Temperature drift modeling and compensation of Fabry-Perot filters based on optimized least square support vector machine

Wenjuan Sheng; Zhengbin Hu; G. D. Peng

doi:10.1117/12.2605941

24 November 2021 Temperature drift modeling and compensation of Fabry-Perot filters based on optimized least square support vector machine

Wenjuan Sheng, Zhengbin Hu, G. D. Peng

Author Affiliations +

Proceedings Volume 12069, AOPC 2021: Novel Technologies and Instruments for Astronomical Multi-Band Observations; 120690F (2021) https://doi.org/10.1117/12.2605941
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China

Abstract

Fiber Fabry-Perot filter (FFP-TF) is one of the key components of the fiber Bragg grating (FBG) demodulation system. Its main principle is to realize wavelength scanning with the inverse piezoelectric effect of piezoelectric ceramics (PZT), but the inherent hysteresis and creep characteristics of PZT make the relationship curve between the transmission wavelength of FFP-TF and the control voltage of the PZT unable. Furthermore, in the temperature-varying environment, the relationship between the transmission wavelength and the control voltage keeps drifting. Aiming at the temperature-induced wavelength drift problem of the tunable optical filter, this paper proposed an improved least square support vector machine (LSSVM) model to capture the internal law of the transmission wavelength drift with temperature, and the BAS-PSO algorithm is employed to search penalty factor and nuclear parameters. Experimental results show that after the optimized least squares support vector machine compensates for the tunable filter's sweep fluctuations, the temperature drift error of the tunable filter is ±0.77 pm, and the standard deviation is 0.35 pm, which improves the temperature stability of the tunable filter demodulation in a variable temperature environment.

Citation Download Citation

Wenjuan Sheng, Zhengbin Hu, and G. D. Peng "Temperature drift modeling and compensation of Fabry-Perot filters based on optimized least square support vector machine", Proc. SPIE 12069, AOPC 2021: Novel Technologies and Instruments for Astronomical Multi-Band Observations, 120690F (24 November 2021); https://doi.org/10.1117/12.2605941

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