Intelligent Fault Diagnosis Method for Blade Damage of Quad-Rotor UAV Based on Stacked Pruning Sparse Denoising Autoencoder and Convolutional Neural Network

This paper introduces a new intelligent fault diagnosis method based on stack pruning sparse denoising autoencoder and convolutional neural network (sPSDAE-CNN). This method processes the original input data by using a stack denoising autoencoder. Different from the traditional autoencoder, stack pr...

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Vydané v:	Machines (Basel) Ročník 9; číslo 12; s. 360
Hlavní autori:	Yang, Pu, Wen, Chenwan, Geng, Huilin, Liu, Peng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.12.2021
Predmet:	Accuracy anti-noise Artificial neural networks convolutional neural network Damage Drones Fault diagnosis Feature extraction Image enhancement intelligent fault diagnosis Kalman filters Mathematical models Neural networks Noise Noise reduction Pruning Sensors Signal processing Signal to noise ratio stacked pruning sparse denoising autoencoder Training Unmanned aerial vehicles
ISSN:	2075-1702, 2075-1702
On-line prístup:	Získať plný text
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