The Deep Convolutional Neural Network for NOx Emission Prediction of a Coal-Fired Boiler

Abstract

This paper presents a methodology for predicting NOx emissions of a coal-fired boiler by using real operation data, coal properties and CNN (Convolutional Neural Network). Two building blocks are carefully designed following the practical guidelines for the light weight CNN architecture design. Furthermore, the building blocks are used to develop the deep CNN-based model for NOx prediction. A comprehensive comparison among different prediction models based on DL (Deep Learning) shows that the proposed deep CNN-based prediction model outperforms other prediction models in terms of RMSE (Root Mean Square Error) criteria. The results indicate that the developed deep CNN-based prediction model has more excellent accuracy and better numerical stability. Besides, the architecture design of the DL-based prediction model has a significant impact on the performance of the prediction model. INDEX TERMS Coal-fired boiler, convolutional neural network, deep learning, NOx emission prediction.

A novel NOx prediction model using the parallel structure and convolutional neural networks for a coal‐fired boiler

“…In this section, a comparative analysis of different DL‐based NO x prediction models was conducted to assess the proposed deep CNN‐based model further. The outlines of these DL‐based models are described as follows: the LSTM‐based model consisting of a single LSTM network, 14 the LSTM‐based model composed of two stacked LSTM networks, 15 the DNN‐based model, 18 and the CNN‐based model 19 . Most of the hyperparameters used in these four models can be found in the original references.…”

“…However, their models' performance was heavily based on the training sets' quality 18 . Li and Hu built NO x prediction models based on the convolutional neural network (CNN) and did a detailed comparative analysis among different CNN‐based NO x prediction models 19 . Their studies suggested that it is a considerable alternative approach to build the NO x prediction model based on CNNs.…”

Causal analysis of nitrogen oxides emissions process in coal-fired power plant with LiNGAM

“…Many studies have applied LSTM and reported good performance in dynamic NOx prediction (Tan et al (2019); Yang et al (2020); Song et al (2022); Xie et al (2020); Wang et al (2022); Tuttle et al (2021)). Some studies have reported that convolutional neural networks (CNN) accurately predicted emissions of NOx from coal-fired boilers (Li and Hu (2020); Saif-Ul-Allah et al (2022,?)). In addition, deep hybrid neural networks also have been applied to CFB gas emission prediction (Hu et al (2020)).…”

Prediction of the 3D Distribution of NOx in a Furnace via CFD Data Based on ELM

“…This method is mainly focused on the NOx emission of the exhaust gas. In this regard, numerous algorithms, including statistical regression (Li et al, 2004;Chunlin Wang et al, 2018), support vector machine (Wei et al, 2013;Zhou et al, 2012;Ahmed et al, 2015;Lv et al, 2013), artificial neural network (ANN) (Chu et al, 2003;Ilamathi et al, 2013;Preeti and Sharad, 2013;Jacob and Tuttll, 2019), and deep learning (Li and Hu, 2020;Yang et al, 2020;Tan et al, 2019;Xie et al, 2020;Kang et al, 2017;Wang et al, 2017) are often used to predict the NOx concentration. Although remarkable achievements have been obtained in this area, the time complexity of support vector machines increases exponentially as the sample size increases.…”