diff --git a/Ferromagnetische_Hysterese/Ferromagnetische_Hysterese_final.ipynb b/Ferromagnetische_Hysterese/Ferromagnetische_Hysterese_final.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..5256b9b461d82cc0bb7dd9e8beb320a540df9408 --- /dev/null +++ b/Ferromagnetische_Hysterese/Ferromagnetische_Hysterese_final.ipynb @@ -0,0 +1,1712 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "885c7767-e912-4e31-b5d6-3a3443ffa58e", + "metadata": {}, + "source": [ + "# Fakultät für Physik\n", + "\n", + "## Physikalisches Praktikum P1 für Studierende der Physik\n", + "\n", + "Versuch P1-61, 62, 63 (Stand: **Oktober 2024**)\n", + "\n", + "[Raum F1-16](https://labs.physik.kit.edu/img/Klassische-Praktika/Lageplan_P1P2.png)\n", + "\n", + "\n", + "\n", + "# Ferromagnetische Hysterese" + ] + }, + { + "cell_type": "markdown", + "id": "6cda71a9-2111-4282-a28a-821dc2202093", + "metadata": {}, + "source": [ + "Name:Reisner Vorname: Christian E-Mail: uqnwo@student.kit.edu\n", + "\n", + "\\begin{equation*}\n", + "\\begin{split}\n", + "&\\\\\n", + "&\\\\\n", + "\\end{split}\n", + "\\end{equation*}\n", + "\n", + "Name:Ben Tov Vorname: Jonthan E-Mail: ufoxj@student.kit.edu\n", + "\n", + "\\begin{equation*}\n", + "\\begin{split}\n", + "&\\\\\n", + "&\\\\\n", + "&\\\\\n", + "\\end{split}\n", + "\\end{equation*}\n", + "\n", + "Gruppennummer: Do06\n", + "\n", + "\\begin{equation*}\n", + "\\begin{split}\n", + "&\\\\\n", + "&\\\\\n", + "&\\\\\n", + "\\end{split}\n", + "\\end{equation*}\n", + "\n", + "\n", + "Betreuer: Finn Rosumek\n", + "\n", + "\\begin{equation*}\n", + "\\begin{split}\n", + "&\\\\\n", + "&\\\\\n", + "&\\\\\n", + "\\end{split}\n", + "\\end{equation*}\n", + "\n", + "Versuch durchgeführt am: 05.12.2024" + ] + }, + { + "cell_type": "markdown", + "id": "9861759e-6c07-4ec5-a750-f307ec3d8028", + "metadata": {}, + "source": [ + "---\n", + "\n", + "**Beanstandungen zu Protokoll Version _____:**\n", + "\n", + "\\begin{equation*}\n", + "\\begin{split}\n", + "&\\\\\n", + "&\\\\\n", + "&\\\\\n", + "&\\\\\n", + "&\\\\\n", + "&\\\\\n", + "&\\\\\n", + "&\\\\\n", + "&\\\\\n", + "&\\\\\n", + "\\end{split}\n", + "%\\text{\\vspace{10cm}}\n", + "\\end{equation*}\n", + "\n", + "<br>\n", + "Testiert am: __________________ Testat: __________________" + ] + }, + { + "cell_type": "markdown", + "id": "e3e27d6b-3390-4401-8300-1dc26021fb2d", + "metadata": {}, + "source": [ + "# Durchführung" + ] + }, + { + "cell_type": "markdown", + "id": "be70efea-bff5-42d5-b5aa-0b9598c33846", + "metadata": {}, + "source": [ + "**Detaillierte Hinweise zur Durchführung der Versuche finden Sie in der Datei [Ferromagnetische_Hysterese_Hinweise.ipynb](https://gitlab.kit.edu/kit/etp-lehre/p1-praktikum/students/-/blob/main/Ferromagnetische_Hysterese/Ferromagnetische_Hysterese_Hinweise.ipynb)**" + ] + }, + { + "cell_type": "markdown", + "id": "8fe74fe8-1b63-48de-832b-ad03e49b0132", + "metadata": {}, + "source": [ + "## Aufgabe 1: Induktivität und Verlustleistung einer Spule" + ] + }, + { + "cell_type": "markdown", + "id": "0f05f94c-cb93-4ac6-b323-7a73a8bffbb0", + "metadata": {}, + "source": [ + "### Aufgabe 1.1: Luftgefüllte Spulte\n", + "\n", + " * Bestimmen Sie die **Spuleninduktivität** $L$, den **Verlustwiderstand** $R_{L}$ und die **elektrische Verlustleistung** $P_{L}$ (aufgrund von $R_{L}$) einer luftgefüllten Spule.\n", + " * Bestätigen oder Widerlegen Sie die Hypothese, dass weder $L$ noch $R_{L}$ von der effektiven Stromstärke $I_{\\mathrm{eff}}$ im Wechselstromkreis abhängen.\n", + " * Berechnen Sie aus den angegebenen Spulendaten im [Datenblatt](https://gitlab.kit.edu/kit/etp-lehre/p1-praktikum/students/-/blob/main/Ferromagnetische_Hysterese/Datenblatt.md) zum Versuch die erwarteten Werte für $L$ und $R_{L}$ und vergleichen Sie Ihre Erwartung mit der Messung.\n", + "\n", + "---" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "72523276-c7ae-467f-97b4-b03495806d9e", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import PhyPraKit as PPK\n", + "import kafe2\n", + "from uncertainties import ufloat\n", + "from uncertainties.umath import sin,cos\n", + "def n(a):\n", + " return np.array([x.n for x in a])\n", + "def s(a):\n", + " return np.array([x.s for x in a])\n", + "def utl(u):\n", + " return [f\"${x.nominal_value:.2f} \\\\pm {x.std_dev:.2f}$\" for x in u]" + ] + }, + { + "attachments": { + "7cd64ca7-6bdc-45d3-a85b-d703b5a97f03.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "b699a264-3663-45b1-9ce4-ab2424a308d5", + "metadata": {}, + "source": [ + "**V E R S U C H S B E S C H R E I B U N G**\n", + "\n", + " \n", + "Quelle: Hinweise für den Versuch Ferromagnetische Hysterese-Impedanz der Spule \n", + "\n", + "\n", + "Es wurde eine Spule mit dem der Windungszahl $N=1000$ der Länge $l=6.8\\,\\mathrm{cm}$, einer Drahtdicke $d=0.7\\,\\mathrm{mm}$ und einer mittleren Wicklungsradius $r=3.4 \\,\\mathrm{cm}$ und einer Querschnitsfläche von $A\\approx 15.21 \\,\\mathrm{cm^2}$ mit dem Wiederstand $R_1=10 \\pm 0.5 \\,\\mathrm{\\Omega}$ in Reihe geschaltet. Diese Schaltung wurde mit einer sinusförmigen Spannung der Frequenz $f= 50 \\pm 0.1 \\,\\mathrm{Hz}$ und einer Ampitude $U_0=12 \\,\\mathrm{V}$. Mit einem Ampermeter wurde der Efektiv Strom durch die Schaltung gemessen. Desweiteren wurden die Spannungen an $R_1$ und $L$ gemessen. Aufgezeichnet wurden für verschiedene Werte für $I_{eff}$ die jeweiligen Pickspannungen $U_{L,0}$ und $U_{L,0}$, sowie die Zeitdifferenz der Nulldurchläufe von $U_R$ und $U_L$. \n", + "Für die Impedanz einer reelen Spule gilt: \n", + "$Z=R_L+ i\\omega L=|Z|\\cdot e^{i\\Delta \\varphi}$ \n", + "und somit nach der Aufspalltung in einen Real und Imaginärteil sowie mit $|Z|=\\dfrac{U_{L,0}}{U_{R,0}}R$ und $\\Delta\\varphi = \\omega\\,\\Delta t$: \n", + "$$\n", + "\\begin{equation*}\n", + "\\begin{split}\n", + "&L = \\frac{U_{L,0}}{U_{R,0}}\\,\\frac{R}{\\omega}\\,\\sin(\\omega\\Delta t);\\\\\n", + "&\\\\\n", + "&R_{L} = \\frac{U_{L,0}}{U_{R,0}}\\,R\\,\\cos(\\omega\\Delta t).\n", + "\\end{split}\n", + "\\end{equation*}\n", + "$$ \n", + "\n", + "sowie aus weiteren Überlegungen: \n", + "$$\n", + "\\begin{equation*}\n", + "\\begin{split}\n", + "&L \\approx N^{2}\\,\\frac{\\mu_{0}\\,\\,A}{\\ell+0.91r}.\n", + "&\\\\\n", + "&R_{L} =\\rho\\,\\frac{l_{Draht}}{A_{Draht}}.