固体燃料燃烧动态过程温度及多组分浓度原位协同检测方法研究

固体燃料燃烧产物的生成与转化是涉及多种气体及基团参与的复杂化学反应过程。原位协同获取燃烧动态过程火焰温度及多种组分浓度信息，对于深刻认识燃烧产物的生成与转化机理具有重要价值。本项目拟将TDLAS和LIBS技术融合，获取固体燃料燃烧过程关键气体(CH4、CO2、CO、H2O等)、主要元素(C、H、O、N等)及相关基团(CN、C2等)的光谱，分析光谱特性及等离子体的演化规律，揭示TDLAS与LIBS融合的互影响机制，建立无影响或微小影响的融合策略；构建变光程下的温度及气体浓度同步反演算法及多元素浓度协同预测模型，实现温度和多组分浓度的协同检测；明确固体燃料燃烧过程有效光谱信号及干扰信号的来源及特性，克服固体燃料的基体效应及燃烧热边界效应、光学干涉、火焰辐射及碳烟消光等关键问题对光谱检测的影响，提高光谱原位检测精度。为固体燃料燃烧过程组分生成与转化机理研究奠定实验数据基础。

The formation and transformation of solid fuel combustion products is a complex chemical reaction process involving a variety of gases and radicals. In situ and collaborative acquisition of flame temperature and various product concentrations in combustion dynamic process is of great value to deeply understand the formation and transformation mechanism of combustion products. In this project, we plan to combine TDLAS and LIBS technology to simultaneously detect and analyze the spectra of key gas products (CH4, CO2, CO, H2O, etc.), main elements (C, H, O, N, etc.) and groups (CN, C2, etc.) in solid fuel combustion process. Study the spectral characteristics and the evolution of plasma, reveal the mutual influence mechanism of the fusion of TDLAS and LIBS, and establish a fusion strategy without (or small) interference; Construct a synchronous inversion algorithm for temperature and gas concentration under variable optical path and a simultaneous prediction model of multi-element concentration to realize the coordinated detection of temperature and multi-product concentration. We plan to systematically study the sources and characteristics of effective spectral signals and interference signals in the combustion process of solid fuels, and establish methods to optimize the matrix effect of solid fuels, combustion thermal boundary effect, optical interference, soot absorption and other key issues , so as to improve the spectral in-situ detection accuracy. It will lay a experimental data foundation for the research on the formation and conversion mechanism of products during the combustion of solid fuels.