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python - 将加速度计数据存储在树莓派 SD 卡中

转载 作者:行者123 更新时间:2023-11-28 22:10:31 27 4
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我正在从事一个项目,我的目标是存储来自电机的加速度数据。为此,我正在使用 adafruit mma8451 加速传感器。现在要存储 3 轴加速度数据,我使用的是 Raspberry pi。我正在尝试将数据存储在 CSV 文件中。现在我需要系统每秒至少存储 250 个样本。现在的问题是,树莓派存储的一秒可能是 230 个样本,下一秒是 210,再下一秒可能是 225。所以基本上,树莓派在这个速度下并不稳定。如果它每秒存储 230 个样本,那将永远不会成为问题。但是不接受不同数量的样本,因为我需要准确的采样频率来进一步分析信号。

为了检查这是否是将数据存储在 csv 文件中的问题,我尝试查看 pi 是否只能打印 250 次“Hello World”。看来,如果我使用 time.sleep() 命令使用计时器,它是不稳定的。现在我想展示我在我的项目中使用的代码

count=0
Path = 0

with open('/home/pi/TrialV10/VibrationsDevice1.csv', 'a+') as csvfile:
sensorwriter = csv.writer(csvfile) #, delimiter=' ',
#quotechar='|', quoting=csv.QUOTE_MINIMAL)
sensorwriter.writerow(['Datetime', 'Time', 'X_Accel (m/s^2)', 'Y_Accel (m/s^2)', 'Z_Accel (m/s^2)', 'Count', 'Path'])



if MotoDetection == 1:
sensor.MotionSetup()
while True:
sensor.Motion()
time.sleep(0)
if sensor.Motion() == True:
if count==0:
TimeStart = time.time()
Timer = 0
pass
while True:
x, y, z = sensor.acceleration
time_now = datetime.datetime.now().strftime("%Y-%m-%d")
TimePresent = time.time()
Timer = TimePresent - TimeStart
X = x #+ Calcx
Y = y #+ Calcy
Z = z #+ Calcz
count = count + 1
print('DateTime={0} Time ={1} X={2:0.3f} m/s^2 Y:{3:0.3f} m/s^2 Z:{4:0.3f} m/s^2 count={5}'.format(time_now, Timer, X, Y, Z, count))
sensorwriter.writerow([time_now, Timer, X, Y, Z, count])
time.sleep(0.004)
if Timer > TimingA:
exit()

最佳答案

执行此操作的一种方法是缓冲您的传感器读数,并让一个单独的线程将它们分组写入文件。例如:

import threading
class FileWriterThread(threading.Thread):
def __init__(self,filename,header):
threading.Thread.__init__(self)
self.buffer = []
self.filename = filename
self.header = header
def run(self):
with open(self.filename,"a+") as f:
csvwriter = csv.writer(f)
csvwriter.writerow(self.header)
while True:
time.sleep(1) #Wait 1 second between writes to the file.
writebuffer = []
while len(self.buffer) > 0: #Clear the current buffer
writebuffer.append(self.buffer.pop(0))
while len(writebuffer) > 0:
csvwriter.writerow(writebuffer.pop(0))
def writerow(self,row):
self.buffer.append(row)

要打开文件并启动线程,您可以运行:

sensorwriter = FileWriterThread(filename,header)
sensorwriter.start()

要存储要写入文件的行,您可以使用:

sensorwriter.writerow(row)

最后,要停止线程并保存文件,您可以使用:

sensorwriter.cancel()

请记住,您必须创建一个新线程才能重新启动它。实现到您当前的代码中,这将导致:

import threading
class FileWriterThread(threading.Thread):
def __init__(self,filename,header):
threading.Thread.__init__(self)
self.buffer = []
self.filename = filename
self.header = header
def run(self):
with open(self.filename,"a+") as f:
csvwriter = csv.writer(f)
csvwriter.writerow(self.header)
while True:
time.sleep(1) #Wait 1 second between writes to the file.
writebuffer = []
while len(self.buffer) > 0: #Clear the current buffer
writebuffer.append(self.buffer.pop(0))
while len(writebuffer) > 0:
csvwriter.writerow(writebuffer.pop(0))
def writerow(self,row):
self.buffer.append(row)

sensorwriter = FileWriterThread('/home/pi/TrialV10/VibrationsDevice1.csv',['Datetime', 'Time', 'X_Accel (m/s^2)', 'Y_Accel (m/s^2)', 'Z_Accel (m/s^2)', 'Count', 'Path'])
sensorwriter.start()

