Skip to main content
Log in

Assessing the Distance from a Given Point to the Maximum of Interference Band

  • Published:
Optoelectronics, Instrumentation and Data Processing Aims and scope

Abstract

The problem of determining the distance from an arbitrary point to the center of interference band with a known profile from the data distorted by random noise is formulated. At the final stage in the developed algorithm, the Wiener–Kolmogorov filtering is used. The numerical simulation shows that the averaged error of estimate computed by the proposed method is 50–75% less than the estimate obtained without noise. The results of processing experimental data also confirm the efficiency of the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

REFERENCES

  1. C. M. West, Holographic Interferometry (New York, John Wiley and Sons, 1979).

    Google Scholar 

  2. V. A. Arbuzov, E. V. Arbuzov, N. A. Dvornikov, Yu. N. Dubnishchev, V. G. Nechaev, and E. O. Shlapakova, ‘‘Optical diagnostics of vortex ring-flame interaction,’’ Optoelectron., Instrum. Data Process. 52, 161–166 (2016). https://doi.org/10.3103/S8756699016020084

    Article  Google Scholar 

  3. A. Ya. Aleksandrov and M. Kh. Akhmetzyanov, Polarization-Optical Methods of Solid Mechanics (Nauka, Moscow, 1973).

    Google Scholar 

  4. S. I. Gerasimov, ‘‘Photoelastic method for analyzing residual stresses in compact disks,’’ J. Appl. Mech. Tech. Phys. 45, 453–456 (2004).

    Article  ADS  Google Scholar 

  5. I. A. Razumovskii, Interference-Optical Methods of Solid Mechanics (Moscow, Mosk. Gos. Tekh. Univ., 2007).

    Google Scholar 

  6. L. V. Stepanova and V. S. Dolgikh, ‘‘Digital processing of optoelectronic measurement results: Photoelasticity method and its application for determining coefficients of multiparametric Williams asymptotic decomposition of stress field,’’ Vestn. Samar. Gos. Tekh. Univ., Ser. Phys.-Mat. Nauki 21, 717–735 (2017).

    Google Scholar 

  7. V. S. Dolgikh, L. V. Stepanova, and V. A. Turkova, ‘‘Digital processing of optoelectronic measurement results (photoelasticity method) with application to problems of fracture mechanics: Multiparametric stress field analysis near crack tip,’’ in Sb. Tr. III Int. Conf. and Young Sci. School Information Technologies and Nanotechnologies (ITNT 2017) (Novaya Tekhnika, Samara, 2017), pp. 1425–1428.

  8. G. N. Albaut, Nonlinear Photoelasticity with Application to Problems of Fracture Mechanics (NGASU, Novosibirsk, 2002).

    Google Scholar 

  9. G. N. Albaut, E. P. Matus, and M. V. Tabanyukhova, ‘‘Studying stress state of disperse-reinforced beams using photoelasticity method,’’ Deform. Razrushenie Mater., No. 4, 46–49 (2009).

  10. K. Ramesh, Digital Photoelasticity: Advanced Techniques and Applications (Spinger, Berlin, 2000). https://doi.org/10.1007/978-3-642-59723-7

  11. T. E. Gerasimova ‘‘Digital processig of images obtained using interference-optical methods of solid mechanics,’’ Vestn. Samar. Gos. Univ., Ser. Mech. 125 (3), 73–87 (2015).

    Google Scholar 

  12. A. N. Kosygin and L. N. Kosygina, ‘‘Digital processing of experimental interferograms obtained by photoelasticity method,’’ Vestn. Samar. Univ., Estestv.-Nauch. Ser. 25 (2), 75–91 (2019).

    Google Scholar 

  13. A. W. Hendry, Elements of Experimental Stress Analysis: Structures and Solid Body Mechanics Division (Pergamon, New York, 2013).

    Google Scholar 

  14. V. I. Guzhov and S. P. Il’inykh, Optical Measurements: Computer Interferometry (Yurait, Moscow, 2019).

    Google Scholar 

  15. T. H. Baek, M. S. Kim, and D. P. Hong, ‘‘Fringe analysis for photoelasticity using image processing techniques,’’ Int. J. Software Eng. Its Appl. 8 (4), 91–102 (2014).

    Google Scholar 

  16. K. V. N. Surendra and K. R. Y. Simha, ‘‘Digital image analysis around isotropic points for photoelastic pattern recognition,’’ Opt. Eng. 54, 081209 (2015). https://doi.org/10.1117/1.OE.54.8.081209

    Article  Google Scholar 

  17. A. B. Sergienko, Digital Signal Processing (Piter, St. Petersburg, 2007).

  18. S. Alsiya, J. C. Leksmi, J. B. P. Priya, and R. C. Mehta, ‘‘Image processing algorithm for fringe analysis in photoelasticity,’’ Scholars J. Eng. Technol. 2016. 4, 325–328. https://doi.org/10.21276/sjet.2016.4.7.5

    Article  Google Scholar 

  19. N. G. Preobrazhenskii and V. V. Pikalov, Instable Problems of Plasma Diagnostics (Nauka, Novosibirsk, 1982).

    Google Scholar 

  20. S. Alsiya, J. C. Leksmi, J. B. P. Priya, and R. C. Mehta, ‘‘Image processing algorithm for fringe analysis in photoelasticity,’’ Scholars J. Eng. Technol. 2016. 4, 325–328. https://doi.org/10.21276/sjet.2016.4.7.5

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to A. V. Likhachev or M. V. Tabanyukhova.

Additional information

Translated by E. Oborin

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Likhachev, A.V., Tabanyukhova, M.V. Assessing the Distance from a Given Point to the Maximum of Interference Band. Optoelectron.Instrument.Proc. 57, 250–256 (2021). https://doi.org/10.3103/S8756699021030109

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S8756699021030109

Keywords:

Navigation