Application of Enhanced Optimal-Detection of Time–Frequency Domain Reflectometry on HTS Cable With High-Resolution
Hobin Lim, Yeong Ho Lee, Su Sik Bang, Yong–June Shin
Abstract
Time–frequency domain reflectometry (TFDR) has been used for sensing various types of cables including high temperature superconducting (HTS) cables. Recently, the optimal-detection of time–frequency domain reflectometry (OD-TFDR) has been proposed and has better detection and localization performance than conventional TFDR. Additionally, OD-TFDR has provided a threshold that can distinguish detected signals from Gaussian noise. However, OD-TFDR does not provide a criterion for classifying the detected signals into fault signals and artifacts. Furthermore, the diagnosis result of OD-TFDR is not intuitive because an additional tool is needed to locate each fault. Thus, this paper proposes a new diagnosis algorithm that can provides a criterion for distinguishing between artifacts and faults by considering the propagation direction of the incident signal in the join time–frequency domain while preserving the detection and localization performance of OD-TFDR. Through a template matching process of generalized time–frequency cross-correlation (GTFCC), the core algorithm of OD-TFDR, a modified–generalized time–frequency cross-correlation (M–GTFCC) function is derived. Next, a modified–time–frequency cross-correlation (M–TFCC) function is derived by slicing the M–GTFCC function considering the propagation direction of signal. Finally, M–TFCC function is proposed as a new intuitive diagnosis result with artifact-free and high-resolution. The performance of the proposed algorithm is tested via experimental setup for a real-world single phase HTS cable with an emulated local quench by heating element, and the efficacy of the proposed algorithm is verified based on three performances: fault detection, locating accuracy, and resolution.