Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding

Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding

Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is...

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Bibliographic Details
Main Authors: Xiang Wang, Yuan Zheng, Zhenzhou Zhao, Jinping Wang
Format: Article
Language:English
Published: MDPI AG 2015-07-01
Series:Sensors
Subjects:
high-dimensional data
fault diagnosis
feature extraction
dimensionality reduction
manifold learning
statistical locally linear embedding
Online Access:http://www.mdpi.com/1424-8220/15/7/16225

Internet

http://www.mdpi.com/1424-8220/15/7/16225

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