Prediction of SO<sub>2</sub> Emission Concentration from Sludge IncinerationBased on ERT Model with BO-TPE Optimization

LUO Song; WANG Lihua; WANG Fei

doi:10.19805/j.cnki.jcspe.2026.240709

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Prediction of SO₂ Emission Concentration from Sludge IncinerationBased on ERT Model with BO-TPE Optimization

更新时间：2026-10-10

- Prediction of SO₂ Emission Concentration from Sludge IncinerationBased on ERT Model with BO-TPE Optimization
- Chinese Journal of Power Engineering Vol. 46, Issue 2, Pages: 174-182(2026)
- 作者机构：
  
  1. 浙江大学能源高效利用全国重点实验室,浙江,杭州,310027
  2. 上海城投污水处理有限公司,上海,201203
- 作者简介：
- 基金信息：
- DOI：10.19805/j.cnki.jcspe.2026.240709
  CLC：
- Online First：10 February 2026，
  
  Published：10 February 2026
- 稿件说明：
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罗松,王丽花,王飞. 基于BO-TPE优化ERT模型的污泥焚烧SO₂排放预测动力工程学报, 2026, 46(2): 174-182 https://doi. DOI: 10.19805/j.cnki.jcspe.2026.240709.

org/10.19805/j.cnki.jcspe.2026.240709
罗松,王丽花,王飞. 基于BO-TPE优化ERT模型的污泥焚烧SO₂排放预测动力工程学报, 2026, 46(2): 174-182 https://doi. DOI: 10.19805/j.cnki.jcspe.2026.240709. DOI：

org/10.19805/j.cnki.jcspe.2026.240709 DOI：

摘要

为提高污泥焚烧过程中SO

排放的预测精度以优化焚烧与烟气处理工况

提出了一种高效稳定的SO

排放混合预测模型。首先

以鼓泡流化床污泥焚烧系统为研究对象

从火焰图像中提取静态与动态火焰特征

并结合分布式控制系统(DCS)参数构建输入特征

排放浓度设为模型输出。然后

利用互信息(MI)确定SO

与各输入特征的最优滞后时间并据此进行数据重组。最终构建基于树结构的贝叶斯优化(BO-TPE)的极端随机树(ERT)预测模型

并与多种主流预测模型进行性能对比。结果表明:基于BO-TPE优化的ERT模型相关系数

为0.93

平均绝对百分比误差(MAPE)小于3%

适用于污泥焚烧系统SO

排放的在线预测与过程优化控制。

Abstract

To enhance the prediction accuracy of SO

emissions during sludge incineration process and optimize incineration and flue gas treatment conditions

an efficient and stable hybrid prediction model for SO

emissions was prorosed. First

using a bubbling fluidized bed sludge incineration system as the research subject

static and dynamic flame features were extracted from flame images and the input features were set combined with distributed control system (DCS) parameters

while SO

emission concentration was set as the model output. Subsequently

mutual information (MI) was employed to determine the optimal lag time between SO

and each input feature

guiding data reorganization. Finally

the extremely randomized trees (ERT) model based on Bayesian optimization-TPE (BO-TPE) was constructed and compared with multiple mainstream prediction models. Results show that the BO-TPE-optimized ERT model achieves correlation coefficient

of 0.93 with mean absolute percentage error(MAPE) below 3%

making it suitable for online prediction and process optimization control of SO

emissions in sludge incineration systems.

关键词

Keywords

references

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Prediction of SO2 Emission Concentration from Sludge IncinerationBased on ERT Model with BO-TPE Optimization

DOI：10.19805/j.cnki.jcspe.2026.240709

摘要

Abstract

关键词

Keywords

references

Prediction of SO₂ Emission Concentration from Sludge IncinerationBased on ERT Model with BO-TPE Optimization