一维信号的时频分析（Python）

哥廷根数学学派

于 2024-06-12 17:19:07 发布

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分类专栏：故障诊断时频分析信号处理文章标签： python 开发语言机器学习人工智能深度学习算法

本文链接：https://blog.youkuaiyun.com/weixin_39402231/article/details/139632119

版权

代码较为简单，很容易读懂。

Importing the required libraries

import os
import numpy as np
import pywt
import pandas as pd
import pickle as pkl
from matplotlib import pyplot as plt

Parameters or Required Variables

DATA_POINTS_PER_FILE = 2560
TIME_PER_REC = 0.1
SAMPLING_FREQ = 25600 # 25.6 KHz
SAMPLING_PERIOD = 1.0/SAMPLING_FREQ


WIN_SIZE = 20
WAVELET_TYPE = 'morl'

Helper Functions

def load_df(pkz_file):
    with open(pkz_file, 'rb') as f:
        df=pkl.load(f)
    return df

# perform CWT on 1d signals and return 2d feature image
def extract_feature_image(ind, feature_name='horiz accel'):
    data_range = df_row_ind_to_data_range(ind)
    data = df[feature_name].values[data_range[0]:data_range[1]]
    # use window to process(= prepare, develop) 1d signal
    data = np.arra