From c957f2902697947b1ae66e596e3dfe8b631aecfe Mon Sep 17 00:00:00 2001 From: Kelu Date: Tue, 3 Apr 2018 20:18:47 +0200 Subject: [PATCH] Adding examples --- README.md | 133 +- images/20180227/20180227a-Loops.ipynb | 231 + .../One-0-VGA@0x22-spimode1-32msps.csv | 8310 ++++++++ .../One-0-VGA@0x22-spimode1-32msps.jpg | Bin 0 -> 22022 bytes .../One-5-VGA@0x22-spimode1-64msps.csv | 16630 ++++++++++++++++ .../One-5-VGA@0x22-spimode1-64msps.jpg | Bin 0 -> 22209 bytes 6 files changed, 25297 insertions(+), 7 deletions(-) create mode 100644 images/20180227/20180227a-Loops.ipynb create mode 100644 images/20180227/One-0-VGA@0x22-spimode1-32msps.csv create mode 100644 images/20180227/One-0-VGA@0x22-spimode1-32msps.jpg create mode 100644 images/20180227/One-5-VGA@0x22-spimode1-64msps.csv create mode 100644 images/20180227/One-5-VGA@0x22-spimode1-64msps.jpg diff --git a/README.md b/README.md index 8347497..5115ecc 100644 --- a/README.md +++ b/README.md @@ -2,30 +2,149 @@ Non destructive testing and imaging ultrasound modalities have been around since the '50s in . More and more ultrasound-based initiative are emerging, mostly focusing on image processing - while hardware has been left behind. Several teams have produced succesful designs for the different possible uses, mostly efforts from research laboratories. Most have been used on commercial US scanners, traditionaly used as experiment platforms, but they are not cheap, and yield very little in terms of data access and control. Others have been developped in labs, but, sadly, very few have been open-sourced. Let's tackle this! -# Results - -* v0.1 version (the __[matty](https://github.com/kelu124/echomods/tree/master/matty)__ prototype) gave good results! -* v0.1 release! https://github.com/kelu124/un0rick/releases/tag/v0.1 - ## Picture of the setup +The board was connected to a single element piezo, in water, with a reflector a few centimers away, immersed in water. Pulser is set up at 25V high pulses. + ![](/images/IMG_20180224_195210.jpg) -## Details of acquisitions +Acquisition is realized, with a small offset, between 32Msps and 64Msps. Data is explored a bit further. ![](/images/2018-02-27.jpg) +* [Jupyter notebook of the acquisition](/images/20180227/20180227a-Loops.ipynb) +* [Dataset at 32Msps](/images/20180227/One-0-VGA@0x22-spimode1-32msps.csv) +* [Datast for 64Msps](/images/20180227/One-5-VGA@0x22-spimode1-64msps.csv) + # Sources * The [source files -- the upverter initial design are here](/source/) * The [production files are here](/build/) -* The [VHDL files](/software/un0rick_v0.1.vhd) +* The [VHDL files](/software/) # Resources * Read more at [un0rick.cc](http://un0rick.cc), upcoming documentation at [doc.un0rick.cc](http://doc.un0rick.cc) * On [Hackaday too](https://hackaday.io/project/28375-un0rick-an-ice40-ultrasound-board) +# __Nunc Ille Est Magicus__ -- Introduction + +Non destructive testing and imaging ultrasound modalities have been around since the '50s in . More and more ultrasound-based initiative are emerging, mostly focusing on image processing - while hardware has been left behind. Several teams have produced succesful designs for the different possible uses, mostly efforts from research laboratories. Most have been used on commercial US scanners, traditionaly used as experiment platforms, but they are not cheap, and yield very little in terms of data access and control. Others have been developped in labs, but, sadly, very few have been open-sourced. This particular project stems from a previous beaglebone-based design, as well as an arduino-like module-based design. + +It has also been shown that simple (be it low-power, low-cost and small) can be achieved - and this, even for relatively complex systems, based on 16 to 64 parallel channels front-end processing and software back-end processing (embedded PC or DSP). This makes it a bit more complex for the layman, hobbyist, or non-specialist researcher to use, not to mention the very little information that is accessible. + +# __Non Quod Maneat, Sed Quod Adimimus__ -- simplified hardware: specs and features + + +1. __FPGA__: Lattice iCE40HX4K - TQFP 