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Feature Selection of Frequency Spectrum for Modeling Difficulty to Measure Process Parameters

  • Jian Tang
  • Li-Jie Zhao
  • Yi-miao Li
  • Tian-you Chai
  • S. Joe Qin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7368)

Abstract

Some difficulty to measure process parameters can be obtained using the vibration and acoustical frequency spectra. The dimension of the frequency spectrum is very large. This poses a difficulty in selecting effective frequency band for modeling. In this paper, the partial least squares (PLS) algorithm is used to analyze the sensitivity of the frequency spectrum to these parameters. A sphere criterion is used to select different frequency bands from vibration and acoustical spectrum. The soft sensor model is constructed using the selected vibration and acoustical frequency band. The results show that the proposed approach has higher accuracy and better predictive performance than existing approaches.

Keywords

soft sensor feature selection frequency spectrum partial least squares 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jian Tang
    • 1
    • 4
  • Li-Jie Zhao
    • 2
    • 4
  • Yi-miao Li
    • 3
  • Tian-you Chai
    • 4
  • S. Joe Qin
    • 5
  1. 1.Unit 92941, PLAHuludaoChina
  2. 2.College of Information EngineeringShenyang University, of Chemical TechnologyShenyangChina
  3. 3.Control Engineering of ChinaNortheastern UniversityShenyangChina
  4. 4.Research Center of AutomationNortheastern UniversityShenyangChina
  5. 5.Work Family Department of Chemical Engineering and Materials Science, Ming Hsieh, Department of Electrical EngineeringUniversity of Southern CaliforniaLos AngelesUSA

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