单喷嘴模型火箭发动机中高频不稳定燃烧的预测  

Prediction of Thermoacoustic Instability in a Single-injector Model Rocket Combustor

作　　者：王治宇 陈朋 林伟 仝毅恒 郭康康 黄卫东 聂万胜 WANG Zhiyu;CHEN Peng;LIN Wei;TONG Yiheng;GUO Kangkang;HUANG Weidong;NIE Wansheng(Department of Aerospace Science and Technology,Space Engineering University,Beijing 101416,China)

机构地区：[1]航天工程大学宇航科学与技术系,北京101416

出　　处：《宇航学报》2024年第3期478-486,共9页Journal of Astronautics

摘　　要：为实现模型火箭发动机中高频不稳定燃烧的早期辨识和提前预测,建立了基于数据驱动的预测框架。该框架基于递归矩阵对燃烧噪声的非线性特征进行提取,并利用深度学习模型对这些特征进行训练和预测。以单喷嘴模型火箭发动机为例,基于热试车试验中的动态压力信号数据,开展了高频不稳定燃烧的预测,可提前约35 ms预测不稳定燃烧的发生。共使用25组动态压力数据,其中包含了不同燃烧室构型的热试车试验数据。对预测框架进行交叉验证后,结果表明模型的预测准确率高于95%,说明了该预测框架的有效性和鲁棒性。To achieve early detection and prediction of high-frequency unstable combustion in model rocket engines,a data-driven prediction framework is established.This framework extracts recurrence matrices for nonlinear feature extraction of combustion noise,and utilizes deep learning models for training and prediction.Based on the dynamic pressure signal measured from the hot-fire tests of a single-injectors rocket combustor,the prediction of combustion instability is carried out,which can predict the occurrence of combustion instability approximately 35 ms in advance.Altogether 25 groups of dynamic pressure datasets are used,including experiments with different combustion chamber geometries.The results of cross validation upon the prediction framework show that the prediction accuracy of the framework was above 95%,which indicates the effectiveness and robustness of the prediction framework.

关 键 词：火箭发动机 燃烧不稳定性 深度学习 混沌分析 

分 类 号：V431[航空宇航科学与技术—航空宇航推进理论与工程]