Research Article Open Access

Soft Sensors for Monitoring Combustion Quality and Flue Gas Emissions in Power Station Boilers

Nallamilli P G Bhavani1, Kesavan Sujatha1 and Ponmagal Rajendran1
  • 1 Dr. M.G.R. Educational and Research Institute, India
American Journal of Applied Sciences
Volume 15 No. 1, 2018, 95-115

DOI: https://doi.org/10.3844/ajassp.2018.95.115

Submitted On: 15 February 2014
Published On: 7 February 2018

How to Cite: Bhavani, N. P. G., Sujatha, K. & Rajendran, P. (2018). Soft Sensors for Monitoring Combustion Quality and Flue Gas Emissions in Power Station Boilers. American Journal of Applied Sciences, 15(1), 95-115. https://doi.org/10.3844/ajassp.2018.95.115

Abstract

This research work includes a combination of Fisher’s Linear Discriminant (FLD) analysis by merging Radial Basis Function (RBF) Network and Back Propagation Algorithm (BPA) for monitoring the combustion conditions of a coal fired boiler. The CCD Camera is used to capture the two dimensional flame images. The features such as images, average intensity, area, brightness and orientation etc., of the flame are extracted after pre-processing the images. The FLD is applied to reduce the n-dimensional feature size to 2 dimensional feature size for faster learning of the RBF network. Also video processing has been done to extract three classes of images corresponding to different burning conditions of the flames. For various flame conditions, the corresponding temperatures and flue gas emissions are obtained using analyzers and sensors. The combustion quality indicates the air/fuel ratio which can be varied automatically. The proposed feed forward control scheme presents an alternative for the existing set-up for measuring SOx, NOx, CO and CO2 emissions that are detected from the samples collected at regular intervals of time in the laboratory or by using gas analyzers. Further training and testing of Parallel architecture of Radial Basis Function and Back Propagation Algorithm (PRBFBPA) with the data obtained has been done and the performance of the algorithms is presented.

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Keywords

  • Flame Image
  • Radial Basis Function Network
  • Back Propagation Network
  • Fisher’s Linear Discriminant
  • Temperature Monitoring
  • Monitoring Flue Gas Emissions
  • Combustion Quality
  • Parallel Architecture