Abstract
To improve the accuracy of rotor fault diagnosis of an asynchronous motor, a method of teaching-learning- based optimization combined with BP neural network (TLBO-BP) is proposed. For the sake of further enhancing the optimization capability of teaching- learning-based optimization (TLBO) algorithm, the elite learning strategy is applied to perform the information feedback between teachers and students once again. Subsequently, according to the feature vectors of rotor fault, TLBO algorithm is adopted to search for the initial weights and thresholds of BP neural network, and then the fault diagnosis model of the asynchronous motor rotor is built. The experimental results indicate that the TLBO-BP approach has higher diagnostic accuracy, and can effectively identify the rotor fault modes of an asynchronous motor.
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