摘要
在航空发动机风扇试验件稳态条件下转速受载荷和电压等影响会出现波动,导致试验件离散噪声频率发生偏移,采用传统频域线性平均(FLAM)算法无法消除转速波动对信号处理影响。为提高风扇离散噪声数据处理精度,提出基于等角度插值的时域同步平均(TSAM-EAI)算法。通过数值方法对TSAM-EAI算法进行验证,在此基础上采用TSAM-EAI算法进行风扇部件噪声试验数据分析。数值仿真结果以及试验分析结果表明:TSAM-EAI算法可以消除转速波动影响,能够准确拾取转/静干涉噪声和激波噪声的频率和幅值。针对风扇试验件,相对于传统算法,TSAM-EAI算法低频噪声分析幅值约高2~3 dB,高频噪声幅值约高6~8 dB,能够准确分析风扇前传噪声模态特征,实现对风扇离散噪声水平的准确评估。
Under steady-state conditions of an aeroengine fan test,rotor speed fluctuations caused by load and voltage variations lead to frequency shifts in discrete noise signals.The traditional Frequency-Domain Linear Averaging Method(FLAM)cannot eliminate the impact of rotational speed fluctuations on signal processing.To improve the data processing accuracy of fan discrete noise,a Time-Domain Synchronous Averaging Method based on Equal Angle Interpolation(TSAM-EAI)algorithm was proposed.The TSAM-EAI algorithm was verified numerically and subsequently applied to fan component test noise data analysis.Numerical and test results show that the TSAM-EAI algorithm can eliminate the influence of rotational speed fluctuations and accurately capture the frequency and amplitude of rotor-stator interference noise and shock noise.For the fan test article,compared with the frequency domain averaging method,the TSAM-EAI algorithm yields approximately 2~3 dB higher amplitude in low-frequency noise analysis,and 6~8 dB higher amplitude in high-frequency noise analysis.The method enables precise evaluation of forward-propagating fan noise modal characteristics and achieves accurate assessment of fan discrete noise levels.
作者
许志远
杨明绥
张健新
王萌
XU Zhi-yuan;YANG Ming-sui;ZHANG Jian-xin;WANG Meng(AECC Shenyang Engine Research Institute,Shenyang 110015,China;AECC Gas Turbine Company,Shenyang 110000,China)
出处
《航空发动机》
北大核心
2025年第3期30-36,共7页
Aeroengine
基金
国家级研究项目资助。
关键词
风扇
离散噪声
时域同步平均
等角度插值
fan
discrete noise
time-domain synchronous averaging method
equal angle interpolation
作者简介
许志远(1991),男,硕士,工程师。
