Uncertainty-Aware Measurement of Corona Discharge Area on Insulators from Solar-Blind Ultraviolet Imagery

The area of the corona discharge region on an insulator is reported as a diagnostic indicator, yet it is almost always obtained by thresholding a segmentation probability map at the conventional 0.5 level and is reported without any uncertainty statement. Using 1600 solar-blind ultraviolet frames, we show that this practice is the dominant error source. Selecting the operating point on a validation split reduces the median relative area error from 20.8% to 3.3% and, unexpectedly, increases Dice from 0.874 to 0.903; a 7.76 M-parameter U-Net then reaches 3.26 ± 0.39% area error, within 0.07 percentage points of an oracle threshold. Dice is not a valid proxy for area: a two-pixel registration shift changes the area by 0.03% but Dice by 0.159, because the annotations are fragmented into about 31 sub-ten-pixel blobs. Split conformal prediction yields intervals whose empirical coverage (93.7–97.8%) meets or exceeds the nominal level even when checkpoint selection, threshold selection and calibration use disjoint data, with a domain of validity of roughly −5% to +10% gain deviation. A GUM budget attributes 15.7% relative standard uncertainty to annotation-boundary ambiguity, against 2.1% for the model and acquisition combined, so the measurement is annotation-limited. The protocol makes the reported image-domain area fraction an interpretable measurand with a stated uncertainty.