小波包分解在液体火箭发动机试验流量数据去噪中的应用  

Application of Wavelet Packet Decomposition in Denoising of Liquid Rocket Engine Test Flow Data

作　　者：杨懿[1] 陈宇泽[1] 陈文丽[1] 王永鹏 贾志杰 Yang Yi;Chen Yuze;Chen Wenli;Wang Yongpeng;Jia Zhijie(Beijing Institute of Aerospace Testing Technology,Beijing 100074,China)

机构地区：[1]北京航天试验技术研究所,北京100074

出　　处：《质量与可靠性》2020年第6期1-5,11,共6页Quality and Reliability

摘　　要：在某次发动机试验中,液氧流量数据受未知干扰含有大量的噪声成分,严重影响比冲量、燃烧效率等关键参数的数值分析与计算。利用小波包树状分解分析在高、低频域描述细致、分析能力强的优点,以信噪比和相关系数作为评价各类型小波基分解效果的标准,选择Sym6和Db5两种小波基,设定合适的阈值和分解层数,对含噪流量信号进行去噪处理。通过与理论计算值的分析对比,验证了该方法的有效性。该方法在其他型号试验流量参数数据去噪中具有重要的推广和应用价值。In an engine test,the data of liquid oxygen flow is interfered by unknown information contained a lot of noises which seriously affect the numerical analysis and calculation of the key parameters such as specific impulse and combustion efficiency.Using the advantages of wavelet packet tree like decomposition analysis in high and low frequency domain,signal-to-noise ratio and correlation coefficient are used to evaluate the decomposition effect of various types of wavelet bases.Two wavelet bases,sym6 and db5,are selected,and appropriate threshold and decomposition levels are set to denoise the noisy traffic signals.The effectiveness of the method is verified by comparing with the theoretical calculation value.This method has an important promotion and application value in other types of test flow parameter data denoising.

关 键 词：发动机试验 流量 小波包 去噪 

分 类 号：V434[航空宇航科学与技术—航空宇航推进理论与工程]