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

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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Bibliographic Details
Main Authors: Kyutae Kim, Jongpil Jeong
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Sensors
Subjects:
hydraulic system
CNN
bidirectional LSTM
attention mechanism
classification
data augmentation
Online Access:https://www.mdpi.com/1424-8220/20/24/7099

Internet

https://www.mdpi.com/1424-8220/20/24/7099

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