Fault Diagnosis and Fault Tolerance Technology of Electrical Control System Based on Deep Learning
This paper proposes a fault diagnosis and fault tolerance method for electrical systems that combines deep learning.Firstly,this method utilizes sparse autoencoders to learn the behavioral characteristics of electrical control systems,and then models the learned features using a bidirectional long short-term memory network to predict the current state of the system and perform fault diagnosis.Once a fault is detected,the corresponding fault tolerance process will be automatically initiated.The results of the simulation experiment fully demonstrate the effectiveness and practicality of this method.
deep learningfault diagnosisfault tolerance technology
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