DISTRIBUTED FIBER OPTICS TECHNOLOGIES FOR EFFECTIVE SHAPE SENSING

Abstract

This paper gives a comprehensive study in the development of a computational model that will replicate functions of the LUNA Optical Backscatter Reflectometer (OBR) within the fiber optic shape-sensing (FOSS) framework. Fiber optic sensors have found their way to the forefront in importance due to the ability to measure sensitive strain, temperature, and curvature in structural integrity in various fields, from engineering to medicine. However, the high accuracy mostly relies on properly working tools like LUNA OBR, thus risking technical faults. This study, thus, tries digital emulation of LUNA OBR shape sensing capabilities through a MATLAB simulation in order to address the challenges presented in the malfunction of such critical equipment. This methodology works on the development of a theoretical model towards simulating backscattering spectra—an essential element in any application of FOSS technologies. In the first place, the backscattering spectra were modeled, making some tuning on the parameters such as fiber length, attenuation coefficients, and refractive index values. Subsequently, such parameters underwent an iterative refinement by comparing the simulated results to the intended real data. A cross-correlation model has been developed that compares an individual backscattering spectrum with a combined spectrum in the study of the composition of the alignment and coherence of the signals. This section, therefore, discusses the simulation results by validating the success of the computational model in matching real-life backscattering spectra behavior cross-correlation analyzed. This methodology proposed in this thesis is of large value not only for the continuity of research for fiber optic sensing without the physical equipment of the experiment but opens new opportunities for innovation in this field. The paper concludes with importance in further developments of distributed fiber optic sensing technologies. This is explained in the research as one of the features of human tenacity and adaptability exercised in scientific research; significance in the exercise of overcoming such stumbling blocks as equipment failures. Further outlined in this thesis were future directions for research, which should further extend more multiplexing methods and enhance computer models for real-world applications of shape sensing.