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Ulsan Univ. Repository Journal Papers Engineering IT Convergence

Blade Rub-Impact Fault Identification Using Autoencoder-Based Nonlinear Function Approximation and a Deep Neural Network

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Author(s): 프로스비린 알렉산데르; farzin piltan; 김종면

Issued Date: 2020

Type: Article

Keyword: data-driven fault diagnosis; deep autoencoder; deep neural network; deep learning-based function approximation; fault diagnosis; rotating machinery; rub-impact fault; nonlinear-based fault diagnosis

DOI: 10.3390/s20216265

URI: https://oak.ulsan.ac.kr/handle/2021.oak/11413

Publisher: SENSORS

Language: 영어

ISSN: 1424-8220

Citation Volume: 20

Citation Number: 21

Citation Start Page: 6265

Citation End Page: 6265

Appears in Collections:: Engineering > IT Convergence

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