Methodology for estimation of sensitivity to vibration of optical components based on wavelet analysis of vibration-modulated radiation
https://doi.org/10.17586/2226-1494-2025-25-4-609-616
Abstract
The vibrations of navigation systems, including fiber optic gyroscopes, affect the intensity of radiation passing through their optical components. This can lead to positioning errors in vehicles. The mechanism by which vibrations influence fiber optic gyroscopes and the reasons for their high vibration sensitivity are still not fully understood. This paper investigates the amplitude modulation of the optical signal caused by the vibration of passive optical components. The sensitivity to vibration is evaluated by registering optical power passing through components on an experimental stand while they vibrate at frequencies between 20 and 2000 Hz with amplitude of 5 g. The measurement results are processed using a wavelet transform and fast Fourier transform algorithm. The algorithm estimates and searches for vibration-induced modulation of transmitted radiation. Typical cases of the time sweep of signals passing through optical components are presented. The influence of vibration on transmitted radiation is demonstrated. Modulation of the optical signal passing through Y-splitters from different manufacturers is detected, manifesting as periodic changes in the measured radiation power and changes in the split ratio. An algorithm is presented that enables accelerated analysis by selecting data rationally for subsequent wavelet analysis. The proposed methodology for analyzing modulation based on wavelet analysis enables the sensitivity of optical components to vibration to be estimated and resonant frequencies for Y-splitters to be selected. This methodology enables the identification of modulation levels below 0.1 % of the initial power.
About the Authors
R. M. SmertinRussian Federation
Roman M. Smertin, Engineer-Reseacher, Student
614990; Perm
I. L. Nikulin
Russian Federation
Illarion L. Nikulin, D.Sc., Professor
614990; Perm
sc 55654671400
References
1. Hati A., Nelson C.W., Taylor J., Ashby N., Howe D.A. Cancellation of vibration-induced phase noise in optical fibers. IEEE Photonics Technology Letters, 2008, vol. 20, no. 22, pp. 1842–1844. doi: 10.1109/lpt.2008.2004697
2. Liu X., Jin B., Bai Q., Wang Y., Wang D., Wang Y. Distributed fiber-optic sensors for vibration detection. Sensors, 2016, vol. 16, no. 8, pp. 1164. doi: 10.3390/s16081164
3. Li R.-J., Lei Y.-J., Chang Z.-X., Zhang L.-S., Fan K.-C. Development of a high-sensitivity optical accelerometer for low-frequency vibration measurement. Sensors, 2018, vol. 18, no. 9, pp. 2910. doi: 10.3390/s18092910
4. Aleksandr A. Vlasov, Mikhail Yu. Plotnikov Artem N. Ashirov, Artem S. Aleynik. The method for protection of sensitive fiber optic components from environmental noise and vibration impacts. Proc. of the IEEE International Conference on Electrical Engineering and Photonics (EExPolytech), 2019, pp. 305–307. doi: 10.1109/EExPolytech.2019.8906889
5. Song N., Zhang C., Du X. Analysis of vibration error in fiber optic gyroscope. Proceedings of SPIE, 2002, vol. 4920, pp. 115–121. doi: 10.1117/12.481959
6. Zhang Y., Gao G. Fiber optic gyroscope vibration error due to fiber tail length asymmetry based on elastic-optic effect. Optical Engineering, 2012, vol. 51, no. 12, pp. 124403. doi: 10.1117/1.OE.51.12.124403
7. Li H., Cui L., Lin Z., Zhang C. Analysis and optimization of dynamic measurement precision of fiber optic gyroscope. Mathematical Problems in Engineering, 2013, vol. 2013, pp. 265895. doi: 10.1155/2013/265895
8. Osunluk B. Enviromental effects on interferometric fiber optic gyroscope performance. Dissertation for the degree of PhD in electrical and electronics engineering. Bilkent University, 2021, 110 p.
9. Frigo M., Johnson S.G. FFTW: An adaptive software architecture for the FFT. Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing, 1998, vol. 3, pp. 1381–1384. doi: 10.1109/icassp.1998.681704
10. Zimenko K.A., Borgul A.S., Margun A.A. Analysis and processing of electromyogram signals. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2013. vol. 13, no 1, pp. 41–43. (in Russian)
11. Kozinov I.A. Detecting local characteristic of analyzed signals and processes using wavelet transformation. Information and Control Systems, 2015, no. 1 (74), pp. 21–28. (in Russian). doi: 10.15217/issn1684-8853.2015.1.21
12. Mahamune R., Laskar S.H. Classification of the four-class motor imagery signals using continuous wavelet transform filter bank-based two-dimensional images. International Journal of Imaging Systems and Technology, 2021, vol. 31, no. 4, pp. 2237–2248. doi: 10.1002/ima.22593
13. Lilly J.M., Olhede S.C. Generalized Morse wavelets as a superfamily of analytic wavelets. IEEE Transactions on Signal Processing, 2012, vol. 60, no. 11, pp. 6036–6041. doi: 10.1109/TSP.2012.2210890
14. Lilly J.M., Olhede S.C. Higher-order properties of analytic wavelets. IEEE Transactions on Signal Processing, 2009, vol. 57, no. 1, pp. 146–160. doi: 10.1109/TSP.2008.2007607
15. Lilly J.M. Element analysis: a wavelet-based method for analysing time-localized events in noisy time series. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2017, vol. 473, no. 2200, pp. 20160776. doi: 10.1098/rspa.2016.0776
16. Qin Z., Chen L., Bao X. Continuous wavelet transform for non-stationary vibration detection with phase-OTDR. Optics Express, 2012, vol. 20, no. 18, pp. 20459–20465. doi: 10.1364/OE.20.020459
Review
For citations:
Smertin R.M., Nikulin I.L. Methodology for estimation of sensitivity to vibration of optical components based on wavelet analysis of vibration-modulated radiation. Scientific and Technical Journal of Information Technologies, Mechanics and Optics. 2025;25(4):609-616. (In Russ.) https://doi.org/10.17586/2226-1494-2025-25-4-609-616