Sensor and Component Fault Detection and Diagnosis for Hydraulic Machinery Integrating LSTM Autoencoder Detector and Diagnostic Classifiers

Sensor and Component Fault Detection and Diagnosis for Hydraulic Machinery Integrating LSTM Autoencoder Detector and Diagnostic Classifiers

Anomaly occurrences in hydraulic machinery might lead to massive system shut down, jeopardizing the safety of the machinery and its surrounding human operator(s) and environment, and the severe economic implications following the faults and their associated damage. Hydraulics are mostly placed in ru...

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Bibliographic Details
Main Authors: Ahlam Mallak, Madjid Fathi
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Sensors
Subjects:
deep learning
LSTM autoencoder
supervised learning
hydraulic test rig
sensor faults
component faults
Online Access:https://www.mdpi.com/1424-8220/21/2/433

Internet

https://www.mdpi.com/1424-8220/21/2/433

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