A High-Dimensional and Small-Sample Submersible Fault Detection Method Based on Feature Selection and Data Augmentation

A High-Dimensional and Small-Sample Submersible Fault Detection Method Based on Feature Selection and Data Augmentation

The fault detection of manned submersibles plays a very important role in protecting the safety of submersible equipment and personnel. However, the diving sensor data is scarce and high-dimensional, so this paper proposes a submersible fault detection method, which is made up of feature selection m...

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Bibliographic Details
Main Authors: Penghui Zhao, Qinghe Zheng, Zhongjun Ding, Yi Zhang, Hongjun Wang, Yang Yang
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Sensors
Subjects:
fault detection
feature selection
data augmentation
high-dimensional sensor data
limited fault event
manned submersible
Online Access:https://www.mdpi.com/1424-8220/22/1/204

Internet

https://www.mdpi.com/1424-8220/22/1/204

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