144 Package +2. __Memory__: + * 8 Mbit SRAM, 10ns, 512 k x 16, equivalent: + * 65 full lines of 120us at 64Msps + * 840 lines of 120us at 10Msps, 8 bits + * 8 Mb SPI Flash for FPGA configuration +3. __Ultrasound processing__: + * __VGA__: AD8331 controled by DAC + * __Pulser__: MD1210 + TC6320 + * __ADC__: 10Msps ADC10065 + * 10 bits of data / sample + * 2 bits of line counters + * 4 bits of IOs (counters, ...) +4. __Parameters__: Settings programable via USB or Raspberry Pi + * Type of acquisition (one line / set of lines) + * Number of lines + * Length of lines acquisitions + * Delay between acquisitions + * Pulse width + * Delay between pulse and beginning of acquisitions + * 200us time-gain-compensation programmable (8 bits, from 0 to Max), every 5us +5. __Extensibility__: + * 2 x Pmod connectors + * SMA plug for transducers + * RPi GPIO +6. __User Interfaces__: + * 2 x PMOD for IOs + * 3 x push button (with software noise debouncing) + * Jumpers for high voltage selection +7. __Input Voltage__: + * 5 V from RPi or USB + * Uses 350mA-450mA at 5V +8. __Fully Open Source__: + * Hardware: _github repository_ + * Software: _github repository_ + * Toolchain: _Project IceStorm_ + * Documentation: _gitbook_ +9. __Operating Voltage__: + * FPGA and logics at at 3.3 V + * High voltage at 25V, 50V, 75V +10. __Dimensions__: @todo! +11. __Weight__: @todo! + +# __Si (Non) Confectus, (Non) Reficiat__ -- a short comparative + +* Ready-made commercial platforms range in the 1000s$ .. and even smallish one-channel boards can be around 2k$. Each has pros and cons (for example a 2k$ board samples at 160Msps but can only store 4k pts). Not open-source. +* Research gigs are not always published. Not open-source. +* Some arduino-like modules were developped. A whole set is around 350$ for AFE+ADC+controls. Open source. DIY quality (acceptable, not for pros). Open source. +* This board has more or less only plusses compared to the competition =) + + +# __Quia Ego Sic Dico__ -- installation steps + +1. Setup +2. Install the image on the Raspberry +3. Burn bitstream +4. Acquire the signal +5. Process and display! + +# __Faber Est Quisqve Fortunae Suae__ -- what can you do with this? + +A couple of ideas to play with the stuff + +* Compressed sensing to be used with [muscle detection](). +* AMode Non destructive testing +* Medical imaging BMode with a probe + +# __Moneta Supervacanea, Magister?__ -- shopping time + +* Send me a mail at __orders@un0rick.cc__ ! +* Or wait for the Tindie shop to order. +* First sets around 349$. Vilis Ad Bis Pretii ! + +# __Non Ante Septem Dies Proxima, Squiri__ + +* V 0.1 [release](https://github.com/kelu124/un0rick/releases/tag/v0.1) -- Prototyping (project codename: MATTY) + * [2018-03-10](https://github.com/kelu124/echomods/tree/master/matty/20180310a) - getting the DAC working + * [2018-02-27](http://un0rick.cc/articles/2018-02/good-news) - first acquisitions at high speed + * [2018-02-02](http://un0rick.cc/articles/2018-02/first-tests) - Getting the first tests done (and repairs) + * [2018-01-23](http://un0rick.cc/articles/2018-01/first-board) - Got the first board from the fab + * [2017-11-19](http://un0rick.cc/articles/2017-11/first-ideas) - Exploring the idea of an ICE40, using Upverter + * [2017-09-15](http://un0rick.cc/articles/2017-09/uniboard) - First ideal specs on the paper + +# __Liber Paginarum Fulvarum__ -- other resources + + +* The full [GitHub Repo](https://github.com/kelu124/un0rick) +* The guy's [Tindie shop](https://www.tindie.com/stores/kelu124/) +* The corresponding [Hackaday](https://hackaday.io/project/28375-un0rick-an-ice40-ultrasound-board) page +* Join the [Slack channel](https://join.slack.com/usdevkit/shared_invite/MTkxODU5MjU0NjI1LTE0OTY1ODgxMDEtMmYyZTliZDBlZA) + +# Thanks to + +* BiVi - _always here to chat_ +* Charles - _bringing neat insights_ +* David - _what would I have done without you?_ +* echOmods - _the fundations of this work_ +* Fabian - _already so many insights_ +* Fouad.. and team - _awesome works there_ +* Jan - _piezooos_ +* Johannes and Felix - _hardware is .. hard, but rewarding!_ +* Marc - _share these echoes =)_ +* Murgen - _early elements_ +* Sofian - _early ideas!_ +* Tindie - _to allow people sharing their niche hardware, and for others to search for these_ +* Visa - _exploring amode_ +* Vlad - _you pulse_ +* .. and all the others ! + # License ## echOmods diff --git a/images/20180227/20180227a-Loops.ipynb b/images/20180227/20180227a-Loops.ipynb new file mode 100644 index 0000000..457023b --- /dev/null +++ b/images/20180227/20180227a-Loops.ipynb @@ -0,0 +1,231 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# `20180227a` Testing the new versions at 32 and 64Msps" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy import signal\n", + "from scipy.interpolate import griddata\n", + "import math\n", + "from scipy.signal import decimate, convolve\n", + "\n", + "import re\n", + "import glob, os" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Creating the set of acquisitions" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "One-5-VGA@0x22-spimode1-64msps.csv\n", + "first\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "AA = []\n", + "lbl = []\n", + "IDLine = []\n", + "\n", + "for CSVFile in glob.glob(\"*.csv\"):\n", + " print CSVFile\n", + " A = np.genfromtxt(CSVFile, delimiter=';').astype(int)[1:]\n", + " tmp = [] \n", + " N = len(A)\n", + " FF = CSVFile.split(\".\")[0].split(\"-\")[-1]\n", + " lbl.append( CSVFile.split(\"-\")[2] )\n", + " f = int(re.sub('[^0-9]','', FF))\n", + " #F = int(CSVFile.split(\".\")[0])\n", + "\n", + " if (A[4]) > 0b111:\n", + " print \"first\"\n", + " for i in range(len(A)/2-1):\n", + " value = 128*(A[2*i+0]&0b111) + A[2*i+1] - 512\n", + " IDLine.append((A[2*i+1]&0b11110000)/16) # Identify the # of the line\n", + " tmp.append( value ) \n", + " else:\n", + " print \"second\"\n", + " for i in range(len(A)/2-1):\n", + " value = 128*(A[2*i+1]&0b111) + A[2*i+2] - 512\n", + " IDLine.append((A[2*i+1]&0b11110000)/16)\n", + " #print A[2*i]&0b10000000,A[2*i+1]&0b10000000,\n", + " tmp.append( value )\n", + " #print A[2*i+1]\n", + " #print A[i+1]-A[i] \n", + " \n", + " #t = t*1.0/f\n", + " t = [ 1.0*x/f for x in range(len(tmp))]\n", + " plt.plot(t,tmp)\n", + " plt.title(CSVFile)\n", + " plt.savefig(CSVFile.split(\".\")[0].split(\"/\")[-1]+\".jpg\")\n", + " plt.show()\n", + " \n", + " AA.append(tmp)\n", + " \n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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wWGLDY3F5XHh8Huw2OxuCqt4yMmBH9g4e/+ZxAHJLcgP7KmbywqIrl2s6S52B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MaNGxMaGkpERARdunThyy+/pGfPnnh5eeHo6Ejt2rWZP38+jo6OLFmyhPfee4+dO3fSsmVLADZs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\nM2fP/Ob3PL8J2/Gxh2DUvPlmfn1Zsya1njTqzMyOO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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "t1 = [ 1.0*x/32 for x in range(len(tmp))]\n", + "t2 = [ 1.0*x/64 for x in range(len(tmp))]\n", + "\n", + "s1 = AA[-1] # 32\n", + "s2 = AA[0] # 64\n", + "\n", + "fLegend = [ 64.0*x/len(s2) for x in range(len(s2))]\n", + "fm = len(fLegend)/2\n", + "\n", + "f, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(15,5))\n", + "\n", + "ax1.plot(t2[0:2500],s2[0:2500],\"b\",label=\"64Msps\")\n", + "ax1.plot(t1[0:2500],s1[0:2500],\"g\",label=\"32Msps\")\n", + "ax1.set_xlabel(\"Time in uS\")\n", + "ax2.plot(t2[2*1100:2*1350],s2[2*1100:2*1350],\"b\",label=\"64Msps\")\n", + "ax2.plot(t1[1100:1350],s1[1100:1350],\"g\",label=\"32Msps\")\n", + "ax2.legend()\n", + "ax2.set_xlabel(\"Time in uS\")\n", + "ax1.set_xlabel(\"Time in uS\")\n", + "ax1.legend()\n", + "\n", + "ax3.plot(t2[2*1250:2*1275],s2[2*1250:2*1275],\"b\",label=\"64Msps\")\n", + "ax3.plot(t1[1250:1275],s1[1250:1275],\"g\",label=\"32Msps\")\n", + "ax3.legend()\n", + "ax3.set_xlabel(\"Time in uS\")\n", + "\n", + "\n", + "ax4.plot(fLegend[1:fm], np.abs(np.fft.fft(s2))[1:fm] ,\"b\",label=\"64Msps\") \n", + "ax4.legend()\n", + "ax4.set_xlabel(\"Frequency MHz\")\n", + "\n", + "\n", + "\n", + "plt.suptitle('Checking 32Msps and 64Msps')\n", + "plt.savefig(\"32_64.jpg\", bbox_inches='tight')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + 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