2020-01-05 19:31:07 +08:00
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import serial
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import queue
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import threading
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2020-01-11 18:41:18 +08:00
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2020-01-11 16:06:54 +08:00
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import numpy as np
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from scipy.signal import blackmanharris
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2020-01-05 19:31:07 +08:00
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class InductionHeater:
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"""Interface to the MHS5200A function generator driving the LC tank"""
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def __init__(self, port, induction_min, induction_max):
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self.port = port
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self.induction_min = induction_min
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self.induction_max = induction_max
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self.queue = queue.Queue(1)
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def start(self):
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self.serial = serial.Serial(self.port, 57600)
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self.thread = threading.Thread(target=self.thread_target)
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self.thread.start()
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def thread_target(self):
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while True:
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amount = self.queue.get()
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if amount is None:
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break
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amount = max(min(amount, 0.5), -0.5)
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freq = ((self.induction_min + self.induction_max)/2
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+ amount*(self.induction_max - self.induction_min))
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command = ":s1f{:010d}\n".format(int(freq*1e2))
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self.serial.write(command.encode())
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self.serial.readline()
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def set(self, amount):
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self.queue.put(amount, block=False)
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def stop(self):
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self.queue.put(None, block=True)
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self.thread.join()
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self.serial.close()
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2020-01-11 16:06:54 +08:00
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# https://gist.github.com/endolith/255291
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def parabolic(f, x):
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xv = 1/2. * (f[x-1] - f[x+1]) / (f[x-1] - 2 * f[x] + f[x+1]) + x
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yv = f[x] - 1/4. * (f[x-1] - f[x+1]) * (xv - x)
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return (xv, yv)
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class Stabilizer:
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def __init__(self, freq_sample, amp_threshold, freq_target, k, tuner):
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self.freq_sample = freq_sample
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self.amp_threshold = amp_threshold
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self.freq_target = freq_target
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self.k = k
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self.tuner = tuner
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def input(self, samples):
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spectrum = np.abs(np.fft.fft(samples*blackmanharris(len(samples)))[0:len(samples)//2])
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for i in range(len(spectrum)//100):
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spectrum[i] = 0
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spectrum[-i] = 0
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i = np.argmax(spectrum)
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true_i, amplitude = parabolic(spectrum, i)
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freq = 0.5 * self.freq_sample * true_i / len(spectrum)
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2020-01-12 19:32:38 +08:00
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if amplitude > self.amp_threshold:
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tuning = (freq - self.freq_target)*self.k
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2020-01-11 16:06:54 +08:00
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else:
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tuning = 0.0
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self.tuner.set(tuning)
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2020-01-11 18:41:18 +08:00
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def continuous_unwrap(last_phase, last_phase_unwrapped, p):
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# note: np.unwrap always preserves first element of array
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p = np.unwrap(p)
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glue = np.array([last_phase_unwrapped, last_phase_unwrapped + (p[0] - last_phase)])
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new_p0 = np.unwrap(glue)[1]
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return new_p0 + p - p[0]
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class PositionTracker:
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def __init__(self, leakage_avg):
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self.last_phase = 0.0
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self.last_position = 0.0
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self.leakage = np.zeros(leakage_avg)
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self.leakage_ptr = 0
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def input(self, ref, meas):
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demod = np.conjugate(ref)*meas
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self.leakage[self.leakage_ptr] = np.real(np.sum(demod)/len(demod))
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self.leakage_ptr = (self.leakage_ptr + 1) % len(self.leakage)
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leakage = np.sum(self.leakage)/len(self.leakage)
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phase = np.angle(demod - leakage)
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position = continuous_unwrap(self.last_phase, self.last_position, phase)/(2.0*np.pi)
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self.last_phase = phase[-1]
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self.last_position = position[-1]
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return position, leakage
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