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A New Waveform Signal Processing Method Based on Adaptive Clustering-Genetic Algorithms

[+] Author Affiliations
Noha Shaaban, Fukuzo Masuda, Hidetsugu Morota

Computer Software Development Company, Ltd., Tokyo, Japan

Paper No. ICONE14-89866, pp. 493-499; 7 pages
doi:10.1115/ICONE14-89866
From:
  • 14th International Conference on Nuclear Engineering
  • Volume 3: Structural Integrity; Nuclear Engineering Advances; Next Generation Systems; Near Term Deployment and Promotion of Nuclear Energy
  • Miami, Florida, USA, July 17–20, 2006
  • Conference Sponsors: Nuclear Engineering Division
  • ISBN: 0-7918-4244-4 | eISBN: 0-7918-3783-1
  • Copyright © 2006 by ASME

abstract

We present a fast digital signal processing method for numerical analysis of individual pulses from CdZnTe compound semiconductor detectors. Using Maxi-Mini Distance Algorithm and Genetic Algorithms based discrimination technique. A parametric approach has been used for classifying the discriminated waveforms into a set of clusters each has a similar signal shape with a corresponding pulse height spectrum. A corrected total pulse height spectrum was obtained by applying a normalization factor for the full energy peak for each cluster with a highly improvements in the energy spectrum characteristics. This method applied successfully for both simulated and real measured data, it can be applied to any detector suffers from signal shape variation.

Copyright © 2006 by ASME

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