Particle Image Velocimetry

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Particle Image Velocimetry

  1. 1. Particle Image Velocimeter Mechanical Engineering Department ,GIET
  2. 2. Contents Introduction Principle 2 Components 3 Experiment & Results 4 Applications 5 1 Advanced PIV’s 6
  3. 3. Flow Measurement Introduction <ul><li>Non-Intrusive Methods </li></ul><ul><li>Particle Image velocimeter </li></ul><ul><ul><li>W ithout interfering with the fluid. </li></ul></ul><ul><li>Intrusive Methods </li></ul><ul><li>Orifice Meter </li></ul><ul><ul><li>Needs to interact directly with the fluid </li></ul></ul>
  4. 4. Principle 1 2 3 4 5 6 Schematic diagram of principle behind PIV.
  5. 5. Components Seeding <ul><li>10μm silver coated glass particles used. </li></ul><ul><li>Enhances Total internal reflection of laser. </li></ul><ul><li>Same density as Fluid </li></ul>Laser <ul><li>Nd:YAG Lasers or Copper vapour lasers used. </li></ul><ul><li>Illuminates the flow field. </li></ul><ul><li>FLASH LIGHT type effect. </li></ul><ul><li>Generates Thin light sheet-single plane is imaged. </li></ul>Camera <ul><li>Converts optical brightness into electrical amplitude signals using CCDs. </li></ul><ul><li>Very high frame rate. </li></ul><ul><li>Calibrated to yield the displacement in the object plane. </li></ul>Co- relation <ul><li>For 2-D pattern recognition. </li></ul><ul><li>Interrogation space= n*tiles </li></ul><ul><li>Searches First image -> in second image. </li></ul><ul><li>Calculates a displacement vector for each tile. </li></ul><ul><li>“ INSIGHT 3G “ package used. </li></ul>
  6. 6. Experimental setup
  7. 7. Results <ul><li>Two Consecutive Frames . </li></ul><ul><li>Arrows show Processed </li></ul><ul><li>image. </li></ul><ul><li>Two vortices-Spotted </li></ul>
  8. 8. Head of displacement arrow at final position and tail of arrow at initial position of SEED. Magnified Results
  9. 9. 2 Motion Of Fishes in water. Aerodynamic Analysis Of Helicopters. Application 3 1 PROSTHETIC Heart Valves.
  10. 10. Future PIV’s are coming up with 3-D Motion tracing facilities. Advanced PIVs
  11. 11. OPEN FOR DISCUSSION References: [1] Markus Raffel, Christian E. Willert, and Jurgen Compenhans, Particle Image Velocimeter- A Practical Guide, Springer Publ. Ltd. [2] Operating Manual, PIV Data Processing, Mechanical Systems & Control Lab., JU, Kolkata, India. Dr.P.C.Mishra & Jadavpur University,kolkata Acknowledgements: By: SAMEER DUBEY
  12. 12. BACKUP1-Cross Co-relation Algorithm <ul><li>The mask and the </li></ul><ul><li>pattern being sought </li></ul><ul><li>are similar the, </li></ul><ul><li>cross correlation will be </li></ul><ul><li>high. </li></ul><ul><li>The mask is itself </li></ul><ul><li>an image which needs </li></ul><ul><li>to have the same </li></ul><ul><li>functional appearance </li></ul><ul><li>as the pattern to be </li></ul><ul><li>found. </li></ul>CROSS CORELATION is a standard method of estimating the degree to which two 2-D Images (series) are correlated. Mask (red rectangle) is centered at every pixel in the 1 st image and the cross correlation is Calculated.
  13. 13. BACKUP2-Charged Coupled devices Charge coupled devices or CCD’s are arrays of semiconductor gates formed on a substrate of an integrated circuit or chip The charge collected and stored in each gate of the array represents a picture element or pixel of an image. IC (integrated circuit) and control circuits typically mounted on a printed wiring assembly for camera control. Add Your Title
  14. 14. BY: Sameer Dubey 4 th Year,Mechanical Engineer Gandhi Institute of Engineering and Technology (GIET) Gunupur,ORISSA And Dr.Purna Chandra Mishra Kalinga Institute of Industrial Technology (KIIT) Bhubaneshwar,ORISSA

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