mirror of
https://github.com/galera951/experiment-automation.git
synced 2024-11-14 18:05:53 +03:00
482 lines
91 KiB
Plaintext
482 lines
91 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "aa41c92f-b4cc-46aa-933e-1d2ff85f409e",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"# %load /home/glebi/git/experiment-automation/processing_tools.py\n",
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"import numpy as np\n",
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"from scipy.optimize import curve_fit\n",
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"import pandas as pd\n",
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"\n",
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"import matplotlib.pyplot as plt\n",
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"import matplotlib\n",
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"import scienceplots\n",
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"\n",
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"plt.style.use(['science', 'russian-font'])\n",
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"\n",
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"matplotlib.rcParams.update({\n",
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" 'figure.figsize': [6, 4],\n",
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" 'savefig.facecolor': 'white',\n",
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" 'figure.dpi': 150.0,\n",
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" 'font.size': 12.0,\n",
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"})\n",
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"\n",
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"line = lambda x, k, b: k*x + b\n",
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"deltaPercent = lambda a, b: (1 - min(a, b) / max(a, b)) * 100"
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]
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},
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{
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"cell_type": "markdown",
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"id": "f4db8318-243e-450c-8dd4-474e5b9fb945",
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"metadata": {},
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"source": [
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"## 1 Усиление ОУ"
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]
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},
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{
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"cell_type": "markdown",
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"id": "518abf57-8909-49f7-a487-46211ec8f416",
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"metadata": {},
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"source": [
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"![scheme1](scheme1.png)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "22d07d19-02ec-468b-aa0f-0738cb65931a",
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"metadata": {},
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"source": [
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"## 2 АЧХ ОУ"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "48d80fc6-9c30-4ec2-ac70-ef9bfde85924",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Крутизна = \t-19.55 дБ/декаду\n",
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"fp0 = \t\t 13.25 Гц\n",
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"fT = \t\t 1.20e+06 Гц\n"
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]
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}
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],
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"source": [
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"data = np.loadtxt(\"data2.txt\", skiprows=1, delimiter=\",\").T\n",
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"f = data[0]\n",
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"Uout = data[1]\n",
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"Ua = data[2]\n",
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"\n",
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"A = 101 * Uout / Ua\n",
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"Adb = 20 * np.log10(A)\n",
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"\n",
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"popt, _ = curve_fit(line, np.log10(f), Adb)\n",
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"print(f\"Крутизна = \\t{popt[0]:.2f} дБ/декаду\")\n",
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"\n",
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"fp0 = 10 ** ((Adb[0] - 3 - popt[1]) / popt[0])\n",
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"print(f\"fp0 = \\t\\t {fp0:.2f} Гц\")\n",
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"\n",
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"fT = 10 ** ((1 - popt[1]) / popt[0])\n",
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"print(f\"fT = \\t\\t {fT:.2e} Гц\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "1348218c-f9c0-4fc6-97a9-19c8a0a18c44",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 900x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.plot(f, Adb, \"o\")\n",
|
||
"plt.plot(f, line(np.log10(f), *popt), \"--\", color=\"C0\")\n",
|
||
"plt.xscale(\"log\")\n",
|
||
"\n",
|
||
"plt.xlabel(\"Frequency, Hz\")\n",
|
||
"plt.ylabel(\"Gain factor, dB\")\n",
|
||
"\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "570b3241-2223-4e98-956b-5b75b608fdd7",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 3 Неинвертирующий усилитель"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"id": "949340bc-88c9-48c0-8c91-3dce05307861",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Входное напряжение сдвига Uos \t1.49e-04 В\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"R1 = 1e3 # Ohm\n",
|
||
"R2 = 1e5 # Ohm\n",
|
||
"\n",
|
||
"Uout_dc = 0.015 # V\n",
|
||
"Uos = Uout_dc / (1 + R2 / R1)\n",
|
||
