Abnormal identification of oil monitoring based on LSTM and SVDD-Reference-Cited by-同舟云学术

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Abnormal identification of oil monitoring based on LSTM and SVDD

Published:2023-08 Issue: Volume:526-527 Page:204793
ISSN:0043-1648
Container-title:Wear
language:en
Short-container-title:Wear

Author:

Li Dayang,Gao Huimin^ORCID,Yang Kun^ORCID,Zhou Fanhao^ORCID,Shi Xinfa

Publisher

Elsevier BV

Subject

Materials Chemistry,Surfaces, Coatings and Films,Surfaces and Interfaces,Mechanics of Materials,Condensed Matter Physics

Reference34 articles.

1. Ieee, Study of On-Line Measure Method in Petroleum Product's Humidity;Tang,2010

2. A review on lubricant condition monitoring information analysis for maintenance decision support;Wakiru;Mech. Syst. Signal Process.,2019

3. Research on feature extraction and representation method of distorted image of lubricating oil moisture online monitoring sensor;Gao;Chin. Equip. Eng.,2022

4. On-line Lubricating Oil Monitoring System Based on Dielectric Constant (2);Zong,2020

5. Monitoring technology of automobile engine lubricating oil by dielectric constant method;Li;J. Southwest Jiaot. Univ.,2011

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1. Spatial-temporal modeling of oil condition monitoring: A review;Reliability Engineering & System Safety;2024-08

2. Bi-AAE: A binary adversarial autoencoder deep neural network model for anomaly detection in system-levels marine diesel engines;Ocean Engineering;2024-06

3. The study of hydraulic machinery condition monitoring based on anomaly detection and fault diagnosis;Measurement;2024-05

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