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The Fault Diagnosis Model Established Based on RVM

  • Yahui Wang
  • An YunEmail author
  • Qinghong Ye
  • Yunfeng Zhao
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 890)

Abstract

This paper introduces the application of Relevance Vector Machine (RVM) in fault diagnosis. First, the theoretical contents of RVM including the algorithm characteristics, the derivation of mathematical models, the characteristics of kernel functions and multimode classification are introduced. Then, the multi-classification fault diagnosis model of building electrical system is established by using RVM. Finally, the experimental results show that the RVM model has good classification effect on small sample data.

Keywords

Fault diagnosis Relevance vector machine Small sample data 

Notes

Acknowledgements

The project was partially supported by “The Fundamental Research Funds for Beijing University of Civil Engineering and Architecture”, Beijing, China with the grant No. X18191.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Electrical and Information EngineeringBeijing University of Civil Engineering & ArchitectureBeijingChina
  2. 2.Shanghai Aerospace Energy LTDShanghaiChina

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