Adaptive fault detection method for airplane rotation actuator driving device based on deep learning
A technology of rotary actuators and driving devices, which is applied in the direction of instruments, electrical testing/monitoring, testing/monitoring control systems, etc., to achieve the effect of increasing the number of layers, improving accuracy, and improving generalization ability
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[0049] The present invention will be described in detail below in conjunction with the drawings and embodiments.
[0050] The invention discloses an adaptive fault detection method of an aircraft rotary actuator drive device based on deep learning. The method is based on the deep learning of sparse Dropout autoencoder and stacked denoising autoencoder (Stacked Denoising Autoencoder) and Logistic regression. Self-adaptive fault detection of aircraft rotary actuator driving device. Based on the failure analysis of the driving device of the aircraft rotary actuator, and in view of the current classification algorithm robustness and accuracy limitations, this method draws on the knowledge of image pattern recognition and adopts deep learning autonomous recognition based on multi-layer neural network. The well-known method uses the sparse Dropout autoencoder in the first layer and the layered noise reduction autoencoder model of the second and third layers to realize the self-expressi...
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