Hilbert Transform Approach to Central Wavelength Detection for Fiber Bragg Grating Sensors

Year 2022, Volume: 25 Issue: 3, 1099 - 1111, 01.10.2022

Zehra Saraç

https://doi.org/10.2339/politeknik.880207

Cited By: 1

Abstract

The accuracy and sensitivity of Fiber Bragg Grating sensors depends on signal processing approaches that detect the wavelength of the centeral peak in the reflection spectra. In the studies carried out so far, there are various noise that seriously affect the system, arising from the electronic elements in their structure and the environment in which they operate. In addition, depending on the coherence length and intensity of the light sources used, the effects such as unwanted interference in the reflection spectrum create noise. Therefore, the reflection spectrum of the FBG sensor is noisy. In recent years, filtering techniques and curve fitting methods etc. have become increasingly important to reduce the effect of this noise. In this study, it is revealed the Hilbert transform approach enables the detection of the more accurate central wavelength of the FBG sensor. This approach is very practical. Because the Hilbert transform already acts as a filter, this approach does not require a filter design, decomposition levels, or any other complex process as in other methods. To demonstrate that the proposed approach improves the accuracy and measurement capability of the FBG temperature sensor, the Wavelet Denoising Approach presented in the literature so far and the results of the proposed approach are compared. As a result, it is concluded that the Hilbert transform approach definitely follows better the true central Bragg wavelength values and shows smaller a relative error.

Keywords

Fiber Bragg Grating Sensor, Hilbert Transform Approach, Wavelet Denoising Approach, OptiSystem 17

Fiber Bragg Izgara Sensörü için Merkezi Dalga Boyu Algılamaya Hilbert Dönüşümü Yaklaşımı

Abstract

Fiber Bragg Izgara sensörlerinin doğruluğu ve hassasiyeti, yansıma spektrumlarındaki merkezi tepenin dalga boyunu tespit eden işaret işleme yaklaşımlarına bağlıdır. Şu ana kadar yapılan çalışmalarda, bu tip sensörlerde yapılarındaki elektronik elemanlardan ve çalıştıkları çevreden dolayı ortaya çıkan, sistemi ciddi şekilde etkileyen çok çeşitli gürültüler vardır. Ayrıca kullanılan ışık kaynaklarının eş faz uzunluğuna ve şiddetine bağlı olarak özellikle yansıma spektrumunda istenmeyen girişim gibi etkiler gürültü oluşturmaktadır. Bundan dolayı FBG sensörünün yansıma spektrumu gürültülüdür. Son yıllarda bu gürültünün etkisini azaltmak için, filtreleme teknikleri ve eğri uydurma yöntemleri vb. giderek önem kazanmaktadır. Bu çalışma, Hilbert dönüşümü yaklaşımının FBG sensörünün daha hassas merkezi dalga boyunun tespitini sağladığı ortaya konmaktadır. Bu yaklaşım oldukça pratiktir. Hilbert dönüşümü zaten bir filtre görevi gördüğünden, bu yaklaşım bir filtre tasarımı, ayrıştırma seviyeleri (Decomposition Levels) veya diğer yöntemlerde olduğu gibi başka herhangi bir karmaşık işlem gerektirmez. Önerilen yaklaşımın FBG sıcaklık sensörünün doğruluğunu ve ölçüm kabiliyetini geliştirdiğini göstermek için şimdiye kadar literatürde sunulan Dalgacık Gürültü Giderme Yaklaşımı ve önerilen yaklaşımın sonuçları karşılaştırılır. Sonuç olarak Hilbert dönüşümü yaklaşımının kesinlikle gerçek merkezi Bragg dalga boyu değerlerini daha iyi takip ettiği ve daha küçük bağıl hata gösterdiği sonucuna varılmıştır.

Keywords

Fiber Bragg Izgara Sıcaklık Sensörü, Hilbert Dönüşüm Yaklaşımı, Wavelet Gürültü Arındırma Yaklaşımı, OptiSystem 17