\n", + "\\end{split}\n", + "\\end{equation*}\n", + "$$ \n", + "\n", + "Wobei $l_{Draht}$ die Länge des Drahtes ist und $A_{Draht}$ der Querschnitt des Drahtes ist. \n", + "\n", + "Die Verlustleistung an $L$ lässt sich über $P_{ver}=R_L\\cdot I_{eff}^2$\n", + "\n", + "Desweiteren kann über eine Anpassung von $\\mu_r$ und $R_L$ als konstante Werte gegen $I_{eff}$ kann gezeigt werden, dass die beiden Werte von $I_{eff}$ unbhängig sind. \n", + "\n", + "Die Fehler wurden aus den Unsicherheiten beim Ablesen und den Begerentzheit der Anzeigen, von den wir ausgehen, dass sie Näherungsweise den gesamten Fehler verantworten, wie follgt abgeschäzt: \n", + "$\\Delta\\omega=0.1\\,\\mathrm{Hz}$ \n", + "die Restlichen Unsicherheiten können der darstellung der Messwerte entnommen werden. \n", + "Die Berechnung der weiteren Unsicherheiten erfollgte mitels der Pythonbibliothek *uncertainties* mithilfe liniarer Fehlerpfortpflanzung berechnet. \n", + "\n", + "\n", + "\n", + "\n", + "\n", + "---" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "8e80a26f-775b-44f1-a90e-21ad5f95ce46", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Es wurde gemessen:\n" + ] + }, + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>$I_{eff}\\mathrm{[mA]} $</th>\n", + " <th>$U_{R,0} \\,\\mathrm{mV} $</th>\n", + " <th>$U_{L,0} \\,\\mathrm{mV} $</th>\n", + " <th>$\\Delta t \\,\\mathrm{ms} $</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>$34.35 \\pm 0.10$</td>\n", + " <td>$0.51 \\pm 0.01$</td>\n", + " <td>$0.72 \\pm 0.01$</td>\n", + " <td>$2.72 \\pm 0.30$</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>$89.80 \\pm 0.10$</td>\n", + " <td>$1.32 \\pm 0.01$</td>\n", + " <td>$1.87 \\pm 0.01$</td>\n", + " <td>$2.15 \\pm 0.30$</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>$126.00 \\pm 0.10$</td>\n", + " <td>$1.85 \\pm 0.01$</td>\n", + " <td>$2.66 \\pm 0.01$</td>\n", + " <td>$2.71 \\pm 0.30$</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>$223.40 \\pm 0.10$</td>\n", + " <td>$3.31 \\pm 0.01$</td>\n", + " <td>$4.67 \\pm 0.01$</td>\n", + " <td>$2.70 \\pm 0.30$</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>$301.50 \\pm 0.10$</td>\n", + " <td>$4.44 \\pm 0.01$</td>\n", + " <td>$6.27 \\pm 0.01$</td>\n", + " <td>$2.72 \\pm 0.30$</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " $I_{eff}\\mathrm{[mA]} $ $U_{R,0} \\,\\mathrm{mV} $ $U_{L,0} \\,\\mathrm{mV} $ \\\n", + "0 $34.35 \\pm 0.10$ $0.51 \\pm 0.01$ $0.72 \\pm 0.01$ \n", + "1 $89.80 \\pm 0.10$ $1.32 \\pm 0.01$ $1.87 \\pm 0.01$ \n", + "2 $126.00 \\pm 0.10$ $1.85 \\pm 0.01$ $2.66 \\pm 0.01$ \n", + "3 $223.40 \\pm 0.10$ $3.31 \\pm 0.01$ $4.67 \\pm 0.01$ \n", + "4 $301.50 \\pm 0.10$ $4.44 \\pm 0.01$ $6.27 \\pm 0.01$ \n", + "\n", + " $\\Delta t \\,\\mathrm{ms} $ \n", + "0 $2.72 \\pm 0.30$ \n", + "1 $2.15 \\pm 0.30$ \n", + "2 $2.71 \\pm 0.30$ \n", + "3 $2.70 \\pm 0.30$ \n", + "4 $2.72 \\pm 0.30$ " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "UUr=0.01\n", + "UUl=0.005\n", + "UIf=0.1\n", + "Udelt=0.3\n", + "UR=np.array([ufloat(0.509,UUr),ufloat(1.316,UUr),ufloat(1.846,UUr),ufloat(3.313,UUr),ufloat(4.438,UUr)]) #mV\n", + "UL=np.array([ufloat(0.724,UUl),ufloat(1.866,UUl),ufloat(2.656,UUl),ufloat(4.665,UUl),ufloat(6.268,UUl)]) #mv\n", + "delt=np.array([ufloat(22.85-20.13,Udelt),ufloat(16.41-14.26,Udelt),ufloat(26.35-23.64,Udelt),ufloat(16.73-14.03,Udelt),ufloat(16.02-13.30,Udelt)]) #ms\n", + "delts=delt/1000\n", + "If=np.array([ufloat(34.35,UIf),ufloat(89.8,UIf),ufloat(126.0,UIf),ufloat(223.4,UIf),ufloat(301.5,UIf)]) #mA\n", + "omega=2*np.pi*ufloat(50,0.1)\n", + "R=ufloat(10,0.5)\n", + "print(\"Es wurde gemessen:\")\n", + "pd.DataFrame({\"$I_{eff}\\mathrm{[mA]} $\":utl(If),\n", + " \"$U_{R,0} \\,\\mathrm{mV} $\":utl(UR),\n", + " \"$U_{L,0} \\,\\mathrm{mV} $\":utl(UL),\n", + " \"$\\Delta t \\,\\mathrm{ms} $\":utl(delt)})" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "7b0c0e29-f5ba-4c38-87ca-4749fca945f6", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 1200x500 with 2 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>$I_{eff}\\mathrm{[mA]} $</th>\n", + " <th>$P_{verl} \\,\\mathrm{W} $</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>$34.35 \\pm 0.10$</td>\n", + " <td>$0.01 \\pm 0.00$</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>$89.80 \\pm 0.10$</td>\n", + " <td>$0.08 \\pm 0.00$</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>$126.00 \\pm 0.10$</td>\n", + " <td>$0.15 \\pm 0.01$</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>$223.40 \\pm 0.10$</td>\n", + " <td>$0.49 \\pm 0.02$</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>$301.50 \\pm 0.10$</td>\n", + " <td>$0.89 \\pm 0.04$</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " $I_{eff}\\mathrm{[mA]} $ $P_{verl} \\,\\mathrm{W} $\n", + "0 $34.35 \\pm 0.10$ $0.01 \\pm 0.00$\n", + "1 $89.80 \\pm 0.10$ $0.08 \\pm 0.00$\n", + "2 $126.00 \\pm 0.10$ $0.15 \\pm 0.01$\n", + "3 $223.40 \\pm 0.10$ $0.49 \\pm 0.02$\n", + "4 $301.50 \\pm 0.10$ $0.89 \\pm 0.04$" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "L=np.array([(UL[i]/UR[i])*(R/omega)*sin(omega*delts[i]) for i in range(len(UR))])\n", + "RL=np.array([(UL[i]/UR[i])*R*cos(omega*delts[i]) for i in range(len(UR))])\n", + "PL=RL*If**2\n", + "L1=L*1000\n", + "def l(r,L2=1):\n", + " return L2\n", + "data = kafe2.XYContainer(x_data=n(If),y_data=n(L1))\n", + "data.add_error(axis='x', err_val=s(If))\n", + "data.add_error(axis='y', err_val=s(L1))\n", + "data.label = '$Induktivität$ '\n", + "fit1=kafe2.XYFit(xy_data=data,model_function=l)\n", + "fit1.do_fit()\n", + "fit1.assign_model_function_latex_name(r\"L\")\n", + "def R2(r,R_L=1):\n", + " return R_L\n", + "data = kafe2.XYContainer(x_data=n(If),y_data=n(RL))\n", + "data.add_error(axis='x', err_val=s(If))\n", + "data.add_error(axis='y', err_val=s(RL))\n", + "data.label = '$Widerstand$ '\n", + "fit2=kafe2.XYFit(xy_data=data,model_function=R2)\n", + "fit2.do_fit()\n", + "RL=ufloat(fit2.parameter_values[0],fit2.parameter_errors[0])\n", + "kafe2.plot({fit1,fit2}, x_label=r\"$I_f\\,\\mathrm{[mA]}$\", y_label=r'$ L\\,\\mathrm{[mH]} \\mathrm{und\\ } R \\,\\mathrm{[\\Omega]} $')\n", + "Pver=RL*(If/1000)**2\n", + "pd.DataFrame({\"$I_{eff}\\mathrm{[mA]} $\":utl(If),\n", + " \"$P_{verl} \\,\\mathrm{W} $\":utl(Pver)})" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "8bd0860c-c28b-4442-b42e-1d0f048deddb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Rechnerisch ergibt sich L=0.04612598620440388 H und R=9.880816326530613 Ohm\n" + ] + } + ], + "source": [ + "N=1000\n", + "r=0.034\n", + "l=0.068\n", + "d=0.0007\n", + "A=np.pi*r**2\n", + "mu0=4*np.pi*10**(-7)\n", + "rhocu=1.78*10**(-8)\n", + "le=N*2*np.pi*r\n", + "Ad=np.pi*(d/2)**2\n", + "Lrech=N**2*mu0*A/(l+0.91*r)\n", + "Rl=rhocu*(le/Ad)\n", + "print(f\"Rechnerisch ergibt sich L={Lrech} H und R={Rl} Ohm\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "565415af-fabb-479d-8e88-1e73d65f71ae", + "metadata": {}, + "source": [ + "**L Ö S U N G**\n", + "\n", + "Aus den Daten von $U_{R,0},U_{R,0}$ und $\\Delta t$ follgt also: \n", + "$R_L=9.78\\pm 0.75 \\,\\mathrm{\\Omega}$ \n", + "$L=33.1\\pm 2.3 \\,\\mathrm{mH}$ \n", + "\n", + "Beide Fits mit einem konstanten Wert beschreiben die Daten im Rahmen der Unsicherheiten sehr gut, wie sich aus $\\chi^2/ndf < 1$ und $chi^2 \\ \\mathrm{proability}\\approx 0.7$ follgern lässt. Sie sind also nicht von $I_{eff}$ abhängig.