Abnormal noise detection of three-phase induction motor using linear predictive coding and neural networks

Abstract

The paper presents an abnormal noise detection method for a three-phase induction motor. The following motor conditions were analyzed: healthy (H), motor with one broken rotor bar (1BRB), motor with two broken rotor bars (2BRB), and motor with three broken rotor bars (3BRB). The dataset was split into 48 training samples (12 per class) and 168 test samples (42 per class) for the training and evaluation of the neural networks. Linear predictive coding (LPC) was used for feature extraction. The next three original neural networks were proposed for classification: Neural Network V01, V02, and V03. The authors of the paper also used ResNet-50. The proposed approach achieved a recognition efficiency of 100%.