Multi-Criteria Approach to Inspect Line Resonance Analysis Signatures of Wind Farm Cables

Cable joints represent critical points in medium-voltage power lines, where localized impedance discontinuities may lead to faults or performance degradation. This paper proposes a multi-criteria peak detection methodology for the analysis of Line Resonance Analysis (LIRA) signatures. The approach is based on a baseline-residual decomposition, where a smooth baseline is estimated via a sparsified median-driven spline, and candidate peaks are identified using prominence and statistical significance criteria. The method is validated on measurements from a 37.95 MW wind power plant, analyzing underground cables over two campaigns (2024-2025). The algorithm detects approximately 6-10 peaks per phase in 2024 and 5-9 in 2025, with spatial repeatability within 100-200 m and amplitude variations below 5-8 dB for most events. These results indicate that the majority of detected peaks correspond to stable structural features, while only a limited subset may be associated with evolving conditions.