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Issue title: Soft computing and intelligent systems: Tools, techniques and applications
Guest editors: Sabu M. Thampi and El-Sayed M. El-Alfy
Article type: Research Article
Authors: Sreedhanya, L.R.a; b | Varghese, Abia | Nair, Madhu S.a; * | Wilscy, M.a
Affiliations: [a] Department of Computer Science, University of Kerala, Kariavattom, Thiruvananthapuram, Kerala, India | [b] Control and Instrumentation Group, Centre for Development of Advanced Computing, Thiruvananthapuram, Kerala, India
Correspondence: [*] Corresponding author. Madhu S. Nair, Department of Computer Science, University of Kerala, Kariavattom, Thiruvananthapuram 695581, Kerala, India. Tel.: +919447364158; Fax: +91 471 2307158; E-mail: madhu_s_nair2001@yahoo.com.
Abstract: Based on a flame image processing technology, a fuzzy based temperature monitoring system in a rotary kiln was reported. In this paper, we propose a Fuzzy based flame analysis, which consider Red, Green and Blue intensity planes, to measure the temperature from the flame image. The proposed approach integrates RGB intensity as fuzzified input variables, temperature as defuzzified output variables and fuzzy inference rules based Mamdani models. Based on the color characteristics of burning flame, temperature of different flame zones are located using a fuzzy logic controller. The temperature level at hotspot area is the highest and through the fuzzy analysis we were able to identify hotspot area from the flame image. In order to evaluate the performance of the proposed method, quantitative metric such as f-measure has been used and it was found that the f-measure metric yields high accuracy for the hotspot area. The visual inspection of the results along with the f-measure values showed the superiority of our work. Experimental results indicate that the proposed approach can be applied to a high resolution video flame image.
Keywords: Temperature mapping, flame image analysis, fuzzy inference system, rotary kiln, Mamdani model
DOI: 10.3233/JIFS-169249
Journal: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 4, pp. 3059-3067, 2017
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