Aug 17, 2021 · A deep regularized variational autoencoder (DRVAE) method is proposed. · Bird swarm algorithm is used to select adaptively the hyper-parameters ...
Hence, this paper proposes a novel deep learning model named deep regularized variational autoencoder (DRVAE) for intelligent fault diagnosis of rotor-bearing ...
A framework for learning autoencoder-based optimal fault detection in nonlinear dynamic systems is established and an analog concept to minimal sufficient ...
Deep regularized variational autoencoder for intelligent fault diagnosis of rotor–bearing system within entire life-cycle process.
Deep regularized variational autoencoder for intelligent fault diagnosis of rotor-bearing system within entire life-cycle process.
Dec 24, 2021 · A novel deep learning model, named stacked variational denoising autoencoder (SVDAE), is proposed, which can effectively process bearing ...
In this paper, a new framework for rotor-bearing system fault diagnosis under varying working conditions is proposed by using a modified convolutional neural ...
To overcome this difficulty, an efficient fault diagnosis method based on deep hypergraph autoencoder embedding (DHAEE) is presented in this study. First, ...
Bearing fault diagnosis with parallel CNN and LSTM - AIMS Press
www.aimspress.com › doi › mbe.2024105
Jia, Deep regularized variational autoencoder for intelligent fault diagnosis of rotor-bearing system within entire life-cycle process, Knowl.-Based Syst., ...
Hence, this paper proposes a novel deep learning model named deep regularized variational autoencoder (DRVAE) for intelligent fault diagnosis of rotor–bearing ...