\n", + "\n", + "\n", + "Eine Berechnung von $R_L$ und $L$ aus den Dimensionierungen der Spule ergibt: \n", + "$R_L\\approx9.88\\,\\mathrm{\\Omega}$ \n", + "$L\\approx 46.1\\,\\mathrm{mH}$ \n", + "\n", + "Des weiterrn lässt sich für den Betrag der $Z=R_L+i\\omega L$ mit den berechnten Werten und den Messwerten: \n", + "$|Z_{Rechnung}|=15.16\\pm 0.03 \\,\\mathrm{\\Omega}$ \n", + "$|Z_{Messung}|=14.2\\pm 0.5 \\,\\mathrm{\\Omega}$ \n" + ] + }, + { + "cell_type": "markdown", + "id": "3d2e8948-810e-4240-9f99-8cb2c8bb2db2", + "metadata": {}, + "source": [ + "**D I S K U S S I O N**\n", + "\n", + "Beide Werte von $R_L$ sind im Rahmen der Messunsicherheit verträglich, die beiden Werte für $L$ nicht. Ein Vergleich mit den Herstellerangben ($L=44\\,\\mathrm{mH}$) legt nahe, dass der Wert für L aus der Berechnung von mithilfe von $U_{R,0},U_{R,0}$ und $\\Delta t$ warscheinlich zu klein ist. Es könnte eine Unsicherheit zu klein Abgeschätz worden sein, oder Beschädigung in der Spule fühert zu einer faktischen Änderung der Daten der Spule von denn Herstellerangaben. \n", + "\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "20887c3e-9c2e-4cf2-918e-c6091ec8f900", + "metadata": {}, + "source": [ + "### Aufgabe 1.2: Spule mit Eisenkern\n", + "\n", + " * Wiederholen Sie die Messungen von **Aufgabe 1.1**, diesmal jedoch mit einem Eisenkern in der Spule.\n", + " * Berechnen Sie aus den Daten der Spule und den gemessenen Werten für $L$ die (mittlere) **relative Permeabilität** $\\langle\\mu_{r}\\rangle$ als Funktion von $I_{\\mathrm{eff}}$.\n", + " * Berechnen Sie aus den gemessenen Werten für $R_{L}$ und $I_{\\mathrm{eff}}$ die **Verlustleistung $P_{L}$ der Spule**, als Funktion von $I_{\\mathrm{eff}}$ und vergleichen Sie mit dem Ergebnis aus **Aufgabe 1.1**.\n", + "\n", + "---" + ] + }, + { + "attachments": { + "61b1d54c-4a46-4ef5-b20b-d113f03ded4e.png": { + 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" + } + }, + "cell_type": "markdown", + "id": "0722c5d3-c073-4d86-a6c0-e6dc05073693", + "metadata": {}, + "source": [ + "**V E R S U C H S B E S C H R E I B U N G**\n", + " \n", + "Quelle: Hinweise für den Versuch Ferromagnetische Hysterese-Impedanz der Spule \n", + "\n", + "\n", + "Der Versuch wurde wie in Aufgabe 1.1 Wiederholt und in soweit Verändert als das ein geschlossenen Eisenkern, welcher durch Schichten von islierdem Matrial Wirbelströme weitestgehend unterdrückt, in die Spule eingefügt wurde. In diesem ist die mittler Feldlinienlänge $l=48 \\,\\mathrm{cm}$. Zur Messbereichserweiterung wurde Das zur Messung von $U_L$ durch das zuschalten eines Wiederstnad $R_S=9 \\,\\mathrm{M\\Omega}$ verzehnfacht. \n", + "Aus: \n", + "\n", + "\\begin{equation*}\n", + "\\begin{split}\n", + "&L = N^{2}\\,\\frac{\\mu_{0}\\cdot \\mu_r\\cdot A}{\\ell}\n", + "\\end{split}\n", + "\\end{equation*}\n", + "follgt: \n", + "$\\mu_r = \\dfrac {\\ell\\cdot L}{N^{2}\\cdot\\mu_{0}\\cdot A}$.\n", + "\n", + "wobei $\\mu_r$ in dem Fall ein Zeitlicher Mittelwert darstellt.\n", + "\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "aa723eed-4a46-41a3-a823-7e61a1d252c7", + "metadata": {}, + "source": [ + "**L Ö S U N G**\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "93e1f6ca-f090-4c7b-bef2-d5276ef6412b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>$I_{eff}\\mathrm{[mA]} $</th>\n", + " <th>$U_{R,0} \\,\\mathrm{[mV]} $</th>\n", + " <th>$U_{L,0} \\,\\mathrm{[mV]} $</th>\n", + " <th>$\\Delta t \\,\\mathrm{[ms]} $</th>\n", + " <th>$\\mu_r $</th>\n", + " <th>$P_{verl} \\,\\mathrm{[W]} $</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>$10.02 \\pm 0.10$</td>\n", + " <td>$0.15 \\pm 0.01$</td>\n", + " <td>$22.01 \\pm 0.10$</td>\n", + " <td>$1.44 \\pm 0.50$</td>\n", + " <td>$526.03 \\pm 175.41$</td>\n", + " <td>$0.13 \\pm 0.01$</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>$15.04 \\pm 0.10$</td>\n", + " <td>$0.23 \\pm 0.01$</td>\n", + " <td>$43.30 \\pm 0.10$</td>\n", + " <td>$3.52 \\pm 0.50$</td>\n", + " <td>$1416.89 \\pm 145.91$</td>\n", + " <td>$0.19 \\pm 0.06$</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>$20.09 \\pm 0.10$</td>\n", + " <td>$0.30 \\pm 0.01$</td>\n", + " <td>$73.70 \\pm 0.10$</td>\n", + " <td>$2.95 \\pm 0.50$</td>\n", + " <td>$1670.88 \\pm 221.32$</td>\n", + " <td>$0.60 \\pm 0.13$</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>$22.68 \\pm 0.10$</td>\n", + " <td>$0.33 \\pm 0.01$</td>\n", + " <td>$91.63 \\pm 0.10$</td>\n", + " <td>$2.99 \\pm 0.50$</td>\n", + " <td>$1875.76 \\pm 241.72$</td>\n", + " <td>$0.84 \\pm 0.19$</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " $I_{eff}\\mathrm{[mA]} $ $U_{R,0} \\,\\mathrm{[mV]} $ \\\n", + "0 $10.02 \\pm 0.10$ $0.15 \\pm 0.01$ \n", + "1 $15.04 \\pm 0.10$ $0.23 \\pm 0.01$ \n", + "2 $20.09 \\pm 0.10$ $0.30 \\pm 0.01$ \n", + "3 $22.68 \\pm 0.10$ $0.33 \\pm 0.01$ \n", + "\n", + " $U_{L,0} \\,\\mathrm{[mV]} $ $\\Delta t \\,\\mathrm{[ms]} $ \\\n", + "0 $22.01 \\pm 0.10$ $1.44 \\pm 0.50$ \n", + "1 $43.30 \\pm 0.10$ $3.52 \\pm 0.50$ \n", + "2 $73.70 \\pm 0.10$ $2.95 \\pm 0.50$ \n", + "3 $91.63 \\pm 0.10$ $2.99 \\pm 0.50$ \n", + "\n", + " $\\mu_r $ $P_{verl} \\,\\mathrm{[W]} $ \n", + "0 $526.03 \\pm 175.41$ $0.13 \\pm 0.01$ \n", + "1 $1416.89 \\pm 145.91$ $0.19 \\pm 0.06$ \n", + "2 $1670.88 \\pm 221.32$ $0.60 \\pm 0.13$ \n", + "3 $1875.76 \\pm 241.72$ $0.84 \\pm 0.19$ " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "UUr=0.01\n", + "UUl=0.01\n", + "UIf=0.1\n", + "Udelt=0.5\n", + "UR=np.array([ufloat(0.154,UUr),ufloat(0.230,UUr),ufloat(0.297,UUr),ufloat(0.332,UUr)]) #mV\n", + "UL=np.array([ufloat(2.201,UUl),ufloat(4.330,UUl),ufloat(7.370,UUl),ufloat(9.163,UUl)])*10 #mv\n", + "delt=np.array([ufloat(36.39-34.95,Udelt),ufloat(19.68-16.16,Udelt),ufloat(28.92-25.97,Udelt),ufloat(20.95-17.96,Udelt)]) #ms\n", + "delts=delt/1000\n", + "If=np.array([ufloat(10.02,UIf),ufloat(15.04,UIf),ufloat(20.09,UIf),ufloat(22.68,UIf)]) #mA\n", + "omega=2*np.pi*ufloat(50,0.1)\n", + "R=ufloat(10,0.5)\n", + "L=np.array([(UL[i]/UR[i])*(R/omega)*sin(omega*delts[i]) for i in range(len(UR))])\n", + "RL=np.array([(UL[i]/UR[i])*R*cos(omega*delts[i]) for i in range(len(UR))])\n", + "PL=RL*(If/1000)**2\n", + "N=1000\n", + "r=0.034\n", + "l=0.48\n", + "d=0.0007\n", + "A=0.038**2\n", + "mu0=4*np.pi*10**(-7)\n", + "rhocu=1.78*10**(-8)\n", + "le=N*2*np.pi*r\n", + "Ad=np.pi*(d/2)**2\n", + "mur=(L*l)/(N**2*mu0*A)\n", + "pd.DataFrame({\"$I_{eff}\\mathrm{[mA]} $\":utl(If),\n", + " \"$U_{R,0} \\,\\mathrm{[mV]} $\":utl(UR),\n", + " \"$U_{L,0} \\,\\mathrm{[mV]} $\":utl(UL),\n", + " \"$\\Delta t \\,\\mathrm{[ms]} $\":utl(delt),\n", + " \"$\\mu_r $\":utl(mur),\n", + " \"$P_{verl} \\,\\mathrm{[W]} $\":utl(PL)\n", + " })\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "b7500752-447c-4130-9711-a14b88d21c0b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 640x480 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.errorbar(n(If),n(PL),s(PL),s(If),marker='None', linestyle='None') \n", + "plt.ylabel(r'$P_L\\,\\mathrm{ [W]}$')\n", + "plt.xlabel('$I_{eff} \\,\\mathrm{ [mA]}$')\n", + "plt.title(\"Verlustleistung\")\n", + "plt.show()\n", + "plt.errorbar(n(If),n(mur),s(mur),s(If),marker='None', linestyle='None') \n", + "plt.ylabel(r'$\\mu_r$')\n", + "plt.xlabel('$I_{eff} \\,\\mathrm{ [mA]}$')\n", + "plt.title(\"Relative Permeabilität\")\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "41f840e3-c7de-4945-8370-b54745a50f95", + "metadata": {}, + "source": [ + "**D I S K U S S I O N**\n", + "\n", + "Die Wert von $\\mu_r$ sind mit den Angaben auf Wikipedia für die magnetische Permeabilität von Eisen (300 bis 10000) (https://de.wikipedia.org/wiki/Magnetische_Permeabilit%C3%A4t) verträglich. Dies ist aber aufgrun des sehr weiten Intervalls nur begernzt Ausagekräftig. \n", + "\n", + "Es lässt sich feststellen, dass die Verlustleistung tendenziell viel größer ist wenn der Eisenkern in die Spule eingeführt ist. ES gilt also $P_{verlustLuft}<P_{verlustLuft}$ wenn nicht $I_{effLuft}\\gg I_{effEisen}$. Es liegt nahe dass die (Um-)Magnetesierung Eisens im Fall mit einem Eisenkern einen erheblichen Teil der Verlustleistung ausmacht. \n", + "\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "3aadb392-61cb-4657-b068-9d9c1216460e", + "metadata": {}, + "source": [ + "## Aufgabe 2: Hysterese" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "e42096c8-8cb9-4937-8b94-8e0c78cdc05c", + "metadata": {}, + "source": [ + "### Aufgabe 2.1: Hysteresekurve\n", + "\n", + " * Stellen Sie die **Hysteresekurve** $B(H)$ für den Eisenkern aus **Aufgabe 1.2** für zwei geeignete effektive Stromestärken von $I_{\\mathrm{eff}}$ (im Primärkreis der Schaltung) auf dem Oszilloskop dar.\n", + " * Bestimmen Sie aus den aufgezeichneten Kurven $\\langle\\mu_{r}\\rangle$ und vergleichen Sie mit Ihren Ergebnissen aus **Aufgabe 1.2**.\n", + "\n", + "---" + ] + }, + { + "attachments": { + "9d8bfa84-6f03-4d9c-81b6-460e11615910.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "e96d00f4-6793-429d-b1f6-7287723557c8", + "metadata": {}, + "source": [ + "**V E R S U C H S B E S C H R E I B U N G**\n", + "\n", + "Quelle: Hinweise für den Versuch Ferromagnetische Hysterese-Magnetisierung und Polarisation\n", + "\n", + "Es wurde die Spule aus der Aufgabe 1.1 und 1.2 wie berits in den Aufgaben 1.2 geschaltet. Es wird zusätzlich eine Spule mit den gleich Spezifikationen aber einer Windungszahl von $N_2=50$ um den Eisenkern gestülpt und die Anordung so zu einem Transformator ergänzt. Diese zweite Spule wird mit einem Wiederstand $R_2=10 \\pm 0.5 \\,\\mathrm{k\\Omega}$ und einem Kondsator mit $C= 10 \\pm 0.5 \\,\\mathrm{\\mu F}$ in Reihe geschaltet. Gemessen wurde die Spannung $U_H$ am Wiederstand $R_1$ und die Spannung $U_H$ an der Spule $C$. \n", + "\n", + "Es gilt: \n", + "$H=N_1\\dfrac{I_1}{l}=N_1\\dfrac{U_H}{l\\cdot R_1}$\n", + "\n", + "sowie im hier vorliegenden Fall $R_2\\cdot 2\\cdot \\pi \\cdot f \\cdot C \\gg 1$: \n", + "$$\n", + "\\begin{equation*}\n", + "U_{B} = \\frac{1}{C\\,R_{2}}\\int U_{i}\\,\\mathrm{d}t = \\frac{N_{2}\\,A}{C\\,R_{2}}\\int \\dot{B}\\,\\mathrm{d}t = \\frac{N_{2}\\,A}{C\\,R_{2}}\\,B.\n", + "\\end{equation*}\n", + "$$ \n", + "also\n", + "$$\n", + "\\begin{equation*}\n", + "B = \\frac{C\\,R_{2}}{N_{2}\\,A}\\,U_{B}\n", + "\\end{equation*}\n", + "$$\n", + "\n", + "Die so erhalten Werte für $B$ können gegen $H$ aufgetragen werden um die Hysterkurve zu erhalten, dabei wurden die Messwerte auf 300 Daten ($H,B,t$) runtergesampelt und mittels des Phyenbibliothek *PhryPraKit* geglättet. Des weitern wurden mithilfe von Spliens zwischen den Dten interpoliert um eine Stetige Hysteriekurve zu erhalten. \n", + "\n", + "Des weiteren lässt sich $\\mu_r$ als zeitlicher Mittelwert wie follgt berechnen: \n", + "$\\mu_{r} = \\frac{B_{S}}{\\mu_{0}\\,H_{S}}$ \n", + "Da für $H\\approx 0$ zu sehr hohen Werten für $mu_r$ auftreten wurde der Median anstelle des arithmetischen Mittels betrachtet.\n", + "\n", + "Die Fehler wurden aus den Unsicherheiten beim Ablesen und den Begerenzheit der Anzeigen bzw. aus den Herstellerangben wie follgt abgeschätzt: \n", + "$\\Delta U_H=\\Delta U_B=0.05\\,\\mathrm{\\mu V}$ \n", + "$\\Delta l=0.01\\,\\mathrm{m}$ \n", + "$\\Delta R_2=500\\,\\mathrm{\\Omega}$ \n", + "$\\Delta R_1=0.5\\,\\mathrm{\\Omega}$ \n", + "$\\Delta C=0.5\\,\\mathrm{\\mu F}$ \n", + "Die Berechnung der weiteren Unsicherheiten erfollgte mitels der Pythonbibliothek *uncertainties* mithilfe liniarer Fehlerpfortpflanzung berechnet. \n", + "\n", + "Die Messungen wurden bei $I_{eff}=10.02 \\pm 0.05 \\,\\mathrm{mA}$ und $I_{eff}=24.24 \\pm 0.05 \\,\\mathrm{mA}$ durchgeführt.\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "db113a38-b1df-4ab9-b89c-a24bfd10b7c8", + "metadata": {}, + "source": [ + "**L Ö S U N G**\n", + "\n", + "*Fügen Sie numerische Berechnungen zur Lösung dieser Aufgabe hier ein. Löschen Sie hierzu diesen kursiv gestellten Text aus dem Dokument. Um Code-Fragmente und Skripte in [Python](https://www.python.org/), sowie ggf. bildliche Darstellungen direkt ins [Jupyter notebook](https://jupyter.org/) einzubinden verwandeln Sie diese Zelle in eine Code-Zelle. Fügen Sie ggf. weitere Code-Zellen zu.* \n", + "\n", + "---" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "02588024-7583-4ec2-a482-e20aec9bddb4", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Resampling by factor 13\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 600x600 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wir erhalten mur=(9.0+/-0.8)e+02 als Median. \n" + ] + } + ], + "source": [ + "#Ur ist Channel B und UC ist Channel A\n", + "#R2 = 10 kOhm\n", + "#C = 10 uF\n", + "N1=1000\n", + "N2=50\n", + "l=ufloat(0.48,0.01)\n", + "R2=ufloat(10000,500)\n", + "R1=ufloat(10,0.5)\n", + "UHfak=N1/(R1*l)\n", + "C=ufloat(10*10**(-6),0.5*10**(-6))\n", + "UHfak=N1/(R1*l)\n", + "UBfak=C*R2/(N2*(0.039)**2)\n", + "mu0=4*np.pi*10**(-7)\n", + "import pandas as pd\n", + "import numpy as np\n", + "from scipy import interpolate\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Read cvs file as pandas dataframe\n", + "#df = pd.read_csv(\"Christian_ist_ein_Schatz2_2_10_02mA2.csv\")\n", + "# Translate dataframe columns into native python lists\n", + "#t = df[\"Frequenz\"].to_list()[1:-1:10]\n", + "#UB = df[\"Kanal A\"].to_list()[1:-1:10] \n", + "#UH = df[\"Kanal B\"].to_list()[1:-1:10] \n", + "#UB=np.array(UB)\n", + "#UH=np.array(UH)\n", + "data = np.genfromtxt('Christian_ist_ein_Schatz2_2_10_02mA2.csv', delimiter=\",\", skip_header=3 )\n", + "t, UB, UH= data[:,0], data[:,1], data[:,2]\n", + "t=t[1:-1:]\n", + "UB=UB[1:-1:]/1000\n", + "UH=UH[1:-1:]/1000\n", + "from PhyPraKit.phyTools import resample, meanFilter\n", + "\n", + "# If length is too large, resample by an appropriate factor, we are fine with \n", + "# 350 data points\n", + "il=len(UH)\n", + "size=300\n", + "if il > size:\n", + " g = int(il/size)\n", + " # This is an example of smoothing by averaging over n neighbors\n", + " #print(\"Smoothing with window size \", n)\n", + " #t = meanFilter(vUH, width=n)\n", + " #UH = meanFilter(vUH, width=n)\n", + " #UB = meanFilter(vUB, width=n)\n", + " # This is an example of down sampling by averaging over n neighbors\n", + " print(\"Resampling by factor\", g)\n", + " t = resample(t , n=g)\n", + " UH = resample(UH, n=g)\n", + " UB = resample(UB, n=g)\n", + "\n", + "CALIB_UH2H = UHfak.n # U_H -> H <-- adjust !\n", + "CALIB_UB2B = UBfak.n # U_B -> B <-- adjust !