对串口数据进行傅里叶变换（FFT）计算功率

Mr Robot

已于 2022-03-24 14:46:21 修改

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分类专栏：信号处理算法 FFT 文章标签： python

于 2022-03-24 14:45:19 首次发布

本文链接：https://blog.youkuaiyun.com/leva345/article/details/123710807

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本文介绍如何使用Python库如PyQtGraph和serial来从串口接收数据，并通过Fast Fourier Transform (FFT) 实时分析，展示数据频率特性。通过定时更新机制，实时显示数据功率变化。

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from pyqtgraph.Qt import QtGui, QtCore
import numpy as np
import pyqtgraph as pg
from pyqtgraph.ptime import time
import serial
import time
from scipy.fftpack import fft as fp
from scipy.fftpack import fftfreq as fpf

global data_display

app = QtGui.QApplication([])

p = pg.plot()
p.setWindowTitle('live plot from serial')
curve = p.plot()
sampling_freq = 250
raw=serial.Serial("com1",baudrate=115200,bytesize=8,stopbits=1,timeout=1)

data_display = []


chunk_size=10# smaller chunk size = slower data
freqs = fpf(chunk_size)*sampling_freq

freq_index = np.arange(int(np.floor(chunk_size*800/sampling_freq)),int(np.ceil(chunk_size*1100/sampling_freq)+1))
power = []

def update():
	
	global  data_display,power
	
	current_data = np.zeros(chunk_size,dtype=int)
	
	for i in range(chunk_size):
		current_data[i]=raw.readline()
	# current_data=int(raw.readline()) # this makes it sloww

	freq_sig = np.abs(fp(current_data)*2*np.pi/chunk_size)
	
	power = np.append(power, np.sqrt(sum(freq_sig[freq_index]**2)))

	curve.setData(power)

	app.processEvents()


timer = QtCore.QTimer()
timer.start() 
timer.timeout.connect(update)



if __name__ == '__main__':
	import sys
	if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
		QtGui.QApplication.instance().exec_()