References

• [1] Kisala, P.,Cieszczyk, S., “Method of simultaneous measurement of two direction force and temperature using FBG sensor head”, Applied Optics 54(10), 2677-2687, (2015).
• [2] Zimmerman, A. C., Veiga, C. L. N., Encinas, L. S., “un ambigous Signal Processing and Measuring Range Extension for Fiber Bragg Gratings Sensors Using Artifical Neural Networks-A Temperature Case”, IEEE Sensors Journal, 8(7), 1229-1235, (2008).
• [3] Cusano, A., Cutolo, A., Nasser, J., Giordano, M., Calabro, A., “Dynamic strain measurements by fiber Bragg Grating Sensor”, Sensors and Actuators a-Physical, 110(1),276-281, (2004).
• [4] Leandro, D., Ams, M., Lopez-Amo, M., Sun, T., Grattan, K. T. V., “Simultaneous Measurement of Strain and Temperature Using a Single Emission Line”, Journal of Lightwave Technology, 33(12), 2426-2431, (2015).
• [5] Roman, M., Balogun, D., Zhuang Y., Gerald II, R. E., Bartlett, L., O’Malley R. J., and Huang, J., “A Spatially Distributed Fiber-Optic Temperature Sensor for Applications in the Stell Industry”, Sensors, 20(14), (2020).
• [6] Grupta, S., Mizunami, T., Yamao, T., and Shimomura, “Fiber Bragg Grating Cryogenic Temperature Sensors”, Appl. Opt.,35,5202,5205,(1996).
• [7] Lin, G., Wang, L., Yang, C., Shih, M., and Chuang, T., “Thermal performance of metal-clad fiber Bragg grating sensors”, IEEE Photonics Techol. Lett., 10, 406-408, (1998).
• [8] Li, X., Prinz, F., and Seim, J., “Thermal behavior of a metal embedded fiber Bragg grating sensor”, Smart Mater. Struct., 10, 575-579, (2001).
• [9] Guan, B. O., Tam, H. Y., Tao, X. M., Dong, X. Y., “Simultaneous strain and temperature measurement using a superstructure fiber Bragg Grating”, IEEE Photonics Techol. Lett., 12, 675-677, (2000).
• [10] Patrick, H., Williams, G., Kersey, A., Pedrazzani, J., Vengsarkar, A., “Hybrid fiber Bragg grating/long period fiber grating sensor for strain/temperature discrimination”, IEEE Photonics Techol. Lett., 8, 1223-1225, (1996).
• [11] Hoffmann, L., Müller, M. S., Kraemer, S., Giebel, M., Schwotzer, G., and Wieduwilt, T., “Applications of fibre optic temperature measurement”, Proc. Estonian Acad. Sci Eng., 13(4) , 363-378, (2007).
• [12] Rosman, N. A., Rashidi, M. B. C., Aljunid, S. A., and Endut, R., “Temperature monitoring system using fiber Bragg grating (FBG) Approach”, AIP Conf. Proc., 2203 (020065), (2020).
• [13] Mikolajek, M., Martinek, R., Koziorek, J., Hejduk, S., Vitasek, J., Vanderka A., Poboril, R., Vasinek, V. And Hercik R., “Temperature Measurement Using Optical Fiber Methods: Overview and Evaluation”, Hindawi Journal of Sensors, *(*): *, (2020).
• [14] Pehlivan C., “Optik Fiber Bragg Algılayıcıların Analizi”, Doktora Tezi, Kocaeli Üniversitesi, Fen Bilimleri Enstitüsü, (2007).
• [15] Wild, G., Richardson, S. and Hinckley, S., "Numerical simulation of optoelectronic sensors: Fiber Bragg grating and noise," 2016 International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD), 167-168, (2016).
• [16] Kipriksiz S. E., Yücel, M., “Düzgün olmayan yapılarda fiber Bragg Izgara sensör tasarımı ve uygulaması”, Politeknik Dergisi,., *(*): *, (2021).
• [17] Burunkaya, M., and Yücel, M., “Measurement and Control of an Incubator Temperature by Using Conventional Methods and Fiber Bragg Grating (FBG) Based Temperature Sensors”, Journal of Medical Systems, 44,(2),( 2021).
• [18] Yücel, M., Ozturk, N., and Goktas, H., “Implementation and design of fiber Bragg grating based rail strain measurement system”, 2018 26th Signal Processing and Communications Applications Conference (SIU), 1-4, (2018).
• [19] Zrelli, A., “Control and Measurement of Pressure, Temperature, and Strain Variation by Modeling Bragg Sensor”, Conference: International Conference on Automation, Control Engineering & Computer Science, (2016).