\n", + "H = UH * CALIB_UH2H\n", + "B = UB * CALIB_UB2B\n", + "# Interpolate the points of (t,H) by spline functions; s=0 means that no extra \n", + "# smoothing will be applied, each point of H will be used for the spline\n", + "spl_Ht = interpolate.UnivariateSpline(t, H, s=0)\n", + "spl_Bt = interpolate.UnivariateSpline(t, B, s=0)\n", + "\n", + "# Plot hysteresis curve as Channel A vs. Channel B\n", + "tplt = np.linspace(t[0], t[-1], 200)\n", + "unitH = \"(A/m)\"; unitB = \"(T)\"\n", + "fig = plt.figure(1, figsize=(6.0, 6.0))\n", + "ax1 = fig.add_subplot()\n", + "ax1.scatter(H, B, color=\"blue\", marker=\"o\", s=5.0, label=\"Data points\")\n", + "ax1.plot(spl_Ht(tplt), spl_Bt(tplt), color=\"red\", label=\"Spline function\")\n", + "ax1.set_xlabel(\"H \" + unitH)\n", + "ax1.set_ylabel(\"B \" + unitB)\n", + "ax1.legend(numpoints=1, loc=\"best\")\n", + "ax1.grid(linestyle=\"dashed\")\n", + "plt.title(r\"Hysteresekurve bei $I_{eff}=10.02 \\pm 0.05 \\,\\mathrm{mA}$\")\n", + "plt.show()\n", + "\n", + "\n", + "stdU=0.00000005\n", + "Uh=np.array([ufloat(x,stdU) for x in UH])\n", + "Ub=np.array([ufloat(x,stdU) for x in UB])\n", + "b=UBfak*Ub\n", + "h=UHfak*Uh\n", + "murt=((b/(mu0*h))**2)**0.5\n", + "#murt2=[x for x in murt if x<2000]\n", + "#murt2=np.sort(murt)[49:-100]\n", + "#plt.plot(range(len(murt)),n(murt))\n", + "#plt.show()\n", + "#mur=np.mean(murt)\n", + "mur=np.median(murt)\n", + "#plt.plot(range(len(murt2)),n(murt2))\n", + "#plt.plot(range(len(murt2)),np.ones(len(murt2))*mur.n)\n", + "#plt.show()\n", + "print(f\"Wir erhalten mur={mur} als Median. \")" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "68df596f-5928-481c-bd9b-d5ab78ef06f0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Resampling by factor 13\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 600x600 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wir erhalten mur=(1.71+/-0.15)e+03 als Median. \n" + ] + } + ], + "source": [ + "#Ur ist Channel B und UC ist Channel A\n", + "#R2 = 10 kOhm\n", + "#C = 10 uF\n", + "N1=1000\n", + "N2=50\n", + "l=ufloat(0.48,0.01)\n", + "R2=ufloat(10000,500)\n", + "R1=ufloat(10,0.5)\n", + "C=ufloat(10*10**(-6),0.5*10**(-6))\n", + "mu0=4*np.pi*10**(-7)\n", + "UHfak=N1/(R1*l)\n", + "UBfak=C*R2/(N2*(0.039)**2)\n", + "import pandas as pd\n", + "import numpy as np\n", + "from scipy import interpolate\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Read cvs file as pandas dataframe\n", + "#df = pd.read_csv(\"Christian_ist_ein_Schatz2_2_10_02mA2.csv\")\n", + "# Translate dataframe columns into native python lists\n", + "#t = df[\"Frequenz\"].to_list()[1:-1:10]\n", + "#UB = df[\"Kanal A\"].to_list()[1:-1:10] \n", + "#UH = df[\"Kanal B\"].to_list()[1:-1:10] \n", + "#UB=np.array(UB)\n", + "#UH=np.array(UH)\n", + "data = np.genfromtxt('Christian_ist_ein_Schatz2_1_24_24_02mA2.csv', delimiter=\",\", skip_header=3 )\n", + "t, UB, UH= data[:,0], data[:,1], data[:,2]\n", + "t=t[1:-1:]\n", + "UB=UB[1:-1:]/1000\n", + "UH=UH[1:-1:]/1000\n", + "from PhyPraKit.phyTools import resample, meanFilter\n", + "\n", + "# If length is too large, resample by an appropriate factor, we are fine with \n", + "# 150 data points\n", + "il=len(UH)\n", + "size=300\n", + "if il > size:\n", + " g = int(il/size)\n", + " # This is an example of smoothing by averaging over n neighbours\n", + " #print(\"Smoothing with window size \", n)\n", + " #t = meanFilter(vUH, width=n)\n", + " #UH = meanFilter(vUH, width=n)\n", + " #UB = meanFilter(vUB, width=n)\n", + " # This is an example of down sampling by averaging over n neighbours\n", + " print(\"Resampling by factor\", g)\n", + " t = resample(t , n=g)\n", + " UH = resample(UH, n=g)\n", + " UB = resample(UB, n=g)\n", + "\n", + "CALIB_UH2H = UHfak.n # U_H -> H <-- adjust !\n", + "CALIB_UB2B = UBfak.n # U_B -> B <-- adjust !\n", + "H = UH * CALIB_UH2H\n", + "B = UB * CALIB_UB2B\n", + "# Interpolate the points of (t,H) by spline functions; s=0 means that no extra \n", + "# smoothing will be applied, each point of H will be used for the spline\n", + "spl_Ht = interpolate.UnivariateSpline(t, H, s=0)\n", + "spl_Bt = interpolate.UnivariateSpline(t, B, s=0)\n", + "\n", + "# Plot hysteresis curve as Channel A vs. Channeel B\n", + "tplt = np.linspace(t[0], t[-1], 200)\n", + "unitH = \"(A/m)\"; unitB = \"(T)\"\n", + "fig = plt.figure(1, figsize=(6.0, 6.0))\n", + "ax1 = fig.add_subplot()\n", + "ax1.scatter(H, B, color=\"blue\", marker=\"o\", s=5.0, label=\"Data points\")\n", + "ax1.plot(spl_Ht(tplt), spl_Bt(tplt), color=\"red\", label=\"Spline function\")\n", + "ax1.set_xlabel(\"H \" + unitH)\n", + "ax1.set_ylabel(\"B \" + unitB)\n", + "ax1.legend(numpoints=1, loc=\"best\")\n", + "ax1.grid(linestyle=\"dashed\")\n", + "plt.title(r\"Hysteresekurve bei $I_{eff}=24.24 \\pm 0.05 \\,\\mathrm{mA}$\")\n", + "plt.show()\n", + "\n", + "stdU=0.00000005\n", + "Uh=np.array([ufloat(x,stdU) for x in UH])\n", + "Ub=np.array([ufloat(x,stdU) for x in UB])\n", + "b=UBfak*Ub\n", + "h=UHfak*Uh\n", + "murt=((b/(mu0*h))**2)**0.5\n", + "#murt2=[x for x in murt if x<2000]\n", + "#murt2=np.sort(murt)[49:-100]\n", + "#plt.plot(range(len(murt)),n(murt))\n", + "#plt.show()\n", + "#mur=np.mean(murt2)\n", + "mur=np.median(murt)\n", + "#plt.plot(range(len(murt2)),n(murt2))\n", + "#plt.plot(range(len(murt2)),np.ones(len(murt2))*mur.n)\n", + "#plt.show()\n", + "print(f\"Wir erhalten mur={mur} als Median. \")" + ] + }, + { + "cell_type": "markdown", + "id": "d3814593-e9d4-428c-8ca9-2c980d56bfd3", + "metadata": {}, + "source": [ + "Es lässt sich aus den Daten errechen: \n", + "Für $I_{eff}=10.02 \\pm 0.05 \\,\\mathrm{mA}$: \n", + "$\\mu_r=900 \\pm 80$ \n", + "Für $I_{eff}=24.24 \\pm 0.05 \\,\\mathrm{mA}$: \n", + "$\\mu_r=1720 \\pm 150$ " + ] + }, + { + "cell_type": "markdown", + "id": "eaa372be-36be-4914-9477-b3025bdee5c5", + "metadata": {}, + "source": [ + "**D I S K U S S I O N**\n", + "\n", + "Der Vergleich mit den Werten aus für $\\mu_r$ aus der Aufgabe 1.2 legt nahe, dass die Werte miteinader weitestgehen Verträglich sind. \n", + "Zwar ist der Pull für die Werte mit $I_{eff}=10.02 \\pm 0.05 \\,\\mathrm{mA}$, mit 1.94 zwar größer als 1 da aber der Wert in der 1.2 aus nur einer Einzigen Messung beruht und somit stastistische Ausgen nur eine begerenzt Ausgekraft haben und der Wert aus der 2.1 aufgrund seiner Bestimmung über den Median auch Unsicher ist, kann von einer groben Verträglichkeit beider Messungen Augegangen werden. \n", + "\n", + "Für den Wert bei $I_{eff}=24.24 \\pm 0.05 \\,\\mathrm{mA}$ gibt es keine direckten Vergleichswerte in der Aufgabe 1.2 zwar ist $\\mu_r$ hier kleiner als $\\mu_r$ für $I_{eff}=22.68 \\pm 0.10 \\,\\mathrm{mA}$, was dem Ablesbaren Trend von $\\mu_r$ für steigenden $I_{eff}$ wiederspricht. Dies bewegt sich aber im Rahmen der Unsicherheiten. \n", + "\n", + "\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "66f60b58-6aac-4a8b-bb6a-adad17f3c95a", + "metadata": {}, + "source": [ + "### Aufgabe 2.2: Hystereseverlust \n", + "\n", + "**Diese Aufgabe ist nur für Studierende mit Hauptfach Physik verpflichtend. Studierende mit Nebenfach Physik und Lehramtstudierende können diese Aufgabe überspringen.