Question

我在使用Raspberry Pi 3 B的项目中工作，我从IR传感器（Sharp GP2Y0A21YK0F）通过ADC MPC3008获取数据，并使用PyQtgraph库实时显示。

ADC的数据表显示，在5.0V时，采样率为200khz。但是我每秒只能获得大约30个样本。

使用Raspberry pi可以达到200khz吗？

如果是，我应该学习或实施什么才能获得它？

如果没有，我该怎么做才能获得尽可能高的采样率？如何找出最高采样率？

这是我的代码：

# -*- coding: utf-8 -*-

import time
import Adafruit_GPIO.SPI as SPI
import Adafruit_MCP3008
from collections import deque
import serial
import pyqtgraph as pg
from pyqtgraph.Qt import QtCore, QtGui
import numpy as np

SPI_PORT   = 0
SPI_DEVICE = 0
mcp = Adafruit_MCP3008.MCP3008(spi=SPI.SpiDev(SPI_PORT, SPI_DEVICE))

win = pg.GraphicsWindow()
win.setWindowTitle('pyqtgraph example: Scrolling Plots')

nsamples=600 #tamanho das matrizes para os dados
tx_aq = 0 #velocidade da aquisição
intervalo_sp = 0.5 #intervalo para secao de poincare

# 1) Simplest approach -- update data in the array such that plot appears to scroll
#    In these examples, the array size is fixed.
p1 = win.addPlot()
p1.setRange(yRange=[0,35])

p2 = win.addPlot()
p2.setRange(yRange=[-100,100])

p3 = win.addPlot()
p3.setRange(yRange=[-100,100])
p3.setRange(xRange=[-0,35])

#p3.plot(np.random.normal(size=100), pen=(200,200,200), symbolBrush=(255,0,0), symbolPen='w')
'''
p3.setDownsampling(mode='peak')
p3.setClipToView(True)
p3.setRange(xRange=[-100, 0])
p3.setLimits(xMax=0)
'''

data1= np.zeros((nsamples,2),float) #ARMAZENAR POSICAO
vec_0=deque()
vec_1=deque()
vec_2=deque()
ptr1 = 0

data2= np.zeros((nsamples,2),float) #ARMAZENAR VELOCIDADE
diff=np.zeros((2,2),float)
diff_v=deque()

data3= np.zeros((nsamples,2),float)
data3_sp=np.zeros((1,2),float)

ptr3=0

curve1 = p1.plot(data1)
curve2 = p2.plot(data2)
curve3 = p3.plot(data3)

#Coeficientes da calibração do IR
c1=-7.246
c2=44.17
c3=-95.88
c4=85.28

tlast=time.clock()
tlast_sp=time.clock()
#print tlast

def getdata():
    global vec_0, vec_1, vec_2, tlast
    timenow=time.clock()

    if timenow-tlast>=tx_aq:
        #name=input("HUGO")

        tlast=timenow

        t0=float(time.clock())
        str_0 =mcp.read_adc(0)
        t1=float(time.clock()) 
        str_1 =mcp.read_adc(0)
        t2=float(time.clock())
        str_2 =mcp.read_adc(0)

        d0x=(float(str_0))*(3.3/1023)
        d0= c1*d0x**3+c2*d0x**2+c3*d0x+c4
        vec_0=(t0, d0)

        d1x=(float(str_1))*(3.3/1023)
        d1= c1*d1x**3+c2*d1x**2+c3*d1x+c4
        vec_1=(t1, d1)

        d2x=(float(str_2))*(3.3/1023)
        d2= c1*d2x**3+c2*d2x**2+c3*d2x+c4
        vec_2=(t2, d2)

        functions()

def diferenciar():
    global data2


    diff=(data1[-1,1]-data1[-3,1])/(data1[-1,0]-data1[-3,0])

    data2[:-1] = data2[1:]
    data2[-1,1] = diff
    data2[-1,0] = data1[-2,0]


def organizar():
    global data1, data3

    data1[:-1] = data1[1:]
    vec_x1=np.array(vec_1)
    data1[-1]=vec_x1

def EF(): #ESPACO DE FASE
    global data3, ptr3

    data3[:-1] = data3[1:]
    data3[-1,0]=data1[-1,1]
    data3[-1,1]=data2[-1,1]

def SP():
    global timenow_sp, tlast_sp

    timenow_sp=time.clock()

    if timenow_sp-tlast_sp>=intervalo_sp:

        tlast_sp=timenow_sp

        data3_sp[0,0]=data3[-2,0]
        data3_sp[0,1]=data3[-2,1]
        p3.plot(data3_sp, pen=None, symbol='o', symbolPen=None, symbolSize=4, symbolBrush=('r'))
        #print data3_sp

def plotar():
    global ptr1
    curve1.setData(data1)    
    ptr1 += 1
    curve2.setData(data2)
    #curve2.setPos(ptr1, 0)

    #p3.plot(data3)

def functions():

    diferenciar()
    organizar()
    EF()
    SP()
    plotar()

def update1():
    global data1, curve1, ptr1

    getdata()


# update all plots
def update():
    update1()

timer = pg.QtCore.QTimer()
timer.timeout.connect(update)
timer.start(50)



## Start Qt event loop unless running in interactive mode or using pyside.
if __name__ == '__main__':
    import sys
    if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
        QtGui.QApplication.instance().exec_()

我正试图找到一种方法来解决它，但到目前为止我都失败了。

你们可以帮助我，或者至少指出我可以找到有关这方面的信息吗？

Answer 1

This kind of Sampling rate is not achievable with a general-purpose computer like Raspberry Pi, especially with MCP3008. The reason being the MCP series of ADC's tops out at ~2.7Mhz SPI clock at 5V.

In order to read at 200KHz rate, you would need a dedicated board.

However, you can try PCM1803A which could evidently achieve sampling rate of up to 96 kHz,

96kHz sampling is easily achived with an I2S ADC. I have 96kHz,24bit stereo input working using a simple I2S codec on a breakout board. Higher sampling rates may be possible but the codec I'm using (PCM1803A) maxes out at 96kHz.

This is also discussed here, as follows,

You are not going to get to 150ksps on a Pi with just SPI ADC(s). Not even with one channel. I think the best I heard of was 50ksps, and there would be a certain amount of jitter on the frequency of sampling.

2 channels * 150ksps = 300ksps

with overhead, assuming about 32 bit per sample, you are looking at 9.6mbps of raw data

NO WAY with just a Pi and ADC.

You need an external microcontroller / adc sending the data to the Pi over USB or Ethernet

and here,

The basic problems are:

the Raspberry Pi is NOT designed for high speed data collection

the MCP series of ADC's tops out at ~2.7Mhz SPI clock at 5V

SPI latency with the RPi

The SPI interface on the Pi is simply not capable of accurately reading 100,000 samples from an ADC at precise intervals.

如何使用ADC获得Raspbery Pi中可能的最高采样率？

1 个答案: