| Title |
Analysis of Reflectometry Signal Characteristics by Measurement Technique According to Metallic Sheath Damage in Dry and Wet Type Submarine Cables for Offshore Wind Farms |
| Authors |
윤성호(Sung-Ho Yoon) ; 이권준(Kwon-Joon Lee) ; 최진욱(Jin-Wook Choe) |
| DOI |
https://doi.org/10.5370/KIEE.2026.75.8.1879 |
| Keywords |
Submarine cable; Metallic sheath; Reflectometry; TDR; FDR; TFDR; Cable diagnostics |
| Abstract |
This paper analyzes reflectometry signal characteristics according to metallic sheath damage severity in dry type (lead sheath) and wet type (copper wire sheath) submarine cables for offshore wind farms. Three reflectometry methods time domain reflectometry (TDR), time-frequency domain reflectometry (TFDR), and frequency domain reflectometry (FDR) were applied to cable specimens with incremental damage levels from 0% to 100%. DC resistance of metallic sheath was simultaneously measured at each damage level to establish a quantitative relationship with reflectometry signals. FDR, which employs broadband impedance spectroscopy via a vector network analyzer, showed high sensitivity to partial damage in wet type cables, detecting characteristic impedance deviation and normalized reflection voltage changes from approximately 60% wire damage. In contrast, TDR and TFDR required complete sheath fracture (100%) for reliable detection in both cable types. For TFDR, cross-term interference arising from closely spaced reflection sources can reduce fault localization accuracy. The dry type lead sheath exhibited negligible impedance change below 100% damage owing to its continuous tubular structure, whereas progressive wire cutting in the wet type cable produced cumulative impedance perturbations detectable by FDR. DC resistance of metallic sheath in the wet type cable increased progressively with damage level, showing a quantitative correlation with FDR reflection coefficient changes. These findings provide practical guidance for selecting reflectometry based diagnostic methods for offshore wind submarine cable health monitoring. |