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Fuzzy pattern recognition of AE signals for grinding burn

Liu, Qiang, Chen, Xun and Gindy, Nabil (2005) Fuzzy pattern recognition of AE signals for grinding burn. International Journal of Machine Tools and Manufacture, 45 (7-8). pp. 811-818. ISSN 08906955

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    Abstract

    Grinding burn is a common phenomenon of thermal damage that has been one of the main constraints in grinding difficult-to-machine materials. Grinding burn damages materials and degrades properties, by causing tensile residual stresses or microfractures in the workpiece surface. Numerous methods have been proposed to identify grinding burn. However, the main problems of current methods are their sensitivity and robustness. This paper describes a new method of grinding burn identification with highly sensitive acoustic emission (AE) techniques. The wavelet packet transform is used to extract features from AE signals and fuzzy pattern recognition is employed for optimising features and identifying the grinding status. Experimental results show that the accuracy of grinding burn recognition is satisfactory.

    Item Type: Article
    Additional Information: UoA 25 (General Engineering)
    Subjects: T Technology > TJ Mechanical engineering and machinery
    T Technology > TS Manufactures
    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
    Related URLs:
    Depositing User: Graham Stone
    Date Deposited: 20 Oct 2008 13:06
    Last Modified: 10 Dec 2010 10:08
    URI: http://eprints.hud.ac.uk/id/eprint/2298

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