基于小波和LMD的振动信号分析方法的应用

R. Song, Mingguo Ma, C. Xie
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引用次数: 5

摘要

提出了一种基于小波预处理和局部均值分解的振动故障诊断方法。为了准确获取时频能量信息,首先对原始信号进行小波变换。从能量的角度出发,采用自适应阈值去噪,在保留大部分信号能量的同时,消除了大部分噪声的in∞影响。然后,利用LMD得到物理感较弱且包含故障信息的信号分量;为了识别异常频率成分,对信号进行时频域分析。最后,通过分析各分量信号的时频信息,诊断水轮机的运行状态。将该方法应用于某电厂1号水轮机,分析结果表明,该方法是有效的,可以正确地评估水轮机的运行状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Vibration Signal Analysis Method Based on Wavelet and LMD
This paper proposes a vibration fault diagnosis method based on wavelet preprocessing and Local Mean Decomposition (LMD). In order to obtain time-frequency energy information accurately, flrstly, the original signal is transformed by wavelet. From the viewpoint of energy, using adaptive threshold for denoising, while most of the signal energy is reserved, the in∞uence of most noise is eliminated at the same time. Then, LMD is used to get the signal component which has deflnite physical sense and contains fault information. To identify the abnormal frequency components, the signal component is analyzed in time-frequency domain. Finally, the running state of hydro turbine can be diagnosed by analyzing the time-frequency information of each component signals. This method is applied in the No.1 hydro turbine of a power plant, the analysis shows that this method is efiective, and the running state of the turbine can be correct evaluated.
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