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Wavelets pp 125–147Cite as

Wavelet Packet-Transform for Defect Severity Classification

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Abstract

Once a defect is detected, the next question that comes up naturally is how severe the defect is. Since machine downtime is physically rooted in the progressive degradation of defects within the machine’s components, accurate assessment of the severity of defect is critically important in terms of providing input to adjusting the maintenance schedule and minimizing machine downtime. This chapter describes how wavelet packet transform (WPT)-based techniques can classify machine defect severity, with specific application to rolling bearings.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, University of Connecticut, Storrs, CT, 06269-3139, USA

    Robert X. Gao

  2. School of Instrument Science and Engineering, Southeast University, Nanjing, Jiangsu, China, People’s Republic

    Ruqiang Yan

Authors
  1. Robert X. Gao
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  2. Ruqiang Yan
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Corresponding author

Correspondence to Robert X. Gao .

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© 2011 Springer Science+Business Media, LLC

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Gao, R.X., Yan, R. (2011). Wavelet Packet-Transform for Defect Severity Classification. In: Wavelets. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1545-0_8

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  • DOI: https://doi.org/10.1007/978-1-4419-1545-0_8

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  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-1544-3

  • Online ISBN: 978-1-4419-1545-0

  • eBook Packages: EngineeringEngineering (R0)

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