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Real-Time Monitoring for Hydraulic States Based on Convolutional Bidirectional LSTM with Attention Mechanism

By monitoring a hydraulic system using artificial intelligence, we can detect anomalous data in a manufacturing workshop. In addition, by analyzing the anomalous data, we can diagnose faults and prevent failures. However, artificial intelligence, especially deep learning, needs to learn much data, a...

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Detalles Bibliográficos
Autores principales:	Kim, Kyutae, Jeong, Jongpil
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2020
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7764528/ https://www.ncbi.nlm.nih.gov/pubmed/33322319 http://dx.doi.org/10.3390/s20247099

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