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2026-01-24 21:10:50 +01:00
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commit 473eb899a7
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import numpy as np
import matplotlib.pyplot as plt
import fft
class IIR_1_Order_LP(object):
"""docstring for fft_meas"""
def __init__(self, fs, fc=200):
self.fs = fs
self.fc = fc
self.dt = 1/self.fs
self.RC = 1 / (2*np.pi*self.fc)
self.alpha = self.dt / (self.RC + self.dt)
self.y = 0
def step(self, x):
self.y = self.y + self.alpha * (x - self.y)
return self.y
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import numpy as np
def fft(x, fs, X_nom=None, epsilon=None):
# Implementation from IEC 61000-4-7:2002/AMD1:2008
# Data length
N = len(x)
# Number of positive-frequency bins
K = int(np.floor(N/2))
# Frequency axis (0 .. fs/2)
#freq = np.linspace(start=0, stop=fs/2, num=K+1, endpoint=True)
freq = np.arange(K + 1) * fs / N
# allocate
a = np.zeros(K + 1)
b = np.zeros(K + 1)
c = np.zeros(K + 1)
Y_C = np.zeros(K + 1)
phi = np.zeros(K + 1)
n = np.arange(N)
# DC
c[0] = np.mean(x) # c0 per IEC
a[0] = 2 * c[0] # not really used; just for completeness
b[0] = 0.0
# k = 1..K
for k in range(1, K+1):
angle = 2 * np.pi * k * n / N
a[k] = (2/N) * np.sum(x * np.cos(angle))
b[k] = (2/N) * np.sum(x * np.sin(angle))
# Nyquist (if N even): do NOT apply the 2/N doubling
if (N % 2 == 0) and (k == K):
a[k] *= 0.5
b[k] *= 0.5
c[k] = np.sqrt(a[k]*a[k] + b[k]*b[k])
# RMS value calculated in Eq.2.
Y_C[k] = c[k] / np.sqrt(2)
# Phase: apply dead-band if provided, else always compute
if (X_nom is not None) and (epsilon is not None):
if (np.abs(a[k]) <= epsilon * X_nom) and (np.abs(b[k]) <= epsilon * X_nom):
phi[k] = 0.0
continue
# IEC quadrant handling (equivalent to the piecewise definition)
phi[k] = np.arctan2(a[k], b[k])
return freq, a, b, c, Y_C, phi
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import numpy as np
import matplotlib.pyplot as plt
import fft
class fft_meas(object):
"""docstring for fft_meas"""
def __init__(self, fs=50e3, tn=0.2):
self.fs = fs
self.ts = 1/fs
self.tn = tn
self.N = int(int(fs*tn))
self.data = np.zeros(self.N)
self.idx = -1
self.time = 0
self.freq = 0
self.a = 0
self.b = 0
self.c = 0
self.Y_C = 0
self.phi = 0
def step(self, data, time, f_H1, unit):
if time - self.time > self.ts:
self.time = time
self.idx += 1
self.data[self.idx] = data
if self.idx == self.N-1:
self.freq , self.a, self.b , self.c, self.Y_C, self.phi = fft.fft(x=self.data, fs=self.fs)
self.idx = -1
def plot(self):
#fs, a, b, c, YC, phi = ftt.fft(Ph1, sample_freq)
plt.plot(self.freq, self.c)
plt.xlabel("x")
plt.ylabel("y")
plt.title("Simple plot")
plt.show()
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import numpy as np
import fft_meas
import zerocross_meas
# to do
# Need a zero-cross algorithem to comply with 61000-4-30
def main():
time = 0
delta_t = 1e-6
t_stop = 1.1
amplitude = 1
base_freq = 50
fft_measurements = fft_meas.fft_meas(fs=50e3, tn=0.2)
zerocross = zerocross_meas.zerocross_meas(fs=50e3, tn=1)
for i in range(0, int(t_stop/delta_t)+1):
Ph1 = np.sin(2*np.pi*time*base_freq)
zerocross.step(x=Ph1, time=time)
fft_measurements.step(data=Ph1, time=time, f_H1=zerocross.freq, unit="I")
time += delta_t
zerocross.print()
#fft_measurements.plot()
if __name__ == '__main__':
main()
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import numpy as np
import matplotlib.pyplot as plt
import fft
import IIR_filter
class zerocross_meas(object):
"""docstring for fft_meas"""
def __init__(self, fs=50e3, tn=1):
self.fs = fs
self.ts = 1/self.fs
self.tn = tn
self.time = 0
self.freq = 0
self.freq_ts = 0
self.y = 0
self.y_old = 0
self.idx = 0
self.LPfilter = IIR_filter.IIR_1_Order_LP(fs=self.fs, fc=200)
def step(self, x, time):
if time - self.time > self.ts:
self.time = time
self.y = self.LPfilter.step(x)
if self.y_old < 0 and self.y > 0:
self.idx += 1
if time - self.freq_ts > self.tn:
self.freq = self.idx / self.tn
self.freq_ts = time
self.idx = 0
self.y_old = self.y
def print(self):
print(self.freq)