ANN Based Broken Rotor Bar Fault Detection in LSPMS Motors

Khalid I Baradieh, Al-Hamouz

Abstract

Line Start Permanent Magnet Synchronous Motors (LSPMSMs) combine the high efficiency of the permanent magnet synchronous motors (PMSM) with the ease of use, simplicity in design and high starting capability of the induction motors (IMs). Due to the rapidly growing usage of this relatively new motor, proposing a diagnostics method for broken rotor bar fault is necessity. In this paper, a diagnostics technique based on Artificial Neural Network (ANN) was developed to detect the broken bars fault in LSPMSM using Singular Value Decomposition (SVD) in order to extract distinguishing features from the stator phase current. This distinguishing attributes were proposed to be the inputs to the built neural network.

Relevant Publications in Electrical & Electronic Systems