| PhD Viva

Name of the Speaker: Ms. Neethu Sasikumar (EE18D043)
Guide: Dr. Balaji Srinivasan
Online meeting link: https://meet.google.com/upq-roac-bmq
Date/Time: 16th December 2025 (Tuesday), 10 am
Title: Investigation on the Performance Trade-offs and Enhancement Strategies in Distributed Acoustic Sensors

Abstract :

Distributed Acoustic Sensing (DAS) based on phase-sensitive Optical Time Domain Reflectometry (Phase-OTDR) has emerged as a transformative technology for real-time monitoring across diverse applications, including structural health monitoring, oil and gas pipeline surveillance, security, and geophysical studies. Optical fiber-based DAS systems offer several significant advantages, including the ability to leverage existing commercial fiber networks, enabling large sensing ranges, and delivering distributed measurements with high spatial resolution. As the demand for higher sensitivity, improved spatial resolution, and longer sensing distances grows, optimizing Phase-OTDR system performance has become a critical research focus.

This work investigates the performance limits and enhancement strategies of various Phase-OTDR schemes. A comprehensive numerical model and a corresponding simulation framework are employed to evaluate key factors that affect DAS performance, measured in terms of sensitivity, signal-to-noise ratio (SNR), and dynamic range. The study also examines the impact of system noise and nonlinearities, providing valuable insights for developing effective optimization strategies. Experimental results demonstrate high dynamic range sensing over distances up to 40 km with a spatial resolution of 10 m, highlighting the inherent trade-offs and practical constraints of phase-OTDR systems. To further enhance performance, advanced techniques such as Time Expanded (TE) Phase-OTDR are explored, demonstrating their potential to improve both SNR and spatial resolution significantly. By integrating theoretical foundations with simulation and experimental validation, this work establishes a comprehensive framework for designing high-performance DAS systems that can meet user-specific applications.