ARTIFICIAL NEURAL NETWORK BASED ONLINE SENSOR CALIBRATION AND COMPENSATION

Authors

  • Shakeb A. Khan
  • Tarikul Islam
  • Gulshan Husain

DOI:

https://doi.org/10.47839/ijc.6.3.454

Keywords:

Artificial neural networks, calibration, compensation, sensor, inverse modeling, nonlinearity

Abstract

This paper presents an artificial neural network (ANN) based generalized online method for sensor response linearization and calibration. Inverse modeling technique is used for sensor response linearization. Multilayer ANN is used for inverse modeling of sensor. The inverse model based technique automatically compensates the associated nonlinearity and estimates the measurand. The scheme is coded in MATLAB® for offline training and for online measurement and successfully implemented using NI PCI-6221 Data Acquisition (DAQ) card and LabVIEW® software. Manufacturing tolerances, environmental effects, and performance drifts due to aging bring up a need for frequent calibration, this ANN based inverse modeling technique provides greater flexibility and accuracy under such conditions.

References

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Published

2014-08-01

How to Cite

Khan, S. A., Islam, T., & Husain, G. (2014). ARTIFICIAL NEURAL NETWORK BASED ONLINE SENSOR CALIBRATION AND COMPENSATION. International Journal of Computing, 6(3), 74-78. https://doi.org/10.47839/ijc.6.3.454

Issue

2007, Volume 6, Issue 3

Section

Articles

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