基于小波分析的火箭发动机试验流量数据去噪处理  

Denoising of Rocket Engine Test Flow Data Based on Wavelet Analysis

作　　者：杨懿[1] 李达银 郭亚男 贾志杰 王永鹏 YANG Yi;LI Da-yin;GUO Ya-nan;JIA Zhi-jie;WANG Yong-peng(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：《宇航计测技术》2021年第2期54-60,共7页Journal of Astronautic Metrology and Measurement

摘　　要：在某型号火箭发动机试验中,液氧流量数据包含有大量的噪声成分,严重影响对发动机性能的评估。采用小波分析方法对含噪信号进行去噪处理。分析硬阈值、软阈值阈值去噪方法的特点。以信噪比作为选用Sym系和Db系小波基函数的衡量标准选取Sym5和Db9小波作为基函数。将Sym5、Db9小波基函数分别与自适应阈值选择无偏似然估计法(Rigrsure)、启发式阈值选择法(Heursure)进行组合对含噪数据进行去噪处理,将信噪比和相关系数作为去噪效果的评价指标。计算去噪后的数据与设计部门提供的理论数据的相对误差,结果显示Rigrsure和Db9基函数组合的去噪方法效果较好。该方法在火箭发动机试验数据去噪领域有重要的应用和推广价值。In the test of a certain type of rocket engine,the data of liquid oxygen flow contains a large number of noise components,which seriously affects the evaluation of engine performance.Wavelet analysis is used to denoise the noisy signal.The characteristics of hard threshold and soft threshold denoising methods are analyzed.The signal-to-noise ratio(SNR)is used as the criterion to select Sym series and DB series wavelet basis functions,and Sym5 and DB9 wavelets are selected as the basis functions.The Sym5 and DB9 wavelet basis functions are combined with adaptive threshold selection unbiased likelihood estimation(Rigrsure)and heuristic threshold selection(Heursure)respectively to denoise the noisy data,and the signal-to-noise ratio and correlation coefficient are used as the evaluation indexes of denoising effect.The relative error between the denoised data and the theoretical data provided by the design department is calculated,and the results show that the denoising effect of the combination of Rigrsure and DB9 basis function is better.This method has important application and promotion value in the field of rocket engine test data denoising.

关 键 词：火箭发动机 小波分析 流量 数据去噪 

分 类 号：V431[航空宇航科学与技术—航空宇航推进理论与工程]