**\n", + "\n", + " * Bestimmen Sie den **Hystereseverlust** $P_{\\mathrm{hyst}}$ und den dazu äquivalenten **Verlustwiderstand** $R_{\\mathrm{hyst}}$ aus den Magnetisierungskurven von **Aufgabe 2.1** für die verwendeten Werte von $I_{\\mathrm{eff}}$.\n", + " * Vergleichen Sie Ihr Ergebnis für $P_{\\mathrm{hyst}}$ mit Ihren Ergebnissen für $P_{L}$ aus **Aufgabe 1**.\n", + "\n", + "---" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "3791b4a9-ce39-473e-a9c8-00a1dcb8258a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Area enclosed by slope: 1.0320554354050826\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 600x600 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# The derivatives of H(t) will be used to determine the upper and lower branches \n", + "# of the hysteresis slope\n", + "spl_Ht_deriv = spl_Ht.derivative()\n", + "Hp = []; Bp = []; Hm = []; Bm = []\n", + "for i, ti in enumerate(t):\n", + " if spl_Ht_deriv(ti) > 0.0:\n", + " # The branch when H was increased (lower branch)\n", + " Hp.append(H[i])\n", + " Bp.append(B[i])\n", + " else:\n", + " # The branch when H was decreased (upper branch)\n", + " Hm.append(H[i])\n", + " Bm.append(B[i])\n", + "# Convert to numpy arrays and sort at the same time increasing in H\n", + "ip = np.argsort(Hp)\n", + "Hp = np.array(Hp)[ip]\n", + "Bp = np.array(Bp)[ip]\n", + "im = np.argsort(Hm)\n", + "Hm = np.array(Hm)[im]\n", + "Bm = np.array(Bm)[im]\n", + "# Provide spline approximations for the upper and lower bracnches of the curve; \n", + "# adjusting the parameter s is a cruical ingredient here to get useful and \n", + "# stable interpolations\n", + "prec = (max(Hp) - min(Hp))*10e-7\n", + "spl_BHp = interpolate.UnivariateSpline(Hp, Bp, s=prec)\n", + "spl_BHm = interpolate.UnivariateSpline(Hm, Bm, s=prec)\n", + "# Detemine boundaries of the contour for integration; choose the smallest \n", + "# interval out the upper and lower branch of the curve\n", + "Hmin = max(np.min(Hp), np.min(Hm))\n", + "Hmax = min(np.max(Hp), np.max(Hm))\n", + "# Calculate the integral of the contour\n", + "integral = spl_BHm.integral(Hmin, Hmax) - spl_BHp.integral(Hmin, Hmax)\n", + "# Print the result to screen\n", + "print(\"Area enclosed by slope:\", integral)\n", + "\n", + "# Plot hysteresis curve as Channel A vs. Channeel B and highlight enclosed \n", + "# area\n", + "fig = plt.figure(1, figsize=(6.0, 6.0))\n", + "ax2 = fig.add_subplot()\n", + "ax2.scatter(Hp, Bp, color=\"red\", marker=\"o\", s=15.0, label=\"Increasing H\")\n", + "ax2.scatter(Hm, Bm, color=\"blue\", marker=\"o\", s=15.0, label=\"Decreasing H\")\n", + "Hplt = np.linspace(Hmin, Hmax, 200)\n", + "ax2.plot(Hplt, spl_BHp(Hplt), color=\"darkred\", label=\"Lower Spline\")\n", + "ax2.plot(Hplt, spl_BHm(Hplt), color=\"darkblue\", label=\"Upper Spline\")\n", + "# Form a single contour to plot a filled area\n", + "ax2.fill(\n", + " np.concatenate((Hplt, np.flipud(Hplt))),\n", + " np.concatenate((spl_BHp(Hplt), np.flipud(spl_BHm(Hplt)))),\n", + " color=\"blue\",\n", + " alpha=0.25, \n", + " label=\"Enclosed area\"\n", + ")\n", + "ax2.legend(numpoints=1, loc=\"best\")\n", + "ax2.set_xlabel(\"H\" + unitH)\n", + "ax2.set_ylabel(\"B\" + unitB)\n", + "ax2.grid(linestyle=\"dashed\")\n", + "ax2.text(-275.0, -0.025, r\"$\\oint B\\,\\mathrm{d}H\\,=\\,%.4g\\,\\mathrm{\\frac{J}{m^{3}}}$\" % integral)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "1874d536-02ab-4d26-a701-b6b3b3003a75", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Area enclosed by slope: 20.08840840627854\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 600x600 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# The derivatives of H(t) will be used to determine the upper and lower branches \n", + "# of the hysteresis slope\n", + "spl_Ht_deriv = spl_Ht.derivative()\n", + "Hp = []; Bp = []; Hm = []; Bm = []\n", + "for i, ti in enumerate(t):\n", + " if spl_Ht_deriv(ti) > 0.0:\n", + " # The branch when H was increased (lower branch)\n", + " Hp.append(H[i])\n", + " Bp.append(B[i])\n", + " else:\n", + " # The branch when H was decreased (upper branch)\n", + " Hm.append(H[i])\n", + " Bm.append(B[i])\n", + "# Convert to numpy arrays and sort at the same time increasing in H\n", + "ip = np.argsort(Hp)\n", + "Hp = np.array(Hp)[ip]\n", + "Bp = np.array(Bp)[ip]\n", + "im = np.argsort(Hm)\n", + "Hm = np.array(Hm)[im]\n", + "Bm = np.array(Bm)[im]\n", + "# Provide spline approximations for the upper and lower bracnches of the curve; \n", + "# adjusting the parameter s is a cruical ingredient here to get useful and \n", + "# stable interpolations\n", + "prec = (max(Hp) - min(Hp))*10e-7\n", + "spl_BHp = interpolate.UnivariateSpline(Hp, Bp, s=prec)\n", + "spl_BHm = interpolate.UnivariateSpline(Hm, Bm, s=prec)\n", + "# Detemine boundaries of the contour for integration; choose the smallest \n", + "# interval out the upper and lower branch of the curve\n", + "Hmin = max(np.min(Hp), np.min(Hm))\n", + "Hmax = min(np.max(Hp), np.max(Hm))\n", + "# Calculate the integral of the contour\n", + "integral = spl_BHm.integral(Hmin, Hmax) - spl_BHp.integral(Hmin, Hmax)\n", + "# Print the result to screen\n", + "print(\"Area enclosed by slope:\", integral)\n", + "\n", + "# Plot hysteresis curve as Channel A vs. Channeel B and highlight enclosed \n", + "# area\n", + "fig = plt.figure(1, figsize=(6.0, 6.0))\n", + "ax2 = fig.add_subplot()\n", + "ax2.scatter(Hp, Bp, color=\"red\", marker=\"o\", s=15.0, label=\"Increasing H\")\n", + "ax2.scatter(Hm, Bm, color=\"blue\", marker=\"o\", s=15.0, label=\"Decreasing H\")\n", + "Hplt = np.linspace(Hmin, Hmax, 200)\n", + "ax2.plot(Hplt, spl_BHp(Hplt), color=\"darkred\", label=\"Lower Spline\")\n", + "ax2.plot(Hplt, spl_BHm(Hplt), color=\"darkblue\", label=\"Upper Spline\")\n", + "# Form a single contour to plot a filled area\n", + "ax2.fill(\n", + " np.concatenate((Hplt, np.flipud(Hplt))),\n", + " np.concatenate((spl_BHp(Hplt), np.flipud(spl_BHm(Hplt)))),\n", + " color=\"blue\",\n", + " alpha=0.25, \n", + " label=\"Enclosed area\"\n", + ")\n", + "ax2.legend(numpoints=1, loc=\"best\")\n", + "ax2.set_xlabel(\"H\" + unitH)\n", + "ax2.set_ylabel(\"B\" + unitB)\n", + "ax2.grid(linestyle=\"dashed\")\n", + "ax2.text(-275.0, -0.025, r\"$\\oint B\\,\\mathrm{d}H\\,=\\,%.4g\\,\\mathrm{\\frac{J}{m^{3}}}$\" % integral)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "e125ea09-a94b-43e1-a873-b7b4634df092", + "metadata": {}, + "source": [ + "**V E R S U C H S B E S C H R E I B U N G**\n", + "\n", + "Aus dem Folder \"tools\" wurde der Code \" Differentiation und Integration von Spline-Funktionen\" zur Berechnung der Fläche der Hysteresis-Kurve verwendet. Die Ergebnisse und Plots sind oben betrachtbar.