Wavelets pp 125-147 | Cite as

Wavelet Packet-Transform for Defect Severity Classification

  • Robert X. Gao
  • Ruqiang Yan


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.


Feature Vector Wavelet Packet Defect Severity Scatter Matrix Wavelet Packet Transform 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringUniversity of ConnecticutStorrsUSA
  2. 2.School of Instrument Science and EngineeringSoutheast UniversityNanjingChina, People’s Republic

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