spectra techniques, namely the power spectrum and the slices of bi-spectrum used for the analysis of induction machine stator current leading to the de...

This paper proposes, investigates, and validates, by comprehensive experiments, new online automatic diagnostic technology for belt conveyor systems based on motor current signature analysis (MCSA). Motor (MCSA) is a method employed detecting faults in electric motors analyzing the waveforms generated during operation. The capitalizes fact that defects, such as mechanical misalignment, bearing ...

In this paper the method of sensorless startup of direct current brushless motor using third harmonic back Electromotive Force (EMF) and motor startup using microcontroller for pulse width modulation, power switch control and motor output analysis is presented which renders RPM control and high speed achievement for motor. The microcontroller is used for processor and MOSFETs are used for power...

Analysis of IC technology trends indicates that Iddq testing may be approaching its limits of applicability. The new concept of the current signature may expand this limit under the condition that an appropriate current-signature-based test methodology is developed. This paper is a first step toward such a goal. It is focused on current signature step detection in a noisy test environment. Appl...

Self-Organizing Maps (SOM) is an excellent method of analyzing multidimensional data. The SOM based classification is attractive, due to its unsupervised learning and topology preserving properties. In this paper, the performance of the self-organizing methods is investigated in induction motor rotor fault detection and severity evaluation. The SOM is based on motor current signature analysis (...

This paper presents the closed-form analytical determination of current signature a surface-mounted permanent magnet synchronous motor drive controlled by means field oriented control strategy, when fault occurs in one or more sensors. Both DC offset and gain for all phase sensors are considered. The proposed model includes response loop related gains, eliminating need voltage complicated state...