一维时间序列的经验模态分解（以轴承振动信号为例，Python）

哥廷根数学学派

于 2024-06-21 11:42:05 发布

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分类专栏：时频分析故障诊断信号处理文章标签： python 开发语言人工智能信号处理机器学习算法

本文链接：https://blog.youkuaiyun.com/weixin_39402231/article/details/139856980

版权

import numpy as np
from pyhht import EMD
import matplotlib.pyplot as plt
from pyhht.visualization import plot_imfs
from time import time
import lee_dataset_CWRU
from lee_dataset_CWRU import *
DE_H1, FE_H1, t_DE_H1, t_FE_H1, RPM_H1, samples_s_DE_H1, samples_s_FE_H1 = lee_dataset('97.mat')
x = DE_H1
t = t_DE_H1
plt.figure(figsize=(7, 4))
plt.plot(t, x)

time0 = time()
decomposer = EMD(x)
imfs = decomposer.decompose()
elapsed_time = time() - time0
Mode 2, Iteration 600
2 minima > 0; 19594 maxima < 0.
Mode 2, Iteration 800
1 minima > 0; 19640 maxima < 0.
Mode 2, Iteration 1000
1 minima > 0; 19677 maxima < 0.
Mode 4, Iteration 1200
3 minima > 0; 7410 maxima < 0.
Mode 5, Iteration 1400
2 minima > 0; 4185 maxima < 0.
Mode 6, Iteration