| 一种基于EMD的低湍流度信号处理分析方法 |
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| 引用本文： | 朱博,彭强,汤更生.一种基于EMD的低湍流度信号处理分析方法[J].实验流体力学,2016,30(5):74-79. |
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| 作者姓名： | 朱博 彭强 汤更生 |
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| 作者单位： | 中国空气动力研究与发展中心 设备设计及测试技术研究所, 四川 绵阳 621000 |
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| 摘 要： | 采用热线风速仪在3座典型低速风洞中进行了流场湍流度测量，这3座低速风洞包括1个低湍流风洞、1个常规闭口风洞和1个开口射流风洞。针对湍流信号通常受噪声干扰的问题，在湍流度值处理中引入了经验模式分解（EMD)自适应滤波和HHT时频谱分析方法。将EMD方法与其他几种湍流度值处理方法进行了比较，包括带通滤波方法（BP)、电磁噪声解耦方法（ENC)和高通惯性衰滤波方法（HPIA)。采用EMD方法测得低湍流风洞的湍流度值，在流场速度30~100 m/s的范围内小于0.05%。采用HHT方法完成了脉动速度信号的时频分析，分析发现开口风洞试验段的脉动速度HHT时频谱有突出的低频信号。所构建的EMD自适应滤波器可以有效控制噪声对热线输出信号的影响，是一种有效的低湍流度信号处理方法。
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| 关 键 词： | 低湍流度 经验模式分解 低速风洞 开口风洞 热线风速仪 |
| 收稿时间： | 2015-12-08 |
Digital signal process of low turbulence intensity based on EMD |
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| Affiliation: | Facility Design and Instrumentation Institute, China Aerodynamics Research and Development Center, Mianyang Sichuan 621000, China |
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| Abstract: | Hot wire anemometer is used in three typical low speed wind tunnels to measure the flow field turbulence intensity, including a low turbulence wind tunnel, a general closed wind tunnel and an open jet wind tunnel. To deal with the disturbance to the turbulence signal caused by noise, an EMD(Empirical Mode Decomposition) self-adaptive filter and HHT(Hilbert-Huang Transform) time-frequency analysis methodology are introduced in turbulence intensity data processing. The EMD method is compared with several other turbulence intensity processing methods, including BPF(Band Pass Filter), ENC(Electronic Noise Correction) and HPIA(High Pass Inertia Attenuation Filter). Using the EMD filter, the turbulence intensity in the low turbulence wind tunnel test section is measured and found to be less than 0.05% in the flow speed range of 30~100m/s. Using HHT method, we complete the time-frequency analysis of the flow fluctuation signal, and the low frequency flow flucturation signal is found predominatnt in the open jet wind tunnel. The designed EMD self-adaptive filter is effective at controlling the influence of the noise on the hot wire output signal, and therefore it is a practical method for low turbulence intensity signal processing. |
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