• DocumentCode
    1776527
  • Title

    Neural network based data validation algorithm for pressure processes

  • Author

    Mounika, Batthina ; Raghu, Guntupalli ; Sreelekha, Surabhi ; Jeyanthi, R.

  • Author_Institution
    Dept. ECE, Amrita Vishwa Vidyapeetham, Bangalore, India
  • fYear
    2014
  • fDate
    10-11 July 2014
  • Firstpage
    1223
  • Lastpage
    1227
  • Abstract
    Effective Control of Complex process in power generation industries is a challenge to instrumentation engineers. Most importantly coordination of sensor functioning should be monitored regularly. So, a sensor validation and data reconciliation methods are adopted for monitoring the data and faulty data are replaced. In this paper neural network based data validation method is developed and tested for pressure sensor. For neural networks, back propagation algorithm is applied for obtaining an estimated value and then a fault detection method called SPRT (Sequential probability ratio test) is applied to identify the trueness of the sensor.
  • Keywords
    backpropagation; fault diagnosis; neurocontrollers; power generation control; pressure sensors; process control; sequential estimation; SPRT; back propagation algorithm; data reconciliation method; data validation algorithm; fault detection method; neural network; power generation industries; pressure sensor; process control; sensor validation method; sequential probability ratio test; Artificial neural networks; Biological neural networks; Instruments; Neurons; Process control; Training; Artificial Neural networks (ANN); Data validation; SPRT; back propagation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2014 International Conference on
  • Conference_Location
    Kanyakumari
  • Print_ISBN
    978-1-4799-4191-9
  • Type

    conf

  • DOI
    10.1109/ICCICCT.2014.6993147
  • Filename
    6993147