Abstract
Squirrel-cage induction motors (IM) are the most popular motors used in industry, consuming around 85% of the power in industrial plants. IM are critical components for most industries, and an early detection of induction motor faults has been a main subject of investigation during last years. Broken rotor bars in induction motors are among the major failures that are desirable to detect at early stages because this failure significantly increases power consumption and is responsible for further damage to the machinery. However, the detection of partially-broken rotor bars at an early stage is not so easily achieved. Therefore, it is necessary to use suitable condition monitoring accompanied with signal processing techniques to detect a partially-broken rotor bar. Thus, this paper focuses on a study and evaluation of a condition monitoring method based on the complete ensemble empirical mode decomposition CEEMD of the stator current; aiming to detect partially broken, one, and two broken rotor bars in a line fed EVI during the startup current transient. From the experimental results, the CEEMD is able to graphically show, in the time domain, the physical effect of the fault evolution during the startup current as an abrupt change in the envelope, and finally, these abrupt changes are quantified in a way that the level of fault can be identified correctly. Also, the CEEMD has the advantage of being an online diagnosis method, which does not require knowing a priori the motor current of the healthy condition.
Published Version
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