Resistivity-Derived Features for Anomaly Detection in Self-Sensing Concrete under Monotonic and Ramp–Hold Loading

Abstract

Abstract

Self-sensing concrete (SSC) can support structural health monitoring by turning the bulk electrical response of cementitious material into a sensing channel. This paper evaluates simple, training-free resistivity-derived features under monotonic destructive tests (MDT) and ramp--hold--ramp monitoring (NMT-RHR). Graphite--milled carbon fibre concrete cubes were tested while resistance, strain, and force were recorded. The electrical response was processed into fractional resistivity change ($\kappa$), its time-rate ($\beta_t$), and supporting strain-normalised variants. Low-load segments were treated as conservative internal references for feature comparison rather than as verified damage-free states. Across the retained MDT specimens, $\kappa$ provided the clearest sustained deviation from the initial reference segment, while $\beta_t$ highlighted abrupt late-stage transitions. Across NMT hold segments, $\kappa$ showed the strongest sustained response as load severity increased, whereas $\beta_t$ behaved as a more transient companion indicator. The strain-normalised variants were less stable and are best treated as secondary comparison features. These results indicate that sustained and rate-sensitive electrical features provide complementary information: $\kappa$ is more suitable for tracking persistent offsets, while $\beta_t$ is more suitable for identifying short transitions. Overall, the study provides a comparative basis for selecting simple electrical features under controlled compression loading, with the reported detections interpreted as reference-relative changes in the electrical response.