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Principal Component Analysis Based Data Reconciliation for a Steam Metering Circuit

  • C. Reddy Varshith
  • J. Reddy Rishika
  • S. Ganesh
  • R. JeyanthiEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 898)

Abstract

Data reconciliation (DR) is playing an important role in reducing random errors usually occurred in measured data. Principal component analysis (PCA), on the other end, deals with the reduction of dimensions when there is large number of variables involved in a complex process. In this paper, we bring these two techniques together to deal with random errors in measured data of a steam metering circuit. The results prove that PCA-based DR is effective in dealing with random errors than DR alone. The study is also extended to work on a partially measured system where only partial information of the system is known.

Keywords

PCA DR Steam metering circuit 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • C. Reddy Varshith
    • 1
  • J. Reddy Rishika
    • 1
  • S. Ganesh
    • 1
  • R. Jeyanthi
    • 1
    Email author
  1. 1.Department of Electronics and Communication EngineeringAmrita School of Engineering, Amrita Vishwa VidyapeethamBengaluruIndia

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