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伴随我国经济发展突飞猛进,电气化的应用越来越广,异步电动机因其经济、安全、高效、低耗被广泛应用于工业生产的各个领域。电动机一旦发生故障不仅会损坏电机本身,还会影响整个工业生产环节,从而造成巨大的经济损失。因此,如何对电机加强保护,对电机故障诊断提出了更高要求。本文对人工神经网络的基本原理进行了研究。利用MATLAB软件,建立基于BP网络的故障诊断结构,根据故障样本数据对网络进行训练,从而实现了对电机的诊断。
With China’s rapid economic development, the electrification of more and more widely used, because of its economy, safety, high efficiency, low consumption induction motor is widely used in various fields of industrial production. Motor failure will not only damage the motor itself, but also affect the entire industrial production processes, resulting in huge economic losses. Therefore, how to strengthen the protection of the motor, the motor fault diagnosis put forward higher requirements. This paper studies the basic principle of artificial neural network. Using MATLAB software, the fault diagnosis structure based on BP network is established, and the network is trained according to the fault sample data to realize the diagnosis of the motor.