我是信号分析和振动的新手。我有振动传感器，可以在F：65536 Hz处采集数据
我确实为Fn实现了一个低通滤波器：30000 Hz
然后，我对数据进行了重新采样，以设置新的低频。
我的代码中使用的低通滤波器来自以下链接：Creating lowpass filter in SciPy - understanding methods and units
def butter_lowpass(cutoff, fs, order=5):
nyq = 0.5 * fs
normal_cutoff = cutoff / nyq
b, a = butter(order, normal_cutoff, btype='low', analog=False)
return b, a
def butter_lowpass_filter(data, cutoff, fs, order=5):
b, a = butter_lowpass(cutoff, fs, order=order)
y = lfilter(b, a, data)
return y
# Filter requirements.
order = 6
fs = 65536.0 # sample rate, Hz
cutoff = 15000 # desired cutoff frequency of the filter, Hz
data =d
length= len(d)
# Get the filter coefficients so we can check its frequency response.
b, a = butter_lowpass(cutoff, fs, order)
# Plot the frequency response.
w, h = freqz(b, a, worN=8000)
plt.subplot(2, 1, 1)
plt.plot(0.5*fs*w/np.pi, np.abs(h), 'b')
plt.plot(cutoff, 0.5*np.sqrt(2), 'ko')
plt.axvline(cutoff, color='k')
plt.xlim(0, 0.5*fs)
plt.title("Lowpass Filter Frequency Response")
plt.xlabel('Frequency [Hz]')
plt.grid()
# Demonstrate the use of the filter.
T = length * (1/ fs) # seconds
n = int(T * fs) # total number of samples
t = np.linspace(0, T, n, endpoint=False)
# Filter the data, and plot both the original and filtered signals.
y = butter_lowpass_filter(data, cutoff, fs, order)
plt.figure(figsize=(20,10))
plt.subplot(211)
plt.plot(t, data, 'b-', label='data')
plt.title('Sensor Data')
plt.subplot(212)
plt.plot(t, y, 'g-', linewidth=2, label='filtered data')
plt.title('filtered signal')
plt.show()
f = signal.resample (y,50000) #there is a mistake here try asking for help to figure out how this really works
length= len(d)
fs = 65536.0
T = length * (1/ fs) # seconds
n = int(T * length) # total number of samples
t = np.linspace(0, T, 50000, endpoint=False)
xnew = np.linspace(0,1000,50000,endpoint=False)
plt.figure(figsize=(20,10))
plt.plot(t, f, 'o-', linewidth=2, label='filtered data')
plt.title('Filtered -Resampled signal')
plt.show()