TDR Inversion for Water Localization and Uncertainty Evaluation.

Area of Science:

• Electrical Engineering
• Sensor Technology
• Measurement Science

Background:

• Distributed sensing elements (SEs) are crucial for monitoring environmental parameters.
• Accurate localization and uncertainty quantification are vital for reliable sensor data.
• Time-Domain Reflectometry (TDR) is a promising technique for distributed sensing but requires robust inversion algorithms.

Purpose of the Study:

• To apply and validate a TDR inversion algorithm for water localization along a bi-wire cable.
• To develop a method for evaluating the uncertainty of water position measurements.
• To establish a general framework for TDR measurements and uncertainty evaluation.

Main Methods:

• Utilized a simplified gray-box circuital model for TDR reflectogram analysis.
• Estimated model parameters from single reflectograms without prior electromagnetic characterization.
• Conducted simulation campaigns and experimental validation with controlled laboratory measurements.

Main Results:

• The TDR inversion algorithm accurately localized water along the sensing element.
• Statistical evaluation of water localization error (confidence intervals, bias, standard deviation) was performed.
• Uncertainty evaluation was validated through 45 actual measurements across multiple SEs.

Conclusions:

• The presented TDR inversion method is viable and performs well for localization and uncertainty evaluation.
• The study establishes a general framework combining physical modeling, simulation, and experimental verification for TDR measurements.
• This approach enhances the reliability and applicability of TDR-based distributed sensing systems.