Temperature mapping of a rotary kiln using fuzzy logic

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.