Combustion Stability Prediction of Hazardous Waste Rotary Kiln Based on Flame Image

LUO Song; ZOU Liangdong; CUI Haibin; WU Zuhang; LIU Haiyun; WANG Fei

doi:10.19805/j.cnki.jcspe.2025.240336

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Combustion Stability Prediction of Hazardous Waste Rotary Kiln Based on Flame Image

更新时间：2026-10-10

- Combustion Stability Prediction of Hazardous Waste Rotary Kiln Based on Flame Image
- Chinese Journal of Power Engineering Vol. 45, Issue 7, Pages: 1109-1115(2025)
- 作者机构：
  
  1. 浙江大学能源清洁利用国家重点实验室,浙江,杭州,310027
  2. 中国节能环保集团有限公司,北京,100082
  3. 浙江省特种设备科学研究院,浙江,杭州,310009
- 作者简介：
- 基金信息：
- DOI：10.19805/j.cnki.jcspe.2025.240336
  CLC：
- Online First：14 July 2025，
  
  Published：2025
- 稿件说明：
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罗松,邹良栋,崔海滨,吴祖航,刘海云,王飞. 基于火焰图像的危险废物回转窑燃烧稳定性预测动力工程学报, 2025, 45(7): 1109-1115 https://doi.

org/10.19805/j.cnki.jcspe.2025.240336
罗松,邹良栋,崔海滨,吴祖航,刘海云,王飞. 基于火焰图像的危险废物回转窑燃烧稳定性预测动力工程学报, 2025, 45(7): 1109-1115 https://doi. DOI： 10.19805/j.cnki.jcspe.2025.240336.

org/10.19805/j.cnki.jcspe.2025.240336 DOI：

摘要

在回转窑焚烧处置危险废物的过程中

针对传统燃烧诊断方法存在依赖人工观测、缺乏实时性等问题

提出了一种基于图像的回转窑火焰燃烧稳定性预测模型。通过搭建中试实验平台

利用CCD相机获取回转窑内火焰燃烧的实时图像

从这些火焰图像中提取包括图像平均灰度、火焰有效面积、火焰高温面积、火焰高温面积率、质心偏移距离和圆形度6种火焰特征量

然后基于主成分分析和支持向量机建立了火焰燃烧稳定性预测模型

最后通过回转窑现场实验验证模型的有效性。结果表明:该模型能够实时监测并预测回转窑的燃烧状态

为操作人员提供决策支持

该模型在实际应用中表现出良好的预测准确性和实用性。

Abstract

In the process of burning hazardous waste in a rotary kiln

an image-based rotary kiln flame combustion stability prediction model was proposed to address the problems of relying on manual observation and lack of real-time performance in traditional combustion diagnostic methods. By building a pilot experimental platform

the CCD camera was used to obtain real-time images of flame combustion in the rotary kiln

and six flame feature quantities were extracted from these flame images

including average gray scale

effective flame area

high temperature area of flame

high temperature area rate of flame

centroid offset distance and circularity

and then a flame combustion stability prediction model was established based on the principal component analysis and support vector machine. Finally

the effectiveness of the model was verified by field experiments. Results show that the model can monitor and predict the combustion state of rotary kiln in real time and provide decision support for operators

and shows good prediction accuracy and practicability in practical application.

关键词

Keywords

references

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