Direct transverse load profile determination using the polarization-dependent loss spectral response of a chirped fiber Bragg grating

Abstract

The determination of stress profiles created by transverse loads was proved to be important in different domains, such as structural health monitoring and biomechanics, and, more specifically, in the prostheses domain. In this paper, we report an original method to estimate the transverse load profile from the polarization-dependent loss (PDL) spectrum of a chirped fiber Bragg grating (CFBG). This method makes use of the relationship between the integration of the PDL of a CFBG, and the force profile has the advantage of not requiring any iterative method to estimate the transverse load profile. The relationship linking the integration of the PDL and the force profile is demonstrated using an analytical approximation of the transmission spectrum of CFBGs. The validity of this method for the determination of non-uniform load profiles is then shown using a numerical analysis. An experimental demonstration is finally reported using a 48 mm-long CFBG subject to different step transverse load profiles.

Review of Chirped Fiber Bragg Grating (CFBG) Fiber-Optic Sensors and Their Applications

“…The work of Bettini et al [ 57 ] proposes the use of CFBG sensors in the determination of multi-point strain profiles in structural health monitoring by means of a spectral reconstruction technique, providing a valuable alternative to the distributed sensing methods [ 103 ] or transverse load estimation by polarization analysis [ 104 ].…”

“…CFBGs compete with distributed sensors [ 42 , 43 , 103 ] that enable detection of strain on a longer region. In multiple applications, the availability and multiplexing capability offered by standard FBG arrays [ 5 , 104 , 105 , 106 ] provides a more straightforward implementation in aerospace, whereas the possibility to have a larger sensing network using time- and wavelength-division multiplexing, and increasing the distance between each sensing point, is a key factor [ 109 ].…”