A Removing Noise Method of Check Valve Early Fault Signal based on ICEEMD and HD
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摘要: 针对往复式高压隔膜泵单向阀早期故障振动信号含有大量背景噪声致使特征信息被噪声淹没的问题, 提出改进的完备集合经验模态分解(Improved complete ensemble empirical mode decomposition, ICEEMD)和豪斯多夫距离(Hausdorff distance, HD)的单向阀早期故障信号降噪方法。首先, 使用ICEEMD将采集信号分解为多个本征模态函数(Intrinsic mode function, IMF); 然后, 计算每个IMF分量与原始信号的概率密度函数的豪斯多夫距离, 利用HD将含噪IMF分量从ICEEMD分解得到的IMF分量中分离; 再次, 以峭度为指标, 选取峭度值较大的部分IMF分量重构; 最后, 对重构信号进行希尔伯特包络解调, 进行对比试验分析降噪效果。仿真结果表明, 该方法可有效提取强噪声下信号特征频率。实测数据试验结果表明, 该方法能够有效提取噪声淹没的单向阀运行基频及其倍频, 具有较好的降噪效果。
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关键词:
- 单向阀 /
- 早期故障 /
- 改进的完备集合经验模态分解 /
- 豪斯多夫距离
Abstract: Aiming at the early failure of the check valve of the reciprocating high-pressure diaphragm pump, the vibration signal contains a large amount of background noise, causing the feature information to be submerged by noise, a removing noise method of improved complete ensemble empirical mode decomposition (ICEEMD) and Hausdorff distance (HD) in check valve early fault signal is proposed. First of all, ICEEMD was used to decompose the acquired signal into multiple intrinsic modal functions (IMF). Then, calculating the Hausdorff distance of the probability density function of each IMF component and the original signal, and HD was used to separate noisy IMF components from IMF components decomposed by ICEEMD. Next, the kurtosis as an indicator, was used to select the IMF component with a larger kurtosis value for reconstruction. Finally, Hilbert envelope was used to demodulate the reconstructed signal, and conduct comparative tests to analyze the noise reduction effect. The simulation results show that the method can effectively extract the feature frequency of the signal under strong noise, and the experimental results of the measured data show that the proposed method can effectively extract the fundamental frequency and its multiplied frequency of check valve submerged by noise, and has a good noise reduction effect. -
表 1 仿真信号各IMF分量峭度值
IMFs 峭度值 IMFs 峭度值 IMF1 2.078 4 IMF8 2.673 8 IMF2 2.798 3 IMF9 2.159 4 IMF3 2.878 8 IMF10 2.450 3 IMF4 3.044 1 IMF11 2.054 3 IMF5 2.887 5 IMF12 2.162 0 IMF6 2.960 8 IMF13 1.530 6 IMF7 2.637 0 表 2 早期磨损故障信号IMF分量峭度值
IMFs 峭度值 IMFs 峭度值 IMF1 43.563 2 IMF7 4.463 0 IMF2 5.746 6 IMF8 3.847 1 IMF3 4.933 5 IMF9 4.961 4 IMF4 3.871 1 IMF10 6.383 6 IMF5 2.831 9 IMF11 1.741 1 IMF6 3.871 5 表 3 不同降噪方法样本熵
编号 降噪方法 样本熵(SE) 1 本文所提方法 0.125 8 2 VMD+HD+峭度 0.653 0 3 ICEEMD+峭度 1.307 4 4 ICEEMD+HD 0.413 4 -
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