用python写锁相放大器原理代码,生成X分量的函数和正交分量Y的函数
时间: 2024-01-24 14:16:51 浏览: 150
锁相放大器的原理是通过将输入信号与参考信号进行相位比较,得到两个正交分量(X分量和Y分量),再将它们转换成幅度和相位的形式输出。以下是用Python实现锁相放大器的代码,包括生成X分量和正交分量Y的函数:
``` python
import numpy as np
def generate_signal(freq, phase, time):
"""
生成输入信号
:param freq: 输入信号频率
:param phase: 输入信号相位
:param time: 时间序列
:return: 输入信号
"""
return np.sin(2 * np.pi * freq * time + phase)
def generate_reference(freq, phase, time):
"""
生成参考信号
:param freq: 参考信号频率
:param phase: 参考信号相位
:param time: 时间序列
:return: 参考信号
"""
return np.cos(2 * np.pi * freq * time + phase)
def lock_in_amplifier(signal, reference, time, filter_freq):
"""
锁相放大器
:param signal: 输入信号
:param reference: 参考信号
:param time: 时间序列
:param filter_freq: 滤波器截止频率
:return: X分量和Y分量
"""
# 相乘
product = signal * reference
# 滤波
filtered = butter_lowpass_filter(product, filter_freq, 1 / (time[1] - time[0]))
# 积分
x = integrate(filtered, time, 0)
y = integrate(filtered, time, np.pi / 2)
return x, y
def butter_lowpass_filter(data, cutoff, fs, order=5):
"""
Butterworth低通滤波器
:param data: 输入信号
:param cutoff: 截止频率
:param fs: 采样频率
:param order: 阶数
:return: 滤波后的信号
"""
nyq = 0.5 * fs
normal_cutoff = cutoff / nyq
b, a = butter(order, normal_cutoff, btype='low', analog=False)
y = lfilter(b, a, data)
return y
def integrate(data, time, phase):
"""
相位积分
:param data: 输入信号
:param time: 时间序列
:param phase: 初始相位
:return: 积分后的信号
"""
dt = time[1] - time[0]
result = np.zeros(len(time))
for i in range(1, len(time)):
result[i] = result[i-1] + data[i] * np.sin(phase) * dt
phase += 2 * np.pi * dt
return result
```
使用方法:
``` python
freq = 100 # 输入信号频率
phase = np.pi / 4 # 输入信号相位
filter_freq = 10 # 滤波器截止频率
time = np.linspace(0, 1, 1000) # 时间序列
signal = generate_signal(freq, phase, time) # 生成输入信号
reference = generate_reference(freq, 0, time) # 生成参考信号
x, y = lock_in_amplifier(signal, reference, time, filter_freq) # 锁相放大器
```
其中,freq是输入信号频率,phase是输入信号相位,filter_freq是滤波器截止频率,time是时间序列。生成输入信号和参考信号的函数分别是generate_signal和generate_reference,锁相放大器的函数是lock_in_amplifier,它返回X分量和正交分量Y。在代码中用到了Butterworth低通滤波器和相位积分。
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