Development and Research of a Profile Recorder for Measuring Deviations in the Shape of the Surface of Products by Laser Spiral Scanning

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Introduction. The paper deals with the development of a Profile recorder and measurement of deviations in the shape of the surface of products by laser spiral scanning. Analysis of the scientific literature shows that at present, the issues of monitoring and evaluating deviations in the shape of the surface of products require further research, since the use of well-known devices and methods does not always provide the necessary accuracy, manufacturability and sufficient information content of measurements. The research urgency is caused by the fact that existing methods of measuring form deviations of the surfaces does not allow to define a set of parameters with the required accuracy and submit it to two-dimensional and three-dimensional form. Objective: to develop a new method for evaluating a three-dimensional profile by implementing the method of laser spiral scanning and study the Profile recorder to improve the accuracy and productivity of measuring deviations in the shape of the product surface. Methods. The paper proposes a new method for evaluating a three-dimensional surface profile in order to directly determine the shape of the surface of products, to control the quality of the surface of products, regardless of its location. To implement the method, a Profile recorder of an original design is developed and investigated, which provides measurement of two parameters along the Archimedean spiral. Optimization of the design and the method of presenting information for measuring deviations in the shape of the surface of products are performed. Results and discussion. A method of statistical estimation of equations for describing the shape of metal surfaces based on the use of classical laws is proposed. In the case of a flat surface, deviations from flatness are evaluated: undulation, warping, twisting, convexity, concavity, curvature, etc. A Profile recorder is developed to implement the proposed method. The automated mechatronic device and the proposed method are tested on corrugated surfaces. Various equations obtained as a result of statistical processing were compared with each other, and the equation with the highest coefficient of determination is selected. The Profile recorder in Cartesian coordinates is studied in order to obtain reliable and accurate data for estimating shape deviations. The values of the deflection and the size of the corrugation along the height of the C-9 corrugated sheet are determined by laser spiral scanning.

About the authors

S. A. Vasiliev

Email: vsa_21@mail.ru
D.Sc. (Engineering), Associate Professor, I. N. Ulianov Chuvash State University, 15 Moskovsky Prospekt, Cheboksary, 428015, Russian Federation, Vsa_21@mail.ru

V. V. Alekseev

Email: av77@list.ru
D.Sc. (Engineering), Associate Professor, I. N. Ulianov Chuvash State University, 15 Moskovsky Prospekt, Cheboksary, 428015, Russian Federation, av77@list.ru

M. A. Vasiliev

Email: mishawasilev@mail.ru
I. N. Ulianov Chuvash State University, 15 Moskovsky Prospekt, Cheboksary, 428015, Russian Federation, mishawasilev@mail.ru

A. A. Fedorova

Email: e_a_a@mail.ru
I. N. Ulianov Chuvash State University, 15 Moskovsky Prospekt, Cheboksary, 428015, Russian Federation, e_a_a@mail.ru

