Abstract
In this paper, the cyclostationary characteristics of electrical signals will be exploited in order to detect the rotor faults of an asynchronous machine. These defects are the most complex in terms of detection since they interact with the 50 Hz carrier with a weak band occupied in frequency. The testing ground used includes an industrial three-phase wound rotor asynchronous motor of 400 V, 6.2 A, 50 Hz, 3 kW, 1385 rpm characteristics. The rotor fault has been carried out by adding an extra 40 mΩ resistance on one of the rotor phases (i.e. 10% of the rotor resistance value per phase, R r = 0.4Ω). From the stator voltage and current acquisition, and by application of the Time Synchronous Averaging (TSA) method to the stator current, the electrical signal will be conditioned in order to obtain a sensitive indicator allowing to easily distinguish the healthy cases from defective ones.
Highlights
Within a predictive maintenance framework, the proposed method is dedicated to the monitoring of asynchronous machines based on a statistical approach by Article published by EDP Sciences
Sampling rate (25.6 kHz in this paper) Residual current Residual current RMS Stator current Synchronous averaged current Stator-current harmonic component Mechanical-structure-related stator current Stator-current random component Stator current RMS Number of samples Number of samples (512 per period in this paper) Sampling period (Tsamp = 1/fsamp) development of an indicator resulting from the electrical signals of the machine
The asynchronous motor operating process and the electric supply fluctuations cause the non-stationary behavior of the stator current signal
Summary
Within a predictive maintenance framework, the proposed method is dedicated to the monitoring of asynchronous machines based on a statistical approach by Article published by EDP Sciences. Sampling rate (25.6 kHz in this paper) Residual current Residual current RMS Stator current Synchronous averaged current Stator-current harmonic component Mechanical-structure-related stator current Stator-current random component Stator current RMS Number of samples Number of samples (512 per period in this paper) Sampling period (Tsamp = 1/fsamp) development of an indicator resulting from the electrical signals of the machine (current and voltage). We are interested in the rotor failures Those generally lead to an increase of a one-phase rotor resistance value [1,2,5,6,7]. A rotor defect has been created by adding a 10% value extra resistance on one phase of the rotor, and acquired the stator voltage and current signals. A simple comparison between the stator current RMS in the healthy and defective modes of the no-load machine does not allow us to detect the failure (the variation is about 1% only). The new energy indicator will allow the easy distinction of the healthy and defective cases (the variation of the indicator value being clearly higher)
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