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Study on Fault Diagnosis of Rolling Mill Main Transmission System Based on EMD-AR Model and Correlation Dimension

  • Guiping Dai
  • Manhua Wu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5755)

Abstract

In order to improve the fault diagnosis accuracy of rolling mill main transmission system, a fault feature extraction method based on EMD (Empirical Mode Decomposition)-AR model and Correlation Dimension is proposed. In the proposed method, EMD is used to decompose the vibration signal of complex machine into several intrinsic mode functions (IMFs), then the AR models of some IMF components which contain main fault information are constructed respectively. Finally, the correlation dimensions of auto-regressive parameters in AR models are calculated. Analysis of the experimental results shows that this method not only can reflect the state changes of dynamic system profoundly and detailedly, but also can realize the separation of state features, thus it may judge the fault conditions of rolling mill main transmission system effectively.

Keywords

Empirical mode decomposition AR model Correlation dimension Rolling mill main transmission system Fault diagnosis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Guiping Dai
    • 1
    • 2
  • Manhua Wu
    • 3
  1. 1.JiangSu Province Support Software Engineering R&D Center for Modern Information Technology Application in Enterprise 
  2. 2.Department of Electronic & Information EngineeringSuzhou Vocational UniversitySuzhouChina
  3. 3.Department of Foreign Languages and International ExchangeSuzhou Vocational UniversitySuzhouChina

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