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    Frequency as a key parameter in discriminating the failure types of thermal barrier coatings: Cluster analysis of acoustic emission signals

    Access Status
    Fulltext not available
    Authors
    Yang, L.
    Kang, H.
    Zhou, Y.
    Zhu, W.
    Cai, C.
    Lu, Chunsheng
    Date
    2015
    Type
    Journal Article
    
    Metadata
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    Citation
    Yang, L. and Kang, H. and Zhou, Y. and Zhu, W. and Cai, C. and Lu, C. 2015. Frequency as a key parameter in discriminating the failure types of thermal barrier coatings: Cluster analysis of acoustic emission signals. Surface & Coatings Technology. 264: pp. 97-104.
    Source Title
    Surface & Coatings Technology
    DOI
    10.1016/j.surfcoat.2015.01.014
    ISSN
    0257-8972
    School
    Department of Mechanical Engineering
    URI
    http://hdl.handle.net/20.500.11937/27294
    Collection
    • Curtin Research Publications
    Abstract

    A key parameter in discriminating the failure types of thermal barrier coatings (TBCs) was found out by using the k-means cluster analysis of acoustic emission (AE) signals. It is shown that there are five classes of mechanisms, including surface vertical cracks, opening interface cracks, sliding interface cracks, substrate deformation and macroscopic cleavage or spallation. Except for the last one, the other four classes can be clearly distinguished from their peak frequency distributions in the ranges of 170–250, 400–500, 260–350 and 40–150 kHz, respectively. However, AE signals overlap with each other in other parameter spaces, e.g., amplitude, energy, rise time, and duration time. The results indicate that the frequency can be applied to identify the AE source mechanisms in TBCs.

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