\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "691ea74e-c262-436d-9f9f-a512e2f7f5b1", + "metadata": {}, + "source": [ + "**L Ö S U N G**\n", + "\n", + "Die Arbeit pro Volumeneinheit, die während eines Magnetisierungszyklus aufgewendet werden muss, um den Spulenkern mit dem Volumen $V$ zu magnetisieren ist: $\\omega=\\dfrac{W}{V}=\\displaystyle\\oint B\\,\\, \\mathrm{d}H$ mit $W$ die Arbeit. Das Integral wurde mit dem obrigen Code berechnen und ergibt: \n", + "\n", + "Für $I_{eff}=10.02 \\pm 0.05 \\,\\mathrm{mA}$: $\\,\\,\\,\\,\\,\\,\\,\\displaystyle\\oint B\\,\\, \\mathrm{d}H=1.032\\,\\mathrm{\\dfrac{J}{m^2}}$\n", + "\n", + "Für $I_{eff}=24.24 \\pm 0.05 \\,\\mathrm{mA}$: $\\,\\,\\,\\,\\,\\,\\,\\displaystyle\\oint B\\,\\, \\mathrm{d}H=20.09\\,\\mathrm{\\dfrac{J}{m^2}}$\n", + "\n", + "Mit der Gleichung $P_{hyst}=\\omega\\,\\nu\\,V$ zur Bestimmung des Hystereseverlustes wobei $\\nu$ die Frequenz der sinusförmigen Wechselspannung ist. Das Volumen $V$ des Spulenkers ist: $V=A\\,l=3.9\\,\\mathrm{cm}\\cdot3.9\\,\\mathrm{cm}\\cdot48\\,\\mathrm{cm}\\approx0.00073\\,\\mathrm{m^3}$.\n", + "\n", + "Somit gilt bei einer Wechselspannung von Frequenz $\\nu= 50 \\pm 0.1 \\,\\mathrm{Hz}$:\n", + "\n", + "Für $I_{eff}=10.02 \\pm 0.05 \\,\\mathrm{mA}$: $\\,\\,\\,\\,\\,\\,\\,P_{hyst}=\\omega\\,\\nu\\,V=1.032\\,\\mathrm{\\dfrac{J}{m^3}}\\cdot50\\,\\mathrm{Hz}\\cdot0.00073\\,\\mathrm{m^3}\\approx0.038 \\,\\mathrm{W}$\n", + "\n", + "Für $I_{eff}=24.24 \\pm 0.05 \\,\\mathrm{mA}$: $\\,\\,\\,\\,\\,\\,\\,P_{hyst}=\\omega\\,\\nu\\,V=20.09\\,\\mathrm{\\dfrac{J}{m^3}}\\cdot50\\,\\mathrm{Hz}\\cdot0.00073\\,\\mathrm{m^3}\\approx0.73 \\,\\mathrm{W}$\n", + "\n", + "Die Berechnung des Verlustwiderstandes $R_{hyst}$ folgt aus der Gleichung: $R_{hyst}=\\dfrac{U_{eff}^2}{P_{hyst}}=\\dfrac{(I_{eff}\\cdot Z_{Mess})^2}{P_{hyst}}$. Somit gilt:\n", + "\n", + "Für $I_{eff}=10.02 \\pm 0.05 \\,\\mathrm{mA}$: $\\,\\,\\,\\,\\,\\,\\,R_{hyst}=\\dfrac{(I_{eff}\\cdot Z_{Mess})^2}{P_{hyst}}=\\dfrac{(0.01002\\,\\mathrm{A}\\cdot 14.2\\,\\mathrm{\\Omega})^2}{0.038\\,\\mathrm{W}}\\approx0.5328\\,\\mathrm{\\Omega}$\n", + "\n", + "Für $I_{eff}=24.24 \\pm 0.05 \\,\\mathrm{mA}$: $\\,\\,\\,\\,\\,\\,\\,R_{hyst}=\\dfrac{(I_{eff}\\cdot Z_{Mess})^2}{P_{hyst}}=\\dfrac{(0.02424\\,\\mathrm{A}\\cdot 14.2\\,\\mathrm{\\Omega})^2}{0.73\\,\\mathrm{W}}\\approx0.1623\\,\\mathrm{\\Omega}$\n", + "\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "a27d59cd-4be9-49dc-b15b-d74960881da5", + "metadata": {}, + "source": [ + "**D I S K U S S I O N**\n", + "\n", + "Aus den Ergebnissen läst sich ablesen, dass hohe Ströme $I_{eff}$ und damit große Magnetisierungszyklen zu unerwünschten Energieverlusten führen können. Ein größerer Teil der Energie verschwindet durch Verluste (in Form von Wärme) im Gegensatz zu niedrigeren Strömen.\n", + "Ein Kernmaterialien mit einer schmalen Hystereseschleife führt auch zu weniger Verlusten an Energie. Im Vergleich zu $P_L$ aus Aufgabe 1 ist erkennbar, dass die Verluste kleiner sind als die gemessenen bei gleichem Strom in Aufgabe 1.2\n", + "\n", + "\n", + "---" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "5aaf2521-dbac-4802-a743-f267363680fc", + "metadata": {}, + "source": [ + "## Aufgabe 3: Magnetische Härte\n", + "\n", + " * Stellen Sie die Hysteresekurve für einen **Ferrit-Schalenkern** am Oszilloskop dar und vergleichen Sie diese mit der Hysteresekurve des Eisenkerns. \n", + " * Ermitteln Sie hierzu zusätzlich jeweils die folgenden Größen:\n", + " * **Remanenz** $B_{R}$,\n", + " * **Koerzitivfeldstärke** $H_{C}$ und\n", + " * **Sättigungsinduktion** $B_{S}$.\n", + " * Diskutieren Sie Ihre Erwartung für $P_{\\mathrm{hyst}}$ für den Ferrit-Schalenkern im Vergleich zum Eisenkern. \n", + "\n", + "---" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "93c09936-b52e-4bc6-b66d-329f5ab3e5a5", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Resampling by factor 13\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 600x600 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wir erhalten mur=(2.38+/-0.21)e+03 als Median. \n" + ] + } + ], + "source": [ + "N1=250\n", + "N2=50\n", + "l=ufloat(0.48,0.01)\n", + "R2=ufloat(10000,500)\n", + "R1=ufloat(10,0.5)\n", + "UHfak=N1/(R1*l)\n", + "C=ufloat(10*10**(-6),0.5*10**(-6))\n", + "UHfak=N1/(R1*l)\n", + "UBfak=C*R2/(N2*(0.039)**2)\n", + "mu0=4*np.pi*10**(-7)\n", + "import pandas as pd\n", + "import numpy as np\n", + "from scipy import interpolate\n", + "import matplotlib.pyplot as plt\n", + "\n", + "data = np.genfromtxt('Jonathan_ist_Gott_3_Eisen.csv', delimiter=\",\", skip_header=3 )\n", + "t, UB, UH= data[:,0], data[:,1], data[:,2]\n", + "t=t[1:-1:]\n", + "UB=UB[1:-1:]\n", + "UH=UH[1:-1:]\n", + "from PhyPraKit.phyTools import resample, meanFilter\n", + "\n", + "# If the length is too large, resample by an appropriate factor, we are fine with \n", + "# 350 data points\n", + "il=len(UH)\n", + "size=300\n", + "if il > size:\n", + " g = int(il/size)\n", + " # This is an example of smoothing by averaging over n neighbours\n", + " #print(\"Smoothing with window size \", n)\n", + " #t = meanFilter(vUH, width=n)\n", + " #UH = meanFilter(vUH, width=n)\n", + " #UB = meanFilter(vUB, width=n)\n", + " # This is an example of down sampling by averaging over n neighbours\n", + " print(\"Resampling by factor\", g)\n", + " t = resample(t , n=g)\n", + " UH = resample(UH, n=g)\n", + " UB = resample(UB, n=g)\n", + "\n", + "CALIB_UH2H = UHfak.n # U_H -> H <-- adjust !\n", + "CALIB_UB2B = UBfak.n # U_B -> B <-- adjust !\n", + "H = UH * CALIB_UH2H\n", + "B = UB * CALIB_UB2B\n", + "# Interpolate the points of (t,H) by spline functions; s=0 means that no extra \n", + "# Smoothing will be applied, each point of H will be used for the spline\n", + "spl_Ht = interpolate.UnivariateSpline(t, H, s=0)\n", + "spl_Bt = interpolate.UnivariateSpline(t, B, s=0)\n", + "\n", + "# Plot hysteresis curve as Channel A vs. Channel B\n", + "tplt = np.linspace(t[0], t[-1], 200)\n", + "unitH = \"(A/m)\"; unitB = \"(T)\"\n", + "fig = plt.figure(1, figsize=(6.0, 6.0))\n", + "ax1 = fig.add_subplot()\n", + "ax1.scatter(H, B, color=\"blue\", marker=\"o\", s=5.0, label=\"Data points\")\n", + "ax1.plot(spl_Ht(tplt), spl_Bt(tplt), color=\"red\", label=\"Spline function\")\n", + "ax1.set_xlabel(\"H \" + unitH)\n", + "ax1.set_ylabel(\"B \" + unitB)\n", + "ax1.legend(numpoints=1, loc=\"best\")\n", + "ax1.grid(linestyle=\"dashed\")\n", + "plt.title(r\"Hysteresekurve bei $I_{eff}=262.2 \\pm 0.05 \\,\\mathrm{mA}$\")\n", + "plt.show()\n", + "\n", + "\n", + "stdU=0.00000005\n", + "Uh=np.array([ufloat(x,stdU) for x in UH])\n", + "Ub=np.array([ufloat(x,stdU) for x in UB])\n", + "b=UBfak*Ub\n", + "h=UHfak*Uh\n", + "murt=((b/(mu0*h))**2)**0.5\n", + "#murt2=[x for x in murt if x<2000]\n", + "#murt2=np.sort(murt)[49:-100]\n", + "#plt.plot(range(len(murt)),n(murt))\n", + "#plt.show()\n", + "#mur=np.mean(murt)\n", + "mur=np.median(murt)\n", + "#plt.plot(range(len(murt2)),n(murt2))\n", + "#plt.plot(range(len(murt2)),np.ones(len(murt2))*mur.n)\n", + "#plt.show()\n", + "print(f\"Wir erhalten mur={mur} als Median. \")" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "b17d3a37-5dec-4013-9d9f-bfd171e86f5f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Resampling by factor 