Online Tool Wear Monitoring via Long Short-Term Memory (LSTM) Improved Particle Filtering and Gaussian Process Regression

Accurate prediction of tool wear plays a vital role in improving machining quality in intelligent manufacturing. However, traditional Gaussian Process Regression (GPR) models are constrained by linear assumptions, while conventional filtering algorithms struggle in noisy environments with low signal...

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Bibliografische gegevens

Hoofdauteurs:	Hui Xu, Hui Xie, Guangxian Li
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	MDPI AG 2025-05-01
Reeks:	Journal of Manufacturing and Materials Processing
Onderwerpen:	tool wear LSTM GPR kernel function KPCA-SPCA
Online toegang:	https://www.mdpi.com/2504-4494/9/5/163
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