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## [Python] vibration analysis

* 原始資訊波形
* RMS波形
* 時頻圖
* 時頻圖(log Data)

``````vibra_ana(10240,df_vib.DateTime,[df_vib.X,df_vib.Y,df_vib.Z])
``````
``````def vibra_ana(Fs,t,x):

print('from {} to {}'.format(t[0],t[len(t)-1]))

l=len(x)
figsize = (10 * l, 20 )
row = 5
col = l

plt.figure(figsize=figsize)

#Determine variables
N = np.int(np.prod(t.shape))#length of the array
T = 1/Fs
T = (t[1]-t[0]).microseconds*0.000001#timedelta(seconds=0.2).total_seconds()
Fs = 1/T 	#sample rate (Hz)
print("Fs :{} , T :{}".format(Fs,T))
print("# Samples:",N)

for index_ele , ele in enumerate(x) :
index = 0 * l + index_ele + 1

#Plot Data
tic = time.clock()
plt.subplot(row,col,index)
plt.plot(t, ele)
plt.xlabel('Time (seconds)')
plt.ylabel('Accel (g)')
plt.title('RAW Data - ' )
plt.grid()
toc = time.clock()
print("Plot Time:",toc-tic)

index = 1 * l + index_ele + 1

#Compute RMS and Plot
tic = time.clock()
w = np.int(np.floor(Fs/10)); #width of the window for computing RMS
print('w :{}'.format(w))
steps = np.int_(np.floor(N/w)) #Number of steps for RMS
t_RMS = np.zeros((steps,1)); #Create array for RMS time values
x_RMS = np.zeros((steps,1)); #Create array for RMS values
for i in range (0, steps):
#             t_RMS[i] = np.mean([(t[(i*w)]-t[0]).microseconds,(t[((i+1)*w-1)]-t[0]).microseconds])
t_RMS[i] = np.mean([(t[(i*w)]-t[0]).seconds,(t[((i+1)*w-1)]-t[0]).seconds])
#         t_RMS[i] = np.mean(t[(i*w):((i+1)*w)]);
x_RMS[i] = np.sqrt(np.mean(ele[(i*w):((i+1)*w)]**2));
plt.subplot(row,col,index)
plt.plot(t_RMS, x_RMS)
plt.xlabel('Time (seconds)')
plt.ylabel('RMS Accel (g)')
plt.title('RMS - ' )
plt.grid()
toc = time.clock()
print("RMS Time:",toc-tic)
index = 2 * l + index_ele + 1

#Compute and Plot FFT
tic = time.clock()
plt.subplot(row,col,index)
xf = np.linspace(0.0, 1.0/(2.0*T), N/2)
yf = fft(ele)
plt.plot(xf, 2.0/N * np.abs(yf[0:np.int(N/2)]))
plt.grid()
plt.xlabel('Frequency (Hz)')
plt.ylabel('Accel (g)')
plt.title('FFT - ' )
toc = time.clock()
print("FFT Time:",toc-tic)
index = 3 * l + index_ele + 1

# Compute and Plot Spectrogram
tic = time.clock()
plt.subplot(row,col,index)
f, t2, Sxx = signal.spectrogram(ele, Fs )#, nperseg = Fs/4)
ax=plt.pcolormesh(t2, f, np.log(Sxx))
#         plt.colorbar(ax)
plt.ylabel('Frequency [Hz]')
plt.xlabel('Time [sec]')
plt.title('Spectrogram(log) - ' )
toc = time.clock()
print("Spectrogram Time:",toc-tic)
index = 4 * l + index_ele + 1

# Compute and Plot Spectrogram
tic = time.clock()
plt.subplot(row,col,index)
plt.pcolormesh(t2, f, (Sxx))
plt.ylabel('Frequency [Hz]')
plt.xlabel('Time [sec]')
plt.title('Spectrogram - ' )
toc = time.clock()
print("Spectrogram Time:",toc-tic)

plt.tight_layout()
plt.show()
``````