count=0
Path = 0

if MotoDetection == 1:
sensor.MotionSetup()
while True:
sensor.Motion()
time.sleep(0)
if sensor.Motion() == True:
if count==0:
TimeStart = time.time()
Timer = 0
pass
while True:
x, y, z = sensor.acceleration
time_now = datetime.datetime.now().strftime("%Y-%m-%d")
TimePresent = time.time()
Timer = TimePresent - TimeStart
X = x #+ Calcx
Y = y #+ Calcy
Z = z #+ Calcz
count = count + 1
print('DateTime={0} Time ={1} X={2:0.3f} m/s^2 Y:{3:0.3f} m/s^2 Z:{4:0.3f} m/s^2 count={5}'.format(time_now, Timer, X, Y, Z, count))
sensorwriter.writerow([time_now, Timer, X, Y, Z, count])
time.sleep(0.004)
if Timer > TimingA:
sensorwriter.cancel()
exit()

希望这对您有所帮助。

编辑:问题似乎与文件 I/O 无关,很可能与打印语句有关。将文本打印到控制台是不稳定的,这实际上是导致稳定性问题的原因。不幸的是,没有办法让它 100% 稳定,但是你可以通过替换来稍微稳定它

print('DateTime={0}  Time ={1} X={2:0.3f} m/s^2  Y:{3:0.3f} m/s^2  Z:{4:0.3f} m/s^2 count={5}'.format(time_now, Timer, X, Y, Z, count))

sys.stdout.write('DateTime={0}  Time ={1} X={2:0.3f} m/s^2  Y:{3:0.3f} m/s^2  Z:{4:0.3f} m/s^2 count={5}\n'.format(time_now, Timer, X, Y, Z, count))

因为 sys.stdout.write() 似乎比 print() 更稳定。请记住在程序开始时导入 sys。不幸的是,总会有一些不稳定,这取决于操作系统当时正在运行的其他任务。

尝试最大化稳定性的一种方法是尝试限制采样率。放上代码

import time
SAMPLERATE = 150 #Number of samples per second.
SAMPLEDELAY = 1/SAMPLERATE
loopwait = 0

在你的程序和代码的开始

while time.time() < loopwait:
pass
loopwait = time.time()+SAMPLEDELAY

作为 while True 循环中的第一条指令。这使得最终代码:

import threading,time
class FileWriterThread(threading.Thread):
def __init__(self,filename,header):
threading.Thread.__init__(self)
self.buffer = []
self.filename = filename
self.header = header
def run(self):
with open(self.filename,"a+") as f:
csvwriter = csv.writer(f)
csvwriter.writerow(self.header)
while True:
time.sleep(1) #Wait 1 second between writes to the file.
writebuffer = []
while len(self.buffer) > 0: #Clear the current buffer
writebuffer.append(self.buffer.pop(0))
while len(writebuffer) > 0:
csvwriter.writerow(writebuffer.pop(0))
def writerow(self,row):
self.buffer.append(row)

sensorwriter = FileWriterThread('/home/pi/TrialV10/VibrationsDevice1.csv',['Datetime', 'Time', 'X_Accel (m/s^2)', 'Y_Accel (m/s^2)', 'Z_Accel (m/s^2)', 'Count', 'Path'])
sensorwriter.start()

SAMPLERATE = 150 #Number of samples per second
SAMPLEDELAY = 1/SAMPLERATE
loopwait = 0

count=0
Path = 0

if MotoDetection == 1:
sensor.MotionSetup()
while True:
sensor.Motion()
time.sleep(0)
if sensor.Motion() == True:
if count==0:
TimeStart = time.time()
Timer = 0
pass
while True:
while time.time() < loopwait:
pass
loopwait = time.time()+SAMPLEDELAY
x, y, z = sensor.acceleration
time_now = datetime.datetime.now().strftime("%Y-%m-%d")
TimePresent = time.time()
Timer = TimePresent - TimeStart
X = x #+ Calcx
Y = y #+ Calcy
Z = z #+ Calcz
count = count + 1
sys.stdout.write('DateTime={0} Time ={1} X={2:0.3f} m/s^2 Y:{3:0.3f} m/s^2 Z:{4:0.3f} m/s^2 count={5}\n'.format(time_now, Timer, X, Y, Z, count))
sensorwriter.writerow([time_now, Timer, X, Y, Z, count])
time.sleep(0.004)
if Timer > TimingA:
sensorwriter.cancel()
exit()

不幸的是,没有真正的方法来确保一致的测量速率,但是这段代码应该有助于使其比以前更加一致。希望这会有所帮助。

关于python - 将加速度计数据存储在树莓派 SD 卡中,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/56595592/

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