"print(f\"Входное напряжение сдвига Uos \\t{Uos:.2e} В\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"id": "247fe705-0dc7-4bf4-ac2a-154d3db03f1b",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 900x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"data = np.loadtxt(\"data3.txt\", skiprows=1, delimiter=\",\").T\n",
|
||
"f = data[0]\n",
|
||
"Uin = data[1]\n",
|
||
"Uout = data[2]\n",
|
||
"\n",
|
||
"A = Uout / Uin\n",
|
||
"Adb = 20 * np.log10(A)\n",
|
||
"\n",
|
||
"plt.plot(f, Adb, \"--o\")\n",
|
||
"plt.xscale(\"log\")\n",
|
||
"\n",
|
||
"plt.xlabel(\"Frequency, Hz\")\n",
|
||
"plt.ylabel(\"Gain factor, dB\")\n",
|
||
"\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"id": "57a10d24-1c60-4f58-add1-009eafa97da2",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Граничная частота Fp \t\t\t1.46e+04 Гц\n",
|
||
"Расхождение между A(f_низк) и K0 \t1.64 %\n",
|
||
"Расхождение между beta*fT и Fp \t\t18.47 %\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"Fp = None\n",
|
||
"for i in range(len(f) - 1):\n",
|
||
" if ((Adb[0] - 3) < Adb[i]) and ((Adb[0] - 3) >= Adb[i+1]):\n",
|
||
" k = (Adb[i] - Adb[i+1]) / (f[i] - f[i+1])\n",
|
||
" b = Adb[i] - k*f[i]\n",
|
||
" Fp = ((Adb[0] - 3) - b) / k\n",
|
||
" break\n",
|
||
"print(f\"Граничная частота Fp \\t\\t\\t{Fp:.2e} Гц\")\n",
|
||
" \n",
|
||
"beta = R1 / (R1 + R2)\n",
|
||
"K0 = 1 / beta\n",
|
||
"print(f\"Расхождение между A(f_низк) и K0 \\t{deltaPercent(A[0], K0):.2f} %\")\n",
|
||
"print(f\"Расхождение между beta*fT и Fp \\t\\t{deltaPercent(Fp, beta*fT):.2f} %\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"id": "eac3816b-84d9-4418-8a1a-2bb85736e712",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# п. 5\n",
|
||
"f = 2e3 # Hz\n",
|
||
"Umax = 10.77 # V\n",
|
||
"# Дальше у сигнала появляется характерная \"полка\""
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"id": "b6f2bc90-bb7a-4cef-8ec0-683f5f702956",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Расхождение между Umax и Um_out \t13.19 %\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# п. 6\n",
|
||
"Fp = 2.22e6 # Hz (A = 1/sqrt(2))\n",
|
||
"Umax = .55 # V\n",
|
||
"Um_out = 3e6 / (2*3.1415 * 1e6) # V\n",
|
||
"print(f\"Расхождение между Umax и Um_out \\t{deltaPercent(Umax, Um_out):.2f} %\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "34a95100-4916-4ef5-a4a3-8c0ec4b036af",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 8 Интегратор"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "77ce8336-45a8-49b9-a26d-f96fffdea6fb",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"source": [
|
||
"### АЧХ интегратора"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "a9fadd8f-3c43-4169-abea-1fa57db853a8",
|
||
"metadata": {},
|
||
"source": [
|
||
"![8-afc](8-afc.bmp)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "fbad0e8d-43c2-4e1e-ba29-1d6cea984697",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"source": [
|
||
"### Интегрирование сигнала"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "466ed0d0-fadd-4509-9c33-c64fd9559dc1",
|
||
"metadata": {},
|
||
"source": [
|
||
"![8-square-integral](8-square-integral.bmp)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "7618109f-45e6-4c52-ada6-835bdf820c00",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 9 Дифференциатор"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "2702a3f2-f7d0-471c-921e-cfca9281eb15",
|
||
"metadata": {},
|
||
"source": [
|
||
"### АЧХ дифференциатора"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "bea67faa-850d-485f-aa50-ee421c910551",
|
||
"metadata": {},
|
||
"source": [
|
||
"![9-afc](9-afc.bmp)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "3fac9fa8-aef6-4ee0-a873-3a76cd5ef2a6",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Дифференцирование сигнала"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "26a3c6d1-f434-4918-98d7-9f85d9c84409",
|
||
"metadata": {},
|
||
"source": [
|
||
"![9-triangle-diff](9-triangle-diff.bmp)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "6c1d7a93-9215-4a93-8ad2-5112d4b1dfde",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 14 Триггер Шмидта"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "5ea617c8-27b8-40e1-b9ad-d559d78bcf75",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Uref = 0, Umax = 1 В (амплитуда синуса)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "353f67bc-720b-4574-957b-52590d5962ae",
|
||
"metadata": {},
|
||
"source": [
|
||
"![14-shmidt-ref0-sine1](14-shmidt-ref0-sine1.bmp)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "0f621ca4-7278-469c-992c-4dbdb4a9beee",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Uref = 4 В, Umax = 5 В (амплитуда синуса)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "008e6439-245a-4ba3-a5dc-dba1dfb206ae",
|
||
"metadata": {},
|
||
"source": [
|
||
"![14-shmidt-ref4-sine5](14-shmidt-ref4-sine5.bmp)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "00aebab3-a3bc-4098-9b00-7362c3212235",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 15 Самовозбуждающийся мультивибратор"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"id": "4f05ba6f-c0c4-431f-9d78-91af6ac2cd7a",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"R = 1.00e+04, C = 1.37e-07\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"beta = 1/11\n",
|
||
"T0 = 0.5e-3 # s\n",
|
||
"RC = T0 / 2 / np.log((1 + beta) / (1 - beta))\n",
|
||
"R = 10e3 # Ohm\n",
|
||
"C = RC / R\n",
|
||
"print(f\"R = {R:.2e}, C = {C:.2e}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "01b684c1-c797-4ea5-8349-c7293ecaa045",
|
||
"metadata": {},
|
||
"source": [
|
||
"![15-multivibrator](15-multivibrator.bmp)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"id": "8c83e108-72e4-4c20-a1b9-8723599d51e9",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Расхождение между T0 и Texp \t\t2.89 %\n",
|
||
"Расхождение beta*Umax между Th и Exp \t0.22 %\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"T = (8.568 - 3.934) / 9 * 1e-3\n",
|
||
"print(f\"Расхождение между T0 и Texp \\t\\t{deltaPercent(T0, T):.2f} %\")\n",
|
||
"\n",
|
||
"Umax = 13.5 # V\n",
|
||
"bUmax_exp = 1.23 # V\n",
|
||
"print(f\"Расхождение beta*Umax между Th и Exp \\t{deltaPercent(bUmax_exp, Umax*beta):.2f} %\")"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3 (ipykernel)",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.10.12"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|