• [20] Majumder, M., Gangopadhyay, T. K., Chakraborty, A. K., Dasgupta, K., Bharracharya, D. K., “Fibre Bragg gratings in structural health monitoring-Present status and applications”, Sensors and Actuators A-Physical, 147(1):150-164, (2008).
• [21] Karaman L., Ünverdi, N.O., “Fiber Bragg Izgara Tabanli Optik Sensörün Analizi” , IV. Ulusal Iletisim Teknolojileri Sempozyumu, (1997).
• [22] Alkoçak, S., Ünverdi, N.Ö., “Analysis and applications of fiber Bragg gratings”, 26th Signal Processing and Communications Applications Conference, (2018).
• [23] Wei, H., Cheng, H. B., Mei, J. C., Jiang, D. S., “Direct measurement of strain-optic effect in fiber Bragg gratings”, Ofs 2002:15th Optical Fiber Sensors Conference Technical Digest, 171-174, (2002).
• [24] Yücel, M., Öztürk, N. F., and Gemci, C., “Design of a fiber Bragg grating multiple temperature sensor”, Sixth International Conference on Digital Information and Communication Technology and its Applications (DICTAP), 6-11, (2016).
• [25] Sun, A., Farrell G., Semenova Y., Chen, B., Li, G. Y., Lin, Z. Q., “The distributed dynamic combined-stresses measurement of ship thruster inner-skin using fiber Bragg grating sensor rosette array”, Optic-International Journal for Light and Electron Optics, 122(19), 1779-1781, (2011).
• [26] Chan C. C., Ni, N., Sun, J., Chu, Y. C., Tang, Y., Poh, C. L., “Interferometric noise suppression in fiber Bragg grating sensors by using wavelet filter”, Journal of Optoelectronics and Advanced Materials, 12(6), 1241-1246, (2010).
• [27] De Pauw, B., Lamberti, A., Rezayat, A., Ertveldt, J., Vanlanduit, S., Van Tichelen, K., “Signal-to-Noise Ratio Evaluation of Fibre Bragg Gratings for Dynamic Strain Sensing at Elevated Teperatures in a Liquid Metal Enviroment”, Journal of Lightwave Technology, 33(12), 2378-2385, (2015).
• [28] Li, Y.,Xie, Y., Yao, G., “Comparison of Peak Searching Algorithm for Wavelength Demodulation in Fiber Bragg Grating Sensors” 2nd International Conference on Information Engineering Computer Science, 1(4), (2010).
• [29] Bodendorfer, T., Muller, M. S., Hirth, F., and Koch, A. W., "Comparison of different peak detection algorithms with regards to spectrometic fiber Bragg grating interrogation systems," 2009 International Symposium on Optomechatronic Technologies, 122-126, ,(2009).
• [30] Kersey, A. D., Davis, M. A., Patrick, H. J., LeBlanc, M., Koo, K. P., Askins, C. G., Putnam, M. A., and Friebele, J., “Fiber Grating Sensors”, Journal of Lightwave Technology,15(8), 1442-1463, (1997).
• [31] Lim, J., Yang, Q., Jones, B. E., and Jackson, P. R., “Strain and Temperature Sensors Using Multimode Optical Fiber Bragg Gratings and Correlation Signal Processing”, IEEE Trans. on Instr. and Mes., 51(4), 622-627, (2002).
• [32] Yücel, M., Torun, M. and Burunkaya, M., "Improvement of signal to noise ratio in Fiber Bragg Grating based sensor systems", 25th Signal Processing and Communications Applications Conference (SIU), 1-4, , (2017).
• [33] Yücel, M , Öztürk, N ., “ FBG Algılama Sistemlerinde Gaussian Uyarlama Yöntemi ile Merkez Dalgaboyunun Belirlenmesi”, Politeknik Dergisi , 24 (1) , 63-68, (2021).
• [34] D. Harasim and G. Kashaganova and Nazym Kussambayeva, “Accuracy improvement of Fiber Bragg Grating peak wavelength demodulation using wavelet transform and various center wavelength detection algorithms”,Przegląd Elektrotechniczny, (2016).
• [35] Caucheteur, C., Chah, K,, Lhomme, F., Blondel, M., Megret, P., “Autocorrelation demodulation technique for fiber Bragg grating sensor”, IEEE Photonics Tech. Lett., 16(10), 2320-2322, (2004).
• [36] Harasim, D., Gulbahar, Y., “Improvement of FBG peak wavelength demodulation using digital signal processing algorithms”, Photonics App. in Astronomy, Comm., Industry and High Energy Physics Experi., 9662, (2015).
• [37] Yücel, M., Torun, M.,“Simplified fiber Bragg grating-based temperature measurement system design with enhanced high signal-to-noise ratio”, Microwave and Optical Technology Letters, 60, 965-969,, (2018).
