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ART-Artificial Immune Network and Application in Fault Diagnosis of the Reciprocating Compressor

  • Maolin Li
  • Na Wang
  • Haifeng Du
  • Jian Zhuang
  • Sun’an Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4222)

Abstract

Inspired by complementary strategies, a new fault diagnostic method, which integrates with the Adaptive Resonance Theory (ART) and Artificial Immune Network (AIN), is proposed in this paper. With the help of clustering of ART neural network, the vaccines that image features of data set are extracted effectively, and then an AIN named aiNet is adopted to realize data compression. Finally the memory antibodies optimized by aiNet can be used to recognize each feature of original dataset and to realize fault diagnosis. The experimental results show that the approach is useful and efficient for the fault diagnosis of the multilevel reciprocating compressor.

Keywords

Artificial Immune System Immune Network Adaptive Resonance Theory Suppression Threshold Reciprocating Compressor 
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-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Maolin Li
    • 1
  • Na Wang
    • 1
  • Haifeng Du
    • 1
  • Jian Zhuang
    • 1
  • Sun’an Wang
    • 1
  1. 1.Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing SystemXi’an Jiaotong UniversityXi’anChina

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