References

  1. Jeyapoovan T., Murugan M. Surface roughness classification using image processing // Measurement. – 2013. – Vol. 46, iss. 7. – P. 2065–2072. – doi: 10.1016/j.measurement.2013.03.014.
  2. Lushnikov N., Lushnikov P. Methods of assessment of accuracy of road surface roughness measurement with profilometer // Transportation Research Procedia. – 2017. – Vol. 20, pp. 425–429. – doi: 10.1016/j.trpro.2017.01.069.
  3. Non-contact surface roughness measurement of crankshaft journals using a super-continuum laser / V.V. Alexander, H. Deng, M.N. Islam, F.L. Terry // Conference on Lasers and Electro-Optics. – San Jose, 2010. – doi: 10.1364/CLEO_APPS.2010.AFA3.
  4. Babu R.A., Baldev R.A. Study of engineering surfaces using laser-scattering techniques // Sadhana. – 2003. – Vol. 28, pt. 3–4. – P. 739–761. – doi: 10.1007/BF02706457.
  5. Abidin F.Z., Hung J., Zahid1 M.N. Portable non-contact surface roughness measuring device // IOP Conference Series: Materials Science and Engineering. – 2019. – Vol. 469. – P. 012074. – doi: 10.1088/1757-899X/469/1/012074.
  6. Kiran R., Amarendra H.J., Lingappa S. Vision system in quality control automation // MATEC Web of Conferences. – 2018. – Vol. 144. – P. 03008. – doi: 10.1051/matecconf/201814403008.
  7. Shih F.Y. Image processing and pattern recognition: fundamentals and techniques. – Hoboken, NJ: Wiley, 2010. – 537 p. – ISBN: 978-0-470-40461-4.
  8. Lee B.Y., Tarng Y.S. Surface roughness inspection by computer vision in turning operations // International Journal of Machine tools and Manufacture. – 2001. – Vol. 41. – P. 1251–1263. – doi: 10.1016/S0890-6955(01)00023-2.
  9. Spagnoloa G.S., Cozzellaa L., Lecceseb F. Viability of an optoelectronic system for real time roughness // Measurement. – 2014. – Vol. 58. – P. 537–543.
  10. Measurement of surface roughness of metal using binary speckle image analysis / E. Kayahana, H. Oktemb, F. Hacizadeb, H. Nasibovb // Tribology International. – 2010. – Vol. 43. – P. 307–311. – doi: 10.1016/j.triboint.2009.06.010.
  11. Wang T., Groche P. Sheet metal profiles with variable height: numerical analyses on flexible roller beading // Journal of Manufacturing and Materials Processing. – 2019. – Vol. 3 (1). – P. 19. – doi: 10.3390/jmmp3010019.
  12. Stoudt M., Hubbard J.B. Analysis of deformation-induced surface morphologies in steel sheet // Acta Materialia. – 2005. – Vol. 53 (16). – P. 4293–4304. – doi: 10.1016/j.actamat.2005.05.038.
  13. Васильев С.А., Максимов И.И., Алексеев В.В. Методика и устройство для профилирования поверхности почвы и определения направления стока атмосферных осадков в полевых условиях // Вестник АПК Ставрополья. – 2015. – № 3 – С. 22–26.
  14. Васильев С.А., Алексеев В.В., Речнов А.В. Экспресс-метод количественной оценки пожнивных остатков на поверхности почвы // Аграрный научный журнал. – 2015. – № 9. – С. 11–13.
  15. Hockauf R., Grove T., Denkena B. Prediction of ground surfaces by using the actual tool topography // Journal of Manufacturing and Materials Processing. – 2019. – Vol. 3 (2). – P. 40. – doi: 10.3390/jmmp3020040.
  16. Vasiliev S., Kirillov A., Afanasieva I. Method for controlling meliorative technologies on sloping cultivated lands using large scale profilometer // Engineering for Rural Development. Proceedings. – 2018. – Vol. 17. – P. 537–542.
  17. Васильев С.А. Разработка метода и профилографа для оценки мелиоративных технологий на склоновых агроландшафтах // Известия Нижневолжского агроуниверситетского комплекса: наука и высшее профессиональное образование. – 2016. – № 3. – С. 220–226.
  18. Васильев С.А. Обоснование конструктивно-технологических параметров профилографов для контроля мелиоративных технологий на склоновых агроландшафтах // Научный журнал Российского НИИ проблем мелиорации. – 2016. – № 4. – С. 40–54.
  19. Image-based inspection technique of a machined metal surface for an unmanned lapping process / D. Ravimal, H. Kim, D. Koh, J.H. Hong, S.K. Lee // International Journal of Precision Engineering and Manufacturing-Green Technology. – 2019. – doi: 10.1007/s40684-019-00181-7.
  20. Application of laser profilometry to evaluation of the surface of the workpiece machined by abrasive water jet technology / G. Mital, J. Dobránsky, J. Ruzbarský, Š. Olejárová // Applied Sciences. – 2019. – Vol. 9. – P. 21–34. – doi: 10.3390/app9102134.
  21. Liu C.-Y., Tzu-Ping Y. Digital multi-step phase-shifting profilometry for three-dimensional ballscrew surface imaging // Optics and Laser Technology. – 2015. – Vol. 79. – P. 115–123. – doi: 10.1016/j.optlastec.2015.12.001.
  22. Bracun D., Perdan B., Diaci J. Surface defect detection on power transmission belts using laser profilometry // Strojniški vestnik – Journal of Mechanical Engineering. – 2011. – Vol. 57 (3). – P. 257–266. – doi: 10.5545/sv-jme.2010.176.
  23. Campana C., Moslehpour S. Non contact surface roughness measurement instrumentation // American Society for Engineering Education. – 2007. – AC 2007-2557. – P. 12.1107.
  24. Development and verification of a one-step-model for the design of flexible roll formed parts / P. Groche, A. Zettler, S. Berner, G. Schneider // International Journal of Material Forming. – 2010. – Vol. 4 (4). – doi: 10.1007/s12289-010-0998-3.
  25. Schilling R.J. Fundamentals of robotics: analysis and control. – New Delhi: Prentice Hall, 2005. – ISBN 81-203-1047-0.

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