Flame Monitoring System of Power Station Plant - A Survey

Mamta C. Mane*, J. S. Kulkarni**
* P.G. Scholar, Department of Electronic & Telecommunication Engineering , Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India.
** Assistant Professor, Department of Electronic & Telecommunication Engineering, Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India.
Periodicity:January - March'2018
DOI : https://doi.org/10.26634/jip.5.1.14289

Abstract

A thermal power plant plays an important role for generating the electricity. The thermal power plants require essential elements, which are fossil fuels, such as coal, oil, etc. Coal is burned to generate heat energy in the furnace. Hence, analysis of flame is very important when fuel combustion takes place in a furnace. Combustion quality plays an important role to reduce the wastage of fuel. The combustion quality of fuel is high and has the less wastage of fuel. As fossil fuels are more expensive in cost, Flame image monitoring system plays an important role in analysing the combustion quality. Flame image monitoring system involves capturing the flame image in different instants of time to check the quality of combustion with the help of Back Propagation Algorithm (BPA) and Ant Colony Optimization (ACO) technique (Sujatha et al., 2017). The quality of combustion also depends on the flame temperature. The intelligent sensors are used to monitor the flame temperature and Internet of things (IoT) is used to make the flame monitoring system smarter.

Keywords

Back Propagation Algorithm (BPA), Ant Colony Optimization (ACO), Internet of Things (IoT).

How to Cite this Article?

Mame,M.C., and Kulkarni,J.S.(2018). Flame Monitoring System of Power Station Plant - A Surveyi-manager’s Journal on Image Processing, 5(1), 33-37. https://doi.org/10.26634/jip.5.1.14289

References

[1]. BBC (n.d.). Generating Electricity. Retrieved from http://www.bbc.co.uk/schools/gcsebitesize/science/ orgateway/energyresources/generatingelectricityrev4s html
[2]. Bhavani, N. P., & Sujatha, K. (2006). Intelligent Estimation of NO Emissions by Flame Monitoring In Power x Station Using Internet of Things. ARPN Journal of Engineering and Applied Sciences, 12(3), 6677-6688.
[3]. Krishnan, P. H., & Vinoth, R. (2014). Monitoring and controlling the combustion quality in thermal power plant boiler using image processing and robotic arm. In Green Computing Communication and Electrical Engineering (ICGCCEE), 2014 International Conference on (pp. 1-4). IEEE.
[4]. Nagori, V. (2016). Fine tuning the parameters of back propagation algorithm for optimum learning performance. In Contemporary Computing and nd Informatics (IC3I), 2016 2 International Conference on (pp. 7-12). IEEE.
[5]. Shobanbabu, P., & Reddy, P. C. (2016). Ant based routing algorithm for videostreaming. In Communication and Electronics Systems (ICCES), International Conference on (pp. 1-6). IEEE.
[6]. Sujatha, K., Bhavani, N. P. G., Godhavari, T., Ponmagal, R. S., & Cao, S. Q. (2015). Smart Sensor for NO x and SO Emissions in Power Station Boilers (SSEPSB). Indian 2 Journal of Science and Technology, 8(27),1-7.
[7]. Sujatha, K., Bhavani, N. P., Reddy, T. K., & Kumar, K. R. (2017). Internet of Things for flame monitoring power station boilers. In Trends in Industrial Measurement and Automation (TIMA), 2017 (pp. 1-7). IEEE.
[8]. Sujatha, K., Pappa, N., & Kalaivani, A. (2011). Soft sensor for flue gas monitoring in power station boilers. In Process Automation, Control and Computing (PACC), 2011 International Conference on (pp. 1-6). IEEE.
[9]. Sujatha, K., Pappa, N., Kumar, K. S., & Nambi, U. S. (2013). Monitoring Power Station Boilers Using ANN and Image Processing. In Advanced Materials Research (Vol. 631, pp. 1154-1159). Trans Tech Publications.
[10]. Wikipedia. (n.d.). Power Station. Retrieved from https://en.wikipedia. org/wiki/Power-Station
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Pdf 35 35 200 20
Online 35 35 200 15
Pdf & Online 35 35 400 25

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.