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 a...

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Vydáno v:	Sensors (Basel, Switzerland) Ročník 15; číslo 7; s. 16225 - 16247
Hlavní autoři:	Wang, Xiang, Zheng, Yuan, Zhao, Zhenzhou, Wang, Jinping
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland MDPI AG 06.07.2015 MDPI
Témata:	Algorithms Classification Datasets dimensionality reduction Engineering Fault diagnosis feature extraction high-dimensional data manifold learning Pattern recognition Sensors statistical locally linear embedding Teaching methods China statistical locally linear embedding dimensionality reduction fault diagnosis feature extraction high-dimensional data manifold learning
ISSN:	1424-8220, 1424-8220
On-line přístup:	Získat plný text
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