Application of hilbert-huang transform to denoising in vortex flowmeter
Application of hilbert-huang transform to denoising in vortex flowmeter
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DOI：
10.1007/s11771-006-0076-7
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发表时间：
2006-10
影响因子：
--
通讯作者：
Zhi-qiang Sun;Jie-min Zhou;Pingwei Zhou
中科院分区：
文献类型：
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作者：
Zhi-qiang Sun;Jie-min Zhou;Pingwei Zhou
由于管道振动、流体脉动和其他环境干扰，涡街流量计的原始信号会产生幅度和频率的变化。从噪声数据中提取指示体积流量的涡流频率很困难，尤其是在低流量时。采用希尔伯特-黄变换来估计涡旋频率。通过经验模态分解将带噪原始信号分解为不同的本征模态，分析各模态的时频特性，并通过计算部分模态的瞬时频率得到涡旋频率。实验结果表明，该方法能够估计涡旋频率，相对误差小于2%；在所研究的低流量范围内，Hilbert-Huang变换的去噪能力明显优于基于傅立叶的算法。这些研究结果表明，该方法对涡旋信号处理准确，同时具有较强的抗干扰能力。
Due to piping vibration, fluid pulsation and other environmental disturbances, variations of amplitude and frequency to the raw signals of vortex flowmeter are imposed. It is difficult to extract vortex frequencies which indicate volumetric flowrate from noisy data, especially at low flowrates. Hilbert-Huang transform was adopted to estimate vortex frequency. The noisy raw signal was decomposed into different intrinsic modes by empirical mode decomposition, the time-frequency characteristics of each mode were analyzed, and the vortex frequency was obtained by calculating partial mode’s instantaneous frequency. Experimental results show that the proposed method can estimate the vortex frequency with less than 2% relative error; and in the low flowrate range studied, the denoising ability of Hilbert-Huang transform is markedly better than Fourier based algorithms. These findings reveal that this method is accurate for vortex signal processing and at the same time has strong anti-disturbance ability.