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基于Hilbert-Huang变换的水轮机非平稳压力脉动信号分析 被引量:21

TRANSIENT HYDRAULIC PRESSURE FLUCTUATION SIGNAL ANALYSIS OF HYDROTURBINE BASED ON HILBERT-HUANG TRANSFORM
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摘要 水力压力脉动在水轮机的运行过程中是不可避免的现象,而且在过渡过程中具有较强的非平稳性。以机组启动过程中的非平稳尾水管水力压力脉动信号分析为例,研究压力脉动在过渡过程中的时变特征。为了降低时频分析的计算量,提高时频分辨率,首先应用采样率转换技术对现场测试信号进行预处理,然后应用Hilbert-Huang变换进行时频分析,识别确定信号中的频率成分及其相对机组运行条件的变化情况。分析结果表明:水轮机尾水管中的水力压力脉动以低频成分为主,其时变性与运行条件密切相关,但是在过渡过程中,其频率成分相对时间的变化情况与机组转速变化不成比例;与其它时频分析方法相比,Hilbert-Huang变换时频分辨率高,适合分析非平稳低频水力压力脉动信号。 Hydaulic pressure fluctuation is inevitable in the operation of hydroturbines. It features nonstationarity, especially in the transients. With the analysis of hydraulic pressure fluctuation in draft tube during the starting process as an example, it attempts to find its time variation with the operation conditions. In order to alleviate the computational burden and improve the resolution of time frequency analysis, the on-site acquired signal is down-sampled via multi-rate filter firstly. Then, it is analyzed based on the nonlinear and nonstationary time series analysis method-Hilbert-Huang transform, and the frequency components and their time variation with the operation conditions are identified clearly. From the analysis result, it can be concluded that the hydraulic pressure fluctuation features low frequency and strong nonstationarity. The amplitude and frequency are time varying, and closely related with the operation conditions, but not proportional to the speed. Compared with the other time-frequency analysis methods, such as the short time Fourier transform, wavelet transform, and Wigner-Ville distribution, it is demonstrated that the Hilbert-Huang transform possesses high time-frequency resolution and applicability to analysis of nonstationary low-frequency hydraulic pressure fluctuation signal.
出处 《中国电机工程学报》 EI CSCD 北大核心 2005年第10期111-115,共5页 Proceedings of the CSEE
基金 国家杰出青年科学基金(50425516) 教育部"跨世纪优秀人才培养计划"基金。~~
关键词 水轮机 尾水管 HILBERT-HUANG变换 压力脉动 脉动信号 Hydroturbine Hilbert-Huang Transform Nonstationary Signal Time-frequency Analysis Hydraulic Pressure fluctuation Transients
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