• [38] Gong, J., Chan, C. , Jin, W., MacAlpine, J., Zhang, M., Liao, Y.B., “Enhancement of wavelength detection accuracy in fiber Bragg grating sensors by using a spectrum correlation technique”, Optics Communications, 212(1), 155- 158, (2002).
• [39] Naim, N. F., Siti, S., Suzi, S., Norsuzila, Y., Latifah, S., “ Design of fiber bragg grating (FBG) temperature sensor based on optical frequency domain reflectometer (OFDR)”, International Journal of Electrical and Computer Engineering (IJECE), 10, 3158-3165, (2020).
• [40] Majkowski, A., Kolodziej, M., Rak, R. J., “Joint time-frequency and wavelet analysis- an introduction”, Metrology and Measurement Systems, 21(4), 741-758, (2014).
• [41] Possetti, G. R. C., Kamikawachi, R. C., Muller M., Fabris, J. L., “Metrological Evaluation of Optical Fiber Grating-Based Sensors: An Approach Toward the Standarization, Jourrnal of Lightwave Technology, 30(8), 1042-1052, (2012).
• [42] Patterno, A. S., Silva, J. C. C., Milczewski, M. S., Arruda, L. V. R., Kalinowski, H. J., “Radial-basis function network fort he approximation of FBG sensor spectra with distorted peaks”, Meas. Sci., Technol., 17, 1039-1045, (2006).
• [43] Wen, X., Zhang, D., Qian , Y., Li, J., Fei, N., “Improving the peak wavelength detection accuracy of Sn-doped H2-loaded FBG high temperature sensors by wavelet filter and Gaussian curve fitting”, Sensors and Actuators A:Physical, 174, 91-95, (2012).
• [44] Tosi, D., “Review and Analysis of Peak Tracking Techniques for Fiber Bragg Grating Sensors”, Sensors, 17, 2368-2403, (2017).
• [45] Dyer, S.D., Williams, P.A., Espejo, R.J., Kofler, J.D., Etzel, S.M., “Fundamental limits in fiber Bragg grating peak wavelength measurements”, Proc. SPIE, 5855, 88–93, (2005).
• [46] Gill, A., Peters, K., Studer, M., “Genetic algorithm for the reconstruction of Bragg grating sensor strain profiles”, Meas. Sci. Technol., 15, 1877, (2004).
• [47] Huang, C., Jing, W., Liu, K., Zhang, Y., Peng, G.,” Demodulation of fiber Bragg grating sensor using cross-correlation algorithm”, IEEE Photonics Technol. Lett., 19, 707–709, (2007).
• [48] Lamberti, A., Vanlanduit, S., de Pauw, B., Berghmans, F. A , “Novel fast phase correlation algorithm for peak wavelength detection of fiber Bragg grating sensors”, Opt. Express, 22, 7099–7112, (2014).
• [49] Chan, C.C., Shi, C.Z., Jin, W., Wang, D.N., “ Improving the wavelength detection accuracy of FBG sensors using an ADALINE network”, IEEE Photonic Technol. Lett. , 15, 1126–1128, (2003).
• [50] Negri L., Nied, A., Kalinowski, H. & Paterno, A.., “Benchmark for Peak Detection Algorithms in Fiber Bragg Grating Interrogation and a New Neural Network for its Performance Improvement”, Sensors, 11, 3466-3482, (2011).
• [51] Optiwave, Optisystem 17, https://optiwave.com/
• [52] Elgaud, M. M., Zan, M. S. D., Abushagur, A. G., Bakar, A. A. A., and Elshirkasi, A. M.., "Analysis and simulation of time domain multiplexed (TDM) fiber Bragg sensing array using OptiSystem and OptiGrating", 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering (ICAEES), 301-304, (2016).
• [53] Elgaud, M. M., Zan, M. S. D., Abushagur, A. A. G., and Bakar, A. A. A., "Analysis of independent strain-temperature fiber Bragg grating sensing technique using OptiSystem and OptiGrating", 2016 IEEE 6th International Conference on Photonics (ICP), 1-3, (2016).
• [54] Gözgöz, U., Gül, E., Karaman, İ., Özkan, H., ve Kılıç, N.., “Dağınık Fiber Optik Sensörler ile Efektif Alanın Rayleigh Saçılmasına Etkisinin OptiSystem Programı Kullanılarak İncelenmesi”, Conference: 3rd International Conference on Data Science and Applications (ICONDATA’20), (2020).
• [55] R2020b, Wavelet Denoising Toolbox, https://www.mathworks.com/?s_tid=gn_logo
• [56] Saraç Z., Birkök H.G. , Taşķn H., Öztürk E., “Evaluation of thermal lens fringes using Hilbert and Fourier transform methods”, IET Science, Measurement and Technology, (5), 81 – 87, (2011).