{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lab 3: Computation of Rotating Unbalance\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clear all\n",
    "close all\n",
    "clc\n",
    "imatlab_export_fig('print-png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "% Obtained from curve fitting sdofcf\n",
    "zeta = 0.0020271;\n",
    "f = 206.94; % second natural frequency in Hz"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Power Spectrum Density plot \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TE+PjvZa//PLLyZMnO3bsmJCQoK3bM8+dO/fzzz8PGjTIx1ub/ZWpp3Nx4cKFX375pW/f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\naMD/A8jynsXMIm/lAAAAAElFTkSuQmCC\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "load('Case3-5-Fn+10')\n",
    "figure\n",
    "A=20*log10(PSD_chan_2);\n",
    "plot(Freq_domain,A);\n",
    "grid on\n",
    "grid minor\n",
    "title('Case 3-5-Fn+10: Freqency vs PSD')\n",
    "xlabel('f(Hz)')\n",
    "ylabel('PSD')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Experimental Data Analysis\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "wr =\n",
      "\n",
      "  single\n",
      "\n",
      "  219.6875\n",
      "\n"
     ]
    }
   ],
   "source": [
    "load('Case3-5-Fn+10')\n",
    "% Driving Freqency\n",
    "[x,y]=max(PSD_chan_2);\n",
    "wr=Freq_domain(y) %in Hz\n",
    "[a,b]=max(A);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "h =\n",
      "\n",
      "  343.3732\n",
      "\n"
     ]
    }
   ],
   "source": [
    "load('Case3-1')\n",
    "\n",
    "HI=abs(Hf_chan_2);\n",
    "h=HI(b)%inertance in 1/kg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Acceleration Response Plot\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VAEiH3pURcQUA0qF3ZURcAQAUQFwBABRAXAGAdOhdGRFXACAdeldGxBUAQAHE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\nnDho0KBVq1alp6cPHz7c7qJ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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "load('Case3-5-Fn+10')\n",
    "figure\n",
    "plot(Time_domain,(Time_chan_2*9.81))\n",
    "grid on\n",
    "grid minor\n",
    "title('Case 3-5-Fn+10: Acc vs Time')\n",
    "xlabel('T(sec)')\n",
    "ylabel('Acc')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Analysis\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Xmax =\n",
      "\n",
      "  single\n",
      "\n",
      "  2.2536e-05\n",
      "\n"
     ]
    }
   ],
   "source": [
    "Amax=max((Time_chan_2*9.81)-1);\n",
    "Xmax=(Amax)/(wr*2*pi)^2 %max displ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "r =\n",
      "\n",
      "  single\n",
      "\n",
      "    1.0616\n",
      "\n"
     ]
    }
   ],
   "source": [
    "r=wr/f % freq ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "moe =\n",
      "\n",
      "  single\n",
      "\n",
      "  6.5630e-08\n",
      "\n"
     ]
    }
   ],
   "source": [
    "moe=Xmax/h %experimental rotating unbalance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Beam Properties\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "m =\n",
      "\n",
      "    0.4812\n",
      "\n"
     ]
    }
   ],
   "source": [
    "l=21.75*0.0254;% length in meters\n",
    "h=0.5*0.0254;% height in meters\n",
    "w=1*0.0254;% width in meters\n",
    "rho=2700;% density in kg/cubicmeter\n",
    "V = l*w*h;% volume (m^3)\n",
    "m=rho*V\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analytical rotating unbalance\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "moeA =\n",
      "\n",
      "  single\n",
      "\n",
      "  1.2226e-06\n",
      "\n"
     ]
    }
   ],
   "source": [
    "moeA=m*Xmax*sqrt((1-r^2)^2+(2*zeta*r)^2)/(r^2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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