基于隐马尔可夫模型的不稳定燃烧模式早期预测方法  

Early prediction method of unstable combustion mode based on hidden Markov model

作　　者：邓子江 刘勇[1,2] 张祥[1,2] 王锁芳 DENG Zijiang;LIU Yong;ZHANG Xiang;WANG Suofang(College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing Jiangsu 210016,China;Areo-Engine Thermal Environment and Structure Key Laboratory of Ministry of Industry and Information Technology(Nanjing University of Aeronautics and Astronautics),Nanjing Jiangsu 210016,China)

机构地区：[1]南京航空航天大学能源与动力学院,南京210016 [2]航空发动机热环境与热结构工业和信息化部重点实验室(南京航空航天大学),南京210016

出　　处：《计算机应用》2022年第S01期380-385,共6页journal of Computer Applications

摘　　要：不稳定燃烧存在多种模式,不同模式会导致后继燃烧状态的不同演化,对燃烧室燃烧模式的实时预测能够为抑制不稳定燃烧提供依据并提高燃烧室设计效率。首先对模型旋流燃烧室不同工况下不稳定燃烧特性进行实验研究,获得动态压力脉动数据;随后建立不稳定燃烧模式-压力脉动数据库;最后在该数据库的基础上,采用隐马尔可夫模型(HMM)作为学习和预测工具,建立模式与压力脉动信号之间的概率模型并对不稳定燃烧模式进行在线识别与预测。研究结果表明,基于实验数据的HMM方法能够在毫秒级准确预测不稳定燃烧是否发生,并且能够较准确识别不稳定燃烧模式。There are different modes of unstable combustion,which will lead to various evolution of combustion states.The real-time prediction of combustion modes in combustor can provide a basis for suppressing unstable combustion and improve the efficiency of combustor design.First of all,the experiment was conducted to study the unstable combustion characteristics of the model swirl combustor under different working conditions,and the dynamic pressure pulsation data was obtained.Secondly,an unstable combustion model-pressure pulsation database was established.Finally,on the basis of the database,Hidden Markov Model(HMM)was used as a learning and prediction tool to establish the probability model between the model and the pressure pulsation signal,and to identify and predict the unstable combustion mode online.The results of the study show that the HMM method based on experimental data can accurately predict the occurrence of unstable combustion at the millisecond level,and can accurately identify the unstable combustion mode.

关 键 词：早期预测 不稳定燃烧 隐马尔可夫模型 旋流燃烧室 燃烧诊断 

分 类 号：TP39[自动化与计算机技术—计算机应用技术] V231[自动化与计算机技术—计算机科学与技术]