Prediction for Abnormal Combustion State of Waste Plants with Multiple Fuzzy Relational Maps of Sensors

Abstract

In waste plants, we need to predict unstable combustion and control it appropriately for keeping combustion state stable. We have proposed a method for computing a stability degree based on fuzzy relational maps of many sensors, where we use only sensor values at the same time. In this paper, we propose a method for predicting combustion states after a certain time with multiple fuzzy relational maps of sensors. With the maps we evaluate samples from data for the maps and calculate the indices for the combustion states. We evaluate unknown data to predict combustion states after a certain time using the indices. We applied this method to data in one year of a waste plant. The result shows that multiple fuzzy relational maps can predict stable combustion states with very high accuracy and an abnormal combustion state with slightly high accuracy.