Fault Detection and Localization of Shielded Cable via Optimal Detection of Time–Frequency-Domain Reflectometry

In recent years, as reliance on factory automation increases, real-time surveillance techniques for electrical systems have received substantial attention. In particular, the fault diagnosis of shielded cables has become crucial in the industrial sector due to their roles in interconnecting each electrical element. The time-frequency-domain reflectometry (TFDR), which is an advanced cable diagnostic technique, has been used to diagnose various types of shielded cable with high accuracy in fault location. However, in the case of reflected signals with a low signal-to-noise ratio (SNR) caused by any soft faults, the method faces ambiguities in interpreting the presence of failures and locating the faults. Thus, this article proposes an algorithm that simultaneously enhances the fault detection and localization performance of TFDR. In addition, the proposed method provides a statistical model-based threshold for fault detection. The performance of the proposed algorithm is tested via three experiments on actual shielded cables, and the efficacy of the proposed method is verified based on statistical analyses with theoretical discussion.