1 / 29

Amorphous Wire Localization Checkpoint Presentation

Amorphous Wire Localization Checkpoint Presentation. April 18, 2001 Matthew Foy Richard Kao Matthias Ziegler. Hardware Project Overview. Objective To create a system in which we can detect the amorphous wire to the highest accuracy that will allow us to test our software Deliverables

daphne-aguirre
Télécharger la présentation

Amorphous Wire Localization Checkpoint Presentation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Amorphous Wire LocalizationCheckpoint Presentation April 18, 2001 Matthew Foy Richard Kao Matthias Ziegler

  2. Hardware Project Overview • Objective • To create a system in which we can detect the amorphous wire to the highest accuracy that will allow us to test our software • Deliverables • A system that is based on 16 sensors that returns a single location of the wire

  3. Proposed Dates • Research Magnetic Fields and 2/26 appropriate hardware • Research current oscilloscope 3/1 software and localization techniques • Develop triangulation software 3/8 • Develop software for sine wave 3/12 data analysis

  4. Proposed Dates (cont.) • Hardware Completion 3/16 (Magnetic Field Hardware) • Create sensors 3/26 • Get signal on oscilloscope 4/6 • Integrate software and hardware 4/13 • Test with one sensor 4/15

  5. Proposed Dates (cont.) • Amplify signal of oscilloscope 4/17 and reduce noise • Integrate computer boards to 4/23 accept 15 signals • Perfect Localization of wire 5/3 with these signals

  6. Magnet Types • Permanent Magnets • Resistive Magnets • Superconducting Magnets • The type we will be concentrating on will be resistive magnets

  7. Permanent Magnets • Typical Kitchen Magnets • Two ends – North and South • Overall Properties: • This provides an additive effect, producing a stronger magnetic field • Attract steel and iron • Opposites attract and Likes repel

  8. Current produces magnetic field • Current flowing through a wire also produces a magnetic field • Differs from permanent magnet because it is temporary (lasts only while current is running)

  9. Resistive Magnets (Electromagnets) • Resistive magnets consist of many windings or coils of wire wrapped around a cylinder or bore through which an electric current is passed

  10. Hardware – Software Integration Hardware Software Magnetic Field Data Analysis Wire Sensors Computer Oscilloscope

  11. Setup Amorphous Wire 30 coils of wire Sensor (250 coils) Magnetic Field of 7-12 Gauss Oscilloscope

  12. Software Overview • Expected Deliverables • Input amplitude and phase for each sensor • Compute distance from the wire to 3 separate sensor arrays • Determine the location and approximate orientation of the wire in 3 space

  13. Software Overview Cont... • Sensor Class • Member Variables • Array of benchmark amplitudes from calibration • Current amplitude being recorded • Current phase being recorded • Sensor Coefficient

  14. Software Overview Cont... • Sensor Array Class • Member Variables • Front and Rear Sensor Objects • 3 Triplet Sensor Objects • Member Functions • Compute Sensor Array Coefficient • Compute distance to wire

  15. Software Overview Cont... • Main function • Creates 3 Sensor Array Objects • Calibrates each Sensor Array • Computes each Sensor Array Coefficient • Computes distance to wire from each Array • Localizes wire in 3-space

  16. Our Results • On top is what our results should like • Our result is the bottom graph • The point where the wire should be magnetized is too small and in the wrong location

  17. Our Results (cont.) • The problem was that the wire was not long enough so the signal it gave off was not strong or what we were looking for • It turned out the wire wasn’t 50 microns as expected but 150 microns, which threw the calculation off

  18. Revised Dates • Hardware/software integration 4/23 • Test with one sensor 4/25 • Amplify signal of oscilloscope 4/27 and reduce noise with 1 signal • Integrate computer boards to 5/2 accept 12 signals • Perfect creation of signals 5/7

  19. Analog Input Board Low Cost High Speed 16 Channel 12-& 16-Bit Analog Input Board 16 Single-Ended/8 Differential Analog Inputs Models with 12-or 16-Bit Analog Input Resolution 160K Samples/Second A/D (DAS-1400-12) 512 Sample FIFO 8-Bits Digital I/O

  20. System Calibration • The wire is rotated through the tilt plane and about the central axis in 10 degree increments, with the amplitude recorded at each step • The phase of the wire is recorded • Each sensor array coefficient (k) is computed based on the calibration distance and the change in signal amplitude from the front to rear sensor in the array

  21. y - tilt axis y - tilt axis wire wire z - central axis z - central axis x x rotation about central axis (yz plane) 36 readings rotation about tilt axis (xz plane) 18 readings System Calibration Cont... 36 readings/sensor * 18 readings/sensor = 648 benchmarks/sensor

  22. Wire Distance • Distance • The rear sensor in the array is a known distance (d) behing the front sensor • With the coefficient known for each sensor array (k) along with the signal amplitude at the front (Af) and rear (Ar) sensors, we can compute the distance to the sensor array (d#)

  23. 1 1 Af - Ar = k( - ) df3 dr3 Distance Equations dr = df + d d - known distance from front sensor to rear sensor in array df - distance from front sensor to wire dr - distance from rear sensor to wire Af - amplitude at front sensor Ar - amplitude at rear sensor k - sensor array coefficient

  24. Wire Localization • Wire is a known radius (r#) from each sensor array, creating a sphere of possible locations around each array • Intersection of 3 spheres is the location of the wire, computed by simultaneously solving 3 distance equations for the 3 unknown variables (x,y,z)

  25. r12 -r32 +cd2 + 0.5( r12 -r22 +cd2 ) x = 2sqrt( cd2 - (0.5cd)2 ) r12 -r22 -cd2 y = 2 cd Localization Equations d2 = (x2-x1)2 + (y2-y1)2 + (z2-z1)2 r1 - distance from sensor array 1 to wire r2 - sensor array 2 to wire r3 - sensor array 3 to wire cd - calibration distance x,y,z - the coordinates of the wire Sensor Array Coordinates s1 = ( 0, 0, 0) s2 = ( 0, cd, 0) s3 = ( sqrt( cd2 - (0.5cd)2), cd/2, 0) z = sqrt( r12 -x2 -y2 )

  26. Software Problems • Noise in the signal sometimes causes irregular readings in the signal amplitude • Removing Noise • Input the 3 peak points from one phase of the sine wave and sum them for one amplitude • This process is repeated for 60 sine waves (1sec) • Total sum is the signal amplitude for the sensor

  27. What’s Next? • Complete hardware-software interface • Use the triplet sensors to estimate the orientation of the wire • By examining how the amplitude measured at each triplet sensor in the array deviates from a mean value during the calibration, we hope to estimate the approximate orientation of the wire • Localize multiple wires at the same time

  28. Dependencies • Finished • Creation of Magnetic Field • Creation of Sensors • Still Working on • Signal Amplifier • Input Computer Board • Need Perfected Signal to Finish Software

More Related