Tracking of High-Order Stray-Flux Harmonics Under Starting for the Detection of Winding Asymmetries in Wound-Rotor Induction Motors

Abstract

Wound rotor induction motors (WRIM) are widely used in a vast number of high output power industrial applications due to their capability of reaching high start torques while maintaining low inrush currents. Nonetheless, these machines are very prone to require early maintenance, and the possibility of presenting rotor winding asymmetry failures is high due to their more complex rotor circuit. Although some recent works have proposed techniques that overcome the drawbacks of conventional methods, an additional research effort for the development of alternative approaches able to enhance their performance and reliability is desirable. In this work, a new method for the diagnosis of rotor asymmetries in WRIM is presented. The proposed methodology is based on a feed-forward neural network fed by suitable fault severity indicators, which rely on the maximum energy density of higher order harmonics (amplified by the failure) at strategic regions of the time-frequency maps obtained from stray flux signals under startup transient. Experimental results for three different levels of rotor asymmetries in a 11-KW WRIM prove the reliability of the enhanced proposed system in comparison to conventional approaches that only rely on the main sideband fault-harmonic amplitudes.