Optical temperature field reconstruction based on joint algorithm of ART and neural network

Abstract

In order to obtain more accurate online information of boiler temperature field and achieve the purpose of real-time measurement and monitoring of flame temperature field distribution in the furnace, an algebraic reconstruction-neural network algorithm (ART-NN) based on optical tomography measurement was proposed. The algorithm combines the advantages of Algebraic Reconstruction Algorithm (ART) and BP neural network. Using this algorithm in the case of adding random errors, a variety of classical temperature fields are numerically simulated. The results show that the stability and reconstruction results of the ART-NN algorithm are better than those of traditional algorithms such as ART and TSVD under the same error level. Optical tomography temperature field measurement provides an efficient method.