Fiber Bragg Grating Sensor Interrogation Using Tunable Erbium-Doped Fiber Ring Laser Source

Abstract

Fiber Bragg gratings (FBG) are ideal sensors for temperature, strain or vibration sensing applications with their advantages over conventional electronics sensor systems. In this paper, two different FBG sensor interrogation schemes based on broadband ASE source and tunable EDFRL source are demonstrated and compared. With both interrogator configurations, the response of the FBG sensor to temperature change is found to be linear and the sensitivities are measured as 11 pm/°C and 10.5 pm/°C, respectively. The experimental results have revealed that the optical power reflected from the FBG sensor is almost 20 dB higher with tunable EDFRL source than broadband ASE source. Thus, an interrogation method with tunable EDFRL can be suitable for remote, quasi-distributed sensor applications requiring high output power and OSNR.

Nonlinear least-squares curve fitting method for detection of overlapped FBG temperature sensor spectra

“…FBG sensors operate on the fundamental principle of wavelengthdependent light reflection within an inscribed optical fiber, making them invaluable tools in diverse sensing applications (Sahota et al, 2020). The intrinsic properties of FBG sensors make them particularly adept at monitoring physical parameters such as temperature (Sadik et al, 2021), strain (Kipriksiz and Yücel, 2020), pressure (Leal-Junior et al, 2019), and refractive index (Wang et al, 2017). FBG sensors offer notable advantages, including high sensitivity, resistance to electromagnetic interference, compact form factor, and the capacity for distributed sensing over extended optical fiber lengths.…”

“…Early approaches often utilized optical spectrum analyzers (OSA) for peak identification , offering reliable results but with limited capacity for dynamic measurements (Sadik et al, 2021). To overcome this limitation, researchers have explored alternative techniques such as spectrometers coupled with advanced signal processing algorithms (Bodendorfer et al, 2009).…”