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Grinding acoustic emission classification in terms of mechanical behaviours

Chen, Xun and Griffin, James Marcus (2007) Grinding acoustic emission classification in terms of mechanical behaviours. Key Engineering Materials, 329. pp. 15-20. ISSN 1662-9795

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Abstract

The material removal in grinding involves rubbing, ploughing and cutting. For grinding
process monitoring, it is important to identify the effects of these different phenomena experienced during grinding. A fundamental investigation has been made with single grit cutting tests. Acoustic Emission (AE) signals would give the information relating to the groove profile in terms of material removal and deformation. A combination of filters, Short-Time Fourier Transform (STFT), Wavelets
Transform (WT), statistical windowing of the WT with the kurtosis, variance, skew, mean and time
constant measurements provided the principle components for classifying the different grinding
phenomena. Identification of different grinding phenomena was achieved from the principle
components being trained and tested against a Neural Network (NN) representation.

Item Type: Article
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Schools: School of Computing and Engineering
School of Computing and Engineering > Centre for Precision Technologies
School of Computing and Engineering > Centre for Precision Technologies > Advanced Machining Technology Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
School of Computing and Engineering > Informatics Research Group > XML, Database and Information Retrieval Research Group
School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering > Informatics Research Group
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Depositing User: Cherry Edmunds
Date Deposited: 03 Jun 2009 10:06
Last Modified: 10 Dec 2010 10:02
URI: http://eprints.hud.ac.uk/id/eprint/4595

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