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Characterizing acoustic emission signals for the online monitoring of a fluid magnetic abrasives finishing process

Sun, Huanwu, Wang, Juan, Longstaff, Andrew P. and Gu, Fengshou (2017) Characterizing acoustic emission signals for the online monitoring of a fluid magnetic abrasives finishing process. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science. ISSN 0954-4062

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Abstract

To implement an automated fluid magnetic abrasive finishing process, an online monitoring scheme is proposed based on characterizing acoustic emission signals in this paper. According to the material removal mechanisms during the fluid magnetic abrasive finishing process, the acoustic emission generation and characteristics are predicted analytically to be dominated by the interactions between the surface asperities and the abrasive particles. Moreover, the interactions and corresponding acoustic emission events will become weaker as the finishing process progresses and the surface becomes smoother. Experimental studies show that the amplitude and the occurrence rate of continuous acoustic emission waves and intermediate bursts reduce gradually with the progression of the finishing process. Based on these features, root mean squared values and burst occurrence rates, being of the lowest computational requirements, are suggested as online monitoring parameters for an automated and intelligent finishing in fluid magnetic abrasive manufacturing. The proposed method is verified experimentally, showing that the root mean squared values are highly consistent with the measured surface roughness values, which confirms the dynamic mechanisms between the fluid magnetic abrasive finishing and acoustic emission generation sources examined.

Item Type: Article
Uncontrolled Keywords: Fluid magnetic abrasive finishing, acoustic emission, precision machining, surface morphology, intelligent manufacturing
Subjects: T Technology > T Technology (General)
T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
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Depositing User: Sally Hughes
Date Deposited: 02 Jun 2017 10:29
Last Modified: 02 Jun 2017 16:35
URI: http://eprints.hud.ac.uk/id/eprint/32091

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