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Quaternion Based Thermal Condition Monitoring System

  • Wai Kit Wong
  • Chu Kiong Loo
  • Way Soong Lim
  • Poi Ngee Tan
Part of the Proceedings in Information and Communications Technology book series (PICT, volume 2)

Abstract

In this paper, we will propose a new and effective machine condition monitoring system using log-polar mapper, quaternion based thermal image correlator and max-product fuzzy neural network classifier. Two classification characteristics namely: peak to sidelobe ratio (PSR) and real to complex ratio of the discrete quaternion correlation output (p-value) are applied in the proposed machine condition monitoring system. Large PSR and p-value observe in a good match among correlation of the input thermal image with a particular reference image, while small PSR and p-value observe in a bad/not match among correlation of the input thermal image with a particular reference image. In simulation, we also discover that log-polar mapping actually help solving rotation and scaling invariant problems in quaternion based thermal image correlation. Beside that, log-polar mapping can have a two fold of data compression capability. Log-polar mapping can help smoother up the output correlation plane too, hence makes a better measurement way for PSR and p-values. Simulation results also show that the proposed system is an efficient machine condition monitoring system with accuracy more than 98%.

Keywords

Reference Image Thermal Image Invariant Problem Thermal Camera Fuzzy Relational Equation 
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 Tokyo 2010

Authors and Affiliations

  • Wai Kit Wong
    • 1
  • Chu Kiong Loo
    • 1
  • Way Soong Lim
    • 1
  • Poi Ngee Tan
    • 1
  1. 1.Faculty of Engineering and TechnologyMultimedia UniversityJln Ayer Keroh LamaMalaysia

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