13\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 600x600 with 1 Axes>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Wir erhalten mur=(2.07+/-0.27)e+03 als Median. \n" + ] + } + ], + "source": [ + "N1=250\n", + "N2=50\n", + "l=ufloat(0.105,0.01)\n", + "R2=ufloat(10000,500)\n", + "R1=ufloat(10,0.5)\n", + "UHfak=N1/(R1*l)\n", + "C=ufloat(10*10**(-6),0.5*10**(-6))\n", + "UHfak=N1/(R1*l)\n", + "UBfak=C*R2/(N2*0.000625)\n", + "mu0=4*np.pi*10**(-7)\n", + "import pandas as pd\n", + "import numpy as np\n", + "from scipy import interpolate\n", + "import matplotlib.pyplot as plt\n", + "\n", + "data = np.genfromtxt('Jonathan_ist_ein_Augenschmaus_252.csv', delimiter=\",\", skip_header=3 )\n", + "t, UB, UH= data[:,0], data[:,1], data[:,2]\n", + "t=t[1:-1:]\n", + "UB=UB[1:-1:]\n", + "UH=UH[1:-1:]\n", + "from PhyPraKit.phyTools import resample, meanFilter\n", + "\n", + "# If the length is too large, resample by an appropriate factor, we are fine with \n", + "# 350 data points\n", + "il=len(UH)\n", + "size=300\n", + "if il > size:\n", + " g = int(il/size)\n", + " # This is an example of smoothing by averaging over n neighbours\n", + " #print(\"Smoothing with window size \", n)\n", + " #t = meanFilter(vUH, width=n)\n", + " #UH = meanFilter(vUH, width=n)\n", + " #UB = meanFilter(vUB, width=n)\n", + " # This is an example of down sampling by averaging over n neighbours\n", + " print(\"Resampling by factor\", g)\n", + " t = resample(t , n=g)\n", + " UH = resample(UH, n=g)\n", + " UB = resample(UB, n=g)\n", + "\n", + "CALIB_UH2H = UHfak.n # U_H -> H <-- adjust !\n", + "CALIB_UB2B = UBfak.n # U_B -> B <-- adjust !\n", + "H = UH * CALIB_UH2H\n", + "B = UB * CALIB_UB2B\n", + "# Interpolate the points of (t,H) by spline functions; s=0 means that no extra \n", + "# Smoothing will be applied, each point of H will be used for the spline\n", + "spl_Ht = interpolate.UnivariateSpline(t, H, s=0)\n", + "spl_Bt = interpolate.UnivariateSpline(t, B, s=0)\n", + "\n", + "# Plot hysteresis curve as Channel A vs. Channel B\n", + "tplt = np.linspace(t[0], t[-1], 200)\n", + "unitH = \"(A/m)\"; unitB = \"(T)\"\n", + "fig = plt.figure(1, figsize=(6.0, 6.0))\n", + "ax1 = fig.add_subplot()\n", + "ax1.scatter(H, B, color=\"blue\", marker=\"o\", s=5.0, label=\"Data points\")\n", + "ax1.plot(spl_Ht(tplt), spl_Bt(tplt), color=\"red\", label=\"Spline function\")\n", + "ax1.set_xlabel(\"H \" + unitH)\n", + "ax1.set_ylabel(\"B \" + unitB)\n", + "ax1.legend(numpoints=1, loc=\"best\")\n", + "ax1.grid(linestyle=\"dashed\")\n", + "plt.title(r\"Hysteresekurve bei $I_{eff}=25.3 \\pm 0.05 \\,\\mathrm{mA}$\")\n", + "plt.show()\n", + "\n", + "\n", + "stdU=0.00000005\n", + "Uh=np.array([ufloat(x,stdU) for x in UH])\n", + "Ub=np.array([ufloat(x,stdU) for x in UB])\n", + "b=UBfak*Ub\n", + "h=UHfak*Uh\n", + "murt=((b/(mu0*h))**2)**0.5\n", + "#murt2=[x for x in murt if x<2000]\n", + "#murt2=np.sort(murt)[49:-100]\n", + "#plt.plot(range(len(murt)),n(murt))\n", + "#plt.show()\n", + "#mur=np.mean(murt)\n", + "mur=np.median(murt)\n", + "#plt.plot(range(len(murt2)),n(murt2))\n", + "#plt.plot(range(len(murt2)),np.ones(len(murt2))*mur.n)\n", + "#plt.show()\n", + "print(f\"Wir erhalten mur={mur} als Median. \")" + ] + }, + { + "attachments": { + "9d8bfa84-6f03-4d9c-81b6-460e11615910.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "761d4efb-fe48-4697-b642-369d7d4f7cfb", + "metadata": {}, + "source": [ + "**V E R S U C H S B E S C H R E I B U N G**\n", + "\n", + "\n", + "*Quelle: Hinweise für den Versuch Ferromagnetische Hysterese-Magnetisierung und Polarisation*\n", + "\n", + "Es gilt die gleiche Schlatung wie in Aufgabe 2.1, jedoch wurde die erste Spule durch eine anderen mit Windungszahl $N_1=250$ genutzt.\n", + "\n", + "Des weiteren lässt sich $\\mu_r$ als zeitlicher Mittelwert wie folgt berechnen: $\\mu_{r} = \\frac{B_{S}}{\\mu_{0}\\,H_{S}}$ \n", + "Da für $H\\approx 0$ zu sehr hohen Werten für $mu_r$ auftreten wurde der Median anstelle des arithmetischen Mittels betrachtet.\n", + "\n", + "Für den Eisenkern wurde die Messungen bei $I_{eff}=262.2 \\pm 0.05 \\,\\mathrm{mA}$ und beim Ferrit-Schalenkern bei $I_{eff}=25.3 \\pm 0.05 \\,\\mathrm{mA}$ aufgenommen.\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "5f5600ea-c2ea-4d77-a77e-e3b471c99146", + "metadata": {}, + "source": [ + "**L Ö S U N G**\n", + "\n", + "Es lässt sich aus den Daten errechen:\n", + "\n", + "Für den Eisenkern bei $I_{eff}=262.2 \\pm 0.05 \\,\\mathrm{mA}$: $\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\mu_r=2380\\pm21$ \n", + "Für den Ferritkern bei $I_{eff}=25.3 \\pm 0.05 \\,\\mathrm{mA}$: $\\,\\,\\,\\,\\,\\,\\,\\,\\,\\,\\mu_r=2070\\pm27$ \n", + "\n", + "Durch eigenhändiges Auslesen von Nullpunkt und Maximum der Daten gelten folgende Größen:\n", + "\n", + "|Material\\Größen |Remanenz $B_R\\,[\\mathrm{T}]$| Koerzitivfeldstärke $H_C\\,[\\mathrm{\\frac{A}{m}}]$|Sättigungsinduktion $B_S\\,[\\mathrm{T}]$|\n", + "|-----|--------|-----|------|\n", + "|$Eisenkern$|$0.46$| $ -92$| $0.680$ |\n", + "|$Ferrit-Schalenkern$|$450$|$ -12500$ | $2270$ |\n", + "\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "a3fb8b19-3453-4ee0-8be3-79e63c9d428f", + "metadata": {}, + "source": [ + "**D I S K U S S I O N**\n", + "\n", + "Die Werte zeigen an, dass Eisen (bzw. der Eisenkern) weichmagnetisch ist. Die niedrige Koerzitivfeldstärke $H_{C_{Eisen}}=-92\\,\\mathrm{\\frac{A}{m}}$ zeigt an, dass nur ein kleines Feld benötigt wird, um das Material zu entmagnetisiert. Die niedrige Remanenz $B_{R_{Eisen}}=0.46\\,\\mathrm{T}$ ist auch Teil der Charakteristiken weichmagnetischer Materialien. Ferrit (bzw. Ferrit-Schalenkern) ist jedoch schwer magnetisierbar und entmagnetisierbar aufgrund des großen Koerzitivfeldstärke $H_{C_{Ferrit}}=-12500\\,\\mathrm{\\frac{A}{m}}$ und der hohen $B_{R_{Ferrit}}=450\\,\\mathrm{T}$. Da die Die Hystereseverluste $P_{hyst}$ proportional zur Fläche des Hysterediagramms $\\omega$ abhängt, kann von der Größenordnung der gemessenen Größen $B_R$, $H_C$ und $B_S$ gefolgert werden, dass der Eisenkern geringe Hystereseverluste $P_{hyst}$ und der Ferrit-Schalenkern hohe Hystereseverluste $P_{hyst}$ aufweisen.\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "id": "b669bee3-e4f2-4a1d-be44-6ef3be4f6170", + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, + "source": [ + "# Beurteilung" + ] + }, + { + "cell_type": "markdown", + "id": "d4ab1a4b-9cdf-43aa-a33c-ae863bd60902", + "metadata": {}, + "source": [ + " * Nach Abschluss des Versuchs haben Sie die Möglichkeit diesen Versuch individuell zu beurteilen.\n", + " * **Folgen Sie zur Beurteilung dieses Versuchs diesem [Link](https://www.empirio.de/s/mlNVWZpooS)**.\n", + " * Beachten Sie, dass jede:r Studierende nur einmal pro Versuch eine Beurteilung abgeben kann.\n", + " * Wir empfehlen die Beurteilung nach der Besprechung Ihrer Versuchsauswertung mit Ihrem:r Tutor:in auszufüllen. " + ] + } + ], + "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": "3.11.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}