Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

1. Methods for Laser Burning Data Preprocessing: Parameterization of Pulses Ing. Jana Hájková DSS 8. 4. 2009

2. laser burning project • project description • aim: to create an adjustable system for laser burning • simulation – part of the system • cooperation • NTC – laser burning simulation, data explorer, measurement of burned samples • Lintech – laser samples burning • KMA – automatic pulse detection algorithm development • possible ways of research • data preprocessing (samples parameterization, pulse detection) • burning simulation • simulation verification, samples comparison Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

3. laser burning principle 1/2 • laser – electromagnetic radiation • after the radiation strikes the material: • reflected, absorbed, transmitted • excitation of free electrons (metals) • vibrating in the structure of the material (insulators) • material heating – melting, boiling, vaporization, plasma Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

4. laser burning principle 2/2 • previous description –laser affects the material surface continuously • more laser pulses burning • parameters affecting the burning results: • used material and laser • material roughness • number and position of burned laser pulses • laser motion • laser angle of incidence according to the material surface Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

5. literature – laser burning • Anisimov, S. I., 1968: Vaporization of metal absorbing laser radiation. Soviet Physics JETP, Vol. 27, pp. 182. • Bäuerle, D., 2000: Laser Processing and Chemistry. Berlin Springer Verlag. ISBN: 978-3540668916. • Bulgakova, N. M., Stoian, R., Rosenfeld, A., Hertel, I. V., Campbell E. E. B., 2007: Fast Electronic Transport and Coulomb Explosion in Materials Irradiated with Ultrashort Laser Pulses. Laser Ablation and its Applications, Springer Berlin / Heidelberg. ISBN: 978-0-387-30452-6. • Dahotre, N. B., Harimkar, S. P. 2008. Laser Fabrication and Machining of Materials, Springer, New York, USA. • Steen, W. M., 1991: Laser Material Processing. Springer-Verlag, New York Berlin Heidelberg. ISBN: 0-387-19670-6. Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

6. laser burning simulation • reasons for the simulation • real burning of experiments with usage of optimal laser parameters • pulse burning: • into one place • along a curve • in area • simulation model design • based on real data Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

7. input data • samples burned and measured by the confocal microscope • surface high map • data set • each sample burned several times • pulses number sequence (influence of the result on the number of laser pulses) Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

8. parametric description of a sample • burning affected area • similar samples exploration • similarity of the pit • irregularity of the transition ring Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

9. pulse approximation 1/3 • approximation of the pit cross-section with a parabole • from the top view – elliptical shape of the pulse • elliptical paraboloid Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

10. pulse approximation 2/3 • transition ring cross-section approximation – parabole • revolving a parabola along the elliptic trajectory • the top half of the parabolic elliptic torus Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

11. pulse approximation 3/3 Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

12. roughness generation • real samples – measured in high detail – roughness of the material • heat affected area – irregularities • roughness on the pit bottom • irregular waves around the outer border of the transition ring • local defects on the transition ring Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

13. Pelin noise function 1/3 • wide range of application in the computer graphics (textures generating, …) • usable for areal noise generation • combination of noise and interpolation functions • 1D • random points generation • Hermit interpolation H(t) = t 2*(3-2t) • final Perlin noise: sum of several functions with different frequencies and amplitudes • octaves (frequency of each function is twice as the frequency of the previous one ) Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

14. Pelin noise function 2/3 • 2D • generation of random matrix • 2D interpolation • different number of summed actaves (2, 4, 6) • same number of octaves, each following summed with ½ and ¼ amplitude than the previous one Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

15. Pelin noise function 3/3 • amplitudes vector • [0.25, 0.25, 1, 1, 0.5, 0.5], [0.5, 0.5, 1, 1, 3, 3], [2, 0, 0, 0, 0.5, 0.5] • surface generation – 3D view • Perlin noise function • ^2 Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

16. Perlin noise function application • pit bottom roughness • local defect generation • mask usage Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

17. waves modulation 1/2 • waves representation – polyline • whole or its part • segmentation (number or representing points) • difference of the points position from the ellipse • width and maximal height of the wave • several waves application on the smooth surface Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

18. waves modulation 2/2 • plain wave × full wave • for the whole polyline • into the center – linear decrementation of the surface height • full wave application on the smooth surface Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

19. sample surface generation results • 10, 50, 100 laser pulses burned into steel real sample generated sample Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

20. literature – sample parameterization • Ebert, S. E., Musgrave, F. K., Peachey, D., Perlin, K., Worley, S., 2003: Texturing & Modelling, A Procedural Approach, Third edition. Elsevier Science. ISBN: 1-55760-848-6. • Perlin, K. 1985. An Image Synthetizer, Proceedings of the 12th annual conference on Computer graphics and interactive techniques, ISBN: 0‑89791-166-0. ACM New York, USA, pp. 287-296. • Perlin, K. 2002. Improving noise, In Proceedings of the 29th annual conference on Computer graphics and interactive techniques, ISBN: 0730‑0301. ACM New York, USA, pp. 681-682. • Polack, T., 2003: Focus on 3D Terrain Programming. Premier Press, USA. ISBN: 1-59200-028-2. • Žára, J., Beneš B., Felkl P. 2005. Modernípočítačová grafika, ISBN: 80‑251-0454-0. Computer Press, Brno, Czech Republic. Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

21. similar samples comparison Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

22. trend of parameters in dependence on the number of burned laser pulses Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

23. Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

24. future research • sample parameterization automation • methods for automatic pulse detection • burning simulation • methods for samples comparison • system verification Methods for Laser Burning Data Preprocessing: Parameterization of Pulses

25. thank you for your attention ? Methods for Laser Burning Data Preprocessing: Parameterization of Pulses