Data distribution based kernel parameter optimization for fault classifier

Research output: Contribution to journalArticlepeer-review

Abstract

Aimed at parameter optimization of fault classifier, the principle of kernel parameter optimization based on data distribution was discussed. Then a simplified algorithm was proposed in order to achieve parameter optimization of fault classifier for turbo-generator sets. Testing results show that the classification capability of the fault classifier can be improved by using the simplified algorithm with high efficiency. But the adaptability of the simplified algorithm needs to be improved.

Original languageEnglish
Pages (from-to)11-14
Number of pages4
JournalZhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis
Volume26
Issue number1
StatePublished - Mar 2006

Keywords

  • Data distribution
  • Fault classifier
  • Kernel functions
  • Parameter optimization
  • Steam turbo-generator sets
  • Support vector machine

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