ECE 497 Capstone Design Will Barrett Asato Tashiro

ECE 497 Capstone Design Will Barrett Asato Tashiro Adam Anderson

Purpose of the System • The purpose is to create a scanning system to determine the location and size of metal fragments in a medium density fiber panel.

Background Information • The Weapons Integration & Development Directorate of the US Army Aviation and Missile Research, Development, & Engineering Center performs a variety of munitions and warhead test programs – Known as the “AMRDEC” – Patrick Taylor is our sponsor • They use bundles of fiber panels to capture shrapnel from the explosions • Each bundle is then searched BY HAND to recover fragments, tabulate the X/Y position, and mass for each panel – The panel location is used to determine the depth of the fragment

Background Information (cont’d) • The process can take up to 100 man hours PER PANEL • Each experiment could require up to 96 panels, or 9600 man-hours per experiment • Removal is done outside on the test range – Personnel have to be in protective clothing – Fragments are bagged by weight – Fragments have to be cleaned and decontaminated for safe handling • Fragments are typically steel, but some tests use titanium or aluminum • Data derived from the analysis is tabulated in a spreadsheet format, with the fragment designation, count, bundle and panel number, X/Y location, and size/weight

Fragment Set Weight Distribution STEEL WARHEAD FRAGMENT SET FOR FRAG BUNDLE SCANNER TESTING

Typical Fragment Morphology

Project Objective • Automate analysis procedures to the maximum degree feasible – Analysis of X/Y location goal is 15 minutes/panel • Portability – system can be setup by 1 person • Battery operated equipment is desirable

Measurement Parameters • X/Y resolution of. 5” • Minimum fragment detection of. 25 g

Approach • Demonstrate a proof-of-concept capability that can be scaled up at a later time • Use commercial-off-the-shelf (COTS) equipment to produce a gray-scale image of the fragments contained in a panel • Process image to identify the centroid of each fragment and X/Y location – Output. csv file with the fragment location data

COTS Imaging Systems • Ground Penetrating Radar (GPR) • Industrial Radiography

What is Ground Penetrating Radar? • GPR is a non-destructive imaging method that uses radar pulses to image the subsurface • The radar pulses used are in the microwave band of the radio spectrum

How does GPR work? • GPR is similar to a metal detector • The GPR system sends out thousands of RF frequency pulses into the ground • The frequencies that are reflected back return to the antennae • Frequency analysis of the reflected RF energy allows correlation of different material compositions in the subsurface

GPR Schematic

Typical Applications • • Pipe Locating Archeology IED Locating (Improvised Explosive Devices) Quality control of reinforced concrete

Ground Penetrating Radar

GPR Scans

Describing Industrial Radiography • Industrial Radiography is also a non-destructive detection method which utilizes X-rays and gamma rays to view materials

How Industrial Radiography Works • Similar to medical radiography, Industrial radiography uses an X-ray source to bombard a sample with high-energy radiation onto a film or a digital detector • This creates a 2 D image of the different materials in the sample.

Radiography Schematic

Typical Applications • Security • Medical Imaging • Non-Destructive Testing – Castings – Welds

Medical X-Ray Radiography X-Ray Source Imaging Surface

Industrial Radiography

• (Insert pic of Xerox)

Program Plan • Contact vendors – Image dummy panels using radiography and GPR – Utilize 2 D images for image processing study • Image Processing Approach – 2 D grayscale image can be processed using MATLAB to determine the centroid and area of each fragment – Tabulate fragments by area and X/Y location

Current Status • Dummy panels have been fabricated • They will be shipped/delivered to USRadar, Hayes, ATS, and University Hospital this week • Start analysis of our simulated fragment panel this week

Simulated Fragment Panel

Simulated Fragment Panel Black and White

Simulated Panel with Border Detection

Image Analysis Data Pixcavator 5. 1 Dark objects: Light objects 61 0 OUTPUT ID Type Location X Location Y Size Perim. Round. Gray Contrast Thick. Length ID 1 D 192 110 210 59 76 44 211 11 17 1 2 D 105 140 225 62 72 45 210 11 20 2 3 D 530 147 198 54 84 38 217 13 13 3 4 D 324 257 638 110 66 28 227 16 38 4 5 D 471 309 1025 151 56 23 232 17 57 5 6 D 270 329 123 43 81 63 192 10 10 6 7 D 164 365 168 53 74 52 203 10 16 7 8 D 540 412 115 42 80 50 205 10 10 8 9 D 270 241 364 88 58 40 215 10 33 9 10 D 139 183 236 61 77 43 212 13 17 10 11 D 434 443 477 87 78 31 224 19 23 11 12 D 229 408 377 33 17 238 22 165 12 13 D 407 382 4338 414 32 16 239 23 183 13 14 D 140 426 816 201 25 39 216 8 91 14 15 D 54 413 1018 164 47 27 228 15 67 15 16 D 346 430 362 77 76 34 221 15 22 16 17 D 110 429 253 62 80 36 219 15 15 17 18 D 319 417 287 74 65 40 215 10 26 18 19 D 510 418 1287 165 59 21 234 20 61 19 20 D 353 392 322 77 